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Table of contents :
Cover
Half Title
Analytical Applications of Functionalized Magnetic Nanoparticles
Copyright
Dedication
Preface
About the Editor
Contents
Section 1: Introduction
1. Analytical Applications of Functionalized Magnetic Nanoparticles (Introduction)
1.1 Introduction
1.2 Sample Preparation Techniques
1.3 Magnetic Solid Phase Extraction (MSPE)
1.4 Functionalized Magnetic Nanoparticles
1.5 Application of MSPE
1.6 Force Interactions Between Analytes and Sorbents
1.7 Conclusion
Acknowledgements
References
2. Design of Functionalized Magnetic Nanoparticles for Improving Stabilization, Biocompatibility and Uptake Efficiency
2.1 Introduction
2.2 Design of Functional Magnetic Nanoparticles (FMNPs)
2.3 Synthetic Route to FMNPs
2.4 Chemical Design of FMNPs
2.4.1 Metal-based Magnetic Nanoparticles (MMNPs)
2.4.2 Metal Alloy-based Magnetic Nanostructures (MAMNs)
2.4.3 Metal Oxide-based Magnetic Nanoparticles (MOMNPs)
2.4.4 Metallic Carbides and Nitride-based Magnetic Nanostructures (MC/NMNs)
2.4.5 Multifunctional Nanoparticle-based Magnetic Nanostructures (MNMNs)
2.5 Physicochemical Features of FMNPs
2.5.1 NP Size
2.5.2 NP Crystallinity
2.5.3 Chemical Composition
2.5.4 Surface Potential
2.5.5 Interfacial Interactions
2.5.6 Magnetism
2.6 Surface Functionalization and Biocompatibility
2.6.1 Surface Stability
Organic/Inorganic Coatings
2.6.2 Organic Coating Materials
2.6.3 Inorganic Coating Materials
2.6.4 Biocompatibility of FMNPs
2.7 Biomedical Applications of FMNPs
2.7.1 FMNPs as Biosensors
2.7.2 FMNPs for Protein Purification/Bioseparation
2.7.3 FMNPs as Contrast Agents for MRI
2.7.4 FMNPs for Targeted Drug Delivery
2.7.5 FMNPs for Magnetic Hyperthermia
2.8 Future Trends and Perspective
Acknowledgements
References
3. Improvement of Adsorbing Properties of Magnetic Nanomaterials by Bioorganic Substrate-mediating Synthesis
3.1 Introduction
3.2 Preparation of Magnetic Nanoparticles
3.2.1 Iron Oxide Magnetic Nanoparticles
3.2.2 Preparation of Iron-containing Hydroxyapatite
3.2.3 Functionalized Nanoscale Magnetic Particles
3.3 Results and Discussion
3.3.1 Mnp, Mnp@YM4 and Mnp@YM10 Characterization
3.3.2 YM–Iron Oxide Magnetic Nanoparticles. Adsorption of MB
3.3.3 Fe-nAp and SBO–Fe-nAp Characterization
3.3.4 Fe-nAp and SBO–Fe-nAp: Adsorption of Pb(II) and Cu(II)
3.4 Conclusion
Acknowledgements
References
Section 2: Functionalized Magnetic Nanoparticles in Sample Pre-treatment
4. Functionalized Magnetic Nanoparticles in Sample Pre-treatment
4.1 Introduction
4.2 Different Magnetic Nanoparticles for Extraction and their Magnetic Behavior
4.3 The Necessity of Functionalized Magnetic Nanoparticles
4.4 Sample Preparation Techniques
4.5 Types of Functionalized Magnetic Materials
4.6 Application of Functionalized MNPs with Silica
4.7 Application of Functionalized MNPs with Octadecylsilane (ODS)
4.8 Application of Functionalized MNPs with a Carbon-based Material
4.9 Activated Carbon-based Magnetic Nanoparticles
4.10 Graphene-based Magnetic Nanoparticles
4.11 Carbon Nanotube (CNT)-based Magnetic Materials
4.12 Surfactant-modified Magnetic Materials
4.13 Polymer-modified Magnetic Nanoparticles
4.14 Extraction Techniques
4.14.1 Functionalized MNPs in Solid-Phase Extraction
4.14.2 Functionalized MNPs in Magnetic Solid-phase Extraction
4.15 Summary
Acknowledgements
References
5. Application of Functionalized Magnetic Nanoparticles for Organic Analyte Extraction
5.1 Introduction
5.2 Polymeric Magnetic Nanoparticles
5.3 Magnetic Nanoparticles Based on Allotropic Forms of Carbon
5.4 Metal Organic Framework Coatings
5.5 Covalent Organic Framework Coatings
5.6 Ionic Liquids
5.7 Miscellaneous
5.8 Conclusions
Abbreviations
Acknowledgements
References
6. Graphene-based Sorbents for Modern Magnetic Solid-phase Extraction Techniques
6.1 Introduction
6.2 Graphene-based Magnetic Sorbents
6.2.1 Preparation of Graphene-based Magnetic Sorbents
6.3 Functionalization of Graphene-based Magnetic Sorbents
6.3.1 Molecularly Imprinted Polymers (MIPs)
6.3.2 Metal–Organic Frameworks (MOFs)
6.3.3 Ionic Liquids (ILs) and Deep Eutectic Solvents (DESs)
6.3.4 Boronate Affinity Materials (BAM)
6.3.5 Supramolecules
6.3.6 Aptamers
6.3.7 Miscellaneous Functionalities
6.4 Characterization of Graphene-based Magnetic Sorbents
6.5 Modern Applications of Graphene-based Magnetic Sorbents
6.5.1 Applications on the Extraction of Organic Pollutants
6.5.2 Applications on the Extraction of Inorganic Pollutants
6.5.3 Applications on the Extraction of Biological Macromolecules
6.6 Conclusion
Acknowledgements
References
7. Magnetic Nanoparticles as an Efficient Tool for Analyte Extraction: Challenges and New Opportunities
7.1 Introduction
7.2 Sample Pre-treatment: A Key Step in Analytical Determination
7.3 MNPs for Analyte Extraction
7.3.1 Environmental Applications
7.3.2 Food Applications
7.3.3 Biological Applications
7.4 Conclusions
References
8. Functionalized Magnetic Nanoparticles for Solid-phase Extraction
8.1 Introduction
8.2 Principles and Methods
8.3 Material Selection and Design
8.3.1 Magnetic Core
8.3.2 Particle Coating and Functionalization
8.4 Applications of MSPE
8.4.1 Environmental Applications
8.4.2 Food Applications
8.4.3 Biological and Pharmaceutical Applications
Abbreviations
References
Section 3: Functionalized Magnetic Nanoparticles in the Separation/Identification Stage of Analysis
9. Use of Functionalized Magnetic Nanoparticles in Modern Separation Techniques
9.1 Introduction
9.2 Synthesis of MNPs
9.2.1 Thermal Decomposition Technique
9.2.2 Sol–Gel Synthesis
9.2.3 Hydrothermal Synthesis
9.2.4 Coprecipitation Technique
9.2.5 Microemulsion-based Synthesis
9.2.6 Flow Injection Synthesis
9.2.7 Aerosol/Vapor-phase-based Synthesis
9.3 Chromatography: An Overview
9.3.1 Considerations for an Effective Chromatographic Separation
9.3.2 Functionalized MNPs in GC
9.3.3 Liquid Chromatography (LC)
9.4 Application of Functionalized MNPs in Separation Techniques
9.4.1 Magnetic Solid Phase Extraction (MSPE)
9.5 Conclusion
References
10. Chromatographic Applications of Functionalized Magnetic Nanoparticles
10.1 Introduction
10.2 Preparation Techniques for MNPs
10.2.1 Thermal Decomposition Approach
10.2.2 Co-precipitation Approach
10.2.3 Sol–Gel Process
10.2.4 Hydrothermal Technique
10.2.5 Microemulsion Technique
10.2.6 Flow Injection Technique
10.2.7 Aerosol/Vapor-phase-based Approaches
10.3 Chromatographic Applications of Functionalized Magnetic Nanoparticles (MNPs)
10.3.1 Capillary Electrochromatography (CEC)
10.3.2 Chip-based Chromatography
10.4 Conclusions
References
Section 4: Functionalized Magnetic Nanoparticles in Detection Stage of Analysis/Miniturization devices
11. Functionalized MNPs in Detection Stage of Analysis/Miniaturization Devices
11.1 Transduction Methods in Sensing Based on MNPs
11.1.1 Electrochemical
11.1.2 Optical
11.1.3 Piezoelectric
11.1.4 Magnetic Field
11.2 Applications of MNPs in Detection Analysis
11.2.1 Biomolecules and Cells
11.2.2 Organic Compounds
11.2.3 Ions and Inorganic Compounds
References
12. MNP-based Sensor Development to Evaluate Food Quality and Safety
12.1 Introduction
12.2 Sensors
12.2.1 Sensor Classification and Properties
12.2.2 NP Properties for NP-based Sensors
12.3 MNP-based Sensor
12.3.1 MNP-based Sensors for Food Safety
12.3.2 MNP-based Sensors for Food Quality
12.4 Conclusion
References
13. Functionalized Magnetic Nanoparticle (MNPs)-based Biosensors
13.1 Introduction
13.2 Synthesis, Properties and Characterization of MNPs
13.3 Biosensors Based on MNPs
13.3.1 Electrochemical Biosensors
13.3.2 Optical Biosensors
13.3.3 Piezoelectric Biosensors
13.3.4 Magnetic Field Biosensors
13.4 Enzyme-based Biosensors
13.4.1 Glucose-based Biosensors
13.4.2 Cholesterol-based Biosensors
13.5 Conclusions and Future Trends
Acknowledgements
References
14. Sensing Applications by Functionalized Magnetic Nanoparticles
14.1 Introduction
14.2 Analytical Strategies Based on Optical Sensing
14.2.1 UV–Visible Absorbance
14.2.2 Luminescence
14.2.3 Surface Enhanced Raman Spectroscopy
14.3 Analytical Strategies Based on Electrochemical Sensing
14.4 Concluding Remarks
Acknowledgements
References
15. Magnetoresistance-based Biosensors
15.1 Introduction
15.2 Magnetoresistive Sensors
15.2.1 Anisotropy Magnetoresistance Sensors
15.2.2 Giant Magnetoresistance Sensors
15.2.3 Tunnel Magnetoresistance Sensors
15.2.4 Spin-Valves and Pseudo Spin-Valves
15.3 MNPs in MR-based Biosensors
15.3.1 High Magnetic Moment
15.3.2 Biocompatibility
15.3.3 Colloidal Stability
15.4 Functionalization
15.5 Assays for MR-based Biosensors
15.5.1 Direct Assay
15.5.2 Sandwich Assay
15.5.3 Competitive Assay
15.6 Device Concept
15.6.1 Magnetic Tags
15.6.2 Magnetic Field Sensor
15.6.3 Sensor Surface Passivation and Functionalization
15.6.4 Magnetic Field Source
15.6.5 Microfluidic Channel
15.6.6 Readout Electronic
15.7 Future Perspectives
Websites of Interest
Acknowledgements
References
Section 5: Other Analytical Applications Functionalized Magnetic Nanoparticles
16. Analytical Applications of Molecularly Imprinted Polymer-decorated Magnetic Nanoparticles
16.1 Introduction
16.2 Generalities
16.2.1 Magnetic Nanoparticles
16.2.2 Molecularly Imprinted Polymers
16.3 Preparation of MIP-decorated MNPs
16.3.1 Preparation and Modification of MNPs
16.3.2 Decoration of MNPs by MIPs
16.4 Characterization of MIP-decorated MNPs
16.4.1 Morphological Characterization
16.4.2 Structural Characterization
16.4.3 Magnetic Characterization
16.4.4 Adsorption Characterization
16.5 Application of MIP-decorated MNPs for Solid-phase Extraction
16.5.1 Introduction to Solid-phase Extraction (SPE) and Dispersive SPE
16.5.2 Application of Magnetic MIPs in Dispersive Solid-phase Extraction
16.6 MIP-decorated MNPs for Sensing
16.6.1 MIP-decorated MNPs for Electrochemical Sensors
16.6.2 MIP-decorated MNPs for Optical Sensors
16.7 Recent Advances in the Analytical Applications of Magnetic MIPs
16.7.1 Food Safety
16.7.2 Emerging Pollutants
16.7.3 Disease Biomarkers
16.7.4 Medical Treatment and Drugs
16.8 Conclusions
References
17. Characterization of Functional Magnetic Nanoparticle-modified Polymeric Composites by Computer Modeling
17.1 Introduction
17.2 Computer Modeling
17.2.1 Fundamental of Electro-magnetic Wave
17.2.2 Effective Permittivity and Permeability of Nanocomposites
17.2.3 Analytical Calculation of Effective Permittivity and Effective Permeability
17.2.4 Modeling of Nanocomposites
17.3 Results and Discussion
17.3.1 Effect of Distribution of Cubic Nanoparticles
17.3.2 Effect of Shape and Orientation of Nanoparticles
17.3.3 More Result Displays of the Randomly Distributed Nanoparticle Model
17.4 Conclusion
Acknowledgements
References
18. Functionalized Magnetic Nanoparticle-based Sensors for Point-of-care Applications: From the Preparation to Practical Application
18.1 Introduction
18.2 Preparation and Functionalization of MNPs
18.2.1 Preparation of MNPs
18.2.2 Functionalization of MNPs
18.3 Point-of-care Approaches
18.4 fMNP-based Sensors for PoC Applications
18.5 Conclusions
Important Websites
References
19. Fourth Industrial Revolution (4IR) and Functionalized MNPs
19.1 Introduction
19.2 On Industry 4.0
19.3 Enabling Technologies
19.4 On Artificial Intelligence and Machine/Deep Learning
19.5 Nanotechnology: Applications of Functionalized Nanoparticles
19.6 Targeted Transport of Medicines (Drug Delivery) and Genes
19.7 Physiological Tissues Treatment
19.8 Metals
19.9 Conclusions
Websites of Interest
References
Section 6: Toxicity, Safety and Risk and Legal Aspects of Functionalized Magnetic Nanoparticles
20. Important Aspects of Safety, Risk & ELSI of Functionalized Magnetic Nanoparticles for Analytical Purposes
20.1 Introduction
20.2 Toxicity of FMNPs
20.3 Biodistribution and Bioelimination of Nanoparticles
20.4 Mechanism of NP Toxicity
20.5 Toxicity Effect on the Environment: Nanoecotoxicity
20.6 Toxicity Effect on Human Health
20.6.1 In Vitro Research on FMNPs
20.6.2 In Vivo Research on FMNPs
20.7 Risk Assessment of FMNPs
20.7.1 Dose–Response Assessment
20.7.2 Exposure Assessment
20.8 Ethical Issues
20.9 Conclusion and Future Trends
Abbreviations
Acknowledgements
References
21. Functionalized Magnetic Nanoparticles (MNPs): Toxicity, Safety and Legal Aspects of Functionalized MNPs
21.1 Introduction
21.2 Physicochemical Properties of Functionalizedand Unfunctionalized-MNPs and Their Influence on Toxicity
21.3 Toxicological Testing
21.3.1 In Vitro Testing of Functionalized-MNPs
21.3.2 In Vivo Toxicity of Functionalized MNPs
21.4 Comparison Between In Vitro and In Vivo
Toxicity Studies of Coated and Bare MNPs
21.4.1 In Vitro Toxicity Comparative Studies of Coated and
Bare MNPs
21.4.2 In Vivo Toxicity Comparative Studies of Coated and
Bare MNPs
21.5 Legal Aspects of Functionalized MNPs
21.6 Conclusion
Abbreviations
Websites of Interest
References
Section 7: Conclusion: The Future of Analytical Chemistry
22. Functionalization of Magnetic Nanoparticles for Tomorrow’s Applications
22.1 Introduction
22.1.1 Intriguing Features of Nanoparticles
22.1.2 Synthesis of Magnetic Nanoparticles
22.1.3 Stabilizing Magnetic Nanoparticles
22.1.4 Application of Magnetic Nanoparticles
22.1.5 Future Prospects
22.2 Conclusion
Websites of Interest
Acknowledgements
References
23. Future of Functionalized Magnetic Nanoparticles in Analytical Chemistry
23.1 Introduction
23.2 Future Scope of Functionalized Magnetic Nanoparticles in Analytical Applications
23.2.1 Application of Functionalized MNPs in Sample Preparation
23.2.2 Scope of Functionalized MNPs in Biological Synthesis
23.2.3 Use of Functionalized MNPs in the Medical Field
23.2.4 Other Applications of Magnetic Nanoparticles
23.3 Conclusion
References
Subject Index
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Analytical Applications of Functionalized Magnetic Nanoparticles

Analytical Applications of Functionalized Magnetic Nanoparticles Edited by

Chaudhery Mustansar Hussain New Jersey Institute of Technology, USA Email: [email protected]

Print ISBN: 978-1-83916-210-7 PDF ISBN: 978-1-83916-275-6 EPUB ISBN: 978-1-83916-276-3 A catalogue record for this book is available from the British Library r The Royal Society of Chemistry 2021 All rights reserved Apart from fair dealing for the purposes of research for non-commercial purposes or for private study, criticism or review, as permitted under the Copyright, Designs and Patents Act 1988 and the Copyright and Related Rights Regulations 2003, this publication may not be reproduced, stored or transmitted, in any form or by any means, without the prior permission in writing of The Royal Society of Chemistry or the copyright owner, or in the case of reproduction in accordance with the terms of licences issued by the Copyright Licensing Agency in the UK, or in accordance with the terms of the licences issued by the appropriate Reproduction Rights Organization outside the UK. Enquiries concerning reproduction outside the terms stated here should be sent to The Royal Society of Chemistry at the address printed on this page. Whilst this material has been produced with all due care, The Royal Society of Chemistry cannot be held responsible or liable for its accuracy and completeness, nor for any consequences arising from any errors or the use of the information contained in this publication. The publication of advertisements does not constitute any endorsement by The Royal Society of Chemistry or Authors of any products advertised. The views and opinions advanced by contributors do not necessarily reflect those of The Royal Society of Chemistry which shall not be liable for any resulting loss or damage arising as a result of reliance upon this material. The Royal Society of Chemistry is a charity, registered in England and Wales, Number 207890, and a company incorporated in England by Royal Charter (Registered No. RC000524), registered office: Burlington House, Piccadilly, London W1J 0BA, UK, Telephone: þ44 (0) 20 7437 8656. Visit our website at www.rsc.org/books Printed in the United Kingdom by CPI Group (UK) Ltd, Croydon, CR0 4YY, UK

Dedication I would like to dedicate this book to my beloved GOD ‘‘Mera Pyarey Allah’’

Analytical Applications of Functionalized Magnetic Nanoparticles Edited by Chaudhery Mustansar Hussain r The Royal Society of Chemistry 2021 Published by the Royal Society of Chemistry, www.rsc.org

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Preface Magnetic nanoparticles (MNPs) uniquely combine superparamagnetic performance with dimensions that are smaller than or a similar size to molecular analytes. The incorporation of magnetic nanoparticles with analytical methods has opened new possibilities for sensing, extraction, and detection analysis. As a result, magnetic nanoparticle-based techniques and procedures can play vital roles in many analytical procedures, as they increase sensitivity, magnify precision and improve the detection limit of modern analysis. Recently, functionalized MNPs were predicted to be a main driver of technology and business in this century and they hold the promise of high-performance materials that will significantly influence all aspects of society. Likewise, functionalized MNPs are taking part in creating development and innovation in different analytical procedures. Despite their participation in modern development, FMNPs are in their infancy and are largely unexplored for their practical applications in many fields. Similarly, they have the potential to have adverse impacts on the environment, human health, and safety, and their sustainable usage is a challenge. This book addresses these challenges for their justifiable usage in analytical chemistry. In general, the aim of this book is to deliver the recent advancements in various analytical methods and techniques because of functionalized MNPs. Furthermore, the legal, economical, and toxicity aspects of functionalized MNPs are presented in detail. To gather all of the combined knowledge into this perspective and add a trace of realism to the thoughts, the book is divided into several sections. The selection of these sections was based on the most recent research, teaching, and practical experience of the editor. The introduction discusses general analytical applications of functionalized MNPs, their design to improve stabilization, biocompatibility and adsorption properties. Then Section 1 explores sample pre-treatment techniques, extraction techniques

Analytical Applications of Functionalized Magnetic Nanoparticles Edited by Chaudhery Mustansar Hussain r The Royal Society of Chemistry 2021 Published by the Royal Society of Chemistry, www.rsc.org

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Preface

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and solid-phase extraction of various analytes with the help functionalized MNPs. Section 2 discusses the use of functionalized MNPs in modern separation techniques and chromatographic techniques. Section 3 elaborates on functionalized MNPs for miniaturization devices, sensors and biosensors. Section 4 describes other analytical applications of functionalized MNPs, such as functionalized MNP-based sensors for point-of-care applications and the fourth industrial revolution. Finally, Section 5 talks about important aspects of toxicity, safety, risk and ELSI of functionalized MNPs. Finally, the conclusion sums up the future of analytical chemistry with functionalized MNPs. Overall, this book is planned to be a reference book for chemists, materials scientists, researchers, and chemical engineers who are searching for new and advance materials for various analytical purposes. Moreover, university graduates will find this book to be very useful in their research and understanding the advancement in analytical techniques with functionalized MNPs and beyond. The editor and authors are famous researchers, scientists and true professionals from academia and industry. On behalf of the Royal Society of Chemistry, we are very appreciative to the authors of all chapters for their magnificent and outstanding efforts in the making of this book. Special thanks to Janet Freshwater (Senior Commissioning Editor) and Liv Towers (Editorial Assistant) at the Royal Society of Chemistry, for their enthusiastic support and committed help during this project. And finally, special thanks to the Royal Society of Chemistry for publishing this book. Chaudhery Mustansar Hussain

About the Editor

Chaudhery Mustansar Hussain, PhD is an Adjunct Professor and Director of Labs in the Department of Chemistry & Environmental Sciences at the New Jersey Institute of Technology (NJIT), Newark, New Jersey, USA. His research is focused on the applications of Nanotechnology & Advanced Technologies & Materials, Analytical Chemistry, Environmental Management, and Various Industries. Dr. Hussain is the author of numerous papers in peer-reviewed journals as a well as prolific author and editor of scientific monographs and handbooks in his research areas.

Analytical Applications of Functionalized Magnetic Nanoparticles Edited by Chaudhery Mustansar Hussain r The Royal Society of Chemistry 2021 Published by the Royal Society of Chemistry, www.rsc.org

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Contents Section 1. Introduction Chapter 1 Analytical Applications of Functionalized Magnetic Nanoparticles (Introduction) Hamid Rashidi Nodeh and Binta Hadi Jume 1.1 Introduction 1.2 Sample Preparation Techniques 1.3 Magnetic Solid Phase Extraction (MSPE) 1.4 Functionalized Magnetic Nanoparticles 1.5 Application of MSPE 1.6 Force Interactions Between Analytes and Sorbents 1.7 Conclusion Acknowledgements References Chapter 2 Design of Functionalized Magnetic Nanoparticles for Improving Stabilization, Biocompatibility and Uptake Efficiency Iqra Azeem, Senem Çitog˘lu, Hatice Duran and Basit Yameen 2.1 2.2 2.3 2.4

Introduction Design of Functional Magnetic Nanoparticles (FMNPs) Synthetic Route to FMNPs Chemical Design of FMNPs 2.4.1 Metal-based Magnetic Nanoparticles (MMNPs)

Analytical Applications of Functionalized Magnetic Nanoparticles Edited by Chaudhery Mustansar Hussain r The Royal Society of Chemistry 2021 Published by the Royal Society of Chemistry, www.rsc.org

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3

3 4 5 6 7 10 10 11 11

20

20 22 22 23 24

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Contents

2.4.2

Metal Alloy-based Magnetic Nanostructures (MAMNs) 2.4.3 Metal Oxide-based Magnetic Nanoparticles (MOMNPs) 2.4.4 Metallic Carbides and Nitride-based Magnetic Nanostructures (MC/NMNs) 2.4.5 Multifunctional Nanoparticle-based Magnetic Nanostructures (MNMNs) 2.5 Physicochemical Features of FMNPs 2.5.1 NP Size 2.5.2 NP Crystallinity 2.5.3 Chemical Composition 2.5.4 Surface Potential 2.5.5 Interfacial Interactions 2.5.6 Magnetism 2.6 Surface Functionalization and Biocompatibility 2.6.1 Surface Stability via Organic/Inorganic Coatings 2.6.2 Organic Coating Materials 2.6.3 Inorganic Coating Materials 2.6.4 Biocompatibility of FMNPs 2.7 Biomedical Applications of FMNPs 2.7.1 FMNPs as Biosensors 2.7.2 FMNPs for Protein Purification/ Bioseparation 2.7.3 FMNPs as Contrast Agents for MRI 2.7.4 FMNPs for Targeted Drug Delivery 2.7.5 FMNPs for Magnetic Hyperthermia 2.8 Future Trends and Perspective Acknowledgements References Chapter 3 Improvement of Adsorbing Properties of Magnetic Nanomaterials by Bioorganic Substrate-mediating Synthesis P. Caregnato, D. F. Mercado and M. C. Gonzalez 3.1 3.2

Introduction Preparation of Magnetic Nanoparticles 3.2.1 Iron Oxide Magnetic Nanoparticles 3.2.2 Preparation of Iron-containing Hydroxyapatite 3.2.3 Functionalized Nanoscale Magnetic Particles

25 26 27 28 30 30 31 32 32 33 33 35 35 36 37 38 38 39 40 41 42 43 45 46 47

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3.3

Results and Discussion 3.3.1 Mnp, Mnp@YM4 and Mnp@YM10 Characterization 3.3.2 YM–Iron Oxide Magnetic Nanoparticles. Adsorption of MB 3.3.3 Fe-nAp and SBO–Fe-nAp Characterization 3.3.4 Fe-nAp and SBO–Fe-nAp: Adsorption of Pb(II) and Cu(II) 3.4 Conclusion Acknowledgements References

60 61 62 64 66 69 70 70

Section 2: Functionalized Magnetic Nanoparticles in Sample Pre-treatment Chapter 4 Functionalized Magnetic Nanoparticles in Sample Pre-treatment Sanu Mathew Simon, M. S. Sajna, V. P. Prakashan, Twinkle Anna Jose, P. R. Biju, Cyriac Joseph and N. V. Unnikrishnan 4.1 4.2 4.3 4.4 4.5 4.6 4.7 4.8 4.9 4.10 4.11 4.12 4.13 4.14

Introduction Different Magnetic Nanoparticles for Extraction and their Magnetic Behavior The Necessity of Functionalized Magnetic Nanoparticles Sample Preparation Techniques Types of Functionalized Magnetic Materials Application of Functionalized MNPs with Silica Application of Functionalized MNPs with Octadecylsilane (ODS) Application of Functionalized MNPs with a Carbon-based Material Activated Carbon-based Magnetic Nanoparticles Graphene-based Magnetic Nanoparticles Carbon Nanotube (CNT)-based Magnetic Materials Surfactant-modified Magnetic Materials Polymer-modified Magnetic Nanoparticles Extraction Techniques 4.14.1 Functionalized MNPs in Solid-Phase Extraction 4.14.2 Functionalized MNPs in Magnetic Solid-phase Extraction

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79 80 82 83 84 84 86 91 91 92 94 98 101 103 103 105

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4.15 Summary Acknowledgements References Chapter 5 Application of Functionalized Magnetic Nanoparticles for Organic Analyte Extraction ´. Gonza ´lez-Curbelo, G. Jime´nez-Skrzypek, M. A ´lez-Sa ´lamo, C. Ortega-Zamora and J. Gonza ´ndez-Borges J. Herna 5.1 5.2 5.3

Introduction Polymeric Magnetic Nanoparticles Magnetic Nanoparticles Based on Allotropic Forms of Carbon 5.4 Metal Organic Framework Coatings 5.5 Covalent Organic Framework Coatings 5.6 Ionic Liquids 5.7 Miscellaneous 5.8 Conclusions Abbreviations Acknowledgements References Chapter 6 Graphene-based Sorbents for Modern Magnetic Solid-phase Extraction Techniques Fernando Mauro Lanças, Deyber Arley Vargas Medina, Natalia Gabrielly Pereira Dos Santos and Marcela Jordan Sinisterra 6.1 6.2

6.3

Introduction Graphene-based Magnetic Sorbents 6.2.1 Preparation of Graphene-based Magnetic Sorbents Functionalization of Graphene-based Magnetic Sorbents 6.3.1 Molecularly Imprinted Polymers (MIPs) 6.3.2 Metal–Organic Frameworks (MOFs) 6.3.3 Ionic Liquids (ILs) and Deep Eutectic Solvents (DESs) 6.3.4 Boronate Affinity Materials (BAM) 6.3.5 Supramolecules 6.3.6 Aptamers 6.3.7 Miscellaneous Functionalities

106 106 106

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122 126 134 141 146 152 157 161 161 163 163

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174 178 178 182 183 183 183 184 185 185 186

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6.4

Characterization of Graphene-based Magnetic Sorbents 6.5 Modern Applications of Graphene-based Magnetic Sorbents 6.5.1 Applications on the Extraction of Organic Pollutants 6.5.2 Applications on the Extraction of Inorganic Pollutants 6.5.3 Applications on the Extraction of Biological Macromolecules 6.6 Conclusion Acknowledgements References

186 189 191 193 194 194 195 195

Chapter 7 Magnetic Nanoparticles as an Efficient Tool for Analyte Extraction: Challenges and New Opportunities 200 M. Rapa, L. Maddaloni, R. Ruggieri, I. Fratoddi and G. Vinci 7.1 7.2

Introduction Sample Pre-treatment: A Key Step in Analytical Determination 7.3 MNPs for Analyte Extraction 7.3.1 Environmental Applications 7.3.2 Food Applications 7.3.3 Biological Applications 7.4 Conclusions References Chapter 8 Functionalized Magnetic Nanoparticles for Solid-phase Extraction Evrim Umut 8.1 8.2 8.3

Introduction Principles and Methods Material Selection and Design 8.3.1 Magnetic Core 8.3.2 Particle Coating and Functionalization 8.4 Applications of MSPE 8.4.1 Environmental Applications 8.4.2 Food Applications 8.4.3 Biological and Pharmaceutical Applications Abbreviations References

200 203 204 205 207 209 211 211

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Section 3: Functionalized Magnetic Nanoparticles in the Separation/Identification Stage of Analysis Chapter 9 Use of Functionalized Magnetic Nanoparticles in Modern Separation Techniques 239 Saurabh Shukla, Ramsha Khan, Abhishek Saxena and Chaudhery Mustansar Hussain 9.1 9.2

Introduction Synthesis of MNPs 9.2.1 Thermal Decomposition Technique 9.2.2 Sol–Gel Synthesis 9.2.3 Hydrothermal Synthesis 9.2.4 Coprecipitation Technique 9.2.5 Microemulsion-based Synthesis 9.2.6 Flow Injection Synthesis 9.2.7 Aerosol/Vapor-phase-based Synthesis 9.3 Chromatography: An Overview 9.3.1 Considerations for an Effective Chromatographic Separation 9.3.2 Functionalized MNPs in GC 9.3.3 Liquid Chromatography (LC) 9.4 Application of Functionalized MNPs in Separation Techniques 9.4.1 Magnetic Solid Phase Extraction (MSPE) 9.5 Conclusion References Chapter 10 Chromatographic Applications of Functionalized Magnetic Nanoparticles ¨stem Keçili, I_ brahim Dolak, Gurbet Canpolat and Ru Chaudhery Mustansar Hussain 10.1 10.2

Introduction Preparation Techniques for MNPs 10.2.1 Thermal Decomposition Approach 10.2.2 Co-precipitation Approach 10.2.3 Sol–Gel Process 10.2.4 Hydrothermal Technique 10.2.5 Microemulsion Technique 10.2.6 Flow Injection Technique 10.2.7 Aerosol/Vapor-phase-based Approaches

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10.3

Chromatographic Applications of Functionalized Magnetic Nanoparticles (MNPs) 10.3.1 Capillary Electrochromatography (CEC) 10.3.2 Chip-based Chromatography 10.4 Conclusions References

266 266 270 274 274

Section 4: Functionalized Magnetic Nanoparticles in Detection Stage of Analysis/Miniturization devices Chapter 11 Functionalized MNPs in Detection Stage of Analysis/Miniaturization Devices Mojtaba Bagherzadeh 11.1

Transduction Methods in Sensing Based on MNPs 11.1.1 Electrochemical 11.1.2 Optical 11.1.3 Piezoelectric 11.1.4 Magnetic Field 11.2 Applications of MNPs in Detection Analysis 11.2.1 Biomolecules and Cells 11.2.2 Organic Compounds 11.2.3 Ions and Inorganic Compounds References

279

281 282 286 288 290 292 292 294 294 295

Chapter 12 MNP-based Sensor Development to Evaluate Food Quality and Safety 310 L. Maddaloni, M. Rapa, R. Ruggieri, M. Santonico and G. Vinci 12.1 12.2

Introduction Sensors 12.2.1 Sensor Classification and Properties 12.2.2 NP Properties for NP-based Sensors 12.3 MNP-based Sensor 12.3.1 MNP-based Sensors for Food Safety 12.3.2 MNP-based Sensors for Food Quality 12.4 Conclusion References Chapter 13 Functionalized Magnetic Nanoparticle (MNPs)-based Biosensors K. Vasic´ and M. Leitgeb 13.1

Introduction

310 312 312 315 315 316 320 320 321

324

324

xvi

Contents

13.2

Synthesis, Properties and Characterization of MNPs 13.3 Biosensors Based on MNPs 13.3.1 Electrochemical Biosensors 13.3.2 Optical Biosensors 13.3.3 Piezoelectric Biosensors 13.3.4 Magnetic Field Biosensors 13.4 Enzyme-based Biosensors 13.4.1 Glucose-based Biosensors 13.4.2 Cholesterol-based Biosensors 13.5 Conclusions and Future Trends Acknowledgements References Chapter 14 Sensing Applications by Functionalized Magnetic Nanoparticles Natalia L. Pacioni 14.1 14.2

Introduction Analytical Strategies Based on Optical Sensing 14.2.1 UV–Visible Absorbance 14.2.2 Luminescence 14.2.3 Surface Enhanced Raman Spectroscopy 14.3 Analytical Strategies Based on Electrochemical Sensing 14.4 Concluding Remarks Acknowledgements References Chapter 15 Magnetoresistance-based Biosensors Apoorva Sharma, Ashok D. Chougale, Georgeta Salvan and Prashant B. Patil 15.1 15.2

15.3

15.4

Introduction Magnetoresistive Sensors 15.2.1 Anisotropy Magnetoresistance Sensors 15.2.2 Giant Magnetoresistance Sensors 15.2.3 Tunnel Magnetoresistance Sensors 15.2.4 Spin-Valves and Pseudo Spin-Valves MNPs in MR-based Biosensors 15.3.1 High Magnetic Moment 15.3.2 Biocompatibility 15.3.3 Colloidal Stability Functionalization

327 327 328 331 333 334 335 336 338 339 340 340

347

347 349 349 356 360 362 365 365 366 369

369 371 373 373 376 378 378 379 380 380 380

Contents

xvii

15.5

Assays for MR-based Biosensors 15.5.1 Direct Assay 15.5.2 Sandwich Assay 15.5.3 Competitive Assay 15.6 Device Concept 15.6.1 Magnetic Tags 15.6.2 Magnetic Field Sensor 15.6.3 Sensor Surface Passivation and Functionalization 15.6.4 Magnetic Field Source 15.6.5 Microfluidic Channel 15.6.6 Readout Electronic 15.7 Future Perspectives Websites of Interest Acknowledgements References

381 381 384 385 386 387 387 387 389 389 389 391 392 392 392

Section 5: Other Analytical Applications Functionalized Magnetic Nanoparticles Chapter 16 Analytical Applications of Molecularly Imprinted Polymer-decorated Magnetic Nanoparticles Abderrahman Lamaoui, Laura Cubillana-Aguilera, Marı´a Luisa Almoraima Gil, Aziz Amine and Jose´ Marı´a Palacios-Santander 16.1 16.2

16.3

16.4

16.5

Introduction Generalities 16.2.1 Magnetic Nanoparticles 16.2.2 Molecularly Imprinted Polymers Preparation of MIP-decorated MNPs 16.3.1 Preparation and Modification of MNPs 16.3.2 Decoration of MNPs by MIPs Characterization of MIP-decorated MNPs 16.4.1 Morphological Characterization 16.4.2 Structural Characterization 16.4.3 Magnetic Characterization 16.4.4 Adsorption Characterization Application of MIP-decorated MNPs for Solid-phase Extraction 16.5.1 Introduction to Solid-phase Extraction (SPE) and Dispersive SPE 16.5.2 Application of Magnetic MIPs in Dispersive Solid-phase Extraction

399

399 402 402 402 407 407 407 409 409 410 410 410 411 411 412

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Contents

16.6

MIP-decorated MNPs for Sensing 16.6.1 MIP-decorated MNPs for Electrochemical Sensors 16.6.2 MIP-decorated MNPs for Optical Sensors 16.7 Recent Advances in the Analytical Applications of Magnetic MIPs 16.7.1 Food Safety 16.7.2 Emerging Pollutants 16.7.3 Disease Biomarkers 16.7.4 Medical Treatment and Drugs 16.8 Conclusions References Chapter 17 Characterization of Functional Magnetic Nanoparticle-modified Polymeric Composites by Computer Modeling Z. Hu and J. Kanagaraj 17.1 17.2

Introduction Computer Modeling 17.2.1 Fundamental of Electro-magnetic Wave 17.2.2 Effective Permittivity and Permeability of Nanocomposites 17.2.3 Analytical Calculation of Effective Permittivity and Effective Permeability 17.2.4 Modeling of Nanocomposites 17.3 Results and Discussion 17.3.1 Effect of Distribution of Cubic Nanoparticles 17.3.2 Effect of Shape and Orientation of Nanoparticles 17.3.3 More Result Displays of the Randomly Distributed Nanoparticle Model 17.4 Conclusion Acknowledgements References Chapter 18 Functionalized Magnetic Nanoparticle-based Sensors for Point-of-care Applications: From the Preparation to Practical Applications Ahmet Ulu and Burhan Ates 18.1

Introduction

414 414 415 417 417 419 420 420 424 424

429

429 435 435 437 439 439 441 441 444 445 446 447 447

454

454

Contents

xix

18.2

Preparation and Functionalization of MNPs 18.2.1 Preparation of MNPs 18.2.2 Functionalization of MNPs 18.3 Point-of-care Approaches 18.4 fMNP-based Sensors for PoC Applications 18.5 Conclusions Important Websites References Chapter 19 Fourth Industrial Revolution (4IR) and Functionalized MNPs Paolo Di Sia 19.1 19.2 19.3 19.4

Introduction On Industry 4.0 Enabling Technologies On Artificial Intelligence and Machine/Deep Learning 19.5 Nanotechnology: Applications of Functionalized Nanoparticles 19.6 Targeted Transport of Medicines (Drug Delivery) and Genes 19.7 Physiological Tissues Treatment 19.8 Metals 19.9 Conclusions Websites of Interest References

455 455 461 475 476 481 481 481

489

489 490 492 493 495 497 497 498 499 500 501

Section 6: Toxicity, Safety and Risk and Legal Aspects of Functionalized Magnetic Nanoparticles Chapter 20 Important Aspects of Safety, Risk & ELSI of Functionalized Magnetic Nanoparticles for Analytical Purposes 507 ¨ce and Hatı¨ce Duran Senem Çı¨tog˘lu, Fatma Go¨zde Yu 20.1 20.2 20.3 20.4 20.5 20.6

Introduction Toxicity of FMNPs Biodistribution and Bioelimination of Nanoparticles Mechanism of NP Toxicity Toxicity Effect on the Environment: Nanoecotoxicity Toxicity Effect on Human Health

507 508 510 511 513 517

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Contents

20.6.1 In Vitro Research on FMNPs 20.6.2 In Vivo Research on FMNPs 20.7 Risk Assessment of FMNPs 20.7.1 Dose–Response Assessment 20.7.2 Exposure Assessment 20.8 Ethical Issues 20.9 Conclusion and Future Trends Abbreviations Acknowledgements References Chapter 21 Functionalized Magnetic Nanoparticles (MNPs): Toxicity, Safety and Legal Aspects of Functionalized MNPs Ladan Rashidi 21.1 21.2

Introduction Physicochemical Properties of Functionalized- and Unfunctionalized-MNPs and Their Influence on Toxicity 21.3 Toxicological Testing 21.3.1 In Vitro Testing of Functionalized-MNPs 21.3.2 In Vivo Toxicity of Functionalized MNPs 21.4 Comparison Between In Vitro and In Vivo Toxicity Studies of Coated and Bare MNPs 21.4.1 In Vitro Toxicity Comparative Studies of Coated and Bare MNPs 21.4.2 In Vivo Toxicity Comparative Studies of Coated and Bare MNPs 21.5 Legal Aspects of Functionalized MNPs 21.6 Conclusion Abbreviations Websites of Interest References

517 520 520 521 521 521 522 523 524 524

527

527

529 530 531 533 534 534 537 538 541 541 542 542

Section 7: Conclusion: The Future of Analytical Chemistry Chapter 22 Functionalization of Magnetic Nanoparticles for Tomorrow’s Applications Aditya Narayan Singh and Chaudhery Mustansar Hussain 22.1

Introduction 22.1.1 Intriguing Features of Nanoparticles 22.1.2 Synthesis of Magnetic Nanoparticles

549

549 552 554

Contents

xxi

22.1.3 Stabilizing Magnetic Nanoparticles 22.1.4 Application of Magnetic Nanoparticles 22.1.5 Future Prospects 22.2 Conclusion Websites of Interest Acknowledgements References Chapter 23 Future of Functionalized Magnetic Nanoparticles in Analytical Chemistry Ramsha Khan, Saurabh Shukla, Achlesh Daverey and Chaudhery Mustansar Hussain 23.1 23.2

Introduction Future Scope of Functionalized Magnetic Nanoparticles in Analytical Applications 23.2.1 Application of Functionalized MNPs in Sample Preparation 23.2.2 Scope of Functionalized MNPs in Biological Synthesis 23.2.3 Use of Functionalized MNPs in the Medical Field 23.2.4 Other Applications of Magnetic Nanoparticles 23.3 Conclusion References Subject Index

558 561 567 567 568 568 568

574

574 579 579 581 581 587 589 590 596

Section 1. Introduction

CHAPTER 1

Analytical Applications of Functionalized Magnetic Nanoparticles (Introduction) HAMID RASHIDI NODEH*a AND BINTA HADI JUMEb a

Food Technology and Agricultural Products Research Centre, Standard Research Institute, Karaj 31745-139, Iran; b Chemistry Department, College of Science and General Studies, University of Hafr Al-Batin, Al-Jamiah 39524, Eastern Province, Kingdom of Saudi Arabia, Email: [email protected] *Emails: [email protected]; [email protected]

1.1 Introduction Over the last decade, researchers in the applied sciences have shown great interest in the synthesis of magnetic nanoparticles (MNPs) and their application in environmental, food and biological approaches.1–3 Different types of these MNPs based on iron oxide II and III were prepared and investigated, such as magnetite, gamma iron oxide, platinum–iron oxide, nickel–iron oxide, titanium–magnetite, cobalt–magnetite, zinc–iron oxide, copper–iron oxide, manganese–magnetite, gold–magnetite, and magnetite–silica. Magnetic metal-oxide based nanoparticles possess high saturation magnetization properties and are a suitable material to use in drug/gene delivery or clinical use.4,5 Various methods have been used to synthesize MNPs including alkaline co-precipitation, microwave, hydrolysis, hydrothermal and flame spray methods.6 Recently, other methods have also been reported, including high thermal, sol–gel, oxidation, sonochemistry, and electrochemistry.4 Among the various types of magnetic nanoparticles, magnetite (Fe3O4) nanoparticles are Analytical Applications of Functionalized Magnetic Nanoparticles Edited by Chaudhery Mustansar Hussain r The Royal Society of Chemistry 2021 Published by the Royal Society of Chemistry, www.rsc.org

3

4

Chapter 1

the most common because they have a relatively small particle size (o100 nm), superior paramagnetic properties, appropriate surface area, good water dispersal, ease of functionalization, have greater permeability, less toxicity and are easy to synthesize via chemical co-precipitation.7–9 Magnetic nanoparticles were widely used in water treatment to extract or remove contaminates such as metal ions, pesticides, aromatic hydrocarbons, sulfonamides and phthalates in food and environmental water samples.10,11 Smart magnetic nanoparticles were also widely used as a sorbent in analytical sample preparation of biological samples and pharmaceutical analysis.11,12 However, pharmaceutical compounds, heavy metal ions, dyes and many other pollutants are hazardous for humans, animals and health,13,14 thus, development of rapid and sensitive techniques is important to analysis of hazardous species prior to discharge in the environmental cycle.13,14 Recently, MNPs and its derivatives are used as sorbents in sample preparation techniques to speed up the conventional techniques and overcome their drawbacks.15–17 Solid phase extraction (SPE) is the well-known sample preparation technique that is widely used in analytical chemistry toward various analytes and samples. Conventional SPE is a sensitive, simple, and flexible technique that has the ability to automate, but it suffers from the fact that it takes a long time for analysis (tedious and time consuming) and cartridges channeling/blocking. Hence, at the end of the 1990s, in order to overcome the limitation of liquid-based and solid-based extraction techniques, magnetic solid phase extraction (MSPE) was introduced.18 In the MSPE technique, magnetic-based nanoparticles are used as sorbents and are dispersed into aqueous solution, followed by rapid collection using an external magnet. The utilization of magnetic nanoparticles in analytical applications has been gaining interest. Figure 1.1 illustrates the trend of the magnetic solid phase extraction, magnetic sample preparation, cleanup and determination in various sample matrices in the last 5 years. The trend has been increasing from 2018 to 2020.

1.2 Sample Preparation Techniques Sample preparation is a key factor in analytical chemistry since it directly affects the instrument’s response, selectivity and analysis recoveries.19–21 Hence, quantitative analysis of analytes or pollutants in environmental water, drinking water, food, agricultural products, biological media of milk, urine, plasma and blood requires the removal of interferences to enhance the high extraction recovery with appropriate selectivity.22–26 Various sample preparation techniques are developed for food, dairy products, grocery, agricultural products, environmental samples and biological samples. The most common sample preparation techniques include liquid–liquid extraction (LLE), liquid–liquid microextraction (LLME), liquid–liquid microextraction (DLLME), QuEChERS (quick, easy, cheap, effective, rugged and safe), column chromatography extraction (CCE), solid phase extraction (SPE), solid phase microextraction (SPME), dispersive solid phase extraction (dSPE), stir bar sportive extraction

Analytical Applications of Functionalized Magnetic Nanoparticles (Introduction)

5

250

200

Frecuency

150

100

50

0 2017

2018

2019

2020

2021

Years

Figure 1.1

Frequency of the use of magnetic materials for extraction and analytical determination of various analytes from various sample matrices from 2017–2021 as obtained from a Scopus search using the keywords ‘‘analytical application of the magnetic material’’ on 04 October 2020.

(SBSE) and magnetic solid phase extraction (MSPE). The proposed techniques owe their advantages and disadvantages e.g., LLE consumes a large volume of hazardous immiscible organic solvents, LLME/DLLME is not selective, QuEChERS is most effective for polar and mid-polar compounds and is highly suitable for food analysis.27 SPME and SBSE are solvent-less methods that enhance the enrichment of organic compounds from headspace and aqueous matrices, respectively. The SPME’s fiber is relatively expensive and fragile.28 SPE is the most popular and standard technique that is widely used as an extraction and clean-up agent. The advantages of SPE techniques include high preconcentration factor, flexible, selective, easy to automate, regenerable and low organic solvent use.29,30 However, SPE is a tedious and time-consuming technique that also needs expensive cartridges, a vacuum manifold chamber, vacuum pump, back pressure and sorbent channeling.23,31 Hence, researchers are addressing these problems through the development of new dispersive SPE based on MNPs, that are known as magnetic solid phase extraction (MSPE). MSPE can enhance the extraction process by using an external magnet, which does not need filtration and centrifugation.

1.3 Magnetic Solid Phase Extraction (MSPE) Magnetic separation technology (MST) was introduced first in 1909 to isolate iron from ore.32 Several decades later, magnetic separation was established

6

Chapter 1

as a powerful separation technique in bio-separation, environmental and material science. As discussed previously, the application of magnetic nanoparticles in extraction methodology can overcome the conventional SPE disadvantages.18 Incorporation of magnetic nanoparticles in sorbent can enhance the extraction process by using an external magnet without the need for a filtration and centrifugation process.33 Hence, using a magneticbased material as the SPE sorbent provides advantages including low cost, easily extracted with an external magnet from liquid samples, quick, short extraction time, water dispersive, high adsorption capacity and sensitive to polar and nonpolar pesticides.23 Magnetic solid phase extraction procedures include several aspects; 1 Synthesis (preparation) of magnetic nanoparticles or magnetic-based materials. 2 Modifying or functionalizing magnetic nanoparticles with different materials in order to increase selectivity, increase adsorption capacity, increase stability and adapt to different environments. 3 Dispersing of the modified magnetic nanoparticles into the solution containing analytes. 4 Shaking or vortexing the solution in order to extract the analytes from the solution onto the solid phase adsorbent. 5 Collecting the magnetic sorbent from the solution by assistance of an external magnet. 6 Desorption of trapped analytes using a suitable solvent with stirring or ultrasound. 7 Separating or collecting the adsorbent again with a magnet for reuse. 8 Collecting solvent that contains analytes. 9 Instrument analysis in order to identify the analytes.

1.4 Functionalized Magnetic Nanoparticles In chromatography applications, sample pre-treatment and sample preparation, getting rid of the undesired complex matrices is essential for eliminating the interferences. Nanotechnology based on nanomaterials has improved the pre-treatment problems in analytical chemistry.34,35 In order to improve the efficiency and performance of MSPE in terms of stability, chemical compatibility and selectivity, researchers have functionalized MNPs with different materials.23,36 MNPs can be easily functionalized with various natural, synthetic and biological materials including carbon-based, polymer-based, liquid-based, supramolecular materials, metal oxides, silica-gel and biomolecules.37–41 A wide variety of SPE sorbents have been introduced including octadecylsilane, hybrid organic–inorganic sol–gel42 multiwall carbon nanotubes,43 and molecularly imprinted polymers.44,45 In the current work, MNP-based dispersive MSPE offers advantages of high extraction percentage due to the high surface area of the adsorbent phase, fast separation, convenient and facile surface modification of the extraction phase, good reusability and excellent

Analytical Applications of Functionalized Magnetic Nanoparticles (Introduction)

7

46,47

dispersibility in aqueous solutions. MNPs can be synthesized by various methods ranging from simple, cheap and scaled-up solution-based coprecipitation, microemulsion, microwave-assisted, sonochemical, thermal decomposition and solvothermal, to more complicated instrumental-based chemical vapor deposition, carbon arc, combustion synthesis and laser pyrolysis techniques.48 Meanwhile various types of analytes were successfully isolated from different matrices such as aqueous solutions, foods, vegetables and fruits using MSPE. In order to improve the selectivity and extraction efficiency of MNPs toward analytes, modifications were made by using materials such as silica-gel, green solvent of ionic liquid or deep eutectic solvent, metal organic framework, synthetic or natural polymers, biological species or biomolecules and carbon nanomaterial. The vast majority of MNPs used for contaminate extraction are composed of carbon-based materials such as activated carbon, carbon nanotube, graphene, carbon black and biochar.15,49–51 Lately plain or imprinted polymers and biopolymer materials (Table 1.1) have been widely applied as modifications for MNPs due to the network nature of polymers that can enhance p–p interactions, covalent bonding and electrostatic interaction toward pollutant analytes.46,52,53 Likewise, the stable, tunable and amphoteric nature of most polymers enable their applicability for extracting both nonpolar and polar analytes.43,54–56 Ionic liquid is one eco-friendly material that is applied for the modification of MNPs in order to improve the sensitivity, rapidity and accuracy of an extraction procedure and analysis.57–60 Hence, the surface functionalization of MNPs via different types of materials can be in three procedures of physical decoration through a facile one-step chemical precipitation, chemical grafting with a silica-gel layer and simultaneous oxidation and polymerization.61

1.5 Application of MSPE MSPE method-based magnetic materials are widely used in food, environmental water and biological sample analysis or bioanalytical application.62,63 Recently, ionic liquids and deep eutectic solvent-supported magnetic nanoparticles have been considered as a green sorbent in analytical sample preparation.64,65 An ionic liquid based on magnetic nanoparticles can provide a large effective contact area, high viscosity and repeatable extractant to analytes from aqueous media.60 Careful tailoring of a magnetic ionic liquid is applicable in both hydrophilic and hydrophobic samples.64 A new type of green magnetic solvent is developed based on iron oxide and deep eutectic solvent for extraction of protein from bovine blood with 97.8% efficiency.66 A novel ternary hydrosulfonyl DES based on magnetic graphene has been used as an MSPE sorbent applied for the preconcentration of mercury ions from water samples. The presence of hydrosulfonyl in DES increases the affinity of the magnetic adsorbent toward mercury ions with a high removal efficiency of 99% and adsorption capacity of 215 mg g1.67 Anion exchange magnetic ionic liquids have been developed for the enhanced preconcentration of pyrethroids pesticides.59 Magnetic polyoxometalate ionic liquids have

Sample

Magnetic materials

Biological samples

Poly(1-vinylimidazole)-MNPs Gold MNPs-melamine-phytate supermolecular Anticancer drug (dasatinib, erlotinib, nilotinib) Carbon nanotube–MNPs Cyanide metabolite Bis(di-2-pyridyl)methylene Mercury thiocarbohydrazide–MNPs Deep eutectic solvent–SiO2–MNPs Trypsin

Food samples

Zr–Fe–C MNPs Magnetic covalent organic framework CuO–ZnO–CNT MNPs

Fluoroquinolones Polycyclic aromatic hydrocarbons Chlorogenic acid

Molecularly imprinted polymer–MNPs Polydopamine–MNPs

Acrylamide Copper

Environmental [1,5-bis (2-pyridyl) samples 3-sulfophenylmethylene] thiocarbonohydrazide–MNPS Metal organic framework–MNPs Polydopamine dendrimer–MNPs Fluorinated carbon nanotube–MNPs Agricultural products

Analytes

Imprinted polymer–MNPs

Arsenic Heterocyclic pesticides Anti-inflammatory drugs Perfluoroalkyl carboxylic acid Lead(II)

LOD

Human urine 7.9 ng L1 Plasma, serum, urine 0.12 mg mL1

Reference 85 86

Urine, bovine blood Biological sample

15 ng mL1 7.8 ng L1

87 88

Crude bovine pancreas Baby food Fish grilled and smoked bacon Plants Food Water Biscuit Baby food, muesli, macaroni, honey Water

233 mg g1 (capacity) 1.5 mg L1 0.83 ng L1

89 90 91

0.034 ng mL1 92 1.3 mg kg1 0.22 mg L1

93 94

2.7 ng L1

95

Water Water Water

0.04 mg L1 0.05 ng mL1 0.01 ng L1

96 97 98

Various types of fruits and vegetables Tea leaves Irrigation water Tomato, cucumber, parsley

0.48 ng mL1

99

99% efficiency 100 101 0.07 mg L1 0.2 mg kg1 102

Chapter 1

Magnetic ionic liquids Polyphenols Metal organic framework–CNTs–MNPs Pesticides Metal organic framework (MIL-101) MNPs Cd(II), Pb(II) and Ni(II)

Matrix name

8

Table 1.1 Magnetic solid phase extraction (MSPE) of different analytes from various samples of biological, food, environmental water and agricultural products.

Analytical Applications of Functionalized Magnetic Nanoparticles (Introduction)

9

been developed as an MSPE sorbent for extraction of organophosphorus pesticides from fruit juice with a low limit of detection of 0.02 ng mL1.57 Hydrophobic magnetic ionic liquids based on perfluoroalkyl ester and iron oxide carboxylate have been applied for extraction of pesticides from water samples.68 Magnetic graphene functionalized ionic liquids effectively extracted the eight polycyclic aromatic hydrocarbons from edible oil within the legal limit of efficiency in the range of commission regulation.69 MNPs anchored over graphene oxide was developed as an efficient sorbet for extraction of HMFs from honey prior to HPLC analysis.70 MNPs was doped on graphene sheets and used for extraction of fluoroquinolone from food with a high enrichment factor of 79-fold and limit of detection of 0.05 ng g1,71 and organophosphorus pesticide extraction from vegetables and fruit with a limit of detection of 6.5 ng mL1.72 Carboxylate graphene-MNPs were applied for extraction of sulfonamide from environmental water; the large volume of –COOH groups highly concentrated the amine-based contamination of sulfonamides with a low limit of detection of 0.4 ng L1 and high enrichment factor of 1702.73 Graphene oxide-decorated MNPs simultaneously extracted heavy metal ions (Ag, Au, Ir, Os, Pd, Pt, Sb and Hg) from aqueous media prior to ICP-OES analysis with a limit of detection in the range of 0.05–0.33 mg L1.74 Cellulose nanocrystal magnetic graphene provided high efficiency for fluoroquinolones from water at pH 6 with a regulation limit of 6.5 ng g1.75 Magnet carbon nanotube and graphene simultaneously isolated the acidic and basic pesticides from food samples with less interference effects at pH 7.4.15,76,77 MNPs functionalized with different silica-based materials of C18, hybrid sol–gel and C8 with hydrophobic interactions applied for fast preconcentration of analytes from water, food, agricultural products and biological media.78–80 Magnetic hybrid silica gel was used as a clean-up sorbent for the isolation and determination of hazardous acrylamide from potatoes, chips, bread, plants and snakes.80 Phenyl-modified MNPs efficiently isolated poly-cyclic aromatic hydrocarbons from soil samples with a regulation limit of 0.07 ng g.81 Originally modified silica-MNPs with formylphenoxypropane provided a low level of extraction for the extraction of valuable metal ions, such as gold, palladium and silver from aqueous samples.82 Synthetic or natural polymers as an amphoteric reagent are widely immobilized with MNPS to extract analytes from various samples. Magnetic polyaniline gained a very low limit of detection for polar antimicrobials from biological samples.62 MSPE based on functionalized magnetic polypyrrole– polythiophene was used for the enrichment of heavy metal ions from aqueous media. The presence of N and S atoms on the adsorbent moieties enhances the high efficiency (80 mg g1) and low limit of detection of 0.15–0.65 mg L1 toward metal ions.61 Natural green magnetic adsorbent was developed based on chitosan to extract organophosphorus pesticides with a high extraction efficiency 99%.52 Polyaniline, polydopamine, and polypyrrole as synthetic polymers were immobilized with magnetic nanoparticles and used as MSPE adsorbents for effective extraction of pyrethroids, benzoylurea and organochlorine pesticides, respectively, from water, fruit and juice samples.58,83,84

10

Chapter 1

Table 1.1 illustrates the application of magnetic solid phase extraction techniques in some biological, food, environmental and agricultural product sample preparation. As illustrated, magnetic nanoparticles were modified and functionalized with different chelates or substrates for the preconcentration of various analytes from complex matrixes. The low level of detection (LOD) for analytes may be due to the fact that the MSPE based on a magnetic material can be used as alternative technique to the extraction, preconcentration, isolation and clean-up process.

1.6 Force Interactions Between Analytes and Sorbents In the SPME technique, nominating the adsorption mechanism or interactions between the magnetic material and analytes is important. Since, by considering the force interactions one can design a selective and efficient adsorbent with high adsorption capacity. Hence, through a survey of the literature, scholars have proposed several force interactions to describe the uptake of analytes into a magnetic adsorbent. The proposed force interactions include van der Waals forces, p–p donor/acceptor, hydrogen bonding, hydrophilic, hydrophobic, dipole–dipole electrostatic, ion exchange, and size exclusion. The functional materials of graphene, carbon nanotube, calixarenes, and benzenoid polymers and MOFs contain large delocalized p-electron systems that promote both hydrophobic interactions and p–p interactions with analytes including the benzene ring (i.e., PAHs, polyphenols, chlorophenols, pesticides, antioxidants, mycotoxins and antibiotics). The proposed substrates can enhance electrostatic, p-cation and electron sharing with metal ions. The long chains of C8, C18 and trimethoxysilane hybrid sol–gel materials can promote only hydrophobic interactions with different analytes. These are potential materials to separate the various organic compounds with high resolution. The presence of active hydroxyl and amine groups in various polymers and other materials provides hydrogen-bonding between the adsorbent and organic compounds that contains oxygen, sulfur, nitrogen and oxygen atoms. Ionic liquids and deep eutectic solvents have potential to provide p–p electron–donor/acceptor and anion exchange interactions with anionic hydrophobic compounds, and these synergic effects enhance the high extraction efficiency. The magnetic materials containing a carboxylic acid moiety (–COOH) can highly concentrate the amine-based compounds.

1.7 Conclusion Sample preparation is a key parameter in isolating a low concentration of analytes from complex matrices such as food, biological and environmental samples. Different types of sample preparation techniques including LLE, DLLE, SPME, SPE and MSPE have been used widely. However, selectivity, cost, and sorption capacity are of primary importance to get a reliable sample preparation technique. SPE is a standard and well-known method in analytical approaches, but still suffers from some drawbacks of preconcentration

Analytical Applications of Functionalized Magnetic Nanoparticles (Introduction)

11

factor, channeling, back pressure and the fact that it is time consuming. Hence, in order to improve the analytical performance of conventional SPE, the magnetic nanoparticles were incorporated into an adsorbent material to overcome some of the drawbacks via paramagnetism. The mSPE based on magnetic materials offers potential benefits which include a fast extraction process via an external magnet. MNPs functionalized with polymers, carbonaceous material, MOFs, calixarene and metal oxides preconcentrated the various analytes efficiently from urine, plasma, fruits, vegetables, plant food and baby food. The high efficiency of MSPE in different types of matrices is probably due to the high affinity of the functional materials toward the target analyte. Polymers and carbons extracted organic compounds via p–p affinity, hydrogen bonding and electrostatic interactions. The hydrophobicity and hydrophilicity of the materials are the other strategies to obtain high extraction efficiency. The MSPE method based on modified MNPs is successfully applied to extraction, isolation and removal of the target analytes. The MSPE improved the speed of sample preparation and exhibited a high performance in the clean-up process. Therefore, based on the literature review, the MSPE based on magnetic materials can be applied for food, water, environment and biological analysis.

Acknowledgements This work did not include financial support.

References 1. L. Mohammed, H. G. Gomaa, D. Ragab and J. Zhu, Magnetic nanoparticles for environmental and biomedical applications: A review, Particuology, 2017, 30, 1–14. 2. L. Gloag, M. Mehdipour, D. Chen, R. D. Tilley and J. J. Gooding, Advances in the application of magnetic nanoparticles for sensing, Adv. Mater., 2019, 31, 1904385. 3. L. Wu, A. Mendoza-Garcia, Q. Li and S. Sun, Organic phase syntheses of magnetic nanoparticles and their applications, Chem. Rev., 2016, 116, 10473–10512. 4. K. Zhu, Y. Ju, J. Xu, Z. Yang, S. Gao and Y. Hou, Magnetic nanomaterials: Chemical design, synthesis, and potential applications, Acc. Chem. Res., 2018, 51, 404–413. 5. L. Shen, B. Li and Y. Qiao, Fe3O4 nanoparticles in targeted drug/gene delivery systems, Materials, 2018, 11, 324. 6. R. Serrano Garcı´a, S. Stafford and Y. K. Gun’ko, Recent progress in synthesis and functionalization of multimodal fluorescent-magnetic nanoparticles for biological applications, Appl. Sci., 2018, 8, 172. 7. B. Maddah and J. Shamsi, Extraction and preconcentration of trace amounts of diazinon and fenitrothion from environmental water by

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8.

9.

10.

11.

12. 13.

14. 15.

16.

17.

18. 19.

20.

magnetite octadecylsilane nanoparticles, J. Chromatogr. A., 2012, 1256, 40–45. H. Rashidi Nodeh, H. Sereshti, H. Gaikani, M. A. Kamboh and Z. Afsharsaveh, Magnetic graphene coated inorganic-organic hybrid nanocomposite for enhanced preconcentration of selected pesticides in tomato and grape, J. Chromatogr. A, 2017, 1509, 26–34. I. S. Ibarra, J. M. Miranda, J. A. Rodriguez, C. Nebot and A. Cepeda, Magnetic solid phase extraction followed by high-performance liquid chromatography for the determination of sulphonamides in milk samples, Food Chem., 2014, 157, 511–517. C. Martinez-Boubeta and K. Simeonidis, Magnetic nanoparticles for water purification, in Nanoscale Materials in Water Purification, Elsevier, 2019, pp. 521–552. A. Akbarzadeh, M. Samiei and S. Davaran, Magnetic nanoparticles: preparation, physical properties, and applications in biomedicine, Nanoscale Res. Lett., 2012, 7, 144. D. Sharma and C. M. Hussain, Smart nanomaterials in pharmaceutical analysis, Arab. J. Chem., 2020, 13, 3319–3343. C. M. Hussain, Magnetic Nanomaterials for Environmental Analysis, in Advanced Environmental Analysis: Applications of Nanomaterials, The Royal Society of Chemistry, 2017, vol. 2, pp. 1–13, DOI: 10.1039/ 9781782629139-00001. ¨yu ¨ktiryaki, Y. Su ¨mbelli, R. Keçili and C. M. Hussain, Lab-on-chip S. Bu platforms for environmental analysis, Encycl. Anal. Sci., 2019, 267–273. S. Moradi Shahrebabak, M. Saber-Tehrani, M. Faraji, M. Shabanian and P. Aberoomand-Azar, Simultaneous magnetic solid phase extraction of acidic and basic pesticides using triazine-based polymeric network modified magnetic nanoparticles/graphene oxide nanocomposite in water and food samples, Microchem. J., 2019, 146, 630–639. Y. Zhou, J. Zhu, J. Yang, Y. Lv, Y. Zhu, W. Bi, X. Yang and D. D. Y. Chen, Magnetic nanoparticles speed up mechanochemical solid phase extraction with enhanced enrichment capability for organochlorines in plants, Anal. Chim. Acta, 2019, 1066, 49–57. V. W. O. Wanjeri, C. J. Sheppard, A. R. E. Prinsloo, J. C. Ngila and P. G. Ndungu, Isotherm and kinetic investigations on the adsorption of organophosphorus pesticides on graphene oxide based silica coated magnetic nanoparticles functionalized with 2-phenylethylamine, J. Environ. Chem. Eng., 2018, 6, 1333–1346. ´ and I. ˇ M. ˇ Safarˇ´kova ı Safarˇ´k, ı Magnetic solid-phase extraction, J. Magn. Magn. Mater., 1999, 194, 108–112. M. Sajid and J. P"otka-Wasylka, ‘‘Green’’ nature of the process of derivatization in analytical sample preparation, TrAC, Trends Anal. Chem., 2018, 102, 16–31. E. V. S. Maciel, A. L. de Toffoli, E. S. Neto, C. E. D. Nazario and F. M. Lanças, New materials in sample preparation: Recent advances and future trends, TrAC, Trends Anal. Chem., 2019, 119, 115633.

Analytical Applications of Functionalized Magnetic Nanoparticles (Introduction)

13

21. C. M. Hussain, Handbook on Miniaturization in Analytical Chemistry: Application of Nanotechnology, Elsevier, 2020. 22. W. A. Wan Ibrahim, H. Rashidi Nodeh and M. M. Sanagi, Graphenebased Materials as Solid Phase Extraction Sorbent for Trace Metal Ions, Organic Compounds and Biological Sample Preparation, Crit. Rev. Anal. Chem., 2015, 46, 267–283. 23. W. A. Wan Ibrahim, H. R. Nodeh, H. Y. Aboul-Enein and M. M. Sanagi, Magnetic Solid-Phase Extraction Based on Modified Ferum Oxides for Enrichment, Preconcentration, and Isolation of Pesticides and Selected Pollutants, Crit. Rev. Anal. Chem., 2015, 45, 270–287. 24. H. Rashidi Nodeh, W. A. Wan Ibrahim, M. M. Sanagi and H. Y. Aboul-Enein, Magnetic graphene-based cyanopropyltriethoxysilane as adsorbent for simultaneous determination of polar and nonpolar organophosphorus pesticides in cow’s milk samples, RSC Adv., 2016, 6, 24853–24864. 25. T. Yu, T. Wang, Z. Huang, N. Huang, H. Zhang, Z. Luo, H. Li, S. Ding and W. Feng, Determination of Multiple Pesticides in Human Blood Using Modified QuEChERS Method with Fe3O4 Magnetic Nanoparticles and GC–MS, Chromatographia, 2017, 80, 165–170. 26. C. M. Hussain and R. Kecili, Modern Environmental Analysis Techniques for Pollutants, Elsevier, 2019. 27. E. Gionfriddo, Green analytical solutions for sample preparation: solid phase microextraction and related techniques, Phys. Sci. Rev., 2020, 5, 1–12. 28. M. A. Farajzadeh, M. Sattari Dabbagh and A. Yadeghari, Deep eutectic solvent based gas-assisted dispersive liquid-phase microextraction combined with gas chromatography and flame ionization detection for the determination of some pesticide residues in fruit and vegetable samples, J. Sep. Sci., 2017, 40, 2253–2260. 29. Y. Cai, G. Jiang, J. Liu and Q. Zhou, Multiwalled Carbon Nanotubes as a Solid-Phase Extraction Adsorbent for the Determination of Bisphenol A, 4-n-Nonylphenol, and 4-tert-Octylphenol, Anal. Chem., 2003, 75, 2517–2521. 30. N. Yahaya, M. M. Sanagi, T. Mitome, N. Nishiyama, W. A. W. Ibrahim and H. Nur, Dispersive micro-solid phase extraction combined with high-performance liquid chromatography for the determination of three penicillins in milk samples, Food Anal. Methods., 2015, 8, 1079–1087. `, Solid31. A. Andrade-Eiroa, M. Canle, V. Leroy-Cancellieri and V. Cerda phase extraction of organic compounds: A critical review. part ii, TrAC, Trends Anal. Chem., 2016, 80, 655–667. 32. C. G. Gunther, Electro-Magnetic Ore Separation, Hill Publishing Company, New York, 1909. 33. A. Mehdinia, F. Roohi and A. Jabbari, Rapid magnetic solid phase extraction with in situ derivatization of methylmercury in seawater by Fe3O4/polyaniline nanoparticle, J. Chromatogr. A, 2011, 1218, 4269–4274. 34. C. M. Hussain, Nanomaterials in Chromatography: Current Trends in Chromatographic Research Technology and Techniques, Elsevier, 2018.

14

Chapter 1

35. C. M. Hussain, Handbook of Nanomaterials in Analytical Chemistry: Modern Trends in Analysis, 2019. 36. E. Lemasson, P. Hennig, S. Bertin, E. Lesellier and W. Caroline, MixedMode Chromatography—A Review, LC  GC Eur., 2017, 30, 22–33. 37. M. K. Mohammadi Nodeh, M. A. Gabris, H. Rashidi Nodeh and M. Esmaeili Bidhendi, Efficient removal of arsenic(III) from aqueous media using magnetic polyaniline-doped strontium–titanium nanocomposite, Environ. Sci. Pollut. Res., 2018, 25, 16864–16874. 38. S. Sayin, F. Ozcan and M. Yilmaz, Synthesis and evaluation of chromate and arsenate anions extraction ability of a N-methylglucamine derivative of calix [4] arene immobilized onto magnetic nanoparticles, J. Hazard. Mater., 2010, 178, 312–319. 39. K. D. Clark, O. Nacham, H. Yu, T. Li, M. M. Yamsek, D. R. Ronning and J. L. Anderson, Extraction of DNA by magnetic ionic liquids: tunable solvents for rapid and selective DNA analysis, Anal. Chem., 2015, 87, 1552–1559. 40. D.-D. Wang, Y. Zhao, M.-N. Ou yang, H.-M. Guo and Z.-H. Yang, Magnetic polydopamine modified with deep eutectic solvent for the magnetic solid-phase extraction of sulfonylurea herbicides in water samples, J. Chromatogr. A, 2019, 1601, 53–59. 41. S. Qin, H. Yin, C. Yang, Y. Dou, Z. Liu, P. Zhang, H. Yu, Y. Huang, J. Feng, J. Hao, J. Hao, L. Deng, X. Yan, X. Dong, Z. Zhao, T. Jiang, H.-W. Wang, S.-J. Luo and C. Xie, A magnetic protein biocompass, Nat. Mater., 2016, 15, 217–226. 42. W. A. Wan Ibrahim, K. V. Veloo and M. M. Sanagi, Novel sol–gel hybrid methyltrimethoxysilane–tetraethoxysilane as solid phase extraction sorbent for organophosphorus pesticides, J. Chromatogr. A, 2012, 1229, 55–62. 43. X. Yang, K. Qiao, Y. Ye, M. Yang, J. Li, H. Gao, S. Zhang, W. Zhou and R. Lu, Facile synthesis of multifunctional attapulgite/Fe3O4/polyaniline nanocomposites for magnetic dispersive solid phase extraction of benzoylurea insecticides in environmental water samples, Anal. Chim. Acta., 2016, 934, 114–121. 44. A. Azizi, F. Shahhoseini and C. S. Bottaro, Magnetic molecularly imprinted polymers prepared by reversible addition fragmentation chain transfer polymerization for dispersive solid phase extraction of polycyclic aromatic hydrocarbons in water, J. Chromatogr. A, 2020, 1610, 460534. 45. R. Keçili and C. M. Hussain, Recent progress of imprinted nanomaterials in analytical chemistry, Int. J. Anal. Chem., 2018, 2018, 1–18. 46. M. Faraji, Recent analytical applications of magnetic nanoparticles, Nanochem. Res., 2016, 1, 264–290. ¨yu ¨ktiryaki, R. Keçili and C. M. Hussain, Functionalized Nanoma47. S. Bu terials in Dispersive Solid Phase Extraction: Advances & Prospects, TrAC, Trends Anal. Chem., 2020, 115893. 48. R. Kaur, A. Hasan, N. Iqbal, S. Alam, M. K. Saini and S. K. Raza, Synthesis and surface engineering of magnetic nanoparticles for

Analytical Applications of Functionalized Magnetic Nanoparticles (Introduction)

49.

50.

51. 52.

53.

54.

55.

56.

57.

58.

59.

15

environmental cleanup and pesticide residue analysis: a review, J. Sep. Sci., 2014, 37, 1805–1825. H.-B. Zheng, Q. Zhao, J.-Z. Mo, Y.-Q. Huang, Y.-B. Luo, Q.-W. Yu and Y.-Q. Feng, Quick, easy, cheap, effective, rugged and safe method with magnetic graphitized carbon black and primary secondary amine as adsorbent and its application in pesticide residue analysis, J. Chromatogr. A., 2013, 1300, 127–133. A. Mandal, N. Singh and T. J. Purakayastha, Characterization of pesticide sorption behaviour of slow pyrolysis biochars as low cost adsorbent for atrazine and imidacloprid removal, Sci. Total Environ, 2017, 577, 376–385. J. Sengupta and C. M. Hussain, Graphene and its derivatives for Analytical Lab on Chip platforms, TrAC, Trends Anal. Chem., 2019, 114, 326–337. M. E. I. Badawy, A. E. M. Marei and M. A. M. El-Nouby, Preparation and characterization of chitosan-siloxane magnetic nanoparticles for the extraction of pesticides from water and determination by HPLC, Sep. Sci. Plus., 2018, 1, 506–519. M. Mahmoudpour, M. Torbati, M.-M. Mousavi, M. de la Guardia and J. E. N. Dolatabadi, Nanomaterial-based molecularly imprinted polymers for pesticides detection: Recent trends and future prospects, TrAC, Trends Anal. Chem., 2020, 115943. Z. He, P. Wang, D. Liu and Z. Zhou, Hydrophilic–lipophilic balanced magnetic nanoparticles: Preparation and application in magnetic solidphase extraction of organochlorine pesticides and triazine herbicides in environmental water samples, Talanta, 2014, 127, 1–8. Z. Jiao, Y. Zhang and H. Fan, Ultrasonic-microwave method in preparation of polypyrrole-coated magnetic particles for vitamin D extraction in milk, J. Chromatogr. A, 2016, 1457, 7–13. ´nez-Skrzypek, J. Gonza ´lez-Sa ´lamo, D. A. Varela-Martı´nez, G. Jime ´. Gonza ´lez-Curbelo and J. Herna ´ndez-Borges, Analysis of phthalic M. A acid esters in sea water and sea sand using polymer-coated magnetic nanoparticles as extraction sorbent, J. Chromatogr. A, 1611, 2020, 460620. A. Amiri, H. R. Saadati-Moshtaghin and F. M. Zonoz, A hybrid material composed of a polyoxometalate of type BeW12O40 and an ionic liquid immobilized onto magnetic nanoparticles as a sorbent for the extraction of organophosphorus pesticides prior to their determination by gas chromatography, Microchim. Acta, 2018, 185, 176. X. Huang, K. Qiao, L. Li, G. Liu, X. Xu, R. Lu, H. Gao and D. Xu, Preparation of a magnetic graphene/polydopamine nanocomposite for magnetic dispersive solid-phase extraction of benzoylurea insecticides in environmental water samples, Sci. Rep., 2019, 9, 8919. C. Fan, Y. Liang, H. Dong, G. Ding, W. Zhang, G. Tang, J. Yang, D. Kong, D. Wang and Y. Cao, In-situ ionic liquid dispersive liquid-liquid microextraction using a new anion-exchange reagent combined Fe3O4 magnetic nanoparticles for determination of pyrethroid pesticides in water samples, Anal. Chim. Acta, 2017, 975, 20–29.

16

Chapter 1

60. R. Zhang, P. Su, L. Yang and Y. Yang, Microwave-assisted preparation of poly(ionic liquids)-modified magnetic nanoparticles for pesticide extraction, J. Sep. Sci., 2014, 37, 1503–1510. 61. K. Molaei, H. Bagheri, A. A. Asgharinezhad, H. Ebrahimzadeh and M. Shamsipur, SiO2-coated magnetic graphene oxide modified with polypyrrole–polythiophene: a novel and efficient nanocomposite for solid phase extraction of trace amounts of heavy metals, Talanta, 2017, 167, 607–616. ´, 3D-printed microflow 62. H. Wang, D. J. Cocovi-Solberg, B. Hu and M. Miro injection analysis platform for online magnetic nanoparticle sorptive extraction of antimicrobials in biological specimens as a front end to liquid chromatographic assays, Anal. Chem., 2017, 89, 12541–12549. ¨yu ¨ktiryaki and C. M. Hussain, Advancement in bioana63. R. Keçili, S. Bu lytical science through nanotechnology: Past, present and future, TrAC, Trends Anal. Chem., 2019, 110, 259–276. 64. M. Sajid, Magnetic ionic liquids in analytical sample preparation: a literature review, TrAC, Trends Anal. Chem., 2019, 113, 210–223. 65. S. M. Yousefi, F. Shemirani and S. A. Ghorbanian, Deep eutectic solvent magnetic bucky gels in developing dispersive solid phase extraction: Application for ultra trace analysis of organochlorine pesticides by GCmicro ECD using a large-volume injection technique, Talanta, 2017, 168, 73–81. 66. K. Xu, Y. Wang, X. Ding, Y. Huang, N. Li and Q. Wen, Magnetic solidphase extraction of protein with deep eutectic solvent immobilized magnetic graphene oxide nanoparticles, Talanta, 2016, 148, 153–162. 67. J. Chen, Y. Wang, X. Wei, P. Xu, W. Xu, R. Ni and J. Meng, Magnetic solid-phase extraction for the removal of mercury from water with ternary hydrosulphonyl-based deep eutectic solvent modified magnetic graphene oxide, Talanta, 2018, 188, 454–462. 68. O. Nacham, K. D. Clark and J. L. Anderson, Synthesis and characterization of the physicochemical and magnetic properties for perfluoroalkyl ester and Fe(III) carboxylate-based hydrophobic magnetic ionic liquids, RSC Adv., 2016, 6, 11109–11117. 69. Y. Zhang, H. Zhou, Z.-H. Zhang, X.-L. Wu, W.-G. Chen, Y. Zhu, C.-F. Fang and Y.-G. Zhao, Three-dimensional ionic liquid functionalized magnetic graphene oxide nanocomposite for the magnetic dispersive solid phase extraction of 16 polycyclic aromatic hydrocarbons in vegetable oils, J. Chromatogr. A, 2017, 1489, 29–38. 70. M. Musa, W. A. Wan Ibrahim, F. Mohd Marsin, A. S. Abdul Keyon and H. Rashidi Nodeh, Graphene-magnetite as adsorbent for magnetic solid phase extraction of 4-hydroxybenzoic acid and 3,4-dihydroxybenzoic acid in stingless bee honey, Food Chem., 2018, 265, 165–172. 71. X. He, G. N. Wang, K. Yang, H. Z. Liu, X. J. Wu and J. P. Wang, Magnetic graphene dispersive solid phase extraction combining high performance liquid chromatography for determination of fluoroquinolones in foods, Food Chem., 2017, 221, 1226–1231.

Analytical Applications of Functionalized Magnetic Nanoparticles (Introduction)

17

72. C. Yuan, Y. Qian, X. Hong, H. Wang, H. He, H. Liu, Z. Chai, Y. Zhang, P. Zhao and Y. Wang, A New Reversed-Dispersive Micro-Solid-Phase Extraction of Organophosphorus Pesticides Based on Three-Dimensional Magnetic Nanoparticles Supported by Graphene-Carbon Nanotubes Nanocomposite, J. Biobased Mater. Bioenergy, 2019, 13, 170–174. 73. Y. Guo, X. Li, X. Wang, J. Wang, F. Qian, H. Gu and Z. Zhang, Magnetic solid phase extraction of sulfonamides based on carboxylated magnetic graphene oxide nanoparticles in environmental waters, J. Chromatogr. A, 2018, 1575, 1–10. 74. J. C. Garcı´a-Mesa, P. M. Leal, M. M. L. Guerrero and E. I. V. Alonso, Simultaneous determination of noble metals, Sb and Hg by magnetic solid phase extraction on line ICP OES based on a new functionalized magnetic graphene oxide, Microchem. J., 2019, 150, 104141. 75. N. Wang, Y.-F. Wang, A. M. Omer and X. Ouyang, Fabrication of novel surface-imprinted magnetic graphene oxide-grafted cellulose nanocrystals for selective extraction and fast adsorption of fluoroquinolones from water, Anal. Bioanal. Chem., 2017, 409, 6643–6653. 76. X. Deng, Q. Guo, X. Chen, T. Xue, H. Wang and P. Yao, Rapid and effective sample clean-up based on magnetic multiwalled carbon nanotubes for the determination of pesticide residues in tea by gas chromatography–mass spectrometry, Food Chem., 2014, 145, 853–858. ´. Gonza ´lez-Curbelo, A. V. Herrera-Herrera, J. Herna ´ndez-Borges 77. M. A ´. Rodrı´guez-Delgado, Analysis of pesticides residues in enand M. A vironmental water samples using multiwalled carbon nanotubes dispersive solid-phase extraction, J. Sep. Sci., 2013, 36, 556–563. 78. H. Rashidi Nodeh, W. A. Wan Ibrahim, M. A. Kamboh and M. M. Sanagi, New magnetic graphene-based inorganic–organic sol-gel hybrid nanocomposite for simultaneous analysis of polar and nonpolar organophosphorus pesticides from water samples using solidphase extraction, Chemosphere, 2017, 166, 21–30. 79. M. Mohsennia, B. Niknahad and A. Eliassi, Effect of polymerization/ complexation agents molar ratio on structure and catalytic activity of La 0.7 Ba 0.3 Co 0.3 Ni 0.7 O 3 nanocatalyst in low-temperature CO oxidation, J. Sol-Gel Sci. Technol., 2017, 82, 458–467. 80. H. Rashidi Nodeh, W. A. Wan Ibrahim, M. A. Kamboh and M. M. Sanagi, Magnetic graphene sol–gel hybrid as clean-up adsorbent for acrylamide analysis in food samples prior to GC–MS, Food Chem., 2018, 239, 208–216. 81. S.-B. Qin, Y.-H. Fan, X.-X. Mou, X.-S. Li and S.-H. Qi, Preparation of phenyl-modified magnetic silica as a selective magnetic solid-phase extraction adsorbent for polycyclic aromatic hydrocarbons in soils, J. Chromatogr. A, 2018, 1568, 29–37. 82. H. Vojoudi, A. Badiei, A. Banaei, S. Bahar, S. Karimi, G. M. Ziarani and M. R. Ganjali, Extraction of gold, palladium and silver ions using organically modified silica-coated magnetic nanoparticles and silica gel as a sorbent, Microchim. Acta, 2017, 184, 3859–3866.

18

Chapter 1

83. Y. Wang, Y. Sun, Y. Gao, B. Xu, Q. Wu, H. Zhang and D. Song, Determination of five pyrethroids in tea drinks by dispersive solid phase extraction with polyaniline-coated magnetic particles, Talanta, 2014, 119, 268–275. 84. Q. Zhao, Q. Lu and Y. Q. Feng, Dispersive microextraction based on magnetic polypyrrole nanowires for the fast determination of pesticide residues in beverage and environmental water samples, Anal. Bioanal. Chem., 2013, 1–12. 85. B. Zhao, M. He, B. Chen, H. Xu and B. Hu, Poly (1-vinylimidazole) functionalized magnetic ion imprinted polymer for fast and selective extraction of trace gold in geological, environmental and biological samples followed by graphite furnace atomic absorption spectrometry detection, Spectrochim. Acta, Part B, 2018, 143, 32–41. 86. L. Adlnasab, M. Ezoddin, R. A. Shojaei and F. Aryanasab, Ultrasonicassisted dispersive micro solid-phase extraction based on melaminephytate supermolecular aggregate as a novel bio-inspired magnetic sorbent for preconcentration of anticancer drugs in biological samples prior to HPLC-UV analysis, J. Chromatogr. B, 2018, 1095, 226–234. 87. S. Y. Li and I. Petrikovics, Development of magnetic carbon nanotubes for dispersive micro solid phase extraction of the cyanide metabolite, 2-aminothiazoline-4-carboxylic acid, in biological samples, J. Chromatogr. B, 2019, 1109, 67–75. ´n 88. E. V. Alonso, M. M. L. Guerrero, P. C. Cueto, J. B. Benı´tez, J. M. C. Pavo and A. G. de Torres, Development of an on-line solid phase extraction method based on new functionalized magnetic nanoparticles. Use in the determination of mercury in biological and sea-water samples, Talanta, 2016, 153, 228–239. 89. K. Xu, Y. Wang, Y. Li, Y. Lin, H. Zhang and Y. Zhou, A novel poly (deep eutectic solvent)-based magnetic silica composite for solid-phase extraction of trypsin, Anal. Chim. Acta, 2016, 946, 64–72. 90. C. Vakh, M. Alaboud, S. Lebedinets, D. Korolev, V. Postnov, L. Moskvin, O. Osmolovskaya and A. Bulatov, An automated magnetic dispersive micro-solid phase extraction in a fluidized reactor for the determination of fluoroquinolones in baby food samples, Anal. Chim. Acta, 2018, 1001, 59–69. 91. N. Li, D. Wu, N. Hu, G. Fan, X. Li, J. Sun, X. Chen, Y. Suo, G. Li and Y. Wu, Effective enrichment and detection of trace polycyclic aromatic hydrocarbons in food samples based on magnetic covalent organic framework hybrid microspheres, J. Agric. Food Chem., 2018, 66, 3572–3580. 92. E. A. Dil, A. Asfaram and F. Sadeghfar, Magnetic dispersive micro-solid phase extraction with the CuO/ZnO@ Fe3O4-CNTs nanocomposite sorbent for the rapid pre-concentration of chlorogenic acid in the medical extract of plants, food, and water samples, Analyst, 2019, 144, 2684–2695. 93. A. R. Bagheri, M. Arabi, M. Ghaedi, A. Ostovan, X. Wang, J. Li and L. Chen, Dummy molecularly imprinted polymers based on a green

Analytical Applications of Functionalized Magnetic Nanoparticles (Introduction)

94.

95.

96.

97.

98.

99.

100.

101.

102.

19

synthesis strategy for magnetic solid-phase extraction of acrylamide in food samples, Talanta, 2019, 195, 390–400. ˘lu and -S. Patat, Core–shell Fe3O4 polydopamine E. Yavuz, -S. Tokalıog nanoparticles as sorbent for magnetic dispersive solid-phase extraction of copper from food samples, Food Chem., 2018, 263, 232–239. P. M. Leal, E. V. Alonso, M. M. L. Guerrero, M. T. S. Cordero, ´n and A. G. de Torres, Speciation analysis of inorganic J. M. C. Pavo arsenic by magnetic solid phase extraction on-line with inductively coupled mass spectrometry determination, Talanta, 2018, 184, 251–259. J. Ma, G. Wu, S. Li, W. Tan, X. Wang, J. Li and L. Chen, Magnetic solid-phase extraction of heterocyclic pesticides in environmental water samples using metal-organic frameworks coupled to high performance liquid chromatography determination, J. Chromatogr. A, 2018, 1553, 57–66. H. Alinezhad, A. Amiri, M. Tarahomi and B. Maleki, Magnetic solidphase extraction of non-steroidal anti-inflammatory drugs from environmental water samples using polyamidoamine dendrimer functionalized with magnetite nanoparticles as a sorbent, Talanta, 2018, 183, 149–157. Y. Huang, W. Zhang, M. Bai and X. Huang, One-pot fabrication of magnetic fluorinated carbon nanotubes adsorbent for efficient extraction of perfluoroalkyl carboxylic acids and perfluoroalkyl sulfonic acids in environmental water samples, Chem. Eng. J., 2020, 380, 122392. Z. Dahaghin, H. Z. Mousavi and S. M. Sajjadi, A novel magnetic ion imprinted polymer as a selective magnetic solid phase for separation of trace lead (II) ions from agricultural products, and optimization using a Box–Behnken design, Food Chem., 2017, 237, 275–281. X. Feng, W. Zhang, T. Zhang and S. Yao, Systematic investigation for extraction and separation of polyphenols in tea leaves by magnetic ionic liquids, J. Sci. Food Agric., 2018, 98, 4550–4560. X. Huang, G. Liu, D. Xu, X. Xu, L. Li, S. Zheng, H. Lin and H. Gao, Novel Zeolitic Imidazolate Frameworks Based on Magnetic Multiwalled Carbon Nanotubes for Magnetic Solid-Phase Extraction of Organochlorine Pesticides from Agricultural Irrigation Water Samples, Appl. Sci., 2018, 8, 959. M. Mehraban, M. Manoochehri and F. A. Taromi, Trace amount determination of Cd (II), Pb (II) and Ni (II) ions in agricultural and seafood samples after magnetic solid phase extraction by MIL-101 (Cr)/phenylthiosemicarbazide-functionalized magnetite nanoparticle composite, New J. Chem., 2018, 42, 17636–17643.

CHAPTER 2

Design of Functionalized Magnetic Nanoparticles for Improving Stabilization, Biocompatibility and Uptake Efficiency ˘ LU,b HATICE DURAN*b AND IQRA AZEEM,a SENEM ÇITOG a BASIT YAMEEN* a

Department of Chemistry and Chemical Engineering, School of Science and Engineering, Lahore University of Management Sciences, Lahore-54792, Pakistan; b Department of Materials Science & Nanotechnology Engineering, ¨˘ ¨zu ¨to ¨ Cad. 43, TOBB University of Economics and Technology, So gu 06560 Ankara, Turkey *Emails: [email protected]; [email protected]

2.1 Introduction Nanotechnology is a topic of pivotal importance in modern science. It deals with nanomaterials, nanodevices, and all processes that occur at the nanometer length scale. Nanomaterials exhibit significantly different properties compared to their bulk counterparts, and these unique physicochemical properties of nanomaterials are being employed by biologists, chemists, engineers, and physicians to deliver significant healthcare-related technology. Among the wide variety of nanomaterials under investigation, magnetic nanoparticles (MNPs) have gained considerable attention due to their interesting Analytical Applications of Functionalized Magnetic Nanoparticles Edited by Chaudhery Mustansar Hussain r The Royal Society of Chemistry 2021 Published by the Royal Society of Chemistry, www.rsc.org

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size-dependent magnetic properties and their suitability for application in a wide range of fields including nanomedicine, nanobiotechnology, and environmental science.1,2 Compared to bulk materials, a high surface-to-volume ratio is an intrinsic advantage that is associated with all the nanomaterials. In the case of MNPs, the size-dependent magnetic behavior is another facet that remains a center of scientific curiosity.3 The magnetism of MNPs is determined by several factors that include chemical composition, crystal framework, particle size, morphology, as well as the physiochemical nature of the matrix holding the particles (Figure 2.1). By changing the chemical composition, size, and morphology, one can tune the magnetic properties of MNPs.4 In this context, novel synthetic methodologies are being developed to offer precise control over the chemical composition, size, and morphology of MNPs. Besides, the development of appropriate surface modification techniques that assist in tuning the surface chemical nature and in turn interaction with the matrix, colloidal stability, and biocompatibility of MNPs are of significant importance for the successful

Figure 2.1

Schematic diagram showing the physicochemical properties, metallic and multifunctional structures, and surface modification of MNPs.

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application of MNPs in healthcare-related applications. MNPs with appropriate physicochemistry and surface properties are being applied in a range of biomedical applications including protein purification, targeted drug delivery, magnetic hyperthermia, magnetic resonance imaging (MRI), tissue engineering, biosensing, and bioanalysis.5–7 In this chapter, we describe the chemical design, physical properties, and surface modification strategies that are crucial for the application of MNPs in addressing healthcare-related challenges.

2.2 Design of Functional Magnetic Nanoparticles (FMNPs) FMNPs have been mostly used in various fields of science and technology. From the perspective of the synthesis, the main challenges include controlling the crystalline structure, morphology, and solid-phase purity as the decrease in size from bulk to a particle in the nanometer (nm) range brings a new level of complexity to their synthetic methodologies. The field of science that deals with the design and development of FMNPs begins with the solidphase inorganic chemistry and material science on one side, and applied and interface chemistry on the other side.8 FMNPs can be synthesized with several different chemical compositions including pure metals (Fe, Ni, and Co), metal-oxides (Fe3O4, Co3O4, and NiO) metal alloys (FePt, CoPt, and FeNiPt), and metallic heterostructures (core–shell NPs, dumbbell shape NPs). Over the past two decades, the synthesis of FMNPs of the aforementioned chemical compositions with different sizes, shapes, surface chemistry, and magnetic characteristics have been developed.9,10

2.3 Synthetic Route to FMNPs Various synthetic pathways have been adopted to develop FMPNs with great control over the morphology and size distribution. Broadly, the magnetic core of FMNPs can be synthesized either by top-down or bottom-up approaches. (1) A variety of different physical methods, such as lithography, ultrasonication, irradiation, gas-phase deposition, laser ablation, are being utilized to fabricate FMNPs from bulk materials. Top-down methods are favored in industrial endeavors since they are straightforward, affordable, and simple to scale up. Despite being convenient, topdown approaches suffer from the limitation of wide size and shape distribution, which limit their usage in biomedical applications.9,11 (2) The bottom-up approaches allude to the chemical methods i.e., sol–gel method, oxidation of metal precursor, co-precipitation, hydrothermal method, flow injection, electro-chemical and vapor-phase deposition, sonochemical decomposition reactions, supercritical fluid method, and nanoreactors based synthesis, to develop FMNPs wherein the nucleation of atoms or groups of atoms is followed by the growth and

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clump formation that ultimately results in the formation of nanoparticles (NPs).12 Synthesis techniques are required to overcome the following strategic issues while broadening the properties and applications of FMNPs in various applications: How to control the size of nanoparticles? How to fabricate monodisperse NPs i.e., narrow size distribution? How to develop nanomaterials with an ideal crystal structure? How to control the morphology of the NPs? How to precisely control the composition of heterostructures and metallic alloys for the optimum magnetic properties? How to ensure batchto-batch uniformity economically?

2.4 Chemical Design of FMNPs The chemical design of FMNPs offers new methodologies for atomic-level control over the nucleation and growth of MNPs that help in optimizing the morphology and size of FMNPs by modifying the surfactants, solvents, and reaction conditions. In this context, a wet-phase chemical approach offers facile ways to synthesize FMNPs.13 As indicated by the LaMer model14 (Figure 2.2), during the wet-phase chemical approach the monomer concentration increases at the initial phase of the reaction, and burst nucleation takes place once the concentration reaches a critical state, prompting a decline in the monomer concentration. The growth of nanoparticles happens when the concentration of monomers passes the nucleation level,

Figure 2.2

LaMer model demonstrating the nucleation and growth processes throughout the fabrication of monodisperse NPs. S and Sc are the supersaturation and critical supersaturation points, respectively. Reproduced from ref. 15 with permission from the Royal Society of Chemistry.

24

Chapter 2

which is favored by the Gibbs free energy of the system. In this manner, the controlled size and morphology of the subsequent NPs can be achieved by monitoring the relationship between the nucleation and growth processes.15 The growth process of the shaped nuclei is governed by their surface free energy, which can be tuned exactly by varying the solvent and the surfactants. The mechanism of controlling the particle size distribution involves: (i) forming a protective surface layer to circumvent oxidation, (ii) dropping the surface free energy to evade aggregation of the NPs, (iii) controlling the sizes by tuning the nucleation and growth process, and (iv) facilitating the oriented growth of nuclei to make shaped FMNPs. Furthermore, the chemical reaction parameters also have an extraordinary effect on the final morphology of the FMNPs. It has been demonstrated that the magnetic character of FMNPs is a strongly size-dependent property. The coercive force, a size-dependent property, reaches a maximum value when the size of FMNPs decreases to a critical state to form a single-domain magnetic nanoparticle. Thus, adjusting the size of FMNPs turns out to be a primary parameter for accomplishing high-performance nanomagnets.16

2.4.1

Metal-based Magnetic Nanoparticles (MMNPs)

The MMNPs have better polarization as compared to the metal oxide-based MNPs, which is fascinating for some applications. However, MMNPs are easily oxidized in air, bringing about the full or incomplete loss of their magnetic character. Iron MMNPs: Iron (Fe), a ferromagnetic solid with the magnetization of about 220 emu g1, is the most studied element among all the metals in terms of its magnetic property and its use in different applications. Synthesis of pure Fe NPs is a difficult task since it mostly comprises oxides, carbides, and other contaminants.17 Numerous methods have been developed to fabricate Fe NPs employing reduction of an iron(II) salt by sodium borohydride, however, the reactive nature of iron makes it difficult to attain the size and phase purity. Alternatively, Fe NPs can also be synthesized by thermal and sonochemical decomposition of iron pentacarbonyl [Fe(CO)5] for the preparation of amorphous iron.18 Industrially, they are produced in bulk via the thermal reduction of Fe2O3, formed by dehydration of Fe(OH)2, in a H2 atmosphere. Through this large-scale manufacturing, it is difficult to attain the desired uniformity.19 To produce monodisperse Fe NPs (5–20 nm), Fe(CO)5 was thermally decomposed in dioctylether with oleic acid and oleylamine as surfactants. The drawback is that the NPs produced by this method were not well crystallized and readily oxidized in the air.20 To improve stability, core–shell Fe@Fe3O4 NPs were synthesized by solvothermal reduction of Fe(acac)3 in the presence of polymer poly(N-vinylpyrrolidone) (PVP), which passivate the metallic surface by polymer coating, and controlled oxidation of the Fe NP surface by treating with a small amount of trimethylamine N-oxide.21 Another Fe-complex Fe[N(SiMe3)2]2 has been employed to produce Fe NPs to replace Fe(CO)5 which is recognized as a

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25

toxic complex. The reductive decay of Fe[N(SiMe3)2]2 in the presence of hexadecylammoniumchloride (HDA  HCl) and oleic acid at 150 1C under a H2 atmosphere yielded 7 nm Fe NPs with a body-centered cubic (bcc) structure. Upon utilization of palmitic acid instead of oleic acid, uniform Fe NPs with controlled sizes from 13 to 30 nm were prepared at various HDA/palmitic acid proportions.22 Along with the conventional approaches, green chemistry approaches have recently been applied to fabricate Fe NPs to reduce toxic and hazardous effects of the precursor materials and reducing agents on human health and the environment in general.23 Cobalt MMNPs: Like Fe, monodispersed cobalt (Co) NPs can be fabricated by the thermal decomposition of Co2(CO)8 in a non-polar solvent (e.g., diphenyl ether) in the presence of oleic acid and tributylphosphine (TBP) as surfactants.24 Similarly, monodisperse polycrystalline Co NPs were formed when dioctylamine was used instead of TBP at 208 1C in tetralin solvent.25 Inversed micelle is a well-known method used to fabricate hexagonal closed pack (hcp) Co NPs from cobalt(II) bis(2-ethylhexyl) sulfosuccinate [Co(AOT)2] reverse micelles using NaBH4 as a reducing agent. Here, the alkyl chain of trialkylphosphine (PR3 where R may be n-butyl or n-octyl) plays an important role in controlling the size and morphology of NPs. For instance, small particles (2–6 nm) were formed while utilizing trioctylphosphine, and large particles (7–11 nm) are favored when tributylphosphine is used. This might be due to the reverse coordination of the surfactants with the neutral metal surface.26 Nickel NPs: Nanosized ferromagnetic nickel (Ni) is a material of interest for diverse applications including storage, ferrofluids, clinical analysis, multilayer capacitors, and catalysis. Like Fe and Co, thermal decomposition, sol–gel, and spray pyrolysis have been utilized to fabricate Ni NPs from precursors such as Ni(CO)4, Ni(COD)2, and Ni(Cp)2.27 At present, Ni NPs are commonly synthesized by microemulsion procedures employing cetyltrimethylammonium bromide (CTAB) as a surfactant, or in the presence of alkylamines or trioctylphosphine oxide (TOPO) surfactants.28 Monodisperse Ni NPs with a narrow size distribution can also be fabricated via the thermal decomposition of nickel acetylacetonate using trioctylphosphine as a surfactant in oleylamine.29

2.4.2

Metal Alloy-based Magnetic Nanostructures (MAMNs)

Fe–Co metallic alloys are a category of soft magnetic materials with very small energy for magnetic anisotropy. These materials are known for having the highest magnetic moment (245 emu g1) among all the magnetic materials. However, due to the different rates of nucleation and growth, it is difficult to control the dimensions and conformation of Fe–Co alloy NPs.30 Fabrication of monodisperse Fe–Co NPs via simultaneous thermal decomposition of Fe(CO)5 and Co2(CO)8 in a non-polar solvent have been reported.31 Alternatively, monodisperse Fe–Co NPs can be fabricated via reductive decomposition of Fe(acac)3 and Co(acac)2 in the presence of surfactants and reducing agents. By controlling Fe/Co ratios Fe-rich Fe–Co alloy NPs could be prepared that offer an opportunity to tune their magnetic property.32 Compared to Fe–Co alloy NPs,

26

Chapter 2

Fe–Pt and Co–Pt NPs with precise control over the size and chemical composition are even more difficult to synthesize because of the marked difference in the chemical reactivities of Pt (noble metal) and Fe and Co (first-row transition metals). To overcome this problem, an organic phase synthesis employing Fe(CO)5/Co2(CO)8 and Pt(acac)2 as precursors in a non-polar solvent at high-temperature was designed using oleic acid and oleylamine as stabilizers. The chemical compositions of the designed metallic alloys were controlled by controlling the molar ratios of the precursors.33,34 Compared to regular particulate shapes, anisotropic nanostructures such as nanowires (NWs) may offer a set of unique properties. In this context, the co-reduction of [Pt(en)2]21 and thermal decay of [Fe(CO)5] led to the synthesis of Fe–Pt NWs. The choice of solvent, ethylenediamine (en), played a significant role in controlling the morphology of Fe–Pt NWs.35 Similarly, replacing Fe(CO)5 with Co2(CO)8 could lead to the formation of Co–Pt nanowires.36 In a separate attempt, heterobimetallic Co–Pt-containing polymer/Fe–Pt-based complex was used as a precursor to fabricate narrow sized distributed ferromagnetic highly ordered face-centered tetragonal (L10 phase) Co–Pt NPs and Fe–Pt NPs respectively. The coercivity of these NPs made these materials effective to be used in data storage devices and as an electrocatalyst in fuel cells.37,38 In addition to the combination with Pt, Fe–Pd MNPs have been prepared through a simple hightemperature based thermal decomposition in an organic solvent using 1-adamantanecarboxylic acid and tributylphosphine as stabilizing agents. By adjusting the molar proportion of surfactants, monodisperse Fe–Pd NPs (11–16 nm) having superparamagnetic properties are synthesized at ambient conditions.39 In a separate report, a one-pot synthesis of FePd–Fe3O4 nanocomposites is designed via controlled thermal decomposition of Fe(CO)5 and Pd(acac)2. At high temperature (500 1C) this nanocomposite converts into L10-FePd–Fe nanocomposite magnets with magnetic moment ranging from 90–190 emu g1. This work helps to understand exchange coupling and to develop super strong nanomagnets for magnetic applications.40 Furthermore, the rare-earth element-based permanent nanomagnets, for example SmCo5 magnets, with a large magnetic property were prepared by facile calcium reduction of the Co@Sm2O3 core–shell. The coercivity value of the resulting nanomagnet was around 8 kOe at room temperature.41

2.4.3

Metal Oxide-based Magnetic Nanoparticles (MOMNPs)

MOMNPs are known for their robust chemical stability and strong magnetic behavior. Among MOMNPs, iron oxides have gained increasing interest because of their broad applications, for example, catalysis, sensors, optical and electromagnetic gadgets. Magnetite (Fe3O4), a cubic ferrite, has a low magnetic moment (soft magnetic material) and showed the most interesting properties among all iron oxides due to Fe21, and Fe31 valence states of iron.4 Among various strategies, the wet phase approach has been the most well-known methodology for both lab-scale and large-scale synthesis. In this context, organic phase synthesis gives a promising option to fabricate monodisperse iron

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27

oxide NPs (4 nm) via reductive thermal decomposition of Fe(acac)3 using 1,2-hexadecandiol as a reducing agent and oleic acid and oleylamine as surfactants. By changing the solvent from phenyl to benzyl ether and the temperature from 250 1C to 300 1C resulted in bigger NPs (6 nm) with better crystallinity and magnetic properties. These 4 or 6 nm NPs were used as seeds to further improve the size to 20 nm via seed-mediated growth.42 Similarly, other metal ferrites can be prepared by simply adding the corresponding metal(acac)2 salt in the reaction mixture and by adjusting the proportion of precursor and surfactant (oleylamine).43 Besides, different metal-doped monodisperse iron ferrites were prepared by reacting metal chlorides with Fe(acac)3 in a dioctylether solution of oleic acid and oleylamine. For example, manganese-based ferrites NPs (MnFe2O4) having spinel geometry are made by adding an aqueous solution of Mn21 and Fe31 chloride salts to a strongly stirred mixture of an alkali.44,45 An advancement with regards to iron oxide NP synthesis was observed by utilizing Fe-oleate as the starting material. This complex was thermally decomposed into monodisperse iron oxide NPs (5–22 nm) in the presence of trimethylamine N-oxide. The same strategy can be adapted to fabricate other ferrites as well. Noticeably, the Fe–oleate complex allowed the large-scale manufacturing of monodisperse iron oxide NPs.46,47 Similarly, the Fe(acac)3 precursor is also suitable for the synthesis of FeO NPs. The surfactant ratio can regulate the competitive growth in specific directions to form condensed octahedral NPs. Furthermore, the FeO NPs can be converted into other iron oxides, such as Fe3O4, after annealing.48 In addition, cobalt oxide (Co3O4) based NPs (15–19 nm) can also be prepared by adopting similar strategies. Co(OH)2 nanoplatelets were synthesized by the hydrothermal process using Co(NO3)3 as a precursor and PVP as a stabilizer.49 The organic phase synthesis was also used to fabricate antiferromagnetic nickel oxide (NiO) but when the sizes of the sample decrease to a few nanometers, they turn out to be superparamagnetic or super-antiferromagnetic. NiO not only possesses magnetic but electrical properties as well. The electric conductivity increases by 6–8 times in nanosized NiO as compared to the bulk. NiO NP-based electrodes show a higher capacity than the regular ceramic material-based electrode.50,51

2.4.4

Metallic Carbides and Nitride-based Magnetic Nanostructures (MC/NMNs)

MCMNs such as Fe5C2, Fe3C, and Fe2C exhibit higher stability and magnetic moment (B140 emu g1) as compared to the metal oxides. Principally, iron carbides comprise carbon present in the interstices between closely packed iron molecules that provide mechanical strength and inertness to these frameworks. In modern investigations, iron carbide nanostructures have been found to have a few one-of-a-kind properties in contrast to iron or iron oxide nanostructures. Despite various benefits in bioimaging, energy storage, and catalysis, iron carbide nanostructures have been considerably less explored than iron oxide or iron nanostructures, which is because of the difficulties

28

Chapter 2

Figure 2.3

Schematic showing the synthesis procedures of binary, doped, ternary, and composite iron nitride nanostructures. Reproduced from ref. 58 with permission from American Chemical Society, Copyright 2015.

related to manufacturing techniques.52 High-temperature strategies such as gas  solid reaction, laser pyrolysis, and sol–gel methods produce iron carbide NPs with non-uniform size and morphology.53–55 A simple synthetic method to fabricate monodispersed Fe5C2 NPs (20 nm) is via the carbonization of crystalline Fe NPs, formed by the organic phase thermal decomposition of Fe(CO)5 using cetyltrimethylammonium bromide (CTAB) as a surfactant. It is noteworthy to mention that bromide from CTAB plays an important role in the conversion of Fe(CO)5 to Fe5C2.56 Similarly, a versatile solution chemistry route was adopted to develop colloidal iron carbide NPs with different crystalline phases i.e., hexagonal, monoclinic, and orthorhombic, from bcc-Fe@Fe3O4. The phases could be controlled via a thermodynamic procedure. Meanwhile, the selective adsorption of Cl1 ions weakened the atomic bonding between Fe and C atoms, consequently interfering with the penetration of C atoms to fabricate lower carbon content containing iron carbide.57 In the same way, metal nitride magnetic nanostructures (MNMNs), especially Fe–N, can be excellent substitutes for the metal oxide NPs. Figure 2.3 gives an overview of designing iron nitride via different wet chemical approaches.58

2.4.5

Multifunctional Nanoparticle-based Magnetic Nanostructures (MNMNs)

MNMNs have distinctive characteristics because of their varied chemical composition, achieved by incorporating multiple components into a single

Design of Functionalized Magnetic Nanoparticles for Improving Stabilization

Figure 2.4

29

Different classes of multifunctional nanoparticle-based magnetic nanostructures.

system. Many multifunctional NPs with distinctive designs have been reported (Figure 2.4).1 Here, we focus on the organic phase synthesis of core– shell and dumbbell-like multifunctional MNPs. The core–shell conformation is under research owing to its exceptional properties.59 For example, Fe3O4–Au/Ag core–shell NPs were synthesized via an organic phase method. The synthesis begins with the coating of Au on the top of Fe3O4 NPs by reducing HAuCl4 using a mild reducing agent, oleylamine, which also acts as a surfactant. After Fe3O4–Au NPs synthesis, they were transferred from an organic to aqueous media having CTAB and sodium citrate. These water-soluble NPs act as seeds for the development of thick gold coating on the surface of Fe3O4–Au NPs by adding more HAuCl4 under reducing conditions. The plasmonic properties of these NPs were optimized by the thickness of the Au shell.60 Alternatively, they are prepared by the direct coating of Au over the MNPs. In this case, MNPs were first functionalized with the amine group which in turn directs the formation of the Au shell. These core–shell NPs are especially interesting as multifunctional probes for biomedical applications.61 Another well-known heterostructure is dumbbell shaped NPs which are usually synthesized by successive growth of a second component on

30

Chapter 2

pre-synthesized seeds. This is analogous to the fabrication of core–shell NPs along with a difference during nucleation and growth processes that are anisotropic and centered on one specific plane of the crystal and are not equally distributed over the surface of the seed. So, the successful preparation of dumbbell shaped NPs depends on endorsing heterogeneous nucleation whereas overwhelming homogeneous nucleation. This can be attained by precisely tuning the ratio between the NP seed and precursor.27 Dumbbell shaped Au–Fe3O4 NPs were synthesized by the decomposition of Fe(CO)5 in the presence of oleylamine, over the top of the pre-synthesized Au NPs, followed by air-oxidation. The AuNP size is precisely tunned either by monitoring the HAuCl4 to oleylamine ratio or by adjusting the temperature during injecting the HAuCl4 solution. The Fe3O4 NP size is tuned by controlling the ratio between Fe(CO)5 and Au.62 These dumbbell-shaped heterostructures can also be synthesized by growing noble metal(Ag) NPs on the pre-synthesized MNPs such as reduction of silver acetate or nitrate by oleylamine on the surface of magnetic ferrite under a mild temperature.63

2.5 Physicochemical Features of FMNPs One of the most significant features of FMNPs is their size-dependent magnetism behavior. Apart from the size, the fine control of the molecular shape, the elemental composition, and the NP crystallinity further tune their magnetic ability. Here, we briefly discuss the physicochemical features of FMNPs.

2.5.1

NP Size

Size is an important characteristic that plays an effective role in the physical stability of MNPs. The size of the MNPs strongly affects their magnetic moment (m) and their subsequent response toward the magnetic field. Decreasing the sizes can certainly transform the materials from multi-domain to singledomain along with the increase in coercivity (Hc). Multi-domain particles have non-uniform magnetization but when the size of the material decreases to a critical value, it becomes a single-domain and such particles have uniform magnetization. The critical radius (rc) of single-domain MNPs is defined as pffiffiffiffiffiffi 9 AK rc  (2:1) m0 Ms2 The critical radius/size, according to the magnetic domain theory, is affected by several factors i.e., magnetic saturation (Ms), crystal anisotropy (K), exchange interaction (A), vacuum permeability (m0), surface energy, and the shape of the single-domain particles.64 The orientations of the magnetic moment within each domain in a multi-domain system are controlled by anisotropic energy (Eb ¼ KeffVm) and domain rotation, while, the magnetic moment of a single-domain system has only two orientations that are antiparallel to each other. An anisotropic energy barrier only prevents these two

Design of Functionalized Magnetic Nanoparticles for Improving Stabilization

Figure 2.5

31

Coercivity-size relations of single and multidomain particles. Reproduced from ref. 2, https://doi.org/10.1186/1556-276X-7-144, under the terms of the CC BY 2.0 license https://creativecommons.org/licenses/ by/2.0/.

preferred orientations from flipping. Consequently, the single-domain systems have higher Hc than their multi-domain counterparts.65 The coercive force is strongly size-dependent (Figure 2.5). When the particle size starts decreasing and reaches the critical value (rc), the coercivity increases to a maximum. On further reduction of size below the critical value, thermal energy (kBT) surpasses anisotropic energy (KeffVm). At this point, these NPs show no coercivity but still have Ms comparable to their bulk counterparts and defined as superparamagnetic NPs.27 Another phenomenon related to the size of the NPs is the surface spin-quenching effect. Smaller NPs show more degree of spin-quenching effect and in turn, have low Ms and Hc values.3

2.5.2

NP Crystallinity

Crystal structure affects the magnetic anisotropy energy, which is a basic value for each magnetic material. This anisotropy energy arises from the spin–orbit coupling i.e., interaction between the electron spin and its orbital motion, which is related to the crystallinity of the material. The amount of magnetic anisotropy energy is measured by anisotropy constant (K). In general, the higher the anisotropic constant value, the higher the coercivity (Hc). This phenomenon is well explained in the Fe–Pt alloy system which exists in two different crystal structures i.e., face-centered cubic (fcc) and chemically ordered L10 structure (Figure 2.6).66 In the fcc crystal structure, the Fe and Pt atoms randomly occupy the lattice points which make this material magnetically isotropic and soft. While in the case of the L10 structure, Fe and Pt form the alternate stacking to form a tetragonal lattice i.e., face-centered tetragonal (fct) or the body-centered tetragonal (bct). Due to the strong coupling between the d-orbitals of Fe and Pt, the L10 structure shows a higher value for K67 i.e., up to 7106 J m3. Similarly, Co NPs exist in a hexagonal closed pack

32

Chapter 2

Figure 2.6

Crystal structures of Fe–Pt (fcc) (a) and L10-Fe–Pt (b).

(hcp) and face-centered cubic (fcc) structure. The magnetization value for hcp is higher than fcc as the K value increases from hcp to fcc.68

2.5.3

Chemical Composition

Chemical composition in another important feature to tune the magnetic property of the MNPs. This is observed in magnetic ferrite with an inverse spinel structure. In Fe3O4, oxygen atoms form a close-packed fcc structure with Fe31 atoms present at the octahedral and tetrahedral sites. The bonding between Fe31 and oxygen results in the cancellation of magnetic moments so, the total magnetic moment of iron ferrites is due to ferrous ions (Fe21).69 The net magnetization is improved by replacing Fe21 with Mn21, Co21, or Ni21 from 4 mB (mB ¼ Bohr magneton) to 5 mB, 3 mB, and 2 mB, respectively. The saturation magnetic moments of monodisperse MFe2O4 NPs have been improved by doping the compound with Mn, Co, Ni, and Zn. When Zn 21 replaced Fe31 at a few tetrahedral sites, the exchange coupling between atoms slightly increased which in turn increases the Ms value from 114 to 161 emu g1.44

2.5.4

Surface Potential

MNPs have been successfully applied in theranostic applications. When they encounter a biological fluid they tend to aggregate due to their surface potential. Thus, in vitro and in vitro stability of the MNPs is only possible if the magnetic attractive forces due to the surface charge are waged by introducing electrostatic repulsion between charged surfaces, hydrophilic dipole– dipole interaction, fabrication of core–shell morphology to create a steric barrier onto the particle surface.70 Generally, NPs get a surface charge when they come in contact with aqueous media. The potential across the surface is because of the ions in the area surrounding the particle surface that results in the formation of an electrical double layer.71 It is very difficult to measure the surface charge but experimental methodologies have been designed to measure the zeta potential (z) which is considered to be a function of the surface charge density. z determinations have likewise been of extraordinary

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assistance during the fabrication of nanocomposites comprising of magnetic cores covered with biodegradable polymers, lipid frameworks or an inorganic shell.72

2.5.5

Interfacial Interactions

Interfacial interactions among MNPs have been effectively useful in defining the tendency of particles to stay dispersed or to aggregate within the media. In an aqueous solution, hydrophobic particles will incline to attract each other due to their hydrophobic nature, while a hydrophilic feature will let them disperse effectively to get better thermodynamic stability. The surface free energy of MNPs may be helpful to quantify its thermodynamic stability in aqueous suspensions. These interactions can be easily measured by utilizing the famous model of van Oss. With the help of this model, the surface free energy components of MNPs are determined for the quantitative measurement of their thermodynamic stability in water.73 Experimentally, these parameters can be determined by contact angle measurements. The contact angle measurements help in the estimation of the van der Waals forces, which if not properly balanced by a comparable repulsion force leads to flocculation of nanoparticles.74,75 The thermodynamic analysis would help in finding the surface engineering of MNPs with a biodegradable polymer or inorganic material. A shift in contact angle measurements is observed when a hydrophilic iron oxide surface changes to hydrophobic composite upon coating.76,77 Furthermore, the hydrophilic/hydrophobic nature governs the interfacial interaction of MNPs with the plasma proteins which is called opsonization which highlights the significance of the surface thermodynamics studies of MNPs.78

2.5.6

Magnetism

The magnetic property of a material is because of the spinning of charged particles i.e., electrons, holes, protons, and positive/negative ions, which is well understood by the hysteresis loop obtained when magnetization is plotted as a function of external magnetic strength (H). Based on the magnetic behavior in the presence of an external magnetic field, magnetic materials are classified into five major groups i.e., ferromagnetic, ferrimagnetic, paramagnetic, antiferromagnetic, and diamagnetic.3 Figure 2.7a showed the hysteresis loop for single-domain ferromagnetic NPs which is characterized by remanence and coercivity. By applying an external magnetic field (H), the magnetic moment reaches a maximum value (Ms), where all spins are aligned, called the magnetic saturation. As the external magnetic field is removed, magnetization drops to zero but the material still has the magnetic flux remaining. This point is called remanence. The coercivity corresponds to the energy required to remove the magnetic remanence.2,12,79 Co, Fe, Ni, and their alloys are ferromagnetic materials as they show magnetic behavior below their Curie temperature even if the external field is removed. Though

34

Figure 2.7

Chapter 2

A typical magnetic hysteresis loop of an array of single-domain ferromagnetic NPs (a) and a typical M–H curve of a group of superparamagnetic NPs (b). Reproduced from ref. 79 with permission from the Royal Society of Chemistry.

above this temperature, they behave as paramagnetic materials which tend to lose their magnetic behavior once the external magnetic field is removed due to robust thermal fluctuations. This concept of magnetism differentiates a ferromagnetic material from a paramagnetic material.2 The single-domain (ferromagnetic) NPs below its critical size show a phenomenon known as superparamagnetism. Figure 2.7b shows the magnetization behavior of superparamagnetic materials which is relatively similar to ferromagnetic materials in an external field. When an external field is applied, the magnetic moments of superparamagnetic NPs tend to align along the field and behave as nanomagnets just like the paramagnet material. For such small NPs, the energy barrier (Eb) is less than the thermal energy (kBT), fast flipping of the magnetic moment from one state to another was observed, and the net magnetization is averaged to zero when the external field is removed. Thus, no hysteresis appears in the magnetization curve.79 The particles show negligible remanence and coercivity upon removal of the magnetic field. The negligible remanence of superparamagnetic particles is a fascinating character that circumvents their aggregation. The time between two flips is called ´el relaxation time (tN) which is defined as: the Ne tN ¼ t0 exp

Keff Vm kB T

(2:2)

The flipping of the magnetic moment is temperature-dependent. In superparamagnetic particles, thermal fluctuations are robust enough to demagnetize a magnetically saturated assembly once the external magnetic field is removed, therefore, such particles have no hysteresis loop and zero coercivity. This behavior of MNPs assists in the design of materials suitable for biological environments. Remarkably, superparamagnetic particles help

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35

to control the transverse relaxation signal (T2/T1) in MRI, which can have significant concerns related to the quality of the diagnosis.3,80

2.6 Surface Functionalization and Biocompatibility Surface functionalization is a simple yet effective way of modifying the surface properties of a material or gadget to achieve the targeted goals. The following are the main reasons why a NP surface would need modification: (1) to improve the dispersion, (2) to enhance surface stability, (3) to improve the physicochemical properties, and (4) to increase the biocompatibility. Monodispersed MNPs synthesized via wet-chemistry routes are usually covered with a longalkyl chain leading to a hydrophobic surface. This hydrophobicity provides steric repulsion which in turn improves the colloidal stability in non-aqueous media. To make these MNPs hydrophilic and biocompatible for biomedical application, the surface chemical properties of MNPs can be conveniently and robustly controlled by surface modification via introducing multiple organic/ inorganic components into a single system.1

2.6.1

Surface Stability via Organic/Inorganic Coatings

Bare NPs are inclined to be attacked by oxidative conditions in such a way that their stability is affected because of their high surface-to-volume proportion. Anchoring capability, oxidation, and agglomeration are the evident reason for building up the concept of coatings. Appropriate coatings are required to modify bare magnetic cores into robust MNP frameworks which have been proven to be useful for a wide scope of in vivo and in vitro applications.81 Covering the surface of MNPs with stabilizers can diminish the interaction among molecules that stem to produce colloidally and physically stable, water-soluble MNPs.82 However, the utilization of non-magnetic coating will decrease the magnetic character to some extent but it doesn’t affect the singledomain structure nor its superparamagnetic behavior in a biological system. In particular, coatings ought to give functionalities to the surface of MNPs (e.g., amino, carboxyl, thiol) that help in designing the specificity of MNPs.83 The coating of MNPs can be done via an in situ or a post-synthetic approach. In an in situ method (one-pot synthesis), both the precursors of MNPs and coating materials are present within the same reaction mixture wherein nucleation and uniformly encapsulation of NPs within the coating occur simultaneously. However, this strategy has some drawbacks related to the magnetic susceptibility of MNPs. During the post-synthesis strategy, the surface of the pre-synthesized MNPs is coated through organic ligand exchange/addition and hydrophilic silica/gold coating.13,81 Such post-synthetic methods either exploit the weak van der Waals forces or hydrogen bonds between the coating materials and the NP surface functionalities or attachment onto the surface via chemisorption.84 However, the limitation of physical adsorption is related to the desorption of the weakly bound ligands that can lead to aggregation and loss of functionality from the NP surface.

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Chapter 2

To overcome this, coating strategies need to be designed in which polymers chemically bind with more than one functional group leading to fully encapsulated yet stable NPs.85

2.6.2 2.6.2.1

Organic Coating Materials Monomeric Ligand-based Coatings

Small organic molecules are most commonly used for stabilizing NPs by forming liposomes or micellular structures. Generally, monomeric ligands such as carboxylates, phosphates, and sulfates are chosen due to their high binding affinity toward iron oxide NPs surfaces.86 Adsorption of carboxylic acid on the surface occurs via physical interaction between the carboxylate anion and the hydroxyl groups present on metal oxide surfaces. Polyacids such as citric and dimercaptosuccinic acids have been used on the commercial scale to get a stable colloidal suspension of iron oxide MNPs. The high coordination of these carboxylates with the NP surface is due to multiple carboxyl functional groups. However, this method suffers as carboxylic groups can be easily decomposed at high temperatures.87 Like carboxylates, organophosphate molecules have been examined as promising stabilizing agents as they comparatively form much stronger bonds than carboxylate molecules and provide stability over several weeks.88

2.6.2.2

Polymeric Ligand-based Coatings

Different synthetic and natural polymers have been used for coating NPs to improve biocompatibility and blood circulation time. Additionally, polymers introduce different functional groups such as carboxylic acids, amines, thiols, etc. which in turn facilitate the conjugation of targeted ligands to the surface.89 Synthetic polymers are either biodegradable or nonbiodegradable. Polymer degradation is influenced by various factors such as structure, chemical composition, and molecular weight of the polymer, shape, and size of the polymer-coated NPs, administration route, and type of degradation (enzymatic or microbial).90 The most commonly used non-toxic synthetic polymer is polyethylene glycol (PEG), which extends the blood circulation time of NPs by making the surface hydrophilic.91 In addition, natural polymers such as dextran, chitosan, gelatin, and alginate, are also useful in terms of their biocompatibility and can be used as stabilizing agents. Several MNPs coated by dextran have been used to enhance the contrast of MRI during the past few decades. Feraheme NPs, a commercially available MRI agent is coated with carboxymethyldextran polymer that provides a carboxyl group to the surface for fluorochrome attachment. Such fluorochrome functionalized NPs are used to image DNA in biological systems.92 Besides, chitosan-coated iron oxide nanoparticles have been well exploited for targeting photodynamic therapy.93 In the same way, different synthetic copolymers are also used to coat the NP surface to improve the

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biocompatibility and stability of the MNPs. For example, superparamagnetic iron oxide NPs (SPIONs) coated with a copolymer (PEG-g-chitosan-g-PEI) were fabricated to be effectively used for delivering DNA.94 Also, iron oxide NPs were coated with a PEGylated amphiphilic triblock copolymer comprising polybutylacrylate polyethylacrylate, polymethacrylic acid, and a hydrophobic alkyl chain for in vivo cancer targeting and imaging.95

2.6.3 Inorganic Coating Materials 2.6.3.1 Silica-based Coating (Silanization) Modification of a MNP surface through an inorganic approach is commonly done by using silica-based matrices, which not only preserves the characteristic features of the MNPs but also enables them to disperse in aqueous media.96 Silica, an amorphous and heat-resisting material, brings hydroxyl groups to the surface during silanization that provides hydrophilicity and offers different chemical ways to graft ligands to the surface for targeted applications.97 Furthermore, the surface of the MNPs coated with silica gets negatively charged when it is introduced in the blood circulation which results in avoiding the agglomeration of the NPs. Also, the transparent nature of the silica matrix provides an efficient pathway to excited and emitted light that results in better imaging.98 Philipse and his colleagues coated magnetite NPs with silica through the sol–gel method to improve its dispersion in water for the very first time.99 The ¨ber method, reverse microemulsions or direct micelle assisted methods are Sto mostly employed to coat silica on MNPs.100,101 Recently, Fe3O4 MNPs were coated with 3-aminopropyl triethoxysilane (APTES) and tetraethyl orthosilicate (TEOS). Along with the increase in their hydrophilicity and pH stability, this study helps to further understand the effect of the thickness of the coating on dispersion; the thicker the coating, the less iron oxide gets dispersed.102

2.6.3.2

Gold-based Coating

The inertness of gold toward oxidation and its non-toxic nature has made this precious metal perfect for conjugation with different biomolecules.103 Protein purification/immobilization of biomolecules and MRI are a few applications where gold-coated MNPs have been used. The advantage of the gold coating is the superparamagnetic nature of magnetic NPs.104–106 Also, the near-infrared (NIR) light-sensitive feature of gold surfaces, when combined with the MNPs, makes these systems practical for MRI as well as optical imaging applications.107 Currently, there has been a considerable number of reports on synthesizing gold-coated MNPs through microemulsion, reduction, co-precipitation, seed-mediated growth, and thermal decomposition.108–110 The direct coating of iron oxide NPs with gold is difficult as the nature of the two crystalline surfaces is completely different from each other.111 In recent times, the effect of gold coatings on the removal of MNPs from blood circulation has been comprehensively studied.

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The in vivo degradation of MNPs and coatings showed that the surface properties have a strong impact on the kinetics of eliminations from the body via the liver and spleen.112

2.6.4

Biocompatibility of FMNPs

In biomedical applications, the most important property of the materials that needs to be considered is high biocompatibility toward cells, tissues, or organisms. Several factors such as surface coatings, size of the MNPs, and nature of the magnetic core could influence the biocompatibility and toxicity of nanocomposites.3,12 In this regard, the effect of different polymers [PEG, bovine serum albumin (BSA) and poly(D,L-lactide-co-glycolide) (PLGA)] on biocompatibility was studied. PEGylated and bare MNPs were more efficiently taken up by A549 cells than the MNPs coated with BSA and PLGA.113 It has also been reported that polyvinyl alcohol (PVA) coated MNPs didn’t invade or induce an inflammatory reaction in the brain cell aggregates. Such systems demonstrated no cytotoxicity toward brain-derived endothelial cells.114 Furthermore, SPIONs were toxic to human dermal fibroblasts while the pullulan polymer coated SPIONs were found to be non-toxic. The cytotoxicity of dimercaptosuccinic acid (DMSA), lactoferrin, and 3,4-dihydroxy-D,L-phenylalanine (DL-DOPA) have also been studied. DMSA and DOPA coated SPIONS can efficiently enter into the target cells without causing any cytotoxicity.115 The second important factor that influences the biocompatibility of the coated MNPs is the size. The inflammatory response of a macrophage was examined by enzyme-linked immunosorbent assay upon the addition of different sized PEGylated or silica-coated iron oxide nanocomposites. The cytotoxicity for PEGylated MNPs was less than those coated with silica.116 In the case of drug nanocarriers, biocompatibility is linked to the response of the immune system after its administration and the toxicity of the carrier. The biocompatibility of bare and PEGylated iron oxide NPs was analyzed by incubating them with primary human fibroblasts. The uncoated showed a significant decrease in cell adhesion whereas PEGylated NPs did not cause any notable change. Similarly, incubation of dextran-coated iron oxide NPs with primary human fibroblasts showed cytotoxicity and apoptosis similar to that of the uncoated NPs. Besides, albumin-coated NPs showed a toxicity level considerably lower than that of bare and dextran-coated NPs.117,118

2.7 Biomedical Applications of FMNPs The multifunctionality is an important feature behind the success of the utilization of these MNPs in several biomedical applications ranging from sensing and bioseparation to theranostic approaches such as MRI, magnetic hyperthermia, and targeted drug delivery. The main advantages of MNPs are associated with their small size (o100 nm), narrow size distributions, high surface–volume ratios, magnetic susceptibility, surface reactivity, and superparamagnetic nature.

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39

FMNPs as Biosensors

FMNPs are of high significance in sensing as they provide practical solutions to the long-term challenges related to non-specific binding effects and lower limit of detection. Among FMNPs, SPIONs having a high Ms value, superparamagnetic behavior, and colloidal stability result in highly selective and durable sensors.119 Resovist, Feraheme, DexIron, and INFeD are FDA approved SPIONs and are commonly used as an MRI contrast agent and they might be useful for sensing applications as well. Different commercial companies like Sigma-Aldrich, creative diagnostics, Nanocomposix, and Avantama have developed magnetite and maghemite-based MNPs that are mostly used for sensing-based applications.120,121 In an ordinary sensor, an analyte diffuses to the detecting surface where an electrochemical or optical transducer produces a signal depending upon the interaction between the analyte and the surface. On the other hand, ligand-specific MNPs have been utilized to capture more analyte from the sample and carry it under magnetic control efficiently to the detecting surface and in return have amplified the detecting signal.122 Fluorescence methods along with magnetic-based biosensors have been widely used for bacterial detection. For example, aptamer-conjugated magnetic NPs as a signal enhancement tool and antibiotic-conjugated gold nanocluster (Au NCs) for the fluorescent signal have been utilized for highly sensitive detection of the S. aureus bacterial strain in milk and human serum samples (Figure 2.8).123 Besides fluorescent Au NCs, fluorescent dyes, conjugated polymers, and quantum dots have also been utilized with magnetic bead-based biosensors for detecting different strains of bacteria.124 In addition to fluorescence signals, surface-enhanced Raman spectroscopy (SERS) techniques have also been coupled with magnetic biosensors. Au NPs functionalized with Raman probe molecules such as 4-mercaptobenzoic acid (4-MBA) and 5,5 0 dithio-bis(2-nitrobenzoic acid) (DTNB) and aptamers represented as a SERS

Figure 2.8

Graphical representation of the specific and sensitive detection of bacteria using aptamer-coated magnetic beads and antibiotic-capped gold nanoclusters. Reproduced from ref. 123 with permission from American Chemical Society, Copyright 2016.

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substrate and aptamer-functionalized Fe3O4 MNPs were used as the capturing probe. This type of sandwich-type SERS-based sensing platform was used for the simultaneous detection of S. typhimurium and S. aureus.125 Noble metal NPs, due to their high surface to volume ratio and high conductivity, are good candidates to be used in electrochemical biosensors. CTAB modified Au NRs were deposited onto the bacterial surface through electrostatic interactions, which results in the enhancement of the electrochemical signal by four times.126 Later, primary antibody conjugated MNPs capture the target bacteria (Salmonella) followed by binding of secondary antibody conjugated Au NPs. Such a complex with the help of a magnetic field was brought to the carbon electrode, a transducer, for rapid and sensitive detection in the form of an electrochemical signal.126,127

2.7.2

FMNPs for Protein Purification/Bioseparation

Conventional purification methods such as chromatography and ultrafiltration, require an expensive and complex setup. However, magnetic nanomaterials offer a cost-effective and simple methodology to purify different biomolecules.128 During the magnetic purification process, the specific ligand having an affinity toward the targeted biomolecule is conjugated to the surface of magnetic nanoparticles, and these smart materials after treating with the extracted protein mixture can be removed with the help of an external magnetic source (Figure 2.9). In such a way, the targeted biomolecules bound to the specific ligand can be separated from the complex mixture of proteins. Streptavidin, Protein A, Protein G, and trypsin are commonly used as affinity ligands for protein purification.5,129–133 Water-dispersible SPIONs conjugated with biotin were used for the magnetic separation of avidin.134 Furthermore, nitrilotriacetic acid (NTA) conjugated MNPs offer a versatile platform for separating the histidine-tagged (his-tag) protein from the mixture. The high surface-to-volume proportion and the good aqueous

Figure 2.9

Basic mechanism of protein purification using MNPs.

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dispersity of the NPs increase the protein binding capacity to the FMNPs and resultantly one can isolate the protein with ease. Furthermore, NTA conjugated MNPs eliminate the cell lysis step and can be reused without losing efficiency. However, during protein purification, the toxicity of the metal– NTA needs caution for in-vivo applications.135,136 While designing materials for biomedical applications, the cytotoxicity level of this material is an important factor that must be considered. For this purpose, the cytotoxicity of Fe3O4 NPs against human Glia, cancer, and normal cell lines was measured as a function of its concentration (0.1 to 100 mg mL1). The results showed that the concentration range from 0.1–10 mg mL1of iron oxide NPs exhibited almost no toxicity. Though at a high concentration of 100 mg mL1, a certain level of cytotoxicity was observed. Overall, iron oxide NPs show good biocompatibility. Additionally, the cytotoxicity can be reduced by surface modification using components with high biocompatibility.137,138

2.7.3

FMNPs as Contrast Agents for MRI

The magnetic signal, one of the important features, produced by MNPs can be detected within the body and allows fast in vivo sensing. Magnetic resonance imaging (MRI) is a leading imaging technique in which magnetic fields penetrate through the body tissue without damaging it for detection and imaging inside the body. The resultant image produced through MRI is based on the contrast difference observed due to different water content in body tissues.119 Principally, protons of water molecules inside the body tissues have an intrinsic tendency to get aligned parallel to an applied external magnetic field. When the external magnetic field is removed, the protons flip back to the ground state from the excited state. The energy released due to this flipping of an electron lies in the radiofrequency (RF) region. The difference in time required for the realignment of protons back to their original state in different tissues corresponds to T1 and T2 relaxation times for longitudinal and transverse components of magnetization vectors.139 Developing effective contrast agents is essential to increase and widen the diagnostic utilization of imaging techniques. Contrast agents are capable of interacting with the water molecules within the biological tissues and modify the T1 or T2 relaxation rates which can more efficiently distinguish and illuminate the tissues.140 For example, gadolinium (Gd)-chelates having high-spin paramagnetic Gd31 ions were first-generation contrast agents. For three decades, they have been combined with different ligands to act as a T1 contrast agent. The intrinsic limitations of these Gd-based complexes are their high levels of toxicity, poor cell uptake, and short life span.141 Therefore, MNPs have arisen as a potential alternative to these conventional contrast agents as they enhance the dark-field contrast, produced by the T2 relaxation of 12 spin protons of water, by coupling with the water molecules present inside the biological tissues. As the T2 relaxation time is inversely proportional to the Ms value, so MNPs with a high Ms value produce higher contrast in MRI.142 This has directed the current research toward the development of Fe(0) and doped ferrite-based

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Figure 2.10

Schematic representation of the synthesis and functionalization of BSAtemplated uBSPIO (a). LHRH–uBSPIO as an LHRH receptor targeted T2 contrast agent for MRI (b). Reproduced from ref. 144 with permission from American Chemical Society, Copyright 2017.

MNPs as an improved MRI contrast agent. Iron-based core–shell MNPs can detect small tumors (1–3 mm) and achieved high MRI contrast at 5 times lower concentrations than bare iron oxide MNPs.143 Similarly, transition metal-based ferrite MNPs produced higher MRI contrast than commercially available SPIONs. These iron and ferrite-based MNPs show low cytotoxicity which makes them nearly ideal T2 MRI contrast agents. Similarly, ultrasmall-sized (4.78  0.55 nm) uBSPIONs with good monodispersity and high relaxivity (444.56  8.82 mM1 s1) are designed as a T2 MRI contrast agent. Figure 2.9 shows the synthesis and functionalization of BSA-templated SPIONs with luteinizing hormone release hormone peptide (LHRH) for targeted accumulation at the tumor site. These SPIONs had good stability and did not induce cytotoxicity in vitro or major organ toxicity in vivo (Figure 2.10).144 The current research focused on developing easy to handle probes that can precisely locate and measure the size of the tumor and provide a non-toxic alternate to radioactive tracers.145

2.7.4

FMNPs for Targeted Drug Delivery

Significant efforts have been focused on drug delivery systems, such as pH/ redox/temperature-responsive nanocarriers, to reduce the side effects and improve the treatment efficiency of drugs. However, biotoxicity, targeted drug delivery, high costs, and large-scale manufacturing are a few big challenges that need to be overcome.146,147 In conventional systems, the drug circulates through the bloodstream, and the disadvantage is that only a small amount

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can reach the infected area and the majority goes to other organs, resulting in side effects. The aim of designing a targeted drug delivery system is to concentrate the drug within the infected tissue/organ.148 Magnetic nanomaterials are promising alternatives for a targeted drug delivery system, as with the help of an external applied magnetic field, stimuli-responsive magnetic drug nanocarriers can effectively accumulate at the targeted site and based on stimulus the drug is released which will be taken up effectively by tumor cells.149 Core–shell magnetic nanostructures are usually developed as a targeted drug delivery system. The loading and release of the drug depend on the size, morphology, porosity, and biocompatibility of the surface.150 Hydrophilic polymers are preferable to construct a shell of the drug nanocarriers of the system because of its applications in various biomedical fields.151 The size of MNPs is very important while designing a magnetic nanocarrier system. Large particles (4200 nm) accumulate within the spleen and are finally removed by cells through phagocytosis, whereas small particles (o10 nm) can be removed by extravasations through the renal system. 10–100 nm sized MNPs with a long blood circulation time are desirable for intravenous injection, which is favorable to behave as an efficient drug nanocarrier.129 Cisplatin encapsulated porous Fe3O4 MNPs conjugated with Herceptin were used to target breast cancer cell lines (SK-BR-3). The release rate of cisplatin was pH-dependent and could be improved via organic/silica coatings (Figure 2.11A).152 Similarly, magnetic Fe3O4@mesoporous silica nanocomposites were developed, by synthesizing Fe3O4 NPs in the mesoporous silica matrix using the sol–gel method in an inert atmosphere, for targeted aspirin (drug) delivery and bioadsorption. However, the biodegradability of silica and other polymer coatings is unsatisfactory.153 For this purpose, the surface of the MNPs is covered with a biodegradable inorganic material such as hydroxyapatite,154 amorphous calcium phosphate/silicate,155,156 and magnesium silicate, for example, superparamagnetic porous yolk/shell iron oxide@magnesium silicate (SPIO@MS) nanospheres are synthesized for targeted drug delivery with improved biodegradability. These nanospheres exhibited a higher drug loading capacity of 526 mg g1 than that of the SPIO which was found to be due to the thicker magnesium silicate shell. The drug release study under various pH values showed that this system is pH-responsive and showed a sustained drug release behavior in vitro. The cytotoxicity assays demonstrated the significant anticancer effect of these nanospheres and the promising application potential as a drug delivery system.157 Similarly, non-toxic magneto-vesicles having tunable layers of densely packed amphiphilic block copolymer around SPIONs were fabricated. This kind of nanoplatform may find applications in effective disease control by targeted drug delivery to organs/tissues that are not readily accessible by conventional delivery methods (Figure 2.11B).158

2.7.5

FMNPs for Magnetic Hyperthermia

Magnetic hyperthermia is considered as another promising method for clinical cancer treatment. In magnetic hyperthermia, heat is produced due to

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Figure 2.11

Chapter 2

(A) Schematic illustration of cisplatin loading into porous hollow NPs and functionalization with Herceptin (a). TEM image of the 16 nm HNPs of Fe3O4 (b). Representative TEM images of an SK-BR-3 cell treated with Her–Pt–PHNPs showing the internalization of Her–Pt–PHNPs in the SK-BR-3 cell (c). Reproduced from ref. 152 with permission from American Chemical Society, Copyright 2009. (B) Fabrication of magneto-vesicles (MVs) with tunable wall thickness (a) and utilization of MVs for imaging-guided magnetic delivery of Dox into tumor-bearing mice (b). Reproduced from ref. 158 with permission from American Chemical Society, Copyright 2018.

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magnetic hysteresis loss when MNPs are subjected to an alternating magnetic field and this heat would cause cancer cell death as a result of apoptosis and necrosis.159 Iron oxide nanocubes with a small size had better magnetic heating efficiency than spherical and large particles. Similarly, iron oxide nanorods with a tunable aspect ratio had a high magnetic heating efficiency as compared to spherical and cubic shaped NPs. This study showed that the heating efficiency of the designed materials in the case of magnetic hyperthermia depends on the aspect ratio and morphology of the designed material (Figure 2.11).160,161 The phenomena of doping the magnetic material with different transition metal ions can also play an important role in tuning heating efficiency. For example, two times enhancement in the magnetic particle imaging signal was observed through selective doping of Fe3O4 NPs with Zn21 metal ions while Fe3O4 nanocubes showed five times enhancement when doped with Zn21 when compared with the heating efficiency observed for the undoped magnetic nanospheres.162 The drawback of MFH is that there is a possibility of damaging healthy cells during the heating of tumor cells, and the difficult part of this therapy is that when heating the tumor part to a significantly high temperature, the normal tissues should be maintained at a lower temperature. To overcome this issue, targeted magnetic hyperthermia is needed for cancer therapy.148 Thus, surface functionalization of MNPs is required to minimize the damage and target only the tumor tissue. The biocompatibility and heating efficiency of magnetic nanostructured materials used for targeted cancer hyperthermia treatment can be improved through surface functionalization, for example alginate/iron oxide core–shell NP surfaces can be further functionalized with D-glactosamine (Fe3O4@Alg–GA) to target the human hepatocellular carcinoma cell line (HepG2) specifically. This magnetic framework consists of a Fe3O4 based core, alginate as a shell, and cell-specific ligand (D-glactosamine). These Fe3O4@Alg–GA NPs showed excellent cell and blood compatibility, and high magnetic hyperthermic efficiency. The 60% decrease in cell viability and targeted hyperthermia effect indicates the high efficacy of surface modification for improving the cancer hyperthermia treatment (Figure 2.12).163,164

2.8 Future Trends and Perspective So far, there has been extraordinary development in the usage of FMNPs for a range of applications from sensing to bioseparation, from imaging to effective drug delivery and thermal ablation. By applying established synthetic protocols to synthesize multicomponent MNPs, various combinations of functionalities have been incorporated which have shown remarkable success on a lab scale. But there are still numerous concerns that remain to be addressed to understand the potential of the FMNPs. Firstly, in vivo toxicity needs to be measured very carefully. As different MNPs are made of toxic elements, the long-term toxic effects after their degradation should be measured. A lot of work regarding polymeric coatings has been done but detailed study beyond cell viability assay is often neglected. Surface coatings

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Figure 2.12

Chapter 2

Synthesis of Fe3O4@Alg–GA nanoparticles for magnetic fluid hyperthermia. Reproduced from ref. 164 with permission from Dove Medical Press Limited, Copyright 2015.

required additional developments to design new materials with improved in vivo stability and long circulation times. Besides, detrimental effects on healthy tissues are observed when MNPs are subjected to kill malignant tissues via ROS generation, thermal ablation, and drug release. Similarly, potentially toxic MNPs localize in the liver and kidney which causes serious health issues. One of the approaches to reduce NP accumulation in various organs is by using small-sized NPs. Furthermore, as multi functionalities are usually achieved by designing a multi-component system, and in this case, it is unavoidable to control the increasing size. Considering this aspect, potential work needs to be done in designing single-component-based multifunctional NPs. A notable benefit of FMNPs is that they comprise a higher degree of design flexibility. In this regard, more broad and efficient research must be directed to comprehend the complex interactions between MNPs and biological systems as a basis to sustain the possibilities of the multifunctional MNPs.

Acknowledgements The support from the Human Frontier Science Program (RGY0074/2016), the Higher Education Commission of Pakistan (for NRPU Project No. 20-1740/ R&D/10/3368, 20-1799/R&D/10-5302 and 5922, TDF-033 grants, Indigenous PhD Fellowship), Lahore University of Management Sciences (LUMS for start-up fund and Faculty Initiative Fund grant), and the Commonwealth Scholarship Commission are acknowledged. H. D. gratefully acknowledges the Max-Planck-Gesellschaft (MPG) for financial support of the MPIP-TOBB ETU Partner Group Program.

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References 1. D. Kim, K. Shin, S. G. Kwon and T. Hyeon, Adv. Mater., 2018, 30, 1802309. 2. A. Akbarzadeh, M. Samiei and S. Davaran, Nanoscale Res. Lett., 2012, 7, 144. 3. K. Wu, D. Su, J. Liu, R. Saha and J.-P. Wang, Nanotechnology, 2019, 30, 502003. 4. S. P. Gubin, Magnetic Nanoparticles, John Wiley & Sons, 2009. 5. G. S. Demirer, A. C. Okur and S. Kizilel, J. Mater. Chem. B, 2015, 3, 7831– 7849. 6. Y. Xiao and J. Du, J. Mater. Chem. B, 2020, 8, 354–367. ´rrez, 7. M. Colombo, S. Carregal-Romero, M. F. Casula, L. Gutie ¨hm, J. T. Heverhagen, D. Prosperi and M. P. Morales, I. B. Bo W. J. Parak, Chem. Soc. Rev., 2012, 41, 4306–4334. ¨th, Angew. Chem., Int. Ed., 2007, 46, 8. A. H. Lu, E. E. L. Salabas and F. Schu 1222–1244. 9. Y. Hou and D. J. Sellmyer, Magnetic Nanomaterials: Fundamentals, Synthesis and Applications, John Wiley & Sons, 2017. 10. M. Duan, J. G. Shapter, W. Qi, S. Yang and G. Gao, Nanotechnology, 2018, 29, 452001. 11. T. J. Merkel, K. P. Herlihy, J. Nunes, R. M. Orgel, J. P. Rolland and J. M. DeSimone, Langmuir, 2010, 26, 13086–13096. 12. L. H. Reddy, J. L. Arias, J. Nicolas and P. Couvreur, Chem. Rev., 2012, 112, 5818–5878. 13. R. Hao, R. Xing, Z. Xu, Y. Hou, S. Gao and S. Sun, Adv. Mater., 2010, 22, 2729–2742. 14. V. K. LaMer and R. H. Dinegar, J. Am. Chem. Soc., 1950, 72, 4847–4854. 15. T. D. Schladt, K. Schneider, H. Schild and W. Tremel, Dalton Trans., 2011, 40, 6315–6343. 16. K. Zhu, Y. Ju, J. Xu, Z. Yang, S. Gao and Y. Hou, Acc. Chem. Res., 2018, 51, 404–413. 17. B. D. Cullity and C. D. Graham, Introduction to Magnetic Materials, John Wiley & Sons, 2011. 18. D. L. Huber, Small, 2005, 1, 482–501. 19. S. Hisano and K. Saito, J. Magn. Magn. Mater., 1998, 190, 371–381. 20. S. Peng, C. Wang, J. Xie and S. Sun, J. Am. Chem. Soc., 2006, 128, 10676– 10677. 21. Y.-L. Hou and S. Gao, J. Alloys Compd., 2004, 365, 112–116. 22. F. Dumestre, B. Chaudret, C. Amiens, P. Renaud and P. Fejes, Science, 2004, 303, 821–823. 23. O. P. Bolade, A. B. Williams and N. U. Benson, Environ. Nanotechnol., Monit. Manage., 2020, 13, 100279. 24. C. B. Murray, S. Sun, W. Gaschler, H. Doyle, T. A. Betley and C. R. Kagan, IBM J. Res. Dev., 2001, 45, 47–56. 25. S. Peng, J. Xie and S. Sun, J. Solid State Chem., 2008, 181, 1560–1564.

48

Chapter 2

26. C. Petit, A. Taleb and M. Pileni, J. Phys. Chem. B, 1999, 103, 1805–1810. 27. L. Wu, A. Mendoza-Garcia, Q. Li and S. Sun, Chem. Rev., 2016, 116, 10473–10512. 28. Y. Hou and S. Gao, J. Mater. Chem., 2003, 13, 1510–1512. 29. Y. Pan, R. Jia, J. Zhao, J. Liang, Y. Liu and C. Liu, Appl. Surf. Sci., 2014, 316, 276–285. 30. R. Sundar and S. Deevi, Int. Mater. Rev., 2005, 50, 157–192. ¨tten, D. Sudfeld, I. Ennen, G. Reiss, K. Wojczykowski and P. Jutzi, 31. A. Hu J. Magn. Magn. Mater., 2005, 293, 93–101. 32. G. S. Chaubey, C. Barcena, N. Poudyal, C. Rong, J. Gao, S. Sun and J. P. Liu, J. Am. Chem. Soc., 2007, 129, 7214–7215. 33. M. Chen, J. Liu and S. Sun, J. Am. Chem. Soc., 2004, 126, 8394–8395. 34. E. V. Shevchenko, D. V. Talapin, A. L. Rogach, A. Kornowski, M. Haase and H. Weller, J. Am. Chem. Soc., 2002, 124, 11480–11485. 35. Y. Hou, H. Kondoh, R. Che, M. Takeguchi and T. Ohta, Small, 2006, 2, 235–238. 36. S. Guo, D. Li, H. Zhu, S. Zhang, N. M. Markovic, V. R. Stamenkovic and S. Sun, Angew. Chem., 2013, 125, 3549–3552. 37. Q. Dong, W. Qu, W. Liang, K. Guo, H. Xue, Y. Guo, Z. Meng, C.-L. Ho, C.-W. Leung and W.-Y. Wong, Nanoscale, 2016, 8, 7068–7074. 38. Z. Meng, F. Xiao, Z. Wei, X. Guo, Y. Zhu, Y. Liu, G. Li, Z.-Q. Yu, M. Shao and W.-Y. Wong, Nano Res., 2019, 12, 2954–2959. 39. Y. Hou, H. Kondoh, T. Kogure and T. Ohta, Chem. Mater., 2004, 16, 5149–5152. 40. Y. Yu, K. Sun, Y. Tian, X.-Z. Li, M. J. Kramer, D. J. Sellmyer, J. E. Shield and S. Sun, Nano Lett., 2013, 13, 4975–4979. 41. Y. Hou, Z. Xu, S. Peng, C. Rong, J. P. Liu and S. Sun, Adv. Mater., 2007, 19, 3349–3352. 42. S. Sun and H. Zeng, J. Am. Chem. Soc., 2002, 124, 8204–8205. 43. S. Sun, H. Zeng, D. B. Robinson, S. Raoux, P. M. Rice, S. X. Wang and G. Li, J. Am. Chem. Soc., 2004, 126, 273–279. 44. J. T. Jang, H. Nah, J. H. Lee, S. H. Moon, M. G. Kim and J. Cheon, Angew. Chem., Int. Ed., 2009, 48, 1234–1238. 45. L. Gao, Z. Liu, Z. Yang, L. Cao, C. Feng, M. Chu and J. Tang, Appl. Surf. Sci., 2020, 508, 145292. 46. N. Bao, L. Shen, Y. Wang, P. Padhan and A. Gupta, J. Am. Chem. Soc., 2007, 129, 12374–12375. 47. R. Chen, M. G. Christiansen and P. Anikeeva, ACS Nano, 2013, 7, 8990– 9000. 48. Y. Hou, Z. Xu and S. Sun, Angew. Chem., 2007, 119, 6445–6448. 49. Y. Hou, H. Kondoh, M. Shimojo, T. Kogure and T. Ohta, J. Phys. Chem. B, 2005, 109, 19094–19098. 50. A. D. Khalaji, M. Jarosova, P. Machek, K. Chen and D. Xue, Scr. Mater., 2020, 181, 53–57. 51. M. Ghosh, K. Biswas, A. Sundaresan and C. Rao, J. Mater. Chem., 2006, 16, 106–111.

Design of Functionalized Magnetic Nanoparticles for Improving Stabilization

49

52. C. Giordano, A. Kraupner, S. C. Wimbush and M. Antonietti, Small, 2010, 6, 1859–1862. 53. J. Stencel, P. Eklund, X.-X. Bi, B. Davis, G. Hager and F. Derbyshire, Studies in Surface Science and Catalysis, Elsevier, 1993, vol. 75, pp. 1797–1800. 54. Z. Schnepp, S. C. Wimbush, M. Antonietti and C. Giordano, Chem. Mater., 2010, 22, 5340–5344. 55. Z. Schnepp, W. Yang, M. Antonietti and C. Giordano, Angew. Chem., Int. Ed., 2010, 49, 6564–6566. 56. C. Yang, H. Zhao, Y. Hou and D. Ma, J. Am. Chem. Soc., 2012, 134, 15814–15821. 57. Z. Yang, T. Zhao, X. Huang, X. Chu, T. Tang, Y. Ju, Q. Wang, Y. Hou and S. Gao, Chem. Sci., 2017, 8, 473–481. 58. S. Bhattacharyya, J. Phys. Chem. C, 2015, 119, 1601–1622. 59. R. Ghosh Chaudhuri and S. Paria, Chem. Rev., 2012, 112, 2373–2433. 60. Z. Xu, Y. Hou and S. Sun, J. Am. Chem. Soc., 2007, 129, 8698–8699. 61. W.-P. Li, P.-Y. Liao, C.-H. Su and C.-S. Yeh, J. Am. Chem. Soc., 2014, 136, 10062–10075. 62. C. Xu, B. Wang and S. Sun, J. Am. Chem. Soc., 2009, 131, 4216–4217. 63. Y. Li, Q. Zhang, A. V. Nurmikko and S. Sun, Nano Lett., 2005, 5, 1689– 1692. 64. S. Bedanta, A. Barman, W. Kleemann, O. Petracic and T. Seki, J. Nanomater., 2013, 2013. 65. K. Wu, J. Liu, Y. Wang, C. Ye, Y. Feng and J.-P. Wang, Appl. Phys. Lett., 2015, 107, 053701. 66. S. Sun, Adv. Mater., 2006, 18, 393–403. 67. A. Kabir, J. Hu, V. Turkowski, R. Wu, R. Camley and T. S. Rahman, Phys. Rev. B, 2015, 92, 054424. ˜ a O’Shea, I. D. P. Moreira, A. Rolda ´n and F. Illas, J. Chem. 68. V. A. de la Pen Phys., 2010, 133, 024701. 69. J.-H. Lee, Y.-M. Huh, Y.-W. Jun, J.-W. Seo, J.-T. Jang, H.-T. Song, S. Kim, E.-J. Cho, H.-G. Yoon and J.-S. Suh, Nature Med., 2007, 13, 95–99. ´n, J. Arias, V. Gallardo and A. Delgado, J. Pharm. Sci., 2008, 97, 70. J. Dura 2948–2983. 71. L. Joly, C. Ybert, E. Trizac and L. Bocquet, Phys. Rev. Lett., 2004, 93, 257805. 72. A. V. Delgado and F. J. Arroyo, Interfacial Electrokinetics Electrophor., 2002, 1–54. 73. C. J. Van OssInterfacial Forces in Aqueous Media, CRC press, 2006. 74. J. Arias, V. Gallardo, S. Gomez-Lopera, R. Plaza and A. Delgado, J. Controlled Release, 2001, 77, 309–321. ´. V. Delgado, Eur. J. Pharm. 75. J. L. Arias, V. Gallardo, M. A. Ruiz and A Biopharm., 2008, 69, 54–63. 76. J. Arias, V. Gallardo, F. Linares-Molinero and A. Delgado, J. Colloid Interface Sci., 2006, 299, 599–607. ´pez-Viota and A. Delgado, Int. J. 77. J. Arias, M. Lopez-Viota, M. Ruiz, J. Lo Pharm., 2007, 339, 237–245.

50

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¨pf, H. Hofmann, M. Hofmann and 78. T. Neuberger, B. Scho B. Von Rechenberg, J. Magn. Magn. Mater., 2005, 293, 483–496. 79. Q. Dong, Z. Meng, C.-L. Ho, H. Guo, W. Yang, I. Manners, L. Xu and W.-Y. Wong, Chem. Soc. Rev., 2018, 47, 4934–4953. 80. N. Lee, D. Yoo, D. Ling, M. H. Cho, T. Hyeon and J. Cheon, Chem. Rev., 2015, 115, 10637–10689. 81. J. Mosayebi, M. Kiyasatfar and S. Laurent, Adv. Healthcare Mater., 2017, 6, 1700306. 82. A. Agarwala, N. Kaynan, S. Zaidiner and R. Yerushalmi, Chem. Commun., 2014, 50, 5397–5399. 83. S. Basiruddin, A. Saha, N. Pradhan and N. R. Jana, J. Phys. Chem. C, 2010, 114, 11009–11017. 84. D. S. Achilleos and M. Vamvakaki, Materials, 2010, 3, 1981–2026. 85. E. Giovanelli, E. Muro, G. Sitbon, M. Hanafi, T. Pons, B. Dubertret and N. Lequeux, Langmuir, 2012, 28, 15177–15184. 86. S. Laurent, A. A. Saei, S. Behzadi, A. Panahifar and M. Mahmoudi, Expert Opin. Drug Delivery, 2014, 11, 1449–1470. 87. K. Turcheniuk, A. V. Tarasevych, V. P. Kukhar, R. Boukherroub and S. Szunerits, Nanoscale, 2013, 5, 10729–10752. 88. S. Mallakpour and M. Madani, Progr. Org. Coat., 2015, 86, 194–207. 89. L. M. Bronstein and Z. B. Shifrina, Chem. Rev., 2011, 111, 5301–5344. 90. H. Tian, Z. Tang, X. Zhuang, X. Chen and X. Jing, Progr. Polym. Sci., 2012, 37, 237–280. 91. T. Blin, A. Kakinen, E. H. Pilkington, A. Ivask, F. Ding, J. F. Quinn, M. R. Whittaker, P. C. Ke and T. P. Davis, Polym. Chem., 2016, 7, 1931– 1944. 92. H. Cho, D. Alcantara, H. Yuan, R. A. Sheth, H. H. Chen, P. Huang, S. B. Andersson, D. E. Sosnovik, U. Mahmood and L. Josephson, ACS Nano, 2013, 7, 2032–2041. 93. Y. Sun, Z.-L. Chen, X.-X. Yang, P. Huang, X.-P. Zhou and X.-X. Du, Nanotechnology, 2009, 20, 135102. 94. F. M. Kievit, O. Veiseh, N. Bhattarai, C. Fang, J. W. Gunn, D. Lee, R. G. Ellenbogen, J. M. Olson and M. Zhang, Adv. Funct. Mater., 2009, 19, 2244–2251. 95. K. Chen, J. Xie, H. Xu, D. Behera, M. H. Michalski, S. Biswal, A. Wang and X. Chen, Biomaterials, 2009, 30, 6912–6919. ´rez-Juste and L. M. Liz-Marza ´n, Adv. Mater., 96. A. Guerrero-Martı´nez, J. Pe 2010, 22, 1182–1195. 97. M. Z. Iqbal, X. Ma, T. Chen, W. Ren, L. Xiang and A. Wu, J. Mater. Chem. B, 2015, 3, 5172–5181. 98. R. Alwi, S. Telenkov, A. Mandelis, T. Leshuk, F. Gu, S. Oladepo and K. Michaelian, Biomed. Opt. Express, 2012, 3, 2500–2509. 99. A. P. Philipse, M. P. Van Bruggen and C. Pathmamanoharan, Langmuir, 1994, 10, 92–99. ¨ber, A. Fink and E. Bohn, J. Colloid Interface Sci., 1968, 26, 100. W. Sto 62–69.

Design of Functionalized Magnetic Nanoparticles for Improving Stabilization

51

101. R. P. Bagwe, C. Yang, L. R. Hilliard and W. Tan, Langmuir, 2004, 20, 8336–8342. 102. M. Kuzminska, N. Carlier, R. Backov and E. M. Gaigneaux, Appl. Catal., A, 2015, 505, 200–212. 103. L. Lou, K. Yu, Z. Zhang, R. Huang, J. Zhu, Y. Wang and Z. Zhu, Nano Res., 2012, 5, 272–282. 104. Y. Okada, T. Y. Takano, N. Kobayashi, A. Hayashi, M. Yonekura, Y. Nishiyama, T. Abe, T. Yoshida, T. A. Yamamoto and S. Seino, Bioconjugate Chem., 2011, 22, 887–893. ˘du, I_ . H. Boyacı and K. Pekmez, J. Nanopart. Res., ¨ndog 105. U. Tamer, Y. Gu 2010, 12, 1187–1196. 106. H.-Y. Xie, R. Zhen, B. Wang, Y.-J. Feng, P. Chen and J. Hao, J. Phys. Chem. C, 2010, 114, 4825–4830. 107. D. M. Fouad, W. A. El-Said and M. B. Mohamed, Spectrochim. Acta, Part A, 2015, 140, 392–397. 108. S.-J. Cho, J.-C. Idrobo, J. Olamit, K. Liu, N. D. Browning and S. M. Kauzlarich, Chem. Mater., 2005, 17, 3181–3186. 109. V. Arora, A. Sood, J. Shah, R. Kotnala and T. K. Jain, Mater. Chem. Phys., 2016, 173, 161–167. 110. B. K. Sodipo, A. A. Aziz and M. Mustapa, Int. J. Nanoelectron. Mater, 2015, 8, 1–6. 111. B. L. Oliva, A. Pradhan, D. Caruntu, C. J. O’Connor and M. A. Tarr, J. Mater. Res., 2006, 21, 1312–1316. 112. J. Kolosnjaj-Tabi, Y. Javed, L. Lartigue, J. Volatron, D. Elgrabli, I. Marangon, G. Pugliese, B. Caron, A. Figuerola and N. Luciani, ACS Nano, 2015, 9, 7925–7939. 113. V. Zavisova, M. Koneracka, A. Gabelova, B. Svitkova, M. Ursinyova, M. Kubovcikova, I. Antal, I. Khmara, A. Jurikova and M. Molcan, J. Magn. Magn. Mater., 2019, 472, 66–73. 114. F. Cengelli, D. Maysinger, F. Tschudi-Monnet, X. Montet, C. Corot, A. Petri-Fink, H. Hofmann and L. Juillerat-Jeanneret, J. Pharm. Exp. Ther., 2006, 318, 108–116. 115. A. K. Gupta and M. Gupta, Biomaterials, 2005, 26, 3995–4021. 116. W. Injumpa, P. Ritprajak and N. Insin, J. Magn. Magn. Mater., 2017, 427, 60–66. 117. A. K. Gupta and A. S. Curtis, J. Mater. Sci.: Mater. Med., 2004, 15, 493–496. 118. A. Simioni, O. Martins, Z. Lacava, R. Azevedo, E. Lima, B. Lacava, P. Morais and A. Tedesco, J. Nanosci. Nanotechnol., 2006, 6, 2413– 2415. 119. L. Gloag, M. Mehdipour, D. Chen, R. D. Tilley and J. J. Gooding, Adv. Mater., 2019, 31, 1904385. 120. M. Mahmoudi, H. Hofmann, B. Rothen-Rutishauser and A. Petri-Fink, Chem. Rev., 2012, 112, 2323–2338. 121. D. Bobo, K. J. Robinson, J. Islam, K. J. Thurecht and S. R. Corrie, Pharm. Res., 2016, 33, 2373–2387.

52

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122. A. J. Kell, G. Stewart, S. Ryan, R. Peytavi, M. Boissinot, A. Huletsky, M. G. Bergeron and B. Simard, ACS Nano, 2008, 2, 1777–1788. 123. D. Cheng, M. Yu, F. Fu, W. Han, G. Li, J. Xie, Y. Song, M. T. Swihart and E. Song, Anal. Chem., 2016, 88, 820–825. 124. H. J. Chung, T. Reiner, G. Budin, C. Min, M. Liong, D. Issadore, H. Lee and R. Weissleder, ACS Nano, 2011, 5, 8834–8841. 125. H. Zhang, X. Ma, Y. Liu, N. Duan, S. Wu, Z. Wang and B. Xu, Biosens. Bioelectron., 2015, 74, 872–877. 126. V. Berry, A. Gole, S. Kundu, C. J. Murphy and R. F. Saraf, J. Am. Chem. Soc., 2005, 127, 17600–17601. ´rez-Lo ´pez, R. C. Faria, L. H. Mattoso, M. Herna ´ndez127. A. S. Afonso, B. Pe ´s, M. Maltez-da Costa and A. Merkoçi, Biosens. Herrero, A. X. Roig-Sague Bioelectron., 2013, 40, 121–126. 128. I. Safarik and M. Safarikova, BioMagnetic Res. Technol., 2004, 2, 7. 129. S. Laurent, D. Forge, M. Port, A. Roch, C. Robic, L. Vander Elst and R. N. Muller, Chem. Rev., 2008, 108, 2064–2110. 130. M. N. Widjojoatmodjo, A. C. Fluit, R. Torensma and J. Verhoef, J. Immun. Methods, 1993, 165, 11–19. 131. Z. Ji, D. I. Pinon and L. J. Miller, Anal. Biochem., 1996, 240, 197–201. 132. X. An, Z. Su and H. Zeng, J. Chem. Technol. Biotechnol.: Int. Res. Process, Environ. Clean Technol., 2003, 78, 596–600. 133. H. P. Khng, D. Cunliffe, S. Davies, N. A. Turner and E. N. Vulfson, Biotechnol. Bioeng., 1998, 60, 419–424. 134. J. Fan, J. Lu, R. Xu, R. Jiang and Y. Gao, J. Colloid Interface Sci., 2003, 266, 215–218. 135. C. Xu, K. Xu, H. Gu, X. Zhong, Z. Guo, R. Zheng, X. Zhang and B. Xu, J. Am. Chem. Soc., 2004, 126, 3392–3393. 136. R. L. Anderson, W. E. Bishop, R. L. Campbell and G. C. Becking, CRC Crit. Rev. Toxicol., 1985, 15, 1–102. 137. W. Xie, Z. Guo, F. Gao, Q. Gao, D. Wang, B.-S. Liaw, Q. Cai, X. Sun, X. Wang and L. Zhao, Theranostics, 2018, 8, 3284. 138. B. Ankamwar, T. Lai, J. Huang, R. Liu, M. Hsiao, C. Chen and Y. Hwu, Nanotechnology, 2010, 21, 075102. 139. G. Kandasamy and D. Maity, Int. J. Pharm., 2015, 496, 191–218. 140. P. B. Santhosh and N. P. Ulrih, Cancer Lett., 2013, 336, 8–17. 141. M. Bartolini, J. Pekar, D. Chettle, F. McNeill, A. Scott, J. Sykes, F. Prato and G. Moran, Magn. Reson. Imaging, 2003, 21, 541–544. 142. Z. Zhou, L. Yang, J. Gao and X. Chen, Adv. Mater., 2019, 31, 1804567. 143. S. Cheong, P. Ferguson, K. W. Feindel, I. F. Hermans, P. T. Callaghan, C. Meyer, A. Slocombe, C. H. Su, F. Y. Cheng and C. S. Yeh, Angew. Chem., 2011, 123, 4292–4295. 144. Y. Wang, C. Xu, Y. Chang, L. Zhao, K. Zhang, Y. Zhao, F. Gao and X. Gao, ACS Appl. Mater. Interfaces, 2017, 9, 28959–28966. 145. A. Cousins, G. Balalis, S. Thompson, D. F. Morales, A. Mohtar, A. Wedding and B. Thierry, Sci. Rep., 2015, 5, 10842. 146. T. M. Allen and P. R. Cullis, Adv. Drug Delivery Rev., 2013, 65, 36–48.

Design of Functionalized Magnetic Nanoparticles for Improving Stabilization

53

147. D. Ha, N. Yang and V. Nadithe, Acta Pharm. Sin. B, 2016, 6, 287–296. 148. W. Wu, Z. Wu, T. Yu, C. Jiang and W.-S. Kim, Sci. Technol. Adv. Mater., 2015, 16, 24. 149. H. Li and Y. J. Zhu, Chem.-Eur. J., 2020, 26, https://doi.org/10.1002/ chem.202000679. 150. S. Arora Wahajuddin, Int. J. Nanomed., 2012, 7, 3445. 151. C. Zhu, L. Liu, Q. Yang, F. Lv and S. Wang, Chem. Re., 2012, 112, 4687– 4735. 152. K. Cheng, S. Peng, C. Xu and S. Sun, J. Am. Chem. Soc., 2009, 131, 10637–10644. 153. S. Huang, C. Li, Z. Cheng, Y. Fan, P. Yang, C. Zhang, K. Yang and J. Lin, J. Colloid Interface Sci., 2012, 376, 312–321. 154. F. Chen, C. Li, Y.-J. Zhu, X.-Y. Zhao, B.-Q. Lu and J. Wu, Biomater. Sci., 2013, 1, 1074–1081. 155. B. Q. Lu, Y. J. Zhu, F. Chen, C. Qi, X. Y. Zhao and J. Zhao, Chem. – Asian J., 2014, 9, 2908–2914. 156. B.-Q. Lu, Y.-J. Zhu, G.-F. Cheng and Y.-J. Ruan, Mater. Lett., 2013, 104, 53–56. 157. T.-W. Sun, Y.-J. Zhu, F. Chen, C. Qi, B.-Q. Lu, J. Wu, D. Zhou and C.-Q. Zhang, RSC Adv., 2016, 6, 103399–103411. 158. K. Yang, Y. Liu, Y. Liu, Q. Zhang, C. Kong, C. Yi, Z. Zhou, Z. Wang, G. Zhang and Y. Zhang, J. Am. Chem. Soc., 2018, 140, 4666–4677. 159. N. Tran and T. J. Webster, J. Mater. Chem., 2010, 20, 8760–8767. 160. C. Martinez-Boubeta, K. Simeonidis, A. Makridis, M. Angelakeris, ´ and F. Peiro ´, Sci. O. Iglesias, P. Guardia, A. Cabot, L. Yedra, S. Estrade Rep., 2013, 3, 1652. 161. R. Das, J. Alonso, Z. Nemati Porshokouh, V. Kalappattil, D. Torres, M.-H. Phan, E. Garaio, J. A. N. Garcı´a, J. L. Sanchez Llamazares and H. Srikanth, J. Phys. Chem. C, 2016, 120, 10086–10093. 162. L. M. Bauer, S. F. Situ, M. A. Griswold and A. C. S. Samia, Nanoscale, 2016, 8, 12162–12169. 163. K. H. Bae, M. Park, M. J. Do, N. Lee, J. H. Ryu, G. W. Kim, C. Kim, T. G. Park and T. Hyeon, ACS nano, 2012, 6, 5266–5273. 164. S.-H. Liao, C.-H. Liu, B. P. Bastakoti, N. Suzuki, Y. Chang, Y. Yamauchi, F.-H. Lin and K. C. Wu, Int. J. Nanomed., 2015, 10, 3315.

CHAPTER 3

Improvement of Adsorbing Properties of Magnetic Nanomaterials by Bioorganic Substrate-mediating Synthesis P. CAREGNATO,* D. F. MERCADO AND M. C. GONZALEZ ´ricas y Aplicadas Instituto de Investigaciones Fisicoquı´mica Teo (INIFTA) – Departamento de Quı´mica, Facultad de Ciencias Exactas, Universidad Nacional de La Plata (UNLP) – CONICET, C.C. 16 Suc.4, 1900, La Plata, Argentina *Email: [email protected]

3.1 Introduction International Standard specifies the requirements for different grades of water for laboratory use. Grade 1 waters are essentially free from dissolved ionic and organic contaminants, which make it suitable for the strictest analytical requirements including those of high-performance liquid chromatography.1 For that reason, water purification is an essential process before any analytical use. Nanotechnology plays a key role in focusing the problems related to water purification and water quality. It is a powerful ally of analytical chemistry to complete its objectives, and to simplify analytical procedures.2 The production of nanostructures, nanocomposites, and modified nanostructures is a growing area of research because of the increasing need to

Analytical Applications of Functionalized Magnetic Nanoparticles Edited by Chaudhery Mustansar Hussain r The Royal Society of Chemistry 2021 Published by the Royal Society of Chemistry, www.rsc.org

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obtain clean water in an efficient way, optimizing the time involved and energy consumption.3 Nanotechnology is able to provide inexpensive, portable and easily cleaned devices that purify water in an efficient way. The main characteristic of nanoparticles is their large specific surface area with multiple binding sites, which make them excellent adsorbents. In fact, nano-enabled technologies introduce different types of membranes and filters based on nanoscale particles.4,5 Moreover, the combination of such surface properties with exceptional physicochemical characteristics such as paramagnetism, high fluorescence yields, high photocatalytic ability, among others, confer nanoparticles promising uses in a wide range of waste treatment procedures.6–8 Adsorption is one of the most efficient and widely used physico-chemical treatment. Various adsorbents, such as clays, biomass, apatites and activated carbon, are currently being used for the treatment of contaminated water.9–13 A key aspect in the development of new approaches for water purification requires that the nanomaterials employed should be of low cost, easily available, of easy manipulation and recuperation, highly stable under oxidizing and reducing conditions, environmentally friendly, and of high affinity to water pollutants. In particular, the separation of the used particles from the clean water stream is an important task in process design, not always easily accomplished. In that sense, magnetic nanocomposites offer advantages because they combine a sorption process with easy, high efficiency, and low cost recovery of the material under an external magnetic field without filtration or centrifugation.14–16 Magnetite nanoparticles, Mnp, have attracted growing interest in environmental remediation because of their biocompatibility, magnetic properties and tunable size and shape employing simple synthesis methods.17 The integration of magnetic nanoparticles with analytical methods has opened new opportunities for sensing, purification, and quantitative analysis.18–20 Successful uses of magnetic nanoparticles for analytical methodologies include preconcentration, separation, and capture of analytes. To that purpose, magnetic nanoparticles must first be functionalized with the appropriate chemistries.21,22 An example is the application of functionalized magnetic nanoparticles for magnetic solid-phase extraction. In this technique the target compound is separated from the sample solution by adsorption onto the magnetic nanoparticles, which are then separated by the application of a magnetic field. At the end, the substance is analyzed, being previously recovered from the adsorbent.23 In the last five years, a wide range of research has been published in the literature concerning adsorption applications of magnetic nanoparticles for water purification. Figure 3.1 shows the number of published articles on that theme since 2015. Hydroxyapatite (Ca10(PO4)6(OH)2) is the principal inorganic constituent of bones, teeth, and hard tissues in vertebrates.15 Natural and synthetic

56

Chapter 3 magnec nanoparcles; adsorpon; low cost coangs; heavy metals; magnec nanoparcles; adsorpon; water; coangs

13

magnec nanoparcles; adsorpon; water

16,500

magnec nanoparcles; adsorpon; low cost coangs; dyes

66,300

magnec nanoparcles; adsorpon; water; contaminants

7

407

magnec nanoparcles; analycal use 167

Figure 3.1

Number of publications obtained through a search in the Google Scholar database with the keywords indicated, for articles published between 2015 and 2020.

hydroxyapatite have been extensively used in the purification of contaminated water and soils from heavy metals.14,24–26 When combined, magnetite (Fe3O4) and hydroxyapatite (HAp) nanocomposites display the magnetic properties and easy usage of magnetite and the excellent biocompatibility and high adsorption capacity of HAp.27 In the present chapter, we examined the improved adsorption properties toward dyes and metal cations of magnetic nanoparticles when they are coated with bioorganic molecules from Yerba Mate extract and templated during the synthesis procedure by waste bioorganic substrates. The particular adsorption selectivity toward Cu(II) and Pb(II) ions of magnetite–HAp nanocomposites templated with waste bioorganic substrates is also discussed.

3.2 Preparation of Magnetic Nanoparticles 3.2.1

Iron Oxide Magnetic Nanoparticles

Physicochemical properties of iron oxide nanoparticles, such as polydispersity, morphology, surface chemistry, and saturation magnetization are dependent on the synthesis route, type of precursors and surface modifications. Below a critical size of 100 nm, iron oxide nanoparticles behave like a single magnetic domain exhibiting superparamagnetic behavior. Depending on the Fe oxidation state (Fe12 or Fe13), iron oxides exhibit different crystal structures, such as magnetite (Fe12 and Fe13 mixed oxides) and maghemite (Fe13 oxide). These particles, no longer show magnetic interaction after the external magnetic field is removed.28,29

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According to the bibliography, there are several approaches for the preparation of iron oxide magnetic nanoparticles. The most common approaches are coprecipitation, hydrothermal/solvothermal synthesis, high-temperature decomposition of organic precursors, sol–gel reactions and spray/laser pyrolysis techniques.29,30 Thermal decomposition takes place in a non-aqueous environment at high temperatures (even 350 1C). Usually it occurs through a reaction between carboxylate groups (coming from the iron source) and iron, forming oxo bridges between iron atoms that progress to the iron oxide nanoparticles.31 The solvothermal/hydrothermal method is a very attractive method to prepare magnetic iron oxides at high temperatures in a high-pressure reactor (150–220 1C and 0.3–4.0 MPa, respectively).32 The nature of the reaction medium defines the nature of the iron oxides obtained. Pure crystalline g-Fe2O3 (maghemite) is formed via the hydrothermal process, and Fe3O4 is obtained through a solvothermal route with organic solvent as the reaction medium. By adjusting the reaction time, temperature, pH and the chelating agent, nanoparticles with different morphology can be obtained by these methods. Iron oxide (Fe3O4 and g-Fe2O3) nanoparticles can be prepared by a sol–gel method where the water for hydrolysis is slowly released by esterification reaction to control the size of the formed nanoparticles. The condensation of monomers forms initially a sol (colloidal solution) and afterward a gel (solid network). Further heat treatments are needed to acquire the final crystalline state.33 Among all the mentioned synthesis routes, the coprecipitation reaction is a very simple and quick method for the synthesis of magnetite. It is achieved by the addition of NaOH or NH4OH to an aqueous solution of Fe21 and Fe31. Nonetheless, due to its relatively low alkaline strength the use of N4OH produces particles with a narrow individual size distribution. Important experimental factors must be optimized to obtain pure magnetite nanoparticles with a proper size distribution, morphology and shape. By modulating the molar ratio of [Fe31]/[Fe21] it is possible to obtain pure magnetite ([Fe31]/[Fe21] o1.75 : 1) or a mixture of magnetite and maghemite ([Fe31]/[Fe21]41.75 : 1).34 Besides, the nanoparticle’s size can be manipulated by changing the concentration of the reactants, ferric and ferrous hydrated salts.35 The size of the ferric and ferrous precursor ions and the ionic strength affect the mean size of the magnetite nanoparticles. The mean size decreases, as the anion size of the precursor salt increases.36 Besides, the higher the ionic strength, the smaller is the particle size.37 In both cases, the morphology is not affected. The initial pH and temperature of the salt solution before initiation of the precipitation reaction and the final pH are critical parameters. It is demonstrated that the initial pHo5 and final pH round 12.5 yield pure magnetite nanoparticles.38

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High stirring velocity in the mixture ensures an optimum solution uniformity and smaller particles and narrower size distributions are obtained.39 Considering the evidence in the literature, Mercado et al. reported a synthetic route to obtain 15 nm sized magnetite nanoparticles by coprecipitation.40 The method consisted in heating up to 90 1C a solution of Fe21 and Fe31 chloride salts with a ferric/ferrous molar ratio below 1.75. After the indicated temperature was reached, an ammonium hydroxide solution is added and the suspension was maintained under constant heating and stirring for 30 min. After washing several times, the nanoparticles were dried at 70 1C under vacuum. These particles will be referred to further in the text as Mnp. For magnetite particles in aqueous media, surface iron atoms are coordinated with water molecules. The adsorbed water molecules usually dissociate yielding a surface covered by hydroxyl groups which are the reactive entities at the surface in an aqueous environment. Besides, adsorbed molecules promote self-adhesion of the particles with the formation of agglomerates.41 Surface hydroxyl groups can be protonated or deprotonated yielding surface FeOH21 or FeO depending on pH values below or above the pHZPC, respectively.42 For this reason, adsorption depends on the aqueous pH because it determines the electrostatic forces between the surface charge and the species that are adsorbed. The measured pHPZC of magnetite nanoparticles is 7.3.40 The state-of-the-art literature concerning the use of magnetic nanomaterials has pointed growing interest in biological and medical applications and in environmental remediation, due to not only to their magnetic properties, but also to their biocompatibility.43 For that reason, it is important to develop parameters which help the stabilization of the particles mainly in water. Surface modification of magnetite nanoparticles with organic molecules improves not only stabilization of the particles in water media but also adsorption of specific metal ions and organic trace pollutants.

3.2.2

Preparation of Iron-containing Hydroxyapatite

Nanostructured hydroxyapatite is an effective adsorbent material, as demonstrated by its high sorption capacity for heavy metals and dyes.27,44,45 The mainly sorption mechanisms of heavy metals are: ion exchange, dissolution/ precipitation, and formation of surface complexes.46 There are several studies on the sorption of metals on hydroxyapatite surfaces for Zn21, Cd21, Sr21, Ni21, Cu21 and for Pb21. Some of them proposed that the ion exchange with Ca on hydroxyapatite surfaces is the main mechanism for their adsorption.46–48 Other authors have determined that the elimination of Pb21 from aqueous solution by hydroxyapatite involucrate the precipitation of pyromorphites. These lead apatites are much more insoluble than hydroxyapatite in aqueous solutions and both phases coexist.49

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In order to combine the high adsorption capacity of HAp nanoparticles with an effective separation method from the media, such as an external magnetic field, magnetite-incorporated hydroxyapatite composites attract much attention.15 Dong and co-workers published that lead adsorption on HAp/Fe3O4 nanomaterials was explained by simultaneous dissolution/precipitation and the surface complexation mechanism, which should be ascribed to the several functionalities of the material.50 However, Zhuang and co-workers demonstrated a dependence of the sorption mechanism with the pH on HAp/Fe3O4 surfaces.49 In the case of other ions such as Cu(II) and Ni(II), Ca21 exchange and surface complexation are the prevailing mechanisms on hydroxyapatite– Fe3O4 nanocomposites.48 The synthesis of Fe-containing hydroxyapatite nanoparticles (Fe-nAp), was developed by an adaptation of the hydroxyapatite preparation method.51,52 Briefly, a solution containing Fe(II) and Fe(III) salts and phosphoric acid was added dropwise into a Ca(OH)2 suspension, adjusting an analytical molar ratio of Fe/Ca ¼ 0.2. After a period, the precipitate was separated by a magnet bar of ca. 2000 G, and washed several times and finally dried at 80 1C. Because of the high surface area and chemistry of Fe-nAp, adsorption properties can be improved when the synthesis is templated with organic materials as SBO.52,53

3.2.3

Functionalized Nanoscale Magnetic Particles

The use of renewable materials in nanoparticle surface coatings and as templates in nanoparticle synthesis facilitates sustainability and the opportunity to utilize waste in a cost-effective manner. The integration of the renewable material with the magnetic nanoparticles reduces costs and enhances properties by providing a functional group in the matrix.53 Adsorptive character and stabilization are the most important properties to improve the use of these nanocomposites in water purification. Surface coating by bio-renewable polymers such as cellulose, starch and lignin has received attention because of the abundance and environmentally friendly nature of these natural polymers.50,54,55 In particular, polyethylenimine lignin applied as a sorbent showed high adsorption efficiency for lead ions from aqueous media and still exhibited good adsorption performance after the fifth regeneration cycle. Nanosorbents consisting of iron oxide nanoparticles functionalized with soil-derived humic acid showed a good adsorption capacity toward metal cations and organic contaminants.56 Organic functional groups of humic acid act as connectors between the surface hydroxyl groups of the nanoparticle and metal ions.57,58 Another group of low-cost adsorbents is bioorganic wastes, which are products isolated from urban green solids. In particular, the use of the soluble fraction of that waste, called soluble biobased products (SBO),59 as templates in the preparation of nanomaterials was reported to affect their morphology

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Chapter 3 51

and surface chemistry. SBO isolation and characterization was published by Bianco Prevot and co-workers.59 Summarizing, SBO are mixtures of molecules differing in molecular weight (from 67 to 463 kg mol1) which contain aliphatic C chains replaced by aromatic rings and several functional groups such as COOH, CON, CO, PhOH, and O-alkyl among others.60 Extracts from leaves of natural plants such as green tea (Camellia sinensis) and yerba mate (YM, Ilex paraguariensis) are other alternative low-cost natural materials for nanomaterial coatings. In South America, mainly Argentina, southern Brazil, Paraguay and Uruguay, YM extract is intensively utilized in infusions and used in the formulation of foods, with a large socioeconomic importance in the area.61 The phytochemical compounds identified in YM are polyphenols, xanthines, alkaloids, flavonoids, amino acids, minerals and vitamins.62 Besides, the YM antioxidant properties are attributed to the presence of caffeic, quinic, caffeoylquinic, feruloylquinic, and dicaffeoylquinic acids, quercitin and rutin.63

3.2.3.1

YM Extract-coated Magnetite Nanoparticle Synthesis

The preparation of these magnetic nanoparticles was developed by the addition of YM extract to the reaction mixture of Fe21 and Fe31 salts and ammonium hydroxide solution, after the coprecipitation reaction. A suspension of YM-coated magnetite nanoparticles was obtained. The following steps of preparation were the separation of the precipitate with a magnet bar, washing and drying the product at 70 1C under vacuum.40 YM extracts were obtained by adding 1 L of ultrapure water into 10 g of commercial YM and left in contact under continuous stirring for 1 h at 70 1C. The solids synthetized were named Mnp@YM10 and Mnp@YM4, which stand for 10 and 4% w/w of YM extract per g particle, respectively.

3.2.3.2

Template Iron-containing Hydroxyapatite (SBO–Fe-nAp) Nanoparticle Synthesis

Bioorganic substrate mediated synthesis has been described in the literature.51,52 In the description, a suspension of SBO and calcium hydroxide with different SBO/Ca w/w ratio (0.05, 0.5 and 2.5) was used. A solution containing Fe(II) and Fe(III) salts and phosphoric acid was added dropwise into the Ca(OH)2–SBO suspension (analytical molar ratio of Fe/Ca ¼ 0.2). After a period, the precipitate was separated by the application of a magnetic field from a magnet bar, washed several times, and finally dried at 80 1C. A batch of SBO–Fe-nAp powders with SBO/Ca w/w ratio of 2.5 was further calcinated at 600 1C. These particles are named SBO–Fe-nAp-cal.

3.3 Results and Discussion Among all the available characterization techniques, the most relevant are those that give information about the magnetic properties of the materials (obtained

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61

through magnetization measurements), crystalline phase content (X-ray Diffraction, XRD), the surface composition and charge (FTIR spectroscopy, X-ray photoelectron spectroscopy, XPS and determination of the particles Zero Point pH, pHPZC), the size and morphology of the nanoparticles (evidenced by high resolution transmission electron microscopy, HRTEM), the thermal behavior of the powders (thermogravimetric analysis, TGA) and Raman.

3.3.1

Mnp, Mnp@YM4 and Mnp@YM10 Characterization

HRTEM micrographs of Mnp and Mnp@YM10 clearly depict 15  1 nm size crystalline particles with individual irregular round-shapes (See Scheme 3.1). FTIR, FTIR–ATR and Raman spectra indicate that phenols, carboxylic acids, and N–H are among the principal organic groups of YM extracts bound to magnetite. The intensity of the corresponding organic bands increases with the YM coverage. TGA curves of Mnp@YM4 and Mnp@YM10 showed a total mass loss of ca. 4 and 10%, respectively, in the temperature range 200 1CoTo500 1C attributed to the loss of organic matter. From analysis of the XPS spectra of both, YM-coated particles indicate the presence of a mixture of Fe(II) and Fe(III) oxides surface oxides and the existence of a more N-rich coating for Mnp@YM10.

Scheme 3.1

HRTEM micrograph of Mnp@YM10 with a sketch of one YM-coated Mnp showing the interaction between the magnetite surface and chlorogenic acids and caffeine derivatives present in YM extracts. Resultant charged surface groups are shown in color.

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Chapter 3

Zeta potential values of 4  1, 7.5  3 and 32  1 mV were observed in aqueous suspensions of pH 7 for Mnp, Mnp@YM4 and Mnp@YM10, respectively. pHPZC determination of Mnp@YM4 and Mnp@YM10 depicted values of 6.7 and 5.4, respectively, thus indicating that YM-coated magnetite might be capable of absorbing H1 and OH resulting in NH1, O, and COO surface charged groups. The smaller hydrodynamic size obtained from DLS measurements for Mnp@YM10 agglomerates suggests that these particles form more stable suspensions than Mnp@YM4 and Mnp. Mnp@YM10 saturation magnetization (Ms) and coercive field (Hc) of powders are lower than those of Mnp. Coercivity values of 830 to 110 A m1 were measured for Mnp and Mnp@YM10, respectively.64 Ms diminution was explained considering the modification of core surface electronic states due to the chemical bond of iron in the different environments. Furthermore, coercivity reduction was discussed on the basis of an increasing interparticle separation and dipolar interaction weakening as a result of the nanoparticle coating with YM extract. Scheme 3.1 depicts a sketch of a YM-coated Mnp nanoparticle emphasizing the interaction between magnetite surface and chlorogenic acids and caffeine derivatives. Among other interesting properties of YM-coated magnetite nanoparticles are their antioxidant capacity. The Trolox Equivalent Antioxidant Capacity, TEAC, is of 1.8 mM trolox per mg L1 Mnp@YM10, which might be ascribed to the scavenging activity of the 0.1 mg YM coating enclosed in 1 mg particles. Polyphenols (epicathechine and quercetin) present in YM extract, are inferred in the antioxidant properties of YM coatings. Some of the characteristic aspects of the Mnp are summarized in Table 3.1.

3.3.2

YM–Iron Oxide Magnetic Nanoparticles. Adsorption of MB

During recent years, several studies concerning magnetite surface coating with bio-renewable material as efficient adsorbents for cationic dye removal Table 3.1

Material

Comparative properties of YM extract-coated magnetite nanoparticles as: DLS hydrodynamic radio (Rhyd) in aqueous suspensions of 0.01 M ionic strength, % w/w organic fraction from TGA experiments, Z-potential (z) in aqueous suspensions of pH 7.5 and 0.05 ionic strength, pH of the point of zero charge (pHPZC), and MB maximum adsorption capacity and Langmuir adsorption constant (b and kl, respectively).40 Rhyd/nm

% w/w organic z potential fraction (mV) pHPZC b/mg g1 kl/L mg1

Mnp 355  75 0 Mnp@YM4 340  60 4 Mnp@YM10 162  5 10

 12  1 83  16  2

7.3 6.7 5.4

14  2 30  2 50  6

0.88  0.06 1.30  0.04 1.51  0.04

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65–68

from aqueous solutions have been reported. In some of them, the surface-coated nanoparticles acted not only as adsorbents but also were capable of inducing oxidative processes of the dyes which involved photoFenton reactions.69,70 Similarly, SBO–iron oxide magnetic nanoparticles enhanced the degradation of caffeine and phenol in combination with (photo)-Fenton treatments, when compared with the same system, but with bare magnetic nanomaterials.59,71 In our work,40 YM–iron oxide magnetic nanoparticles were examined for the elimination of methylene blue cationic dye (MB). Isotherms were described with the one-adsorption site Langmuir model (eqn (3.1)). x=m ¼

kl bCe 1 þ kl Ce

(3:1)

Where x/m (mg g1) is the equilibrium adsorption capacity, Ce (mol L1) is the MB equilibrium adsorption remanent concentration on the solution, b (mg g1) is the maximum adsorption capacity, and kl (L mg1) is the affinity coefficient or Langmuir constant. MB adsorption on YM–iron oxide magnetic nanoparticles revealed a reversible adsorption processes with a maximum adsorption of 50 mg g1. MB adsorption isotherms for Mnp, Mnp@YM4 and Mnp@YM10 are exhibited in Figure 3.2A. Besides, b values linearly increase with the YM content as is represented in the inset of Figure 3.2A. The adsorption mechanism is dominated by electrostatic forces. The maximum adsorption capacity, varying the pH from 4 to 10 follows the order MnpoMnp@YM4oMnp@YM10. Increasing the pH, the nanoparticles may convert to be more negatively charged with a main influence of electrostatic interactions with the positively charge MB. Adsorption parameters derived from Langmuir model are depicted in Table 3.1. In addition to the adsorption developments, oxidative MB degradation processes taking place on the Mnp surface can be initiated producing highly oxidative SO4  radical anions by interaction of S2O82 with Fe21 from magnetite or by photochemically or thermally inducing S2O82 homolysis. However, when YM covers the magnetite core as in either Mnp@YM4 or Mnp@YM10, an inhibition effect in MB oxidative degradation is observed. YM-coating presents scavenging activity of SO4  radical anion, and protects the magnetite core from S2O82 interactions. This effect is represented in Figure 3.2B. YM-coating scavenging activity of SO4  was supported by the study of the decay rates of the radical anion generated by flash photolysis of peroxodisulfate ion with an excitation laser at 266 nm, in the absence and presence of Mnp and Mnp@YM10. In conclusion, YM coatings act as protective scavengers toward oxidation of methylene blue in strong oxidative media, an interesting property if the adsorbate needs to be protected for its further recuperation. Scheme 3.2 is a representation of the explained YM coating effect.

64

Chapter 3 B

x/m (mg g-1)

50

1 0.8

40

[MB(t)]e /[MB(t=0)]e

b / mg g-1

A

20 0 0.00

0.04

0.08

wYM/g

25

0

0.3 0.2

0.1 0

5

Figure 3.2

3.3.3

0.6 0.5 0.4

Ce (mg L-1)

10

0

50

100

150

Time / minutes

(A) MB adsorption isotherms in aqueous solutions of pH 7 and 25 1C obtained for experiments with 0.6 g L1 suspensions of either Mnp@YM10, Mnp@YM4, or Mnp. Black, dark grey and light grey (from button to top) symbols stand for Mnp, Mnp@YM4, and Mnp@YM10, respectively. Closed and opened symbols stand for adsorption and desorption experiments, respectively, and lines stand for the fitting of the data to the one-adsorption site Langmuir model. Inset: Linear dependence of b with the YM content per gram of particle (wYM/g). (B) Semilogarithmic plot of MB solution concentration vs. time in 1.0102 M Na2S2O82 aqueous solutions of pH 7 and 25 1C in the absence (J) and presence of 0.6 g L1 of either Mnp (K), Mnp@YM4 (m), and Mnp@YM10 (D). Reproduced from ref. 40 with permission from Springer Nature, Copyright 2017.

Fe-nAp and SBO–Fe-nAp Characterization

HRTEM micrographs show that Fe-nAp particles are cylindrical, 50–100 nm in length, with acicular shapes of irregular contour. The SBO–Fe-nAp sample shows a more heterogeneous size distribution of irregular acicular particles. In both samples, globular lumps, assignable to the iron-containing area of nanometric size (o10 nm) are present. These lumps are dispersed quite homogeneously in the materials, indicating that iron-containing phases are well spread on Ap-based materials.51 The HRTEM picture of SBO–Fe-nAp is shown in Scheme 3.3. The XRD diffractograms of nAp-based materials show the crystalline structure of hydroxyapatite except for SBO-templated particles for which an important reduction in the crystalline structure was observed. Besides, magnetite and maghemite crystalline phases are also present. FTIR spectrum of SBO–Fe-nAp showed characteristic peaks of HO groups assigned to phenols, alcohols, and carboxyl groups and distinctive peaks of CQO bonds of carboxyl and carbonyl moieties. In contrast, the FTIR spectrum of SBO–Fe-Ap-cal indicates that calcination eliminates SBO residues. In fact, the average hydrodynamic particle size distribution determined by DLS measurement indicates that the SBO template particles present less aggregation than the others, thus strongly supporting the stabilization effect of surface groups on the colloidal suspension stability.

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Scheme 3.2

Yerba Mate coated magnetite nanoparticles are efficient adsorbents and antioxidants.

Scheme 3.3

HRTEM picture of SBO–Fe-nAp and a representation of the proposed surface groups present in the nanoparticles.

Analysis of TGA curves of SBO–Fe-nAp samples indicates a mass loss of 5% w/w ascribed to carbon content in the temperature range from 200 to 380 1C in an oxygen atmosphere. The presence of an extra C-content in SBO–Fe-nAp samples correlates with a larger specific surface area determined by the BET model for SBO–Fe-nAp samples (71 m2 g1) compared to that of Fe-nAp and SBO–Fe-nAp cal samples (both of 64 m2 g1). XPS results indicate that loading with Fe31/Fe21 ions and the use of SBO templates during nAp synthesis concludes with a decrease in the quantity of

66

Chapter 3 21

Ca content, formation of surface Fe phosphates salts and Fe31/Fe21 oxides, and an increase in surface OH groups. A comparison between the ratio of Fe : Ca contents in the particles volume and at the surface concludes that Fe ions are preferentially integrated in the core. The saturation magnetization of Fe-nAp is 4 emu g1, with a saturation magnetization given per gram of iron of 57 emu g1, half the expected value for magnetite nanoparticles. Scheme 3.3 presents the surface main characteristics of SBO–Fe-nAp nanoparticles.

3.3.4 3.3.4.1

21

Fe-nAp and SBO–Fe-nAp: Adsorption of Pb(II) and Cu(II) Enhanced Cu Adsorption Maximum Uptake on SBO–FenAp Nanocomposites

Isotherms were described with the one-adsorption site (vide supra eqn (3.1)) and the Freundlich model (eqn (3.2)) x/m ¼ kfC1/n e

(3.2)

Where kf (mg g1) is the Freundlich constant related to the maximum adsorption capacity and 1/n is an experimentally determined exponent. According to the characterization techniques, it is concluded that the Cu(II) adsorption mechanism on Fe-nAp, occurs through metal ion coordination, with an adsorption capacity up to (265  60) mg g1. The use of SBO in the synthesis results in further modifications of the physicochemical properties of the material (SBO–Fe-nAp) as was described previously. SBO has amino, phenolic, hydroxyls, and aromatic carboxylated components that can provide lone pairs of electrons for chelating Cu(II) ions. It was observed that the same groups are present in the surface of SBOcontaining materials. An important increase in the Cu(II) adsorption was detected when Fe-nAp synthesis is the template with SBO. Maximum adsorption capacity (b) values are (850  400) and (550  200) mg g1, for 0.5 and 0.05 SBO/Ca w/w ratio, which are higher than those observed for the SBO-free material, Fe-nAp. Alternatively, copper adsorption on SBO–Fe-nAp and SBO–Fe-nAp-cal particles (SBO/Ca w/w ratio of 2.5 in the preparation) were better fitted by the Freundlich model of a heterogeneous surface with a distribution of different adsorption sites. The results are summarized in Table 3.2. Such improvement in Cu(II) maximum adsorption capacity is correlated to the presence of surface negatively charged phosphate and hydroxyl iron groups and SBO-containing organic groups with lone pairs of electrons. However, the smaller size of the agglomerates of the colloid solution might play a role, as a higher surface is available in these suspensions for adsorption compared to more agglomerated Fe-nAp and SBO–Fe-nAp-cal colloids.

Improvement of Adsorbing Properties of Magnetic Nanomaterials Table 3.2

Material Fe-nAp SBO–FenAp SBO–FenApCalc

67

Properties of the different magnetic hydroxyapatite derivates. Surface stoichiometric ratio obtained by XPS analysis, and fitting parameter values of the Langmuir and Freundlich models.

Surface composition

Monometal adsorption data Cu(II) b (mg g1) kl (L mg1) 1/n

Pb(II) kf >b (mg g1) (mg g1)

265  60 0.24  0.02 — — Ca1P0.9 O4.6F0.14 Ca1P0.75 — — 1.3  0.2 90  22 O3.7F0.09 — — 1.2  0.2 50  15 Ca1P0.8 O3.3F0.06

kl (L mg1)

1500  150 0.30  0.07 870  25

2.4  0.3

1400  70

0.32  0.07

Cu(II) desorption experiment from Fe-nAp and SBO–Fe-nAp only evidence the leaching of less than 0.2% of Cu(II) after two hours. Thus suggesting a strong chemisorption of Cu(II) onto the surfaces at pH 7.0.

3.3.4.2

Pb Adsorption Maximum Uptake on SBO–Fe-nAp Nanocomposites

Pb(II) maximum adsorption uptake on the materials shows a different trend when compared with the Cu(II) adsorption process. This might evidence a different adsorption mechanism. For Fe-nAp, the maximum adsorption capacity is 1500  150 mg g1. The introduction of iron phases onto the hydroxyapatite modifies not only its surface but also the surface concentration of phosphate groups due to the formation of iron phosphate (vide supra). Interestingly, the literature suggests that Fe(II) inhibits the Pb(II) adsorption onto hydroxyapatite due to the relatively lower solubility of iron phosphates when compared to its calcium analog and therefore inhibits formation of lead phosphates.72 On the other hand, reported data on Pb(II) adsorption onto pure magnetite materials was between 20 to 91 mg g1.73,74 The proposed mechanism for this phenomenon is through the formation of surface complexes between RFeOH and Pb(II) ions. Eqn (3.3) describes the proposed process.75 xH2O þ y(RFeOH) þ zPb212(RFeOH)yPbz(OH)x(2yx) þ (x þ y)H1 (3.3) Where x, y and z are the stoichiometry coefficients. Surface organic material plays a role in Pb(II) adsorption with a different adsorption mechanism, as evidenced in the adsorption differences observed for SBO–Fe-nAp and SBO–Fe-nAp-cal substrates (SBO/Ca w/w ratio of 2.5 in the preparation). SBO–Fe-nAp shows a maximum adsorption capacity value of (870  25) mg g1. It is proposed that surface organic groups provide a

68

Chapter 3

steric barrier that results in difficulties for the interaction of Pb(II) ions with the proposed adsorption sites suggested in Fe-nAp. In the case of SBO–FenAp-cal, adsorption parameters b and kl are, within the experimental error, similar to those of Fe-nAp. See Table 3.2 for the synopsized data. In fact, the literature suggests that Pb(II) interacts with organic matter through deprotonation and metal cation complexation with OH groups, binding to carboxylate groups or coordinated by a covalent bond with one or two amine groups to form monodentate or bidentate complexation metal complexes.76,77

3.3.4.3

Bi-metal (Pb(II) and Cu(II)) Adsorption on SBO–Fe-nAp Nanocomposites

Figure 3.3 shows that all materials have different behavior concerning simultaneous Pb(II) and Cu(II) adsorption performance. Regarding Fe-nAp, competition between Cu(II) and Pb(II) is observed. The total number of adsorbed Pb(II) ions (nT) in mono- and bi-metal adsorption experiments are 4.2 and 4.6 mmol g1, respectively, which suggests that both

0.004

0.005

SBO-Fe-nAp

Fe-nAp 0.003

0.002

Cu(II)

0.004 -1 x/m (mole g )

-1

x/m (mole g )

Pb(II)

Pb(II)

0.003

0.002

Cu(II)

0.001 0.001 0.000 0

2

4

0.000

6

0

2

-1

Ce (mg Pb(II) L )

4

6

8

Ce (mg Pb(II) L-1)

Fe-nAp

0.006

-1 x/m (mole g )

x/m (mole g-1)

0.004

0.003

0.002

0.005 0.004 0.003 0.002

0.001

SBO-Fe-nAp

0.001 0.000

0.000 0

2

4

Ce (mg ions L-1)

Figure 3.3

6

0

2

4

6

8

-1 Ce (mg ions L )

Pb(II) (K) and Cu(II) (m) adsorption isotherms at 25 1C in bi-metal experiments when the substrate is A: Fe-nAp and B: SBO–Fe-nAp. C and D: } stands for the total number of adsorbed ions in bi-metal experiments (nT) and ~ stands for Pb(II) adsorption isotherms in single metal experiments when the substrate is C: Fe-nAp and D: SBO–Fe-nAp. Lines in C and D stand for a fitting according to the Langmuir model.

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metals share the same adsorption sites with a higher affinity for Pb(II). The reason could be due to the hydrated ionic radii of Pb(II) (4.01 Å) compared to that of Cu(II) (4.19 Å).78 The proposed adsorption sites for monocomponent tests are iron or calcium phosphates and oxide/hydroxide groups. Interestingly, bi-metal adsorption on SBO–Fe-nAp showed an intrinsic, not competitive mechanism. nT (6.2 mmol g1) is higher than the maximum adsorption capacity of Pb(II) ions (4.2 mmol g1), which indicates that both ions may accommodate on different adsorption sites. In fact, for monocomponent experiments, Cu(II) adsorption capacity by this material not only depends on the organic molecules on the surface but also on the colloidal substrate agglomeration. In contrast, the presence of the organic functional groups plays a critical role in Pb(II) adsorption. In conclusion, in solutions containing Pb(II) and Cu(II) ions, ion adsorption on Fe-containing hydroxyapatite nanoparticles selectivity depends on the relative [Pb]/[Cu] ratio while SBO-patterned Fe-containing hydroxyapatite is capable of adsorbing both ions with similar specificity.

3.4 Conclusion In the present chapter, two different methods of synthesis and functionalization of magnetic nanoparticles showing particular physicochemical properties, colloidal solution stability, and adsorption selectivity among different water contaminants were discussed. Extracts of leaves of natural plants and soluble bio-based products were immobilized onto inorganic magnetic substrates with an improvement in the adsorption properties and facilities of recyclability by simply applying an external magnetic field. The results herein discussed strongly indicate that these substances are a promising alternative for water purification from Cu(II) and Pb(II) metal cations and positively charged dyes such as methylene blue dye. In the case of Fe-containing hydroxyapatite materials, the surface chemistry can be conveniently manipulated to achieve nanomaterials with adsorption selectivity to both Cu(II) and Pb(II) ions without loss of the magnetic properties of the material that allowed the separation of the adsorbent by application of magnetic fields with a commercial-accessible magnet bar. YM-coated magnetite are magnetic nanoparticles with surface containing carboxylic acid groups, phenols and a high content of organic nitrogen. Stable homogeneous aqueous suspensions are formed with promising sorption of cationic dyes by electrostatic interactions. Also, YM-coating gives the particles an antioxidant protection to the adsorbed substrate which may be of potential use for the extraction and recovery on the adsorbed molecules. In consequence, new developments in nano-magnetic materials were shown with great potential for water purification for analytical use. Moreover, the nanomaterials studied in the present chapter might have potential applications in different stages of analytical processes such as sample treatment, separation and detection.

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Acknowledgements PC and MCG are research members of CONICET, Argentina. DFM is at the ´lisis moment a postdoc student in Centro de Investigaciones en Cata ´gico Guatiguara ´ (PTG), Universidad Industrial (@CICAT UIS), Parque Tecnolo de Santander, Km. 2 vı´a El Refugio, Santander, Colombia. This research had financial support from ANPCyT (PICT 2015-1266) and UNLP.

References 1. Iso BSEN, Water for analytical laboratory use — Specification and test methods, 1995. 2. M. Sajid, M. K. Nazal and S. O. Adio, Applications of Nanomaterials in Miniaturized Extraction Techniques, Elsevier Inc., 2018. 3. X. Qu, P. J. J. Alvarez and Q. Li, Applications of nanotechnology in water and wastewater treatment, Water Res., 2013, 47(12), 3931–3946. 4. C. M. Hussain and R. Keçili, Use of Nanomaterials for Environmental Analysis, 2020. ¨yu ¨ktiryaki and C. M. Hussain, Membrane applications of 5. R. Keçili, S. Bu nanomaterials, Handb. Nanomater Anal. Chem. Mod. Trends Anal., 2019, 159–182. 6. T. Ahmed, S. Imdad, K. Yaldram, N. M. Butt and A. Pervez, Emerging nanotechnology-based methods for water purification: A review, Desalin. Water Treat., 2014, 52(22–24), 4089–4101. 7. R. Keçili and C. M. Hussain, Recent Progress of Imprinted Nanomaterials in Analytical Chemistry, Int. J. Anal. Chem., 2018, 8503853, https:// doi.org/10.1155/2018/8503853. ¨yu ¨ktiryaki and C. M. Hussain, Advancement in bioana8. R. Keçili, S. Bu lytical science through nanotechnology: Past, present and future, TrAC, Trends Anal. Chem., 2019, 110, 259–276. 9. G. Libralato, D. Minetto and G. Lofrano, et al., Toxicity assessment within the application of in situ contaminated sediment remediation technologies: A review, Sci. Total Environ., 2018, 621, 85–94. 10. Z. Anfar, H. Ait Ahsaine and M. Zbair, et al., Recent trends on numerical investigations of response surface methodology for pollutants adsorption onto activated carbon materials: A review, Crit. Rev. Environ. Sci. Technol., 2020, 50(10), 1043–1084. 11. C. Piccirillo, I. S. Moreira, R. M. Novais, A. J. S. Fernandes, R. C. Pullar and P. M. L. Castro, Biphasic apatite-carbon materials derived from pyrolysed fish bones for effective adsorption of persistent pollutants and heavy metals, J. Environ. Chem. Eng., 2017, 5(5), 4884– 4894. 12. M. K. Uddin, S. S. Ahmed and M. Naushad, A mini update on fluoride adsorption from aqueous medium using clay materials, Desalin. Water Treat., 2019, 145, 232–248.

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13. M. E. M. Ali, A. M. Abd El-Aty, M. I. Badawy and R. K. Ali, Removal of pharmaceutical pollutants from synthetic wastewater using chemically modified biomass of green alga Scenedesmus obliquus, Ecotoxicol. Environ. Saf., 2018, 151, 144–152. 14. Y. Wu, L. Chen, X. Long, X. Zhang, B. Pan and J. Qian, Multi-functional magnetic water purifier for disinfection and removal of dyes and metal ions with superior reusability, J. Hazard. Mater., 2018, 347, 160–167. 15. M. Elkady, H. Shokry and H. Hamad, Microwave-Assisted Synthesis of Magnetic Hydroxyapatite for Removal of Heavy Metals from Groundwater, Chem. Eng. Technol., 2018, 41(3), 553–562. 16. C. Martinez-Boubeta and K. Simeonidis, Magnetic Nanoparticles for Water Purification, Elsevier Inc., 2018. 17. C. Su, Environmental implications and applications of engineered nanoscale magnetite and its hybrid nanocomposites: A review of recent literature, J. Hazard. Mater., 2017, 322, 48–84. ¨yu ¨ktiryaki, I. Dolak and C. M. Hussain, The use of mag18. R. Keçili, S. Bu netic nanoparticles in sample preparation devices and tools, Handb. Nanomater Anal. Chem. Mod. Trends Anal., 2019, 75–95. 19. P. Minakshi, M. Ghosh, B. Brar, K. Ranjan, H. S. Patki and R. Kumar, Separation Techniques with Nanomaterials, Elsevier Inc., 2019. 20. A. K. da Silva, T. G. Ricci, A. L. de Toffoli, E. V. S. Maciel, C. E. D. Nazario and F. M. Lanças, The Role of Magnetic Nanomaterials in Miniaturized Sample Preparation Techniques, Elsevier Inc., 2020. 21. J. S. Beveridge, J. R. Stephens and M. E. Williams, The Use of Magnetic Nanoparticles in Analytical Chemistry, Annu. Rev. Anal. Chem., 2011, 4(1), 251–273. ¨yu ¨ktiryaki, R. Keçili and C. M. Hussain, Functionalized nanoma22. S. Bu terials in dispersive solid phase extraction: Advances & prospects, TrAC, Trends Anal Chem., 2020, 127, 115893. 23. M. Faraji, Recent analytical applications of magnetic nanoparticles, Nanochem. Res., 2016, 1(2), 264–290. 24. Q. Y. Ma, S. J. Tralna, T. J. Logan and J. A. Ryan, Effects of Aqueous Al, Cd, Cu, Fe(II), Ni, and Zn on Pb Immobilization by Hydroxyapatite, Environ. Sci. Technol., 1994, 28(7), 1219–1228. 25. B. Sandrine, N. Ange, B. A. Didier, C. Eric and S. Patrick, Removal of aqueous lead ions by hydroxyapatites: Equilibria and kinetic processes, J. Hazard. Mater., 2007, 139(3), 443–446. 26. R. R. Sheha, Sorption behavior of Zn(II) ions on synthesized hydroxyapatites, J. Colloid Interface Sci., 2007, 310(1), 18–26. ´k, J. Vejpravova, H. N. Vu, J. Lederer and T. Munshi, 27. D. N. Thanh, P. Nova Removal of copper and nickel from water using nanocomposite of magnetic hydroxyapatite nanorods, J. Magn. Magn. Mater., 2018, 456, 451–460. 28. M. Mahmoudi, S. Sant, B. Wang, S. Laurent and T. Sen, Superparamagnetic iron oxide nanoparticles (SPIONs): Development, surface

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30.

31.

32.

33.

34.

35.

36.

37.

38.

39.

40.

41.

Chapter 3

modification and applications in chemotherapy, Adv. Drug Delivery Rev., 2011, 63(1–2), 24–46. R. Strobel and S. E. Pratsinis, Direct synthesis of maghemite, magnetite and wustite nanoparticles by flame spray pyrolysis, Adv. Powder Technol., 2009, 20(2), 190–194. ¨th, Magnetic nanoparticles: Synthesis, A. H. Lu, E. L. Salabas and F. Schu protection, functionalization, and application, Angew Chem., Int Ed., 2007, 46(8), 1222–1244. ´rrez, H. Gavila ´n, M. E. Fortes Brollo, A. G. Roca, L. Gutie S. Veintemillas-Verdaguer and M. D. P. Morales, Design strategies for shape-controlled magnetic iron oxide nanoparticles, Adv. Drug Delivery Rev., 2019, 138, 68–104. J. Kurian and M. J. Mathew, Structural, optical and magnetic studies of CuFe2O4, MgFe2O4 and ZnFe2O4 nanoparticles prepared by hydrothermal/ solvothermal method, J. Magn. Magn. Mater., 2018, 451, 121–130. S. Laurent, D. Forge and M. Port, et al., Erratum: Magnetic iron oxide nanoparticles: Synthesis, stabilization, vectorization, physicochemical characterizations, and biological applications, Chem. Rev., 2010, 110(4), 2574. W. Jiang, K. L. Lai and H. Hu, et al., The effect of [Fe31]/[Fe21] molar ratio and iron salts concentration on the properties of superparamagnetic iron oxide nanoparticles in the water/ethanol/toluene system, J. Nanoparticle Res., 2011, 13(10), 5135–5145. C. V. Thach, N. H. Hai and N. Chau, Size controlled magnetite nanoparticles and their drug loading ability, J. Korean Phys. Soc., 2008, 52(5), 1332–1335. F. Yazdani and M. Seddigh, Magnetite nanoparticles synthesized by co-precipitation method: The effects of various iron anions on specifications, Mater. Chem. Phys., 2016, 184, 318–323. `res, C. Chane ´ac, E. Tronc and J. P. Jolivet, Size tailoring of L. Vayssie magnetite particles formed by aqueous precipitation: An example of thermodynamic stability of nanometric oxide particles, J. Colloid Interface Sci., 1998, 205(2), 205–212. G. Gnanaprakash, S. Mahadevan, T. Jayakumar, P. Kalyanasundaram, J. Philip and B. Raj, Effect of initial pH and temperature of iron salt solutions on formation of magnetite nanoparticles, Mater. Chem. Phys., 2007, 103(1), 168–175. R. Valenzuela, M. C. Fuentes and C. Parra, et al., Influence of stirring velocity on the synthesis of magnetite nanoparticles (Fe3O4) by the coprecipitation method, J. Alloys Compd., 2009, 488(1), 227–231. D. F. Mercado, P. Caregnato, L. S. Villata and M. C. Gonzalez, Ilex paraguariensis Extract-Coated Magnetite Nanoparticles: A Sustainable Nano-adsorbent and Antioxidant, J. Inorg. Organomet. Polym. Mater., 2018, 28(2), 519–527. R. M. Cornell and U. Schwertmann, The Iron Oxides: Structure, Properties, Reactions, Occurrences and Uses, VCH, Wiley, 2nd edn, 2003.

Improvement of Adsorbing Properties of Magnetic Nanomaterials

73

42. S. Rajput, C. U. Pittman and D. Mohan, Magnetic magnetite (Fe3O4) nanoparticle synthesis and applications for lead (Pb21) and chromium (Cr61) removal from water, J. Colloid Interface Sci., 2016, 468, 334–346. 43. P. Taylor, P. Majewski and B. Thierry, Critical Reviews in Solid State and Materials Sciences Functionalized Magnetite Nanoparticles — Synthesis, Properties, and Bio-Applications Functionalized Magnetite Nanoparticles — Synthesis, Properties, and Bio-Applications, Small, 2007, 8436, 37–41. 44. H. Bensalah, S. A. Younssi, M. Ouammou, A. Gurlo and M. F. Bekheet, Azo dye adsorption on an industrial waste-transformed hydroxyapatite adsorbent: Kinetics, isotherms, mechanism and regeneration studies, J. Environ. Chem. Eng., 2020, 8(3), 103807. 45. W. Wei, X. Han, M. Zhang, Y. Zhang and C. Zheng, Macromolecular humic acid modified nano-hydroxyapatite for simultaneous removal of Cu(II) and methylene blue from aqueous solution: Experimental design and adsorption study, Int. J. Biol. Macromol., 2020, 150(Ii), 849–860. 46. Y. Feng, J. L. Gong and G. M. Zeng, et al., Adsorption of Cd (II) and Zn (II) from aqueous solutions using magnetic hydroxyapatite nanoparticles as adsorbents, Chem. Eng. J., 2010, 162(2), 487–494. 47. Y. Xu, F. W. Schwartz and S. J. Traina, Sorption of Zn21 and Cd21 on Hydroxyapatite Surfaces, Environ. Sci. Technol., 1994, 28(8), 1472–1480. ´k, J. Vejpravova, H. N. Vu, J. Lederer and T. Munshi, 48. D. N. Thanh, P. Nova Removal of copper and nickel from water using nanocomposite of magnetic hydroxyapatite nanorods, J. Magn. Magn. Mater., 2018, 456, 451–460. 49. F. Zhuang, R. Tan, W. Shen, X. Zhang, W. Xu and W. Song, Monodisperse magnetic hydroxyapatite/Fe3O4 microspheres for removal of lead(II) from aqueous solution, J. Alloys Compd., 2015, 637, 531–537. 50. L. Dong, Z. Zhu, Y. Qiu and J. Zhao, Removal of lead from aqueous solution by hydroxyapatite/magnetite composite adsorbent, Chem. Eng. J., 2010, 165(3), 827–834. 51. D. F. Mercado, G. Magnacca and M. Malandrino, et al., Paramagnetic iron-doped hydroxyapatite nanoparticles with improved metal sorption properties. A bioorganic substrates-mediated synthesis, ACS Appl. Mater. Interfaces, 2014, 6(6), 3937–3946. 52. D. F. Mercado, A. Rubert and G. Magnacca, et al., Versatile Fe-containing hydroxyapatite nanomaterials as efficient substrates for lead ions adsorption, J. Nanosci. Nanotechnol., 2017, 17(12), 9081–9090. 53. G. Magnacca, A. Allera and E. Montoneri, et al., Novel magnetite nanoparticles coated with waste-sourced biobased substances as sustainable and renewable adsorbing materials, ACS Sustainable Chem. Eng., 2014, 2(6), 1518–1524. 54. X. Zhang, Y. Li and Y. Hou, Preparation of magnetic polyethylenimine lignin and its adsorption of Pb(II), Int. J. Biol. Macromol., 2019, 141, 1102– 1110.

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55. P. Wang, L. Chen, J. K. Guo, S. Shen, C. T. Au and S. F. Yin, Synthesis of Submicron-Sized SAPO-34 as Efficient Catalyst for Olefin Generation from CH3Br, Ind. Eng. Chem. Res., 2019, 58(40), 18582–18589. 56. S. G. Singaraj, B. Mahanty, D. Balachandran and A. Padmaprabha, Adsorption and desorption of chromium with humic acid coated iron oxide nanoparticles, Environ. Sci. Pollut. Res., 2019, 26(29), 30044–30054. 57. X. Zhang, P. Zhang, Z. Wu, L. Zhang, G. Zeng and C. Zhou, Adsorption of methylene blue onto humic acid-coated Fe3O4 nanoparticles, Colloids Surf., A, 2013, 435, 85–90. 58. J. D. Hu, Y. Zevi, X. M. Kou, J. Xiao, X. J. Wang and Y. Jin, Effect of dissolved organic matter on the stability of magnetite nanoparticles under different pH and ionic strength conditions, Sci. Total Environ., 2010, 408(16), 3477–3489. 59. A. Bianco Prevot, A. Arques, L. Carlos, E. Laurenti, G. Magnacca and R. `, Innovative Sustainable Materials for the Photoinduced Remediation Nistico of Polluted Waters, Elsevier Inc, 2019. 60. J. Gomis, A. Bianco Prevot and E. Montoneri, et al., Waste sourced biobased substances for solar-driven wastewater remediation: Photodegradation of emerging pollutants, Chem. Eng. J., 2014, 235, 236–243. 61. F. E. Garcı´a, A. M. Senn and J. M. Meichtry, et al., Iron-based nanoparticles prepared from yerba mate extract. Synthesis, characterization and use on chromium removal, J. Environ. Manage., 2019, 235, 1–8. 62. C. I. Heck and E. G. De Mejia, Yerba mate tea (Ilex paraguariensis): A comprehensive review on chemistry, health implications, and technological considerations, J. Food Sci., 2007, 72(9), R138–R151. 63. D. H. M. Bastos, L. A. Saldanha and R. R. Catharino, et al., Phenolic ´ (Ilex), Molecules, Antioxidants Identified by ESI-MS from Yerba Mate 2007, 12, 423–432. ´lez and F. H. Sa ´nchez, Yerba 64. D. F. Mercado, M. Cipollone, M. C. Gonza Mate applications: Magnetic response of powders and colloids of iron oxide nanoparticles coated with Ilex paraguariensis derivatives, J. Magn. Magn. Mater., 2018, 462, 13–21. 65. H. Veisi, S. B. Moradi, A. Saljooqi and P. Safarimehr, Silver nanoparticledecorated on tannic acid-modified magnetite nanoparticles (Fe3O4 @TA/ Ag) for highly active catalytic reduction of 4-nitrophenol, Rhodamine B and Methylene blue, Mater. Sci. Eng. C, 2019, 100(2018), 445–452. 66. M. Stan, I. Lung and M. L. Soran, et al., Starch-coated green synthesized magnetite nanoparticles for removal of textile dye Optilan Blue from aqueous media, J. Taiwan Inst. Chem. Eng., 2019, 100, 65–73. 67. C. Anushree and J. Philip, Efficient removal of methylene blue dye using cellulose capped Fe 3 O 4 nanofluids prepared using oxidationprecipitation method, Colloids Surf., A, 2019, 567, 193–204. 68. M. E. Mahmoud and M. S. Abdelwahab, Fabricated and functionalized magnetite/phenylenediamine/cellulose acetate nanocomposite for adsorptive removal of methylene blue, Int. J. Biol. Macromol., 2019, 128, 196–203.

Improvement of Adsorbing Properties of Magnetic Nanomaterials

75

69. R. G. L. Gonçalves, P. A. Lopes and J. A. Resende, et al., Performance of magnetite/layered double hydroxide composite for dye removal via adsorption, Fenton and photo-Fenton processes, Appl. Clay Sci., 2019, 179(2018), 105152. ´ , S. Łon ´ ski and T. Warski, et al., Catalytic activity of non-spherical 70. A. Radon shaped magnetite nanoparticles in degradation of Sudan I, Rhodamine B and Methylene Blue dyes, Appl. Surf. Sci., 2019, 487, 1018–1025. ` and F. Cesano, et al., Biowaste-derived substances 71. F. Franzoso, R. Nistico as a tool for obtaining magnet-sensitive materials for environmental applications in wastewater treatments, Chem. Eng. J., 2017, 310, 307–316. 72. L. Li and R. Stanforth, Distinguishing adsorption and surface precipitation of phosphate on goethite (a-FeOOH), J Colloid Interface Sci., 2000, 230(1), 12–21. 73. Y. Wang, Y. Xie, W. Li, Z. Wang and D. E. Giammar, Formation of lead(IV) oxides from lead(II) compounds, Environ. Sci. Technol., 2010, 44(23), 8950–8956. 74. S. Nasrazadani, V. Paliwal, M. Du, R. F. Reidy, J. Stevens and R. Theimer, Lead adsorption on magnetite at 200 1C, Corrosion, 2008, 64(6), 509–516. 75. X. S. Wang, H. J. Lu, L. Zhu, F. Liu and J. J. Ren, Adsorption of lead(II) ions onto magnetite nanoparticles, Adsorpt. Sci. Technol., 2010, 28(5), 407–417. 76. J. Chung, J. Chun, J. Lee, S. H. Lee, Y. J. Lee and S. W. Hong, Sorption of Pb(II) and Cu(II) onto multi-amine grafted mesoporous silica embedded with nano-magnetite: Effects of steric factors, J. Hazard. Mater., 2012, 239–240, 183–191. 77. S. Orsetti, M. de las Mercedes Quiroga and E. M. Andrade, Binding of Pb(II) in the system humic acid/goethite at acidic pH, Chemosphere, 2006, 65(11), 2313–2321. 78. F. Zhang, X. Ou, S. Chen, C. Ran and X. Quan, Competitive adsorption and desorption of copper and lead in some soil of North China, Front. Environ. Sci. Eng. China, 2012, 6(4), 484–492.

Section 2: Functionalized Magnetic Nanoparticles in Sample Pre-treatment

CHAPTER 4

Functionalized Magnetic Nanoparticles in Sample Pre-treatment SANU MATHEW SIMON,a M. S. SAJNA,a,b V. P. PRAKASHAN,a TWINKLE ANNA JOSE,a P. R. BIJU,a CYRIAC JOSEPHa AND N. V. UNNIKRISHNAN*a a

School of Pure & Applied Physics, Mahatma Gandhi University, Kottayam-686 560, India; b Department of Optoelectronics, University of Kerala, Thiruvananthapuram-695 581, India *Email: [email protected]

4.1 Introduction The examination of compounds available in a sample at low concentrations or ultra-trace levels typically needs an initial step of isolation or enrichment of analytes since most analytical procedures are not sensitive enough for the precise detection of trace amounts of a compound.1 To reduce the quantity of residue at the stage of sample preparation, harmless, safe extraction media are employed and novel micro-extraction methods are established which require less time and are less labor intensive when compared with multi-step actions.2 These micro-extraction procedures permit a combination of actions such as sampling, extraction and finding the concentration of analyte to a level higher than the detection limit of the method, in addition to the isolation of the analyte from the matrix taken as a sample which cannot easily be incorporated into measuring apparatus. This method is considered to be a green approach since it completely allows solvents to be replaced, reduced Analytical Applications of Functionalized Magnetic Nanoparticles Edited by Chaudhery Mustansar Hussain r The Royal Society of Chemistry 2021 Published by the Royal Society of Chemistry, www.rsc.org

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and recycled (replacing poisonous solvents with green solvents, reducing solvent utilization and waste generation, and solvent recycling).3,4 The high surface area to volume ratio and surface functionality of nanoparticles show their potential for easy usage in selective sample extraction and hence they can be widely used for sample preparation. Magnetic nanoparticles (MNPs) attract great interest in separation processes compared with other nanoparticles since they possess a better surface area, low cost and unique super-paramagnetism at room temperature. The main property of these MNPs is that due to their super-paramagnetic behavior they can be attracted to a magnetic field, but retain no residual magnetism when the field is detached.5–7 As a result, it is effortless to separate these super-paramagnetic particles attached to analytes from an aqueous solution or intricate matrix by just applying an exterior magnetic force, and therefore avoiding filtration or centrifugation. The remarkable features shown by magnetic nanoparticles are high field irreversibility, high saturation field, extra anisotropy contributions or shifted loops after field cooling, etc. These features mainly occur from slight and finite-size effects and surface effects that govern the magnetic properties of individual nanoparticles. Other advantages offered by MNPs are that they can save time by avoiding the problem of blockage, as well as the step of sample loading.8,9 This chapter deals with the application of functionalized magnetic nanoparticles in sample treatment and summarizes the modification of magnetic nanoparticles with organic as well as inorganic coating materials as adsorbent materials in sample preparation methods. An immense deal of attention is given to the extraction of environmental toxins, treatment of proteins and cells, and enrichment of biological macromolecules of the proteome and impurities in foods.7 The aim of this work is to concentrate on both presentative as well as critical points of view regarding all types of functionalized magnetic materials used for the separation or pre-concentration of compounds from environmental, biological and food samples.

4.2 Different Magnetic Nanoparticles for Extraction and their Magnetic Behavior Usually, MNPs comprise magnetic elements like iron, nickel or cobalt or their oxides (magnetite or maghemite) and alloys exhibiting ferromagnetic or superparamagnetic behavior. However, iron-oxide particles with a number of diverse compositions and phases (Fe3O4 and g-Fe2O3) are the most preferably used materials in sample preparation because of their characteristics like huge magnetic moments, biological compatibility, the easiness of their preparation procedure, and formation of their corresponding ferrites such as MFe2O4 (M ¼ Cu, Ni, Mn, Mg, etc.), and metal alloys like FePt, and CoPt.10–12 The basic issue of employing pure metals and their alloys such as Mn3O4, Fe, Co, Ni, FePt, and FePd, is that they show quick oxidation in air and potential for cytotoxicity.13–18 Since the magnetism is so significant in different steps of analytical methods, numerous combinations of nanocomposites consisting the

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magnetic nanoparticles have been developed recently. Hu et al. described the synthesis of different kinds of MNPs as the adsorbent material for the recovery of Cr(VI) from wastewater such as CoFe2O4, CuFe2O4, MgFe2O4, MnFe2O4, NiFe2O4, and ZnFe2O4. The authors evaluated the behavior of the different materials in the elimination of Cr(VI) and explored the influence of various factors such as contact time, pH, shaking rate, and magnetic properties. The outcome implies that their adsorption abilities were in the following order: MnFe2O44MgFe2O44ZnFe2O44CuFe2O44NiFe2O44CoFe2O4.19,20 Karatapanis et.al. reported the development of a magnetic Fe–Fe2O3 nanoscavenger for the analytical enrichment and estimation of concentrations of Cd(II), Pb(II), Ni(II), Cr(VI) and As(V) up to subparts per billion from water samples.21 Several methods such as the chemical co-precipitation method, solvothermal technique, and cation diffusion method are used to prepare the magnetic nanoparticles usually. Based on the response to an exterior applied magnetic field, materials are classified into five types and can be described as diamagnet, paramagnet, ferromagnet, anti-ferromagnet and ferrimagnet materials. Diamagnetic materials can be defined as the material that shows weak repulsion to the field since the atomic current loops produced due to the orbital motions of electrons resist the applied magnetic field.22 Paramagnetic materials are those possessing an uncoupled magnetic moment with no long-range order. Meanwhile, ferromagnets show aligned atomic magnetic moments with equal magnitude and increase the flux density in crystalline form by the direct coupling interactions between magnetic moments. The special feature of ferromagnets is that they can confer spontaneous magnetization even if the magnetic field is absent. Materials that can maintain permanent magnetization when the field is not applied can be called hard magnets.23 Materials display anti-ferromagnetism when net magnetization is zero because the equal magnitudes of atomic moments are arranged in the opposite direction. Furthermore, ferrimagnetism is shown by atoms or ions of the materials which ascribe an ordered unparallel arrangement in a zero applied field below Neel temperature. Specifically, ferromagnets exhibit permanent magnetism to form a lattice when the magnetic field is removed. On the other hand, superparamagnetic particles do not maintain magnetism when an external field is detached. Hence these MNPs have attracted special attention in the scientific society due to their superparamagnetic character as well as their exceptional physical and chemical behavior. The main objectives of using MNPs for sample preparation can be listed as: 1. Higher efficiency in extraction due to the large surface-area-to-volume ratio of the extraction phase. 2. In comparison with traditional solid-phase extraction (SPE) methods, this technique exhibits fast separation. 3. It is more convenient and simpler to prepare and modify the surface of the extraction phase. 4. The selectivity of the target analytes and appropriateness for the complex matrices increase.

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5. Better reusability since MNPs don’t show any direct contact between analytes and targets. 6. Shows excellent dispersibility in aqueous solution and is also very simple to operate. 7. Magnetic nanoparticles exhibit an inert nature and simplify the analytical procedure. 8. MNPs also act as an agent to enhance the detection of the signal.

4.3 The Necessity of Functionalized Magnetic Nanoparticles The novel microextraction technique magnetic solid-phase extraction (MSPE) using magnetic particles (MPs) as the adsorbents has had a significant impact on the analytical as well as research community in recent years. For the first time, separation using magnetic nanoparticles was studied by Robinson et al.24 in 1973 for biotechnological purposes. In 1987, Wikstrom et al. described rapid phase separations by introducing magnetically susceptible additives (ferrofluids or iron oxide particles) with an exterior magnetic field in liquid–liquid extraction techniques compared with other older methods.25 Later, in 1996, Towler et al. reported the use of manganese dioxide coated magnetite as a sorbent material for the recovery of radium, lead and polonium from seawater samples.26 Nevertheless, the name magnetic solid-phase extraction (MSPE) was first coined by Safarikova et al. in 1999 for analytical uses.27 Many researchers have devoted efforts to significantly enhance the efficiency of magnetic solid-phase extraction (MSPE) through the preparation of novel functionalized MNPs.7,27 The main aim of functionalizing the nanoparticles is to avoid the agglomeration of the particles which reduces their intrinsic instability. Due to the higher chemical activity of the naked metallic nanoparticles, their tendency to be oxidized in air is greater, which results in a loss of magnetism and dispersibility. Hence, for various applications it is essential to build up protection methods to chemically protect the naked magnetic nanoparticles. These methods include grafting or coating using an inorganic layer, for instance silica or carbon, or coating with organic species including surfactants and polymers.28 Furthermore, these MNPs could be functionalized with nanocomponents like ligands, metal oxides, enzymes, antibodies, etc. showing many applications in various areas like environmental, biological and food analysis. It is striking that in numerous cases, the protective coatings not only stabilize but also promote the functionalization of nanoparticles.29 Another important reason for using MNPs is that they can be reused and recycled. In the last five years, this topic has become more significant due to its versatile applications. Figure 4.1 represents the progress in the topic ‘‘functionalized magnetic nanoparticles in sample pretreatment’’ on the basis of the number of articles published and the number of citations received for articles during the period of 2015 to 2020.

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Figure 4.1

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(a) Tremap representing the number of articles published in each year during the period 2015–2020. (b) Bar diagram representing the number of citations per year received for various articles on the same topic and same duration of time. (Source: Web of Science database searching the keyword ‘‘Functionalization of Magnetic nanoparticles in Sample pre-treatment’’).

4.4 Sample Preparation Techniques Generally, in a magnetic solid-phase extraction (MSPE) technique, it is permitted to add functionalized MNPs into sample matrices consisting of target analytes and untargeted compounds. Subsequently, incubation or application of supplementary disturbance by irradiation (e.g., sonication) for the time required for the target analytes to be adsorbed by the adsorbent and then the functionalized MNPs are simply removed from the solution with the application of an external magnetic field. The removal of the external magnetic field allows the re-dispersal of the functionalized MNPs in the solution, which is suitable for successive washing and desorption. This means that in magnetic

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solid-phase extraction, usually MNPs are mixed into the prepared solution, and the target analyte is allowed to adsorb on the surface of the magnetic beads which can then be alienated from the aqueous solution with the aid of an exterior magnetic force. Afterwards, the target analyte is removed by the eluent for advanced determination. In contrast with generally used sorbent materials, suspended magnetic nanoparticles can be easily separated from high-volume samples with the help of a magnet as an alternative to high-speed centrifugation or filtration which simplifies and speeds up the isolation process. Hence, magnetic solid-phase extraction technologies have grown to be a powerful complement to other batch SPE methods.1

4.5 Types of Functionalized Magnetic Materials To overcome the aforementioned problems, an effortless, speedy, gentle and efficient method of functionalizing magnetic nanoparticles is the better strategy. Functionalized magnetic materials are divided into two types according to the style of coating/shell: (i) Inorganic coating: the coating is made up of an inorganic part (e.g., silica). (ii) Organic coating: modified using organic molecules [e.g., octadecylsilane, polymer or surfactant].

4.6 Application of Functionalized MNPs with Silica Silica is a versatile material extensively used in sample preparation due to its low cost, chemical inertness, and thermal stability. Silica gel is also considered as a prominent material for SPE as it has several advantages including high mass exchange, does not swell, provides a simple way to modify the surface, easy control of interactions between interparticles and is also stable under acidic as well as aqueous conditions. MNPs entrenched in a silica matrix can easily be dispersed in liquid media since it can monitor the magnetic dipolar interactions between these magnetic nanoparticles which shields them from leaching in an acidic situation.30 Silica-modified MNPs combine the benefits of both silica and MNPs and have been extensively used in the extraction of different analytes from various targets. The coating covers the magnetic core and prevents direct contact of the magnetic core with further agents coupled to the silica surface and hence avoids unnecessary interactions. Additionally, the coating of silica over MNPs allows the easy tailoring of the surface, especially to graft different desirable functional groups over the MNPs. This means the abundant silanol groups on the surfaces of silica NPs exhibit a hydrophilic nature which makes the surface perfect for further modification with functional groups or additional materials (e.g., titania and zirconia).31 Recently, many studies have shown the use of silica-coated Fe3O4 particles tailored with diverse functional groups for metal detection through solid-phase

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extraction. It is estimated that integrating a silica coating on a magnetic core could achieve the advantages of silica, such as its high chemical stability and biocompatibility without surrendering the inimitable magnetization properties of Fe3O4.33 Kim et al. made magnetite nanocrystals embedded in mesoporous silica spheres which can be used as a magnetic fluorescent delivery vehicle.34 Bagheri et al. successfully developed a new magnetic metal–organic framework made up of Fe3O4 and pyridine (N-[3(triethoxysilyl)propyl]isonicotinamide (TPI) was used as the functionalizing agent) applied for the pre-concentration and extraction of low concentrations of palladium in fish, sediment, soil and water samples by flame atomic absorption spectrometry (FAAS).35 Huang et al. developed g-mercaptopropyltrimethoxysilane (g-MPTMS)-functionalized silicacoated magnetic nanoparticles as an SPE adsorbent for determining and extracting trace amounts of Cd, Cu, Hg, and Pb before studying with inductively coupled plasma mass spectrometry (ICP–MS).36 Luo et al. synthesized silicacoated magnetic microspheres adsorbed over two-dimensional planar graphene sheets for the extraction and detection of sulfonamide antibiotics from environmental water samples.37 Superparamagnetic highly magnetized C18-functionalized silica-coated magnetite nanoparticles with a diameter of 320 nm were used for the extraction and determination of the concentration of methylprednisolone (MP) in rat plasma through the hydrophobic interaction of the interior C18 groups.38 Magnetic nanoparticles comprising a magnetite core covered with a silica shell as well as zincon as functional groups were developed to work as a sorbent substance for tracing the concentration of lead from natural and drinking waters through electrothermal atomic absorption spectrometry (ETAAS).39 Zhai et al. developed a technique for determining the amount of mercury(II) in an aqueous medium using silica-coated MNPs functionalized with 1,5-diphenylcarbazide as the extractant and the analysis is carried out using cold-vapor atomic absorption spectrometry (CV-AAS), and the limit of detection (LOD) was found to be 0.16 mg L1.40 Mixing metal–organic framework MIL-101 microcrystals and silica-coated Fe3O4 nanoparticles in sample solution under sonication is used for quick sampling of polycyclic aromatic hydrocarbons (PAHs) from environmental water samples.41 Furthermore, MNPs coated with silica and functionalized with diphenyl groups is used to determine the PAHs in urine from smokers and non-smokers.42 Schiff basefunctionalized silica-coated MNPs were developed for the estimation and quantification of Pb(II), Cd(II) and Cu(II) in water, food and biological samples using the technique inductively coupled plasma atomic emission spectrometry (ICP–AES).6 Fe3O4 NPs functionalized with tris(2-aminoethyl)amine (TREN) synthesized following activation of the iron oxide surface with NaOH solution and silane agents were used for the selective extraction, and estimation of the concentrations of Ag(I) and Au(III) from natural samples.43 Fe3O4 NPs prepared via a chemical co-precipitation method coated and with 3-(trimethoxysilyl)-1propantiol (TMSPT), which was directly adsorbed on the surface of the MNPs forming a single layer (shell) can be used as an adsorbent for SPE of trace silver, cadmium, copper and zinc from tap water and mineral samples prior to their estimation by ICP–AES.44 Silica-coated magnetic microparticles modified with

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Figure 4.2

Chapter 4

TEM micrographs of (a) Fe3O4 particles, (b) Fe3O4@nSiO2, (c–e) Fe3O4@ nSiO2@mSiO2 microspheres, and (f) SEM micrographs of Fe3O4@ n-SiO2@mSiO2 microspheres. Reproduced from ref. 30 with permission from American Chemical Society, Copyright 2008.

N-methyl-D-glucamine developed using a sol–gel method were used for the extraction and also to determine the amount of boron in aqueous solutions.45 Studies show that the magnetic mesoporous silica spheres might be a better adsorbent for the quick and highly able elimination of 1,1-bis(4-chlorophenyl)2,2,2-trichloroethane from aqueous sources. The morphology of functionalized silica-coated MNPs is depicted in Figure 4.2 and their different applications and properties are listed in Table 4.1.46

4.7 Application of Functionalized MNPs with Octadecylsilane (ODS) Another way to protect and keep MNPs stable is through modification of the MNPs by grafting with silane coupling agents since it immobilizes the surface of the MNPs.53 Octadecylsilane modified magnetite nanoparticles have been extensively used for the preconcentration of environmental pollutants due to their excellent separation ability, better stability and long lifetime. ODS-functionalized magnetic NPs are therefore predicted to have an outstanding performance in the adsorption and separation of substances from complicated samples.54,55 Figure 4.3 represents the effect of functionalized C18–SiO2 in the bonding between MNPs. It can be seen that octadecylsilane Fe3O4 functionalized with SiO2–C18 prepared via a chemical co-precipitation method was used for finding

Functionalized silica-coated Fe3O4 magnetic nanoparticles and their properties.

Analyte Cd(II) Cu(II) Hg(II) Pb(II) Uranyl ions ([UO2]21) Al(III) Cr(III)

Functional group

Limit of detection 1

g-Mercaptopropyltrimethoxysilane 24 pg L 92 pg L1x 107 pg L1 56 pg L1

Technique

Application

Reference

Inductively coupled plasma mass spectrometry

Lake sediment, seawater and milk powder samples

36

Spiked ground and mineral 47 water samples Human plasma, human urine, 48 tap water, and drinking water samples Tap water samples 49

Quercerin

12.33 mg g1



3-Mercaptopropionic acid

0.09 ng mL1 0.19 ng mL1

Flame atomic absorption spectrometry

Thiols

Anodic stripping voltammetry Hydride generation atomic fluorescence spectrometry Inductively coupled plasma mass spectrometry Inductively coupled plasma mass spectrometry

Hg(II) Pb(II) Cd

Amino

0.08 mg L1 0.02 mg L1 3.15 ng L1

As(V)

Amino

0.21 ng L1

Se(IV)

Mercapto

0.094 ng L1

Environmental water samples

50

Environmental waters of tobacco growing area Environmental water samples

51

Functionalized Magnetic Nanoparticles in Sample Pre-treatment

Table 4.1

52

87

88

Figure 4.3

Chapter 4

FTIR spectra of (a) Fe3O4, (b) Fe3O4/SiO2, (c) Fe3O4/SiO2/SiO2 and (d) Fe3O4/SiO2/SiO2–C18 microspheres. Reproduced from ref. 71 with permission from the Royal Society of Chemistry.

trace amounts of organo-phosphorous pesticides such as oxadizon and profenlofos in environmental water.56 Stable hydrophobic magnetic nanoparticles functionalized with trichlorooctadecylsilane resistant to acidic medium were developed by Lobato et al. for various applications.57 The SBA-15 mesoporous silica bi-functionalized with octadecylsilane and sulfonic acid represented in Figure 4.4 can act as a mixed oxide sorbent for determining veterinary drug concentrations in meat samples.58 C18-functionalized magnetic silica nanoparticles are applied for the rapid investigation of ergosterol in ordinary and rotten cigarettes followed by microwave-assisted derivatization and gas chromatography/mass spectrometry. The time required for isolation was about 2 s, with the help of a strong magnet. The adsorbed analyte was simply desorbed in n-hexane, with no carryover seen in the next study.59 Qiao et al. synthesized octadecyl functionalized core–shell magnetic silica nanoparticles that can be employed as a strong nanosorbent to determine endogenous urinary volatile organic metabolites.60 C18-functionalized magnetic silica nanoparticles are also considered as sorbents in rapid magnetic solid-phase extraction for finding endocrine disruptors i.e., 20 organo-chlorine pesticides and 6 polychlorinated biphenyls from milk samples.61 Maddah et al. synthesized magnetite octadecylsilane nanoparticles for use in the extraction and assessment of trace amounts of diazinon and fenitrothion from environmental water samples which was followed by high performance liquid chromatography with UV detection.62 Another study used Fe3O4–SiO2– C18 paramagnetic nanoparticles as sorbents in magnetic solid-phase extraction of Zinab from agricultural aqueous samples through ultrasonication and

Functionalized Magnetic Nanoparticles in Sample Pre-treatment

Figure 4.4

89

TEM images of (a) SBA-15 and (b) SBA-15–C18–SO3. SEM images of (c) SBA-15 and (d) SBA-15–C18–SO3. Reproduced from ref. 58 with permission from Elsevier, Copyright 2017.

quantification using a first derivative spectrophotometric method.63 Zhang et al. prepared C18/C8-functionalized magnetic silica nanospheres to act as capture probes for the purification and enrichment of residues of veterinary drugs in food.64 Caon et al. reported the preparation and application of core– shell magnetic nanoparticles based on CoFe2O4, g-Fe2O3 and MnFe2O4 coated with octadecylsilane for the magnetic solid-phase extraction of triclosan from aqueous samples.65 Yu et al. reported the preparation of highly magnetized C18-functionalized silica nanoparticles which mainly focused on the enrichment and determination of methylprednisolone etc. in rat plasma, by acting as the sorbent in magnetic solid-phase extraction followed by high-performance liquid chromatography.66 Another work by Chu et al. used the same adsorbent as a sorbent material for on-column extraction of lidocaine in rat plasma. The on-column method with ODS-modified magnetic nanoparticles has the properties of simple substitution and regeneration by operating the magnetic field. Thus it presented a simple fabrication method for on-column extraction with low cost and excellent reproducibility. Furthermore, it needs just a minute amount of eluting solvent (microliter amounts), which could diminish the damage to the human body and the environment.67 Similar work on the low cost and rapid detection of puerarin in rat plasma samples, using a small amount of solvent has been carried out.68

90

Chapter 4

A simple, sensitive and robust C18-functionalized magnetic silica nanoparticle-based magnetic solid-phase extraction method was effectively proved to be practically applicable to the analysis of microcystin-LR in the reservoir water samples followed by HPLC.69 Deng et al. prepared magnetic core–mesoporous shell microspheres with inner pore walls with an average diameter of about 300 nm modified with ODS and used them for the rapid extraction of phthalates in water samples. The highlight of these C18-functionalized MNPs is that they show excellent dispersibility and quick magnetic response due to the presence of abundant silanol groups on the shell’s outer surface with strong magnetic responsivity which improves the extraction process.70 Excellent hydrophobic–hydrophobic bonding between C18-functionalized Fe3O4–mSiO2 microspheres and phthalates enhance the extraction and enrichment process up to very minute amounts of the adsorbents within a short span of 10 minutes. Zhang et al. coated a C18-functionalized mesoporous silica shell over Fe3O4–SiO2 magnetic microspheres to develop Fe3O4/SiO2/SiO2–C18 microspheres exhibiting an ultrahigh extraction performance of organic targets from the water with a better anti-interference ability toward natural organic matter. C18-modified MNPs are compared with Fe3O4–SiO2 microspheres which exhibit less efficiency in extraction over the whole pH range concluding that the modification of C18 is the reason for the extraction of the target to the surface.71 TEM images of the microspheres are shown in Figure 4.5. Zhang et al. prepared robust silica-coated MNPs modified with both C18 as well as NH2 groups that can be used as the sorbent for the extraction of anionic organic pollutants under acidic conditions. The main advantage found in this work is that more than 90% extraction of targets is possible from a 500 mL aqueous solution using 0.1 g Fe3O4–SiO2–C18 þ NH2 nanoparticles at pH 3 due to the hydrophobic interaction and electrostatic draw of the anionic perfluorinated compounds offered by the mixed groups on the surface.72

Figure 4.5

TEM images of the synthesized C18-functionalized Fe3O4@mSiO2 microspheres. Reproduced from ref. 70 with permission from Elsevier, Copyright 2011.

Functionalized Magnetic Nanoparticles in Sample Pre-treatment

Scheme 4.1

91

Schematic representation of the synthesis of Fe3O4–SiO2–C18 þ NH2 nanoparticles. Reproduced from ref. 72 with permission from Elsevier, Copyright 2011.

A schematic representation of the synthesis method is shown in Scheme 4.1. Ultrafine magnetic silica nanoparticles prepared via a chemical co-precipitation method functionalized with ODS can be utilized to extract four types of Sudan dye from water samples followed by ultrafast liquid chromatography.73

4.8 Application of Functionalized MNPs with a Carbon-based Material Carbon functionalized magnetic materials have recently attracted extensive attention as sorbents in extraction processes mainly due to their hydrophobic and p–p interactions. The carbon-based magnetic materials are considered to be more versatile than silica due to their advantages such as advanced chemical and thermal stability and biocompatibility, and the possibility of alteration of the surface and establishment of pores. The standard method for the development of magnetic carbon materials is to introduce the magnetic source into carbon supplies including graphitized carbon black, carbon nanotubes (CNTs), and fullerenes or to introduce carbon materials into the magnetic source which finally shows strong adsorption affinity for a large range of organic species and efficiency over a broad pH range.

4.9 Activated Carbon-based Magnetic Nanoparticles Recent work on a NiFe2O4/activated carbon magnetic composite (NiAC), produced via a hydrothermal method, applied as a prospective magnetic adsorbent for adsorption of the emerging contaminants ibuprofen and ketoprofen pharmaceuticals from aqueous diluted solutions, has been carried out. The new material shows higher efficiency in treating a simulated pharmaceutical effluent, with a removal percentage higher than 85%.74 A magnetic activated carbon composite synthesized through the impregnation of activated carbon over magnetite (Fe3O4) prepared using a simple co-precipitation method was used as a new adsorbent for MSPE of 2,4-dichlorophenol

92

Chapter 4

(2,4-DCP) in water samples. The limit of detection (LOD) along with the limit of quantification (LOQ) in this work were reported as 0.293 mg mL1 and 0.890 mg mL1, respectively.75 Shokry et al. focused on the production of an eco-friendly magnetic activated carbon nanohybrid through the advantageous use of waste biomass from water hyacinth as an innovative nano-magnetic adsorbent material which is efficient for the effective clean-up of oil spills from waste water.76 Low cost oil palm fiber waste activated carbon reinforced with Fe3O4 and polypyrrole was developed as a sorbent for the extraction of organochlorine pesticides in waste samples. Oil palm fiber waste increases the surface area for adsorption. The prepared oil palm fiber-based activated carbon reinforced with Fe3O4 and polypyrrole was successfully demonstrated for the extraction of two organochlorine pesticides i.e., endosulfan and dieldrin from various environmental water bodies.77 Magnetic waste tire activated carbon– chitosan composite prepared via a one-step co-precipitation method was used as a suitable sorbent material in the removal of adsorptive parabens from model as well as real waste-water samples. From the Langmuir model, clearly the maximum adsorption capacity for monolayer adsorption of methylparaben and propylparaben is calculated as 85.9 mg g1 and 90.0 mg g1, respectively. The composite is observed to be stable even after seven cycles of adsorption– desorption with greater than 95% adsorption efficiency.78 Various reports on activated carbon magnetic nanoparticles are summarized in Table 4.2.

4.10 Graphene-based Magnetic Nanoparticles Graphene possesses several peculiar features including a 2D planar structure conjugated with one atom thickness, large surface area and better electrical, and thermal behavior in addition to mechanical properties. The large delocalized p-electron system present in graphene makes it a better adsorbent for the extraction of compounds. CoFe2O4 magnetic nanoparticles embedded in reduced graphene oxide sheets are used as a sorbent phase in a rapid analytical technique for estimating polycyclic aromatic hydrocarbons in cosmetic samples. The entire method is developed based on stir bar sorptive-dispersive microextraction. The target analytes are allowed to desorb in toluene followed by analysis by gas chromatography–mass spectrometry.86 Graphene-based magnetic nanocomposites prepared via a partial reduction co-precipitation method is used for adsorbing La(III) from aqueous solutions. The influence of pH, ion concentration, adsorbent dosage, contact time and temperature on the adsorption of ions was also studied.87 Newly developed self-assembled magnetic Prussian blue reduced graphene oxide aerogel (Figure 4.6) acts as an adsorbent for developing a less expensive and easier method for the elimination of radioactive Cs from nuclear waste effluents and a schematic representation of the synthesis method is shown in Scheme 4.2.88 The graphene oxide–g-Fe2O3 composite prepared by a co-precipitation method is applied as a sorbent for SPE and enrichment of estrogen from tap water samples and thereafter was determined via high-performance liquid chromatography with a fluorescence detector. The limit of detections obtained for estrogens 17 b-estradiol and 17

Different activated carbon magnetic nanoparticles and their properties.

Magnetic material Carbon coated Fe3O4 nanoparticles Carbon-ferromagnetic nanocomposite

Preparation Method

Source of activated carbon

Hydrothermal method Glucose Co-precipitation method

Glucose

Analyte Polycyclic aromatic hydrocarbons Polycyclic aromatic hydrocarbons

Limit of detection 0.2–0.6 ng L

1

0.015–0.335 ng mL1 0.5–2.0 ng g1

Method

Reference

Solid-phase extraction Magnetic Solid-phase extraction Magnetic Solid-phase extraction Magnetic Solid-phase extraction Solid-phase extraction-

79 80

Carbon coated Fe3O4 magnetic particles

Hydrothermal method Tree leaves

Polycyclic aromatic hydrocarbons

Carbon coated Fe3O4 nanoparticles

Co-precipitation method

Glucose

Organophosphorous 4.3–47.4 pg mL1 pesticides

Glucose

Polycyclic aromatic hydrocarbons

0.7–50 pg mL1

Aromatic heavy oil Glucose







84

Organic pollutants



Solid-phase extraction

85

0.293 mg mL1

Solid-phase extraction

75

Ceramic/carbon coated Fe3O4 Hydrothermal method magnetic nanocomposites combined with sol– gel method Carbon encapsulated iron Co-carbonization nanoparticles Coreshell structured carbon Co-precipitation encapsulated magnetic method nanoparticles Co-precipitation Activated carbon/Fe3O4 composite method Magnetic activated carbon Chemical nanohybrid modification Oil palm fiber activated carbon modified with magnetite and Polypyrrole

Chemical activation

Activated 2,4-dichlorophenol carbon Waste biomass Oil spills from water hyacinth Oil palm fiber Endosulfan Dieldrin

— 7.3 ng L1 8.6 ng L1

81 82 83

Functionalized Magnetic Nanoparticles in Sample Pre-treatment

Table 4.2

76 Magnetic Solid-phase extraction

77 93

94

Figure 4.6

Chapter 4

(a and b) SEM images of magnetic Prussian blue reduced graphene oxide aerogel. (c and d) TEM image and SAED pattern. Reproduced from ref. 88 with permission from Elsevier, Copyright 2020.

a-ethinyl estradiol are 2.7 and 0.8 ng L1 respectively. The central composite design shows great significance in achieving the excellent adsorption conditions for estrogens.89 Fe3O4 nanoparticles conjugated on GO nanosheets with the help of coupling agents like deep eutectic solvents is tested for their applicability in the elimination of organic and inorganic pollutants from water i.e., organic dye methylene blue and heavy metal lead(II).90 An easy and efficient preconcentration method is developed for the sensitive determination of endocrine disrupting compounds (i.e., two alkyl phenols, two organochlorine pesticides, one organophosphate pesticide) from different water and baby food samples using a gas chromatography flame ionization detector.91 The studies on graphene-based magnetic materials are summarized in Table 4.3.

4.11 Carbon Nanotube (CNT)-based Magnetic Materials Pure Fe3O4 nanoparticles have the tendency to aggregate which results in a loss of magnetic properties. Modification of Fe3O4 with carbon nanotubes will reduce this problem since CNT possesses unique physiochemical aspects such as high surface area, better stability and mechanical strength, hydrophobicity,

Functionalized Magnetic Nanoparticles in Sample Pre-treatment

Scheme 4.2

95

Schematic representation of the synthesis method of magnetic Prussian blue reduced graphene oxide aerogel. Reproduced from ref. 88 with permission from Elsevier, Copyright 2011.

a delocalized p-electron system and capacity for functionalization. These properties will allow multiple interaction forces like p–p stacking, electrostatic interaction, hydrophobic effect and dispersion forces between CNT and targeted analytes and combines the merits of both materials.98–100 Magnetic CNT modified with polymeric deep eutectic solvent is used as an extractant for the MSPE of bovine serum albumin. The entire procedure for the fabrication of multiwalled CNT and modification with polymeric deep eutectic solvent for the quantification of bovine serum albumin is represented in Scheme 4.3.101 Magnetic restricted-access carbon nanotubes were developed as a sorbent for dispersive solid-phase extraction and pre-concentration of organophosphates from commercial milk samples. Moreover, these CNT-based restricted access materials are mainly employed in on-line systems and column-switching liquid chromatography.102 Magnetic multiwalled CNT was used first time as an adsorbent material for the estimation of five target mycotoxins in human urine samples followed by ultrahigh performance liquid chromatography which is coupled to high resolution mass spectrometry. The LOD is observed between 0.04 and 0.1 mg L1 whereas the recovery percentage was calculated to be 89.3 5% and 98.9% respectively. The main merits of the proposed methods are an increase in mass transfer, upgrading of the extraction efficiency and the

96

Table 4.3

Different activated graphene-based magnetic nanoparticles and their properties.

Magnetic material

Preparation method

Chemical reduction Graphene grafted and cosilica-coated Fe3O4 precipitation method Graphene-based Chemical comagnetic precipitation nanocomposite method

Sample type

Analyte

Pear and tomato

Neonicotinoid pesticides

Environmental Carbamate water samples pesticides

Recovery Limit of detection range Reference

0.08 to 0.15 ng g1 93.1% to 92 High performance 107.4% liquid chromatography 0.02–0.04 ng m L1 87% to High 93 performance 97.3% liquid chromatography — — 82.2% to 94 99.4%

Graphene-based magnetic nanocomposite Graphene-based Fe3O4 magnetic nanocomposite

In situ chemical coprecipitation method In situ chemical coprecipitation method

Water

Environmental Triazine water samples herbicides

89% to 96.2%

Magnetic graphene nanocomposite

In situ chemical coprecipitation method —

Water samples

80.7% to 96 105.3%

Graphene-based magnetic nanoparticles

Organic dyes

Method of detection

0.025 to High 0.040 ng mL1 performance liquid chromatography Chloroacetanilide Gas 0.02 to chromatography 0.05 ng mL1

Environmental Triazole water samples fungicides

0.005 to High 0.01 ng mL1 performance liquid chromatography

86 to 102%

95

97

Chapter 4

Functionalized Magnetic Nanoparticles in Sample Pre-treatment

Scheme 4.3

97

Synthesis of multi-walled CNT modified with polymeric deep eutectic solvent as an extractant of bovine serum albumin. Reproduced from ref. 101 with permission from Elsevier, Copyright 2020.

decrease of organic volume solvent in the desorption step, avoiding filtration or centrifugation steps.103 Magnetic multiwalled carbon nanotube–gold nanoparticle composites were used as an excellent solid-phase extraction adsorbent for the determination of four triazine herbicides from rice which was followed by high-performance liquid chromatography. Herein, CNTs provide p–p and hydrophobic interactions, whereas Au nanoparticles show selective adsorption interactions for triazine herbicides that contain S, N and O.104 Magnetic CNTs encapsulated with Co nanoparticles prepared by a one-step pyrolysis strategy is used as an adsorbent to extract profens from human serum with a limit of detection of 0.60 ng L1 and 0.70 ng L1 respectively. The synthesized one is employed as an excellent adsorbent due to the presence of nanopores, better specific surface area and strong magnetic response.105 New methodology is developed for the extraction and estimation of catecholamines and associated metabolites in red deer urine and hair fabricated via magnetic multi-walled CNT poly(styrene-co-divinyl benzene) composites.106 A novel nanocomposite made up of multi-walled carbon nanotube and Cu2O–CuO ball-like nanoparticles were prepared via a hydrothermal method to develop a low cost and thermal stable potential adsorbent for the ultrasound-assisted SPE of uranium followed by inductively coupled plasma mass spectrometry.107

98

Chapter 4

4.12 Surfactant-modified Magnetic Materials Hemimicelles and adimicelles were developed as a result of the adsorption of better ionic surfactants on mineral oxides such as titanium oxide, alumina, silica and ferric oxyhydro-oxides which received great attraction as versatile sorbents for SPE with better results.108,109 Hemimicelles consist of surfactants with monolayers which are able to be adsorbed by their headgroup toward the oppositely charged surface of the mineral-oxide, and meanwhile, the hydrocarbon tail groups project toward the solution. Accumulating a greater concentration of surfactant over the surface of mineral oxide will lead to the saturation of the surface and hence, the hydrophobic interactions arising among the tails of the hydrocarbon chains of the surface will allow the formation of adimicelles. Mixed hemimicelles are formed when simultaneously both hemimicelles and adimicelles exist over the surface of the magnetic nanoparticles and a representation is given in Scheme 4.4. This results in the formation of hydrophobic as well as electrostatic interactions resulting in a better extraction efficiency to different compounds. Mixed hemimicelles made by adsorbing ionic surfactants above the surface of metal oxides for example, sodium dodecyl sulfate (SDS) coated alumina or cetyl trimethylammonium bromide (CTAB) coated silica can be developed as an excellent sorbent in the SPE method for the preconcentration of different organic pollutants from complex environmental samples. The main benefits observed for these sorbents are better extraction effectiveness, lower cost, exceptional usefulness and wide applicability. A combination of silica-coated magnetic nanoparticles and mixed hemimicelles will obtain nanosized SPE adsorbents with better surface area along with high chemical stability and superior magnetic separability.110–113 Mixed hemimicelles assembly of CTAB coated Fe3O4 nanomagnets is used as a sorbent to determine the concentration of four chlorophenols from collected environmental water samples, followed by HPLC–UV analysis.114 CTAB coated Fe3O4 nanoparticle mixed hemimicelles are also used to investigate the amount of phenolic compounds in environmental water samples.115 Karatapanis et al. developed cetylpyridinium bromide modified magnetite nanoparticles coated with silica possessing the capacity to attract metal ions after complexation with 8-hydroxyquinoline.116 Sodium dodecylsulfate functionalized Fe3O4–Al2O3 nanoparticles forming a hemimicellar structure can be used to quantify trimethoprim in water samples from different sources like taps, hospitals, sewage overflow and rivers.117 Octadecyl trimethylammonium bromide coated magnetite nanoparticles (mixed hemimicelles) are used for the preconcentration of sulfonamides whereas hexadecyl-3-methylimidazolium Fe3O4 magnetic nanoparticles coated with bromide are used for determining the concentration of chlorophenols from environmental water sources.118,119 Fe3O4 magnetic nanoparticles (Fe-MNPs) functionalized and dispersed with regularly used cationic surfactants were applied to eradicate Sb contamination in real surface waters.120 Magnetite nanoparticles (Fe3O4) stabilized by two nonionic and one cationic surfactant

Ionic surfactants adsorbed on the surface of Fe3O4 nanoparticles. The arrows designate a rise in the concentration of surfactant. Reproduced from ref. 38 with permission from the Royal Society of Chemistry.

Functionalized Magnetic Nanoparticles in Sample Pre-treatment

Scheme 4.4

99

100 Mechanism behind the formation of surfactant coated magnetite and heavy metal adsorption on magnetite–surfactant composite through (a) cationic surfactant and (b) non-ionic surfactant. Reproduced from ref. 121 with permission from Elsevier, Copyright 2020

Chapter 4

Scheme 4.5

Functionalized Magnetic Nanoparticles in Sample Pre-treatment

101

were prepared for the exclusion of heavy metal ions and a comparison is given in Scheme 4.5.121

4.13 Polymer-modified Magnetic Nanoparticles Magnetic nanoparticles functionalized by polymers have been extensively used as a better sorbent for extracting and determining the concentration of analytes. Polymers anchored or physisorbed on the respective magnetic core covering the nanoparticles from quick oxidation by forming a single or else double layer which acts as a shell structure over it. Mainly magnetic nanoparticles can be anchored on a polymer via covalent bonding or via electrostatic interaction. Usually, covalent bonding occurs in the case of molecularly imprinted polymers (MIPs) or by polypyrrole, whereas electrostatic interactions deal with biopolymers like chitosan, alignate etc.122–126 Ashtari et al. developed microparticles consisting of cross-linked poly acrylamide, acrylic acid trapped with charcoal and Fe3O4 nanoparticles in the weight ratio 1 : 1 : 1 functionalized with neocuproine for the preconcentration and removal of trace amounts of copper from water sources.127 Fabrication of chitosancoated octadecyl modified magnetic nanoparticles further coated with a layer of hydrophilic chitosan–tripolyphosphate polymer via ionotropic gelation are used for withdrawal of perfluorinated compounds and various phthalate esters from environmental samples.124,125 Fe3O4 coated with poly (divinyl benzene-co-methacrylic acid) microspheres have been used for the removal of estrogenic endocrine-disrupting chemicals from natural water sources which follows liquid chromatography tandem mass spectrometry analysis. The detection limit is obtained in the range 1 to 36 pg mL1. Recovery percentages for the analytes are calculated as 56 to 111%.128 Polypyyrole coated Fe3O4 microspheres were effectively used to extract and determine the amount of phthalates in water. The p–p bonding arising among polypyrrole and analytes makes the extraction simple, rapid and sensitive. The main merits found in these microspheres are large surface area, simple and quick separation capacity, etc. Moreover, the coating could hinder the aggregation of microspheres and enhance their dispersibility.129 Molecularly imprinted polymers (MIPs) attained significant attraction since they provide selective recognition sites for a template molecule depending on its size, structure and functional groups because they are tailormade for the target molecule. Molecularly imprinted polymer-modified magnetic materials are used as sorbents for efficient chiral separation of racemic tryptophan from aqueous media and the method is represented in Scheme 4.6.130 Subsequent to polymerization, templates are eliminated from the polymer which leaves specific sites that can selectively anchor molecules from the template depending on their size, shape as well as functionality. Chen et al. proposed a novel method to develop a magnetic sorbent made up of MIPs for the separation and determination of fluoroquinolones from environmental water sources. Herein, ciprofloxacin is used as the template molecule, cross-linking agent like ethylene glycol dimethacrylate and Fe3O4

102

Scheme 4.6

Chapter 4

Schematic representation of (a) the development of Fe3O4@MIPs and (b) the route of Fe3O4@MIPs-based SPE. Reproduced from ref. 130 with permission from Elsevier, Copyright 2020.

magnetic nanoparticles as a magnetic counterpart for the development of MIPs.131 Development of Fe3O4–polydopamine core–shell structures as magnetic sorbents in MSPE can be applied to quantify the traces of PAHs from environmental samples.132 Sulfonated polystyrene modified Fe3O4 nanoparticles prepared using the emulsion polymerization method can be applied for the detection of trace levels of seleno-amino acids and selenopeptide from almost 800 selenium-enriched yeast cells.133 Studies are carried out on the amalgamation of microparticle shaped polymeric Oasis MCX with cobalt ferrite nanoparticles for the determination of six nitroaromatic hydrocarbons in water by dispersive micro-solid-phase extraction.134 Fe3O4– C–polyaniline core–shell structured microspheres can be used as sorbents for extraction and determining the concentration of phenolic compounds from real water samples.135

Functionalized Magnetic Nanoparticles in Sample Pre-treatment

103

A rapid, simple and eco-friendly method using polyethylene glycol-modified magnetic covalent organic framework material based on the Schiff base reaction as the sorbent for the detection of benzoylurea pesticides has been developed.136 Fe3O4 magnetic nanoparticles coated by molecular imprinted polymer can act as an excellent adsorbent for the extraction of piroxicam from aqueous media. The sorbent material is synthesized via a surface imprinting method.137 Naphthalene-based polyimide polymer-modified Fe3O4 magnetic nanocomposite can be explored as the sorbent for extraction of Sudan dyes especially in chili sauce followed by HPLC determination.138 Zhang et al. prepared cationic polymer poly(acryloyloxyethyltrimethyl ammonium chloride) functionalized magnetic chitosan beads for a better adsorption of highly poisonous and non-biodegradable heavy metals and organic dyes over a wide pH range from wastewater.139 Moreover, various polymer-modified magnetite nanoparticles coated with SiO2 such as Fe3O4–SiO2–PMMA, Fe3O4–SiO2– P(MMA-co-VBC-co-DVB), and Fe3O4–SiO2–P(AMPS-co-EGDMA) act as an excellent adsorbent for MSPE.140–142

4.14 Extraction Techniques 4.14.1

Functionalized MNPs in Solid-Phase Extraction

The role of solid-phase extraction (SPE) is very relevant in the preparation of samples before determining the amount of analyte in the samples with an intricate composition, and has attained great interest recently since it is considered as a green technique for sample preparation. Pauliszyn and Arthur developed and applied this technique in practice in 1993.143 The various advantages offered by SPE techniques are: (i) easiness in operation, (ii) versatility, (ii) relatively low cost required for the apparatus, (iv) time required for extraction is much less, (v) absolute eradication of using organic solvents in the analytical steps, (vi) possibility to collect in situ as well as in vivo samples, (vii) possibility for complete automation of the procedure, and (viii) likely to desorb analytes directly from the fiber within a measuring system.4,144–146 The entire SPE equipment comprises a fused silica core or else a metal core which is coated with the aid of a thin layer of extraction medium and the fiber is placed within a needle of the syringe-type device. The extraction process is done by immersion of the fiber in the medium (liquid/gas) or otherwise by sampling of analytes from the headspace over the medium. Usually, the fiber is fixed in the interior of the injector of the measuring apparatus after the extraction. Research focused on widening technologies is ongoing in many scientific centers over the entire world for the generation of new materials showing high affinity for the analytes used for coating the fiber in SPE techniques. The synthesized sorbent should have the merits of high stability over the entire pH range, better mechanical and thermal resistance and high affinity toward the extracted analytes. Studies are concentrated on materials devoted to peculiar compounds showing high selectivity for some collection of analytes and also

104

Chapter 4

affinity toward one style of structure which can be used as a coating in SPE fibers. MIPs are used as sorbents for extracting analytes from different media like biological fluids, food and environmental samples.4,147–149 Ionic liquids can also be considered as extraction media due to their high selectivity and viscosity. Fiber coated with polymer Nafion and thereafter with an ionic liquid is used for removing polycyclic aromatic hydrocarbons (PAHs) from aqueous samples. Low durability of these types of sorbents can be replaced by the use of polymeric ionic liquids. Furthermore, ionic liquid coated fibers dealt with the extraction as well as preconcentration of a large variety of compounds like benzene, toluene, ethylbenzene, xylene, phenols, aromatic amines, esters, alcohols and the analysis of biological fluids.150–153 Owing to the high surface area, the high catalytic nature along with adsorption behavior, the nanomaterials carbon nanotubes are also used in SPE sorbents. The main advantages of these materials are that they possess mechanical and thermal stability, electrical and thermal conductivity and strong capacity to adsorb organic pollutants with a hydrophilic nature. Several works have been carried out on nanotubes coated with SPE fibers as sorbents to determine the amount of analytes such as pesticides, phenols, poly brominated diphenyl ethers, and pyrethroids in aqueous media as well as body fluid etc. Meanwhile, the modification of carbon nanotubes with carboxyl groups can enhance the polarity of the extraction layer which attracts highly polar analytes.154 Carbon nanotubes inserted into a polypropylene tube with the help of a sol–gel method is used for sampling Phenobarbital from wastewater. Poly(ethylene glycol)–MWCNT coated over fibers was reported for the sampling of non-steroid anti-inflammatory drugs.155 Their properties such as elasticity, low electrical resistance, and being 100 times stronger than steel, and translucent make graphene useful as a coating over SPE fibers to extract analytes. The graphene-coated SPE fibers are also used to extract several analytes such as pyrethroid pesticides, organo-chlorine pesticides, triazines, phenols, and PAH analytes. Mesoporous as well as nanoporous silicates with controlled morphology showing a high specific area, better mechanical and thermal strength used for coating SPE fibers are employed to determine the concentration of aromatic hydrocarbons as well as phenolic compounds from aqueous sources. Many silica-based nanocomposites such as MCM-41, and SBA-15 can be coated over a fiber for extraction purposes.156 Fibers firstly coated with silica material and again coated with an organic solvent can be used for the purpose of extraction of organophosphorous pesticides.157 The coating of metal nanoparticles like gold, silver, zinc oxide, titania oxide, and lead oxide via methods such as electroless plating, hydrothermal methods, and layer by layer self-assembly procedures can be applied to determine the amount of analytes such as phthalate esters, diphenyls, aldehydes, and BTEX.158–163 Another technique for the preparation of fibers is by producing physical separation involving the polar extraction medium and the sample for the analysis with the help of a membrane.164 The work carried out on twolayered poly(ethylene glycol) and poly(dimethyl siloxane) as the sorbent can

Functionalized Magnetic Nanoparticles in Sample Pre-treatment

105

be employed to extract phenols. Poly(dimethyl siloxane)/divinyl benzene composite coated over a fiber is used to find concentration of triazole pesticides from aqueous sources and grapes pulp.

4.14.2

Functionalized MNPs in Magnetic Solid-phase Extraction

The primary usage of nanoparticles with magnetic nature in SPE decreases the time duration and labor for the procedure by eliminating various steps in the extraction process. Magnetic solid-phase extraction (MSPE) shows many merits over traditional SPE techniques since the magnetic sorbent can be dispersed in the sample solution and hence enhances the interfacial area between the sorbent and sample. Magnetic nanoparticle sorbents applied for MSPE are generally nanometer-sized structures with excellent magnetism and allow the functionalization by various groups. These magnetic sorbents could be used for the separation and enrichment of analytes from a complex matrix like biological, environmental and food samples.165–168 Silica-coated magnetic materials are commonly used for bio-analytical purposes because of their physico-chemical behaviors. To overcome the limit of less stability in difficult conditions of strongly alkaline nature, inorganic and organic polymer coatings can be applied. Therefore, these MNPs can be employed for the separation, purification and immobilization of several biomolecules like ribonucleic acid (RNA), deoxyribonucleic acid (DNA) from bacteria, viruses and biological fluids.169–175 The benefits found in using MNPs in magnetic SPE for DNA extraction are (i) the reduction of extraction time required for the analytes, (ii) the reduction of usage of harmful reagents and (iii) automation. Research studies have also been reported on the separation, purification, and immobilization of proteins along with peptides using MNPs.176–179 This will allow the rapid and efficient extraction of peptides from samples and hence reduces the necessity of complicated steps. This type of work is mainly based on harmonic parts like antigen and antibody. For better extraction, the type of antibody and the type of magnetic nanoparticles should be fixed first. MNPs can separate inorganic along with organic compounds from complex biological samples such as blood, urine, saliva, bile, and sperm. Another field where MNPs are widely applicable is for the analysis of toxins in environmental samples. Magnetic nanoparticles coated with carbon are used for the analysis of PAHs. Besides this, MNPs can be used for isolation and extraction of metal ions, pesticides, dyes, surfactants, drugs and antibiotics, carcinogenic and mutagenic compounds, etc. The existence of chemical contaminants in food can be monitored and isolated using MNPs which arouse great interest due to their direct application in public health. The main challenge observed in this area is the lowering of the limit of detection of analytes in different food samples. There are also more works focused on applications of functionalized MNPs in MSPE to isolate contaminants like ochratoxin A, acetanilide herbicides, and pyrethroids from food samples.180–185

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4.15 Summary The progressive attempt to find, identify and estimate compounds available at very low trace levels in various samples with an apt level of sensitivity along with selectivity should be measured as the central strength that drives the effort of analytical chemists in the path of elaborating methods, including initial steps of isolation/enrichment of the target analytes. The utilization of magnetic nanomaterials in sample preparation plays a great role in analytical sciences due to its wide application in magnetic separation technology which simplifies sample pretreatment. Magnetic nanoparticles are generally used in the separation of various types of analytes from uncomplicated inorganic compounds to complicated biomolecules. Magnetic nanoparticles that undergo functionalization merge the merits of both magnetic particles as well as modified layers to form excellent adsorbents in SPE. The exceptional properties of MNPs like better surface-area-to-volume ratio offer very hopeful expectations for their use with better sensitivity and speedy extraction in this field. The incorporation of magnetic particles using other available nanomaterials, and the use of promising techniques for synthesis and functionalization of the materials and improvement of their physicochemical strength, duration, and selectivity are other possible areas of applications in this field.

Acknowledgements The present work was funded by DST-PURSE PII (SR. 417 & SR. 416 dated 27-2-2017). Sanu Mathew Simon thankfully acknowledges Mahatma Gandhi University, Kottayam, Kerala, India for providing the fellowship. The author Sajna M S acknowledges UGC for Dr. D.S Kothari Post-Doctoral Fellowship (F.4-2/2006 (BSR)/PH/18-19/0037). The author Twinkle Anna Jose is grateful to the University Grants Commission, Govt. of India for the award of the CSIR-UGC Junior Research fellowship.

References 1. X. S. Li, G. T. Zhu, Y. B. Luo, B. F. Yuan and Y. Q. Feng, Synthesis and applications of functionalized magnetic materials in sample preparation, TrAC, Trends Anal. Chem., 2013 Apr 1, 45, 233–247. 2. Z. Huang and H. K. Lee, Materials-based approaches to minimizing solvent usage in analytical sample preparation, TrAC, Trends Anal. Chem., 2012, 39, 228–244. 3. C. J. Welch, N. Wu, M. Biba, R. Hartman, T. Brkovic, X. Gong, R. Helmy, W. Schafer, J. Cuff, Z. Pirzada and L. Zhou, Greening analytical chromatography, TrAC, Trends Anal. Chem., 2010, 29(7), 667–680. 4. A. Spietelun, Ł. Marcinkowski, M. de la Guardia and J. Namies´nik, Recent developments and future trends in solid phase microextraction techniques towards green analytical chemistry, J. Chromatogr. A, 2013, 1321, 1–3.

Functionalized Magnetic Nanoparticles in Sample Pre-treatment

107

5. A. Henglein, Small-particle research: physicochemical properties of extremely small colloidal metal and semiconductor particles, Chem. Rev., 1989, 89(8), 1861–1873. 6. H. Bagheri, A. Afkhami, M. Saber-Tehrani and H. Khoshsafar, Preparation and characterization of magnetic nanocomposite of Schiff base/silica/magnetite as a preconcentration phase for the trace determination of heavy metal ions in water, food and biological samples using atomic absorption spectrometry, Talanta, 2012, 97, 87–95. 7. G. Giakisikli and A. N. Anthemidis, Magnetic materials as sorbents for metal/metalloid preconcentration and/or separation. A review, Anal. Chim. Acta, 2013, 789, 1–6. 8. H. H. Yang, S. Q. Zhang, X. L. Chen, Z. X. Zhuang, J. G. Xu and X. R. Wang, Magnetite-containing spherical silica nanoparticles for biocatalysis and bioseparations, Anal. Chem., 2004, 76(5), 1316–1321. 9. L. L. Vatta, R. D. Sanderson and K. R. Koch, Magnetic nanoparticles: Properties and potential applications, Pure Appl. Chem., 2006, 78(9), 1793–1801. 10. M. Faraji, Y. Yamini and M. Rezaee, Magnetic nanoparticles: synthesis, stabilization, functionalization, characterization, and applications, J. Iran. Chem. Soc., 2010, 7(1), 1–37. 11. U. Jeong, X. Teng, Y. Wang, H. Yang and Y. Xia, Superparamagnetic colloids: controlled synthesis and niche applications, Adv. Mater., 2007, 19(1), 33–60. ¨th, Magnetic nanoparticles: syn12. A. H. Lu, E. E. Salabas and F. Schu thesis, protection, functionalization, and application, Angew. Chem. Int. Ed., 2007, 46(8), 1222–1244. 13. W. S. Seo, H. H. Jo, K. Lee, B. Kim, S. J. Oh and J. T. Park, Sizedependent magnetic properties of colloidal Mn3O4 and MnO nanoparticles, Angew. Chem. Int. Ed., 2004, 43(9), 1115–1117. 14. T. Hyeon, S. S. Lee, J. Park, Y. Chung and H. B. Na, Synthesis of highly crystalline and monodisperse maghemite nanocrystallites without a size-selection process, J. Am. Chem. Soc., 2001, 123(51), 12798– 12801. 15. S. Sun and C. B. Murray, Synthesis of monodisperse cobalt nanocrystals and their assembly into magnetic superlattices, J. Appl. Phys., 1999, 85(8), 4325–4330. 16. J. Park, E. Kang, S. U. Son, H. M. Park, M. K. Lee, J. Kim, K. W. Kim, H. J. Noh, J. H. Park, C. J. Bae and J. G. Park, Monodisperse nanoparticles of Ni and NiO: synthesis, characterization, self-assembled superlattices, and catalytic applications in the Suzuki coupling reaction, Adv. Mater., 2005, 17(4), 429–434. 17. S. Sun, C. B. Murray, D. Weller, L. Folks and A. Moser, Monodisperse FePt nanoparticles and ferromagnetic FePt nanocrystal superlattices, Science, 2000, 287(5460), 1989–1992. 18. M. Chen and D. E. Nikles, Synthesis of spherical FePd and CoPt nanoparticles, J. Appl. Phys., 2002, 91(10), 8477–8479.

108

Chapter 4

19. J. Hu, G. Chen and I. M. Lo, Removal and recovery of Cr(VI) from wastewater by maghemite nanoparticles, Water Res., 2005, 39(18), 4528–4536. 20. J. Hu, I. M. Lo and G. Chen, Performance and mechanism of chromate(VI) adsorption by d-FeOOH-coated maghemite (g-Fe2O3) nanoparticles, Sep. Purif. Technol., 2007, 58(1), 76–82. 21. A. E. Karatapanis, D. E. Petrakis and C. D. Stalikas, A layered magnetic iron/iron oxide nanoscavenger for the analytical enrichment of ng-L1 concentration levels of heavy metals from water, Anal. Chim. Acta, 2012, 726, 22–27. 22. I. R. Harris and A. J. Williams, Material Science and Engineering, Vol. II, Magnetic Materials, I R Harris and A J Williams School of Metallurgy and Materials-University of Birmingham–Birmingham-UK, 2000. 23. A. Akbarzadeh, M. Samiei and S. Davaran, Magnetic nanoparticles: preparation, physical properties, and applications in biomedicine, Nanoscale Res. Lett., 2012, 7(1), 144. 24. P. J. Robinson, P. Dunnill and M. D. Lilly, The properties of magnetic supports in relation to immobilized enzyme reactors, Biotechnol. Bioeng., 1973, 15(3), 603–606. ¨m, S. Flygare, A. Gro ¨ndalen and P. O. Larsson, Magnetic 25. P. Wikstro aqueous two-phase separation: a new technique to increase rate of phase-separation, using dextran-ferrofluid or larger iron oxide particles, Anal. Biochem., 1987, 167(2), 331–339. 26. P. H. Towler, J. D. Smith and D. R. Dixon, Magnetic recovery of radium, lead and polonium from seawater samples after preconcentration on a magnetic adsorbent of manganese dioxide coated magnetite, Anal. Chim. Acta, 1996, 328(1), 53–59. ´ and I. ˇ 27. M. ˇ Safarˇ´kova ı Safarˇ´k, ı Magnetic solid-phase extraction, J. Magn. Magn. Mater., 1999, 194(1–3), 108–112. 28. K. Aguilar-Arteaga, J. A. Rodriguez and E. Barrado, Magnetic solids in analytical chemistry: a review, Anal. Chim. Acta, 2010, 674(2), 157–165. 29. L. Xie, R. Jiang, F. Zhu, H. Liu and G. Ouyang, Application of functionalized magnetic nanoparticles in sample preparation, Anal. Bioanal. Chem., 2014, 406(2), 377–399. 30. Y. Deng, D. Qi, C. Deng, X. Zhang and D. Zhao, Superparamagnetic high-magnetization microspheres with an Fe3O4@ SiO2 core and perpendicularly aligned mesoporous SiO2 shell for removal of microcystins, J. Am. Chem. Soc., 2008, 130(1), 28–29. ´n and M. E. Dı´az-Garcı´a, Synthesis and analytical 31. J. A. Garcı´a-Calzo potential of silica nanotubes, TrAC, Trends Anal. Chem., 2012, 35, 27–38. 32. L. Chen, T. Wang and J. Tong, Application of derivatized magnetic materials to the separation and the preconcentration of pollutants in water samples, TrAC, Trends Anal. Chem., 2011, 30(7), 1095–1108. 33. V. Strelko Jr., D. J. Malik and M. Streat, Interpretation of transition metal sorption behavior by oxidized active carbons and other adsorbents, Sep. Sci. Technol., 2005, 39(8), 1885–1905.

Functionalized Magnetic Nanoparticles in Sample Pre-treatment

109

34. J. Kim, J. E. Lee, J. Lee, J. H. Yu, B. C. Kim, K. An, Y. Hwang, C. H. Shin, J. G. Park, J. Kim and T. Hyeon, Magnetic fluorescent delivery vehicle using uniform mesoporous silica spheres embedded with monodisperse magnetic and semiconductor nanocrystals, J. Am. Chem. Soc., 2006, 128(3), 688–689. 35. A. Bagheri, M. Taghizadeh, M. Behbahani, A. A. Asgharinezhad, M. Salarian, A. Dehghani, H. Ebrahimzadeh and M. M. Amini, Synthesis and characterization of magnetic metal-organic framework (MOF) as a novel sorbent, and its optimization by experimental design methodology for determination of palladium in environmental samples, Talanta, 2012, 99, 132–139. 36. C. Huang and B. Hu, Silica-coated magnetic nanoparticles modified with g-mercaptopropyltrimethoxysilane for fast and selective solid phase extraction of trace amounts of Cd, Cu, Hg, and Pb in environmental and biological samples prior to their determination by inductively coupled plasma mass spectrometry, Spectrochim. Acta, Part B, 2008, 63(3), 437–444. 37. Y. B. Luo, Z. G. Shi, Q. Gao and Y. Q. Feng, Magnetic retrieval of graphene: extraction of sulfonamide antibiotics from environmental water samples, J. Chromatogr. A, 2011, 1218(10), 1353–1358. 38. A. Rios, M. Zougagh and M. Bouri, Magnetic (nano) materials as an useful tool for sample preparation in analytical methods. A review, Anal. Methods, 2013, 5(18), 4558–4573. 39. H. M. Jiang, Z. P. Yan, Y. Zhao, X. Hu and H. Z. Lian, Zinconimmobilized silica-coated magnetic Fe3O4 nanoparticles for solidphase extraction and determination of trace lead in natural and drinking waters by graphite furnace atomic absorption spectrometry, Talanta, 2012, 94, 251–256. 40. Y. Zhai, Q. He, X. Yang and Q. Han, Solid phase extraction and preconcentration of trace mercury (II) from aqueous solution using magnetic nanoparticles doped with 1, 5-diphenylcarbazide, Microchim. Acta, 2010, 169(3–4), 353–360. 41. S. H. Huo and X. P. Yan, Facile magnetization of metal–organic framework MIL-101 for magnetic solid-phase extraction of polycyclic aromatic hydrocarbons in environmental water samples, Analyst, 2012, 137(15), 3445–3451. 42. F. Bianchi, V. Chiesi, F. Casoli, P. Luches, L. Nasi, M. Careri and A. Mangia, Magnetic solid-phase extraction based on diphenyl functionalization of Fe3O4 magnetic nanoparticles for the determination of polycyclic aromatic hydrocarbons in urine samples, J. Chromatogr. A, 2012, 1231, 8–15. 43. H. R. Lotfi Zadeh Zhad, F. Aboufazeli, O. Sadeghi, V. Amani, E. Najafi and N. Tavassoli, Tris (2-Aminoethyl) Amine-Functionalized Fe3O4 magnetic nanoparticles as a selective sorbent for separation of silver and gold ions in different pHs, J. Chem., 2013, 2013, 482793.

110

Chapter 4

44. M. H. Mashhadizadeh and Z. Karami, Solid phase extraction of trace amounts of Ag, Cd, Cu, and Zn in environmental samples using magnetic nanoparticles coated by 3-(trimethoxysilyl)-1-propantiol and modified with 2-amino-5-mercapto-1, 3, 4-thiadiazole and their determination by ICP-OES, J. Hazard. Mater., 2011, 190(1–3), 1023–1029. 45. B. Tural, Separation and preconcentration of boron with a glucamine modified novel magnetic sorbent, Clean: Soil, Air, Water, 2010, 38(4), 321–327. 46. A. Mehdinia, S. Einollahi and A. Jabbari, Magnetite nanoparticles surface-modified with a zinc (II)-carboxylate Schiff base ligand as a sorbent for solid-phase extraction of organochlorine pesticides from seawater, Microchim. Acta, 2016, 183(9), 2615–2622. 47. S. Sadeghi, H. Azhdari, H. Arabi and A. Z. Moghaddam, Surface modified magnetic Fe3O4 nanoparticles as a selective sorbent for solid phase extraction of uranyl ions from water samples, J. Hazard. Mater., 2012, 215, 208–216. 48. M. H. Mashhadizadeh and M. Amoli-Diva, Atomic absorption spectrometric determination of Al31 and Cr31 after preconcentration and separation on 3-mercaptopropionic acid modified silica coated-Fe3O4 nanoparticles, J. Anal. At. Spectrom., 2013, 28(2), 251–258. 49. A. Mandil, L. Idrissi and A. Amine, Stripping voltammetric determination of mercury (II) and lead (II) using screen-printed electrodes modified with gold films, and metal ion preconcentration with thiolmodified magnetic particles, Microchim. Acta, 2010, 170(3–4), 299–305. 50. Y. Wang, T. Tian, L. Wang and X. Hu, Solid-phase preconcentration of cadmium (II) using amino-functionalized magnetic-core silica-shell nanoparticles, and its determination by hydride generation atomic fluorescence spectrometry, Microchim. Acta, 2013, 180(3–4), 235–242. 51. C. Huang, W. Xie, X. Li and J. Zhang, Speciation of inorganic arsenic in environmental waters using magnetic solid phase extraction and preconcentration followed by ICP-MS, Microchim. Acta, 2011, 173(1–2), 165–172. 52. C. Huang, W. Xie, X. Liu, J. Zhang, H. Xu, X. Li and Z. Liu, Highly sensitive method for speciation of inorganic selenium in environmental water by using mercapto-silica-Fe3O4 nanoparticles and ICP-MS, Anal. Methods, 2012, 4(11), 3824–3829. 53. Nanomaterials in Chromatography: Current Trends in Chromatographic Research Technology and Techniques, ed. C. M. Hussain, Elsevier, 2018. 54. D. J. Anderson, High-performance liquid chromatography (advances in packing materials), Anal. Chem., 1995, 67(12), 475–486. 55. J. G. Dorsey, W. T. Cooper, B. A. Siles, J. P. Foley and H. G. Barth, Liquid chromatography: Theory and methodology, Anal. Chem., 1996, 68(12), 515–568. 56. B. Maddah, A. Sabouri and M. Hasanzadeh, Magnetic Solid-Phase Extraction of Oxadiazon and Profenofos from Environmental Water

Functionalized Magnetic Nanoparticles in Sample Pre-treatment

57.

58.

59.

60.

61.

62.

63.

64.

65.

66.

111

Using Magnetite Fe3O4@ SiO2–C18 Nanoparticles, J. Polym. Environ., 2017, 25(3), 770–780. N. C. Lobato, A. de Mello Ferreira, P. G. Weidler, M. Franzreb, G. C. Silva and M. B. Mansur, Microstructure and chemical stability analysis of magnetic core coated with SILICA and functionalized with silane OTS, Appl. Surf. Sci., 2020, 505, 144565. ´rez-Quintanilla, S. Morante-Zarcero and I. Sierra, EvaluN. Casado, D. Pe ation of bi-functionalized mesoporous silicas as reversed phase/cationexchange mixed-mode sorbents for multi-residue solid phase extraction of veterinary drug residues in meat samples, Talanta, 2017, 165, 223–230. Y. Sha, C. Deng and B. Liu, Development of C18-functionalized magnetic silica nanoparticles as sample preparation technique for the determination of ergosterol in cigarettes by microwave-assisted derivatization and gas chromatography/mass spectrometry, J. Chromatogr. A, 2008, 1198, 27–33. ´rdenas, Z. Qiao, R. Perestrelo, E. M. Reyes-Gallardo, R. Lucena, S. Ca ˆmara, Octadecyl functionalized core–shell magJ. Rodrigues and J. S. Ca netic silica nanoparticle as a powerful nanocomposite sorbent to extract urinary volatile organic metabolites, J. Chromatogr. A, 2015, 1393, 18–25. M. E. Synaridou, V. A. Sakkas, C. D. Stalikas and T. A. Albanis, Evaluation of magnetic nanoparticles to serve as solid-phase extraction sorbents for the determination of endocrine disruptors in milk samples by gas chromatography mass spectrometry, J. Chromatogr. A, 2014, 1348, 71–79. B. Maddah and J. Shamsi, Extraction and preconcentration of trace amounts of diazinon and fenitrothion from environmental water by magnetite octadecylsilane nanoparticles, J. Chromatogr. A, 2012, 1256, 40–45. F. Ahmadi, M. Rajabi, F. Faizi, M. Rahimi-Nasrabadi and B. Maddah, Magnetic solid-phase extraction of Zineb by C18-functionalised paramagnetic nanoparticles and determination by first-derivative spectrophotometry, Int. J. Environ. Anal. Chem., 2014, 94(11), 1123–1138. H. Zhang, Q. S. Liu, C. L. Yang, J. Z. Lv, L. Q. Xie, M. J. Tang, Z. F. Yue and Z. G. Wan, C 18/C 8-functionalized magnetic silica nanospheres (Fe3O4@ Si-C8/C18) as capture probes for highly efficient and rapid purification of veterinary drug residues, Food Analytical Methods, 2013, 6(3), 933–940. N. B. Caon, C. dos Santos Cardoso, F. L. Faita, L. Vitali and A. L. Parize, Magnetic solid-phase extraction of triclosan from water using n-octadecyl modified silica-coated magnetic nanoparticles, J. Environ. Chem. Eng., 2020, 104003. P. Yu, Q. Wang, X. Zhang, X. Zhang, S. Shen and Y. Wang, Development of superparamagnetic high-magnetization C18-functionalized magnetic silica nanoparticles as sorbents for enrichment and determination of methylprednisolone in rat plasma by high performance liquid chromatography, Anal. Chim. Acta, 2010, 678(1), 50–55.

112

Chapter 4

67. B. Chu, D. Lou, P. Yu, S. Hu and S. Shen, Development of an on-column enrichment technique based on C18-functionalized magnetic silica nanoparticles for the determination of lidocaine in rat plasma by high performance liquid chromatography, J. Chromatogr. A, 2011, 1218(41), 7248–7253. 68. Q. Wang, L. Huang, P. Yu, J. Wang and S. Shen, Magnetic solid-phase extraction and determination of puerarin in rat plasma using C18-functionalized magnetic silica nanoparticles by high performance liquid chromatography, J. Chromatogr. B, 2013, 912, 33–37. 69. J. Ma, F. Yan, F. Chen, L. Jiang, J. Li and L. Chen, C18-functionalized magnetic silica nanoparticles for solid phase extraction of microcystinLR in reservoir water samples followed by HPLC-DAD determination, J. Liq. Chromatogr. Relat. Technol., 2015, 38(6), 655–661. 70. Z. Li, D. Huang, C. Fu, B. Wei, W. Yu, C. Deng and X. Zhang, Preparation of magnetic core mesoporous shell microspheres with C18-modified interior pore-walls for fast extraction and analysis of phthalates in water samples, J. Chromatogr. A, 2011, 1218(37), 6232–6239. 71. H. Y. Niu, W. H. Li, Y. L. Shi and Y. Q. Cai, A core–shell magnetic mesoporous silica sorbent for organic targets with high extraction performance and anti-interference ability, Chem. Commun., 2011, 47(15), 4454–4456. 72. X. Zhang, H. Niu, Y. Pan, Y. Shi and Y. Cai, Modifying the surface of Fe3O4/SiO2 magnetic nanoparticles with C18/NH2 mixed group to get an efficient sorbent for anionic organic pollutants, J. Colloid Interface Sci., 2011, 362(1), 107–112. 73. C. Jiang, Y. Sun, X. Yu, L. Zhang, X. Sun, Y. Gao, H. Zhang and D. Song, Removal of sudan dyes from water with C18-functional ultrafine magnetic silica nanoparticles, Talanta, 2012 Jan 30, 89, 38–46. ¨hlich, E. L. Foletto and G. L. Dotto, Preparation and charac74. A. C. Fro terization of NiFe2O4/activated carbon composite as potential magnetic adsorbent for removal of ibuprofen and ketoprofen pharmaceuticals from aqueous solutions, J. Cleaner Prod., 2019 Aug 20, 229, 828–837. 75. S. C. Rodrigues, M. C. Silva, J. A. Torres and M. L. Bianchi, Use of Magnetic Activated Carbon in a Solid Phase Extraction Procedure for Analysis of 2, 4-dichlorophenol in Water Samples, Water, Air, Soil Pollut., 2020, 231, 1–3. 76. H. Shokry, M. Elkady and E. Salama, Eco-friendly magnetic activated carbon nano-hybrid for facile oil spills separation, Sci. Rep., 2020, 10(1), 1–7. 77. F. M. Marsin, W. A. Ibrahim, H. R. Nodeh and M. M. Sanagi, New magnetic oil palm fiber activated carbon-reinforced polypyrrole solid phase extraction combined with gas chromatography-electron capture detection for determination of organochlorine pesticides in water samples, J. Chromatogr. A, 2020, 1612, 460638. 78. G. P. Mashile, A. Mpupa, A. Nqombolo, K. M. Dimpe and P. N. Nomngongo, Recyclable magnetic waste tyre activated carbonchitosan composite as an effective adsorbent rapid and simultaneous

Functionalized Magnetic Nanoparticles in Sample Pre-treatment

79.

80.

81.

82.

83.

84.

85.

86.

87.

88.

89.

113

removal of methylparaben and propylparaben from aqueous solution and wastewater, J. Water Process Eng., 2020, 33, 101011. S. Zhang, H. Niu, Z. Hu, Y. Cai and Y. Shi, Preparation of carbon coated Fe3O4 nanoparticles and their application for solid-phase extraction of polycyclic aromatic hydrocarbons from environmental water samples, J. Chromatogr. A, 2010, 1217(29), 4757–4764. L. Bai, B. Mei, Q. Z. Guo, Z. G. Shi and Y. Q. Feng, Magnetic solid-phase extraction of hydrophobic analytes in environmental samples by a surface hydrophilic carbon-ferromagnetic nanocomposite, J. Chromatogr. A, 2010, 1217(47), 7331–7336. F. Yang, J. Wang, Y. Li, S. Xie, C. Chen, Q. Cai and S. Yao, Application of magnetic material in the determination of polycyclic aromatic hydrocarbons in tree leaves by high performance liquid chromatography, Anal. Methods, 2011, 3(12), 2909–2914. H. Heidari and H. Razmi, Multi-response optimization of magnetic solid phase extraction based on carbon coated Fe3O4 nanoparticles using desirability function approach for the determination of the organophosphorus pesticides in aquatic samples by HPLC–UV, Talanta, 2012, 99, 13–21. H. Heidari, H. Razmi and A. Jouyban, Preparation and characterization of ceramic/carbon coated Fe3O4 magnetic nanoparticle nanocomposite as a solid-phase microextraction adsorbent, J. Chromatogr. A, 2012, 1245, 1–7. J. Huo, H. Song and X. Chen, Preparation of carbon-encapsulated iron nanoparticles by co-carbonization of aromatic heavy oil and ferrocene, Carbon, 2004, 42(15), 3177–3182. H. Niu, Y. Wang, X. Zhang, Z. Meng and Y. Cai, Easy synthesis of surface-tunable carbon-encapsulated magnetic nanoparticles: adsorbents for selective isolation and preconcentration of organic pollutants, ACS Appl. Mater. Interfaces, 2012, 4(1), 286–295. ´llez-Gomis, J. Grau, J. L. Benede ´, A. Chisvert and A. Salvador, V. Va Reduced graphene oxide-based magnetic composite for trace determination of polycyclic aromatic hydrocarbons in cosmetics by stir bar sorptive dispersive microextraction, J. Chromatogr. A, 2020, 461229. A. E. Oral, S. Aytas, S. Yusan, S. Sert, C. Gok, Elmastas and O. Gultekin, Preparation and Characterization of a Graphene-Based Magnetic Nanocomposite for the Adsorption of Lanthanum Ions from Aqueous Solution, Anal. Lett., 2020, 53(11), 1812–1833. H. Seema, Novel self assembled magnetic Prussian blue graphene based aerogel for highly selective removal of radioactive cesium in water, Arabian J. Chem., 2020, 13(2), 4417–4424. F. N. Ferreira, A. P. Benevides, D. V. Cesar, A. S. Luna and J. S. de Gois, Magnetic solid-phase extraction and pre-concentration of 17b-estradiol and 17a-ethinylestradiol in tap water using maghemite-graphene oxide nanoparticles and determination using HPLC with fluorescence detector, Microchem. J., 2020, 104947.

114

Chapter 4

90. N. Mehrabi, U. F. Haq, M. T. Reza and N. Aich, Application of Deep Eutectic Solvent for Conjugation of Magnetic Nanoparticles onto Graphene Oxide for Lead (II) and Methylene Blue Removal, J. Environ. Chem. Eng., 2020, 104222. ˘lu, D. S. Chormey and S. Bakırdere, A 91. M. F. Ayyıldız, M. S. Fındıkog simple and efficient preconcentration method based on vortex assisted reduced graphene oxide magnetic nanoparticles for the sensitive determination of endocrine disrupting compounds in different water and baby food samples by GC-FID, J. Food Compos. Anal., 2020, 88, 103431. 92. X. Ma, J. Wang, M. Sun, W. Wang, Q. Wu, C. Wang and Z. Wang, Magnetic solid-phase extraction of neonicotinoid pesticides from pear and tomato samples using graphene grafted silica-coated Fe3O4 as the magnetic adsorbent, Anal. Methods, 2013, 5(11), 2809–2815. 93. Q. Wu, G. Zhao, C. Feng, C. Wang and Z. Wang, Preparation of a graphene-based magnetic nanocomposite for the extraction of carbamate pesticides from environmental water samples, J. Chromatogr. A, 2011, 1218(44), 7936–7942. 94. C. Wang, C. Feng, Y. Gao, X. Ma, Q. Wu and Z. Wang, Preparation of a graphene-based magnetic nanocomposite for the removal of an organic dye from aqueous solution, Chem. Eng. J., 2011, 173(1), 92–97. 95. G. Zhao, S. Song, C. Wang, Q. Wu and Z. Wang, Determination of triazine herbicides in environmental water samples by highperformance liquid chromatography using graphene-coated magnetic nanoparticles as adsorbent, Anal. Chim. Acta, 2011, 708(1–2), 155–159. 96. Z. Li, S. Bai, M. Hou, C. Wang and Z. Wang, Magnetic graphene nanoparticles for the preconcentration of chloroacetanilide herbicides from water samples prior to determination by GC-ECD, Anal. Lett., 2013, 46(6), 1012–1024. 97. W. Wang, X. Ma, Q. Wu, C. Wang, X. Zang and Z. Wang, The use of graphene-based magnetic nanoparticles as adsorbent for the extraction of triazole fungicides from environmental water, J. Sep. Sci., 2012, 35(17), 2266–2272. ˜ a98. C. Herrero-Latorre, J. Barciela-Garcı´a, S. Garcı´a-Martı´n, R. M. Pen ´rola-Jime ´nez, Magnetic solid-phase extraction Crecente and J. Ota using carbon nanotubes as sorbents: a review, Anal. Chim. Acta, 2015, 892, 10–26. ´s, E. Gionfriddo, G. A. Go ´mez-Rı´os, M. N. Alam, 99. N. Reyes-Garce E. Boyacı, B. Bojko, V. Singh, J. Grandy and J. Pawliszyn, Advances in solid phase microextraction and perspective on future directions, Anal. Chem., 2017, 90(1), 302–360. 100. A. Speltini, M. Sturini, F. Maraschi and A. Profumo, Recent trends in the application of the newest carbonaceous materials for magnetic solid-phase extraction of environmental pollutants, Trends Environ. Anal. Chem., 2016, 10, 11–23. 101. R. Ni, Y. Wang, X. Wei, J. Chen, J. Meng, F. Xu, Z. Liu and Y. Zhou, Magnetic carbon nanotube modified with polymeric deep eutectic

Functionalized Magnetic Nanoparticles in Sample Pre-treatment

102.

103.

104.

105.

106.

107.

108.

109.

110.

111.

112.

115

solvent for the solid phase extraction of bovine serum albumin, Talanta, 2020, 206, 120215. A. C. do Lago, M. H. da Silva Cavalcanti, M. A. Rosa, A. T. Silveira, C. R. Tarley and E. C. Figueiredo, Magnetic restricted-access carbon nanotubes for dispersive solid phase extraction of organophosphates pesticides from bovine milk samples, Anal. Chim. Acta, 2020, 1102, 11–23. ˜alver-Soler, N. Campillo and P. Vin ˜as, N. Arroyo-Manzanares, R. Pen Dispersive Solid-Phase Extraction using Magnetic Carbon Nanotube Composite for the Determination of Emergent Mycotoxins in Urine Samples, Toxins, 2020, 12(1), 51. Q. Wang, X. Wu, Y. Zhang, M. Hu, J. Chen, J. Gao and Y. Cheng, Preparation of a Magnetic Multiwalled Carbon Nanotube-Gold Nanoparticle Hybrid Material for the Efficient Extraction of Triazine Herbicides from Rice, Anal. Lett., 2020, 1–7. W. Wu, F. Lin, X. Yang, B. Wang, X. Lu, Q. Chen, F. Ye and S. Zhao, Facile synthesis of magnetic carbon nanotubes derived from ZIF-67 and application to magnetic solid-phase extraction of profens from human serum, Talanta, 2020, 207, 120284. ´. Rı´os and M. Zougagh, LC-MS ´s, I. Galva ´n, A K. Murtada, F. de Andre determination of catecholamines and related metabolites in red deer urine and hair extracted using magnetic multi-walled carbon nanotube poly (styrene-co-divinylbenzene) composite, J. Chromatogr. B, 2020, 1136, 121878. ¨ lmez and M. Soylak, Cu2O-CuO ball like/ F. Aydin, E. Yilmaz, E. O multiwalled carbon nanotube hybrid for fast and effective ultrasoundassisted solid phase extraction of uranium at ultra-trace level prior to ICP-MS detection, Talanta, 2020, 207, 120295. T. Saitoh, Y. Nakayama and M. Hiraide, Concentration of chlorophenols in water with sodium dodecylsulfate–g-alumina admicelles for high-performance liquid chromatographic analysis, J. Chromatogr. A, 2002, 972(2), 205–209. ´rez-Bendito, Evaluation and optimization F. Merino, S. Rubio and D. Pe of an on-line admicelle-based extraction-liquid chromatography approach for the analysis of ionic organic compounds, Anal. Chem., 2004, 76(14), 3878–3886. X. Zhao, Y. Shi, T. Wang, Y. Cai and G. Jiang, Preparation of silica-magnetite nanoparticle mixed hemimicelle sorbents for extraction of several typical phenolic compounds from environmental water samples, J. Chromatogr. A, 2008, 1188(2), 140–147. ´rez-Bendito, Determination of alkylM. Cantero, S. Rubio and D. Pe phenols and alkylphenol carboxylates in wastewater and river samples by hemimicelle-based extraction and liquid chromatography–ion trap mass spectrometry, J. Chromatogr. A, 2006, 1120(1–2), 260–267. ´rez-Bendito, Sodium dodecyl A. Moral, M. D. Sicilia, S. Rubio and D. Pe sulphate-coated alumina for the extraction/preconcentration of benzimidazolic fungicides from natural waters prior to their quantification

116

113.

114.

115.

116.

117.

118.

119.

120.

121.

122.

Chapter 4

by liquid chromatography/fluorimetry, Anal. Chim. Acta, 2006, 569(1–2), 132–138. X. Zhao, J. Li, Y. Shi, Y. Cai, S. Mou and G. Jiang, Determination of perfluorinated compounds in wastewater and river water samples by mixed hemimicelle-based solid-phase extraction before liquid chromatography–electrospray tandem mass spectrometry detection, J. Chromatogr. A, 2007, 1154(1–2), 52–59. J. Li, X. Zhao, Y. Shi, Y. Cai, S. Mou and G. Jiang, Mixed hemimicelles solid-phase extraction based on cetyltrimethylammonium bromidecoated nano-magnets Fe3O4 for the determination of chlorophenols in environmental water samples coupled with liquid chromatography/ spectrophotometry detection, J. Chromatogr. A, 2008, 1180(1–2), 24– 31. X. Zhao, Y. Shi, Y. Cai and S. Mou, Cetyltrimethylammonium bromidecoated magnetic nanoparticles for the preconcentration of phenolic compounds from environmental water samples, Environ. Sci. Technol., 2008, 42(4), 1201–1206. A. E. Karatapanis, Y. Fiamegos and C. D. Stalikas, Silica-modified magnetic nanoparticles functionalized with cetylpyridinium bromide for the preconcentration of metals after complexation with 8-hydroxyquinoline, Talanta, 2011, 84(3), 834–839. L. Sun, C. Zhang, L. Chen, J. Liu, H. Jin, H. Xu and L. Ding, Preparation of alumina-coated magnetite nanoparticle for extraction of trimethoprim from environmental water samples based on mixed hemimicelles solid-phase extraction, Anal. Chim. Acta, 2009, 638(2), 162–168. L. Sun, L. Chen, X. Sun, X. Du, Y. Yue, D. He, H. Xu, Q. Zeng, H. Wang and L. Ding, Analysis of sulfonamides in environmental water samples based on magnetic mixed hemimicelles solid-phase extraction coupled with HPLC–UV detection, Chemosphere, 2009, 77(10), 1306–1312. Q. Cheng, F. Qu, N. B. Li and H. Q. Luo, Mixed hemimicelles solid-phase extraction of chlorophenols in environmental water samples with 1-hexadecyl-3-methylimidazolium bromide-coated Fe3O4 magnetic nanoparticles with high-performance liquid chromatographic analysis, Anal. Chim. Acta, 2012, 715, 113–119. W. Guo, Z. Fu, Z. Zhang, H. Wang, S. Liu, W. Feng, X. Zhao and J. P. Giesy, Synthesis of Fe3O4 magnetic nanoparticles coated with cationic surfactants and their applications in Sb (V) removal from water, Sci. Total Environ, 2020, 710, 136302. F. I. El-Dib, D. E. Mohamed, O. A. El-Shamy and M. R. Mishrif, Study the adsorption properties of magnetite nanoparticles in the presence of different synthesized surfactants for heavy metal ions removal, Egypt. J. Petrol., 2020, 29(1), 1–7. X. Zhang, H. Niu, Y. Pan, Y. Shi and Y. Cai, Chitosan-coated octadecylfunctionalized magnetite nanoparticles: preparation and application in extraction of trace pollutants from environmental water samples, Anal. Chem., 2010, 82(6), 2363–2371.

Functionalized Magnetic Nanoparticles in Sample Pre-treatment

117

123. Y. Geng, M. Ding, H. Chen, H. F. Li and J. M. Lin, Preparation of hydrophilic carbon-functionalized magnetic microspheres coated with chitosan and application in solid-phase extraction of bisphenol A in aqueous samples, Talanta, 2012, 89, 189–194. 124. H. F. Zhang and Y. P. Shi, Magnetic retrieval of chitosan: Extraction of bioactive constituents from green tea beverage samples, Analyst, 2012, 137(4), 910–916. 125. X. Le Zhang, H. Y. Niu, S. X. Zhang and Y. Q. Cai, Preparation of a chitosan-coated C 18-functionalized magnetite nanoparticle sorbent for extraction of phthalate ester compounds from environmental water samples, Anal. Bioanal. Chem., 2010, 397(2), 791–798. 126. S. Zhang, H. Niu, Y. Cai and Y. Shi, Barium alginate caged Fe3O4@ C18 magnetic nanoparticles for the pre-concentration of polycyclic aromatic hydrocarbons and phthalate esters from environmental water samples, Anal. Chim. Acta, 2010, 665(2), 167–175. 127. P. Ashtari, K. Wang, X. Yang, S. Huang and Y. Yamini, Novel separation and preconcentration of trace amounts of copper(II) in water samples based on neocuproine modified magnetic microparticles, Anal. Chim. Acta, 2005, 550(1–2), 18–23. 128. Q. Li, M. H. Lam, R. S. Wu and B. Jiang, Rapid magnetic-mediated solid-phase extraction and pre-concentration of selected endocrine disrupting chemicals in natural waters by poly (divinylbenzene-comethacrylic acid) coated Fe3O4 core-shell magnetite microspheres for their liquid chromatography–tandem mass spectrometry determination, J. Chromatogr. A, 2010, 1217(8), 1219–1226. 129. J. Meng, J. Bu, C. Deng and X. Zhang, Preparation of polypyrrole-coated magnetic particles for micro solid-phase extraction of phthalates in water by gas chromatography–mass spectrometry analysis, J. Chromatogr. A, 2011, 1218(12), 1585–1591. 130. Y. Liu, Z. Li and L. Jia, Synthesis of molecularly imprinted polymer modified magnetic particles for chiral separation of tryptophan enantiomers in aqueous medium, J. Chromatogr. A, 2020, 461147. 131. L. Chen, X. Zhang, Y. Xu, X. Du, X. Sun, L. Sun, H. Wang, Q. Zhao, A. Yu, H. Zhang and L. Ding, Determination of fluoroquinolone antibiotics in environmental water samples based on magnetic molecularly imprinted polymer extraction followed by liquid chromatography–tandem mass spectrometry, Anal. Chim. Acta, 2010, 662(1), 31–38. 132. Y. Wang, S. Wang, H. Niu, Y. Ma, T. Zeng, Y. Cai and Z. Meng, Preparation of polydopamine coated Fe3O4 nanoparticles and their application for enrichment of polycyclic aromatic hydrocarbons from environmental water samples, J. Chromatogr. A, 2013, 1283, 20–26. 133. B. Chen, B. Hu, M. He, Q. Huang, Y. Zhang and X. Zhang, Speciation of selenium in cells by HPLC-ICP-MS after (on-chip) magnetic solid phase extraction, J. Anal. At. Spectrom., 2013, 28(3), 334–343. ´s, R. Lucena, S. Ca ´rdenas and 134. E. M. Reyes-Gallardo, G. Lasarte-Aragone ´rcel, Hybridization of commercial polymeric microparticles M. Valca

118

135.

136.

137.

138.

139.

140.

141.

142.

143.

144.

145.

146.

Chapter 4

and magnetic nanoparticles for the dispersive micro-solid phase extraction of nitroaromatic hydrocarbons from water, J. Chromatogr. A, 2013, 1271(1), 50–55. J. Meng, C. Shi, B. Wei, W. Yu, C. Deng and X. Zhang, Preparation of Fe3O4@ C@ PANI magnetic microspheres for the extraction and analysis of phenolic compounds in water samples by gas chromatography– mass spectrometry, J. Chromatogr. A, 2011, 1218(20), 2841–2847. J. Fan, Z. Liu, J. Li, W. Zhou, H. Gao, S. Zhang and R. Lu, PEG-modified magnetic Schiff base network-1 materials for the magnetic solid phase extraction of benzoylurea pesticides from environmental water samples, J. Chromatogr. A, 2020, 460950. M. Rezaei, H. R. Rajabi and Z. Rafiee, Selective and rapid extraction of piroxicam from water and plasma samples using magnetic imprinted polymeric nanosorbent: Synthesis, characterization and application, Colloids Surf., A, 2020, 586, 124253. K. Hu, J. Qiao, W. Zhu, X. Chen and C. Dong, Magnetic naphthalenebased polyimide polymer for extraction of Sudan dyes in chili sauce, Microchem. J., 2019, 149, 104073. M. Zhang, Z. Zhang, Y. Peng, L. Feng, X. Li, C. Zhao and H. Zheng, Novel cationic polymer modified magnetic chitosan beads for efficient adsorption of heavy metals and dyes over a wide pH range, Int. J. Biol. Macromol., 2020, 156, 289–301. H. Chen, C. Deng and X. Zhang, Synthesis of Fe3O4@ SiO2@ PMMA core–shell–shell magnetic microspheres for highly efficient enrichment of peptides and proteins for MALDI-ToF MS analysis, Angew. Chem. Int. Ed., 2010, 49(3), 607–611. Q. Gao, C. Y. Lin, D. Luo, L. L. Suo, J. L. Chen and Y. Q. Feng, Magnetic solid-phase extraction using magnetic hypercrosslinked polymer for rapid determination of illegal drugs in urine, J. Sep. Sci., 2011, 34(21), 3083–3091. Z. Liu, B. D. Cai and Y. Q. Feng, Rapid determination of endogenous cytokinins in plant samples by combination of magnetic solid phase extraction with hydrophilic interaction chromatography–tandem mass spectrometry, J. Chromatogr. B, 2012, 891, 27–35. C. L. Arthur and J. Pawliszyn, Solid phase microextraction with thermal desorption using fused silica optical fibers, Anal. Chem., 1990, 62(19), 2145–2148. X. Zhang, K. D. Oakes, S. Wang, M. R. Servos, S. Cui, J. Pawliszyn and C. D. Metcalfe, In vivo sampling of environmental organic contaminants in fish by solid-phase microextraction, TrAC, Trends Anal. Chem., 2012, 32, 31–39. H. Kataoka, Current developments and future trends in solid-phase microextraction techniques for pharmaceutical and biomedical analyses, Anal. Sci., 2011, 27(9), 893. F. Zhu, J. Xu, Y. Ke, S. Huang, F. Zeng, T. Luan and G. Ouyang, Applications of in vivo and in vitro solid-phase microextraction

Functionalized Magnetic Nanoparticles in Sample Pre-treatment

147.

148.

149.

150. 151.

152.

153.

154.

155.

156.

157.

119

techniques in plant analysis: A review, Anal. Chim. Acta, 2013, 794, 1–4. X. Hu, J. Pan, Y. Hu and G. Li, Preparation and evaluation of propranolol molecularly imprinted solid-phase microextraction fiber for trace analysis of b-blockers in urine and plasma samples, J. Chromatogr. A, 2009, 1216(2), 190–197. L. Qiu, W. Liu, M. Huang and L. Zhang, Preparation and application of solid-phase microextraction fiber based on molecularly imprinted polymer for determination of anabolic steroids in complicated samples, J. Chromatogr. A, 2010, 1217(48), 7461–7470. J. He, R. Lv, H. Zhan, H. Wang, J. Cheng, K. Lu and F. Wang, Preparation and evaluation of molecularly imprinted solid-phase micro-extraction fibers for selective extraction of phthalates in an aqueous sample, Anal. Chim. Acta, 2010, 674(1), 53–58. R. Liu, J. F. Liu, Y. G. Yin, X. L. Hu and G. B. Jiang, Ionic liquids in sample preparation, Anal. Bioanal. Chem., 2009, 393(3), 871–883. ´pez-Darias, V. Pino, Y. Meng, J. L. Anderson and A. M. Afonso, J. Lo Utilization of a benzyl functionalized polymeric ionic liquid for the sensitive determination of polycyclic aromatic hydrocarbons; parabens and alkylphenols in waters using solid-phase microextraction coupled to gas chromatography–flame ionization detection, J. Chromatogr. A, 2010, 1217(46), 7189–7197. ´lez and A. M. Afonso, Ionic liA. Martı´n-Calero, J. H. Ayala, V. Gonza quids as desorption solvents and memory effect suppressors in heterocyclic aromatic amines determination by SPME–HPLC fluorescence, Anal. Bioanal. Chem., 2009, 394(4), 937–946. Y. Meng, V. Pino and J. L. Anderson, Exploiting the versatility of ionic liquids in separation science: Determination of low-volatility aliphatic hydrocarbons and fatty acid methyl esters using headspace solid-phase microextraction coupled to gas chromatography, Anal. Chem., 2009, 81(16), 7107–7112. X. Liu, Y. Ji, Y. Zhang, H. Zhang and M. Liu, Oxidized multiwalled carbon nanotubes as a novel solid-phase microextraction fiber for determination of phenols in aqueous samples, J. Chromatogr. A, 2007, 1165(1–2), 10–17. A. Sarafraz-Yazdi, A. Amiri, G. Rounaghi and H. Eshtiagh-Hosseini, Determination of non-steroidal anti-inflammatory drugs in water samples by solid-phase microextraction based sol–gel technique using poly (ethylene glycol) grafted multi-walled carbon nanotubes coated fiber, Anal. Chim. Acta, 2012, 720, 134–141. M. B. Gholivand, M. M. Abolghasemi and P. Fattahpour, Polypyrrole/ hexagonally ordered silica nanocomposite as a novel fiber coating for solid-phase microextraction, Anal. Chim. Acta, 2011, 704(1–2), 174– 179. M. Saraji and B. Farajmand, Microporous silica with nanolayer structure coated with renewable organic solvent film as a novel extracting

120

158.

159.

160.

161.

162.

163.

164.

165. 166. 167.

168.

169.

170.

171.

Chapter 4

phase: a combination of solid-and liquid-phase microextraction, Anal. Chim. Acta, 2012, 721, 61–67. J. Feng, M. Sun, H. Liu, J. Li, X. Liu and S. Jiang, Au nanoparticles as a novel coating for solid-phase microextraction, J. Chromatogr. A, 2010, 1217(52), 8079–8086. J. Feng, M. Sun, J. Li, X. Liu and S. Jiang, A novel silver-coated solid-phase microextraction metal fiber based on electroless plating technique, Anal. Chim. Acta, 2011, 701(2), 174–180. R. Alizadeh, N. M. Najafi and S. Kharrazi, A new solid phase micro extraction for simultaneous head space extraction of ultra traces of polar and non-polar compounds, Anal. Chim. Acta, 2011, 689(1), 117–121. J. Ji, H. Liu, J. Chen, J. Zeng, J. Huang, L. Gao, Y. Wang and X. Chen, ZnO nanorod coating for solid phase microextraction and its applications for the analysis of aldehydes in instant noodle samples, J. Chromatogr. A, 2012, 1246, 22–27. ¨, J. F. Liu and G. B. Jiang, In situ fabrication of D. D. Cao, J. X. Lu nanostructured titania coating on the surface of titanium wire: a new approach for preparation of solid-phase microextraction fiber, Anal. Chim. Acta, 2008, 611(1), 56–61. A. Mehdinia, M. F. Mousavi and M. Shamsipur, Nano-structured lead dioxide as a novel stationary phase for solid-phase microextraction, J. Chromatogr. A, 2006, 1134(1–2), 24–31. A. Kloskowski, M. Pilarczyk and J. Namies´nik, Membrane Solid-Phase Microextraction A New Concept of Sorbent Preparation, Anal. Chem., 2009, 81(17), 7363–7367. Nanomaterials in Chromatography: Current Trends in Chromatographic Research Technology and Techniques, ed. C. M. Hussain, Elsevier, 2018. C. M. Hussain and R. Kecili, Modern Environmental Analysis Techniques for Pollutants, Elsevier, 2019. ¨yu ¨ktiryaki, R. Keçili and C. M. Hussain, Functionalized NanoS. Bu materials in Dispersive Solid Phase Extraction: Advances & Prospects, TrAC, Trends Anal. Chem., 2020, 115893. T. R. Sarkar and J. Irudayaraj, Carboxyl-coated magnetic nanoparticles for mRNA isolation and extraction of supercoiled plasmid DNA, Anal. Biochem., 2008, 379(1), 130–132. C. L. Chiang, C. S. Sung, T. F. Wu, C. Y. Chen and C. Y. Hsu, Application of superparamagnetic nanoparticles in purification of plasmid DNA from bacterial cells, J. Chromatogr. B, 2005, 822(1–2), 54–60. Z. Shan, X. Li, Y. Gao, X. Wang, C. Li and Q. Wu, Application of magnetic hydroxyapatite nanoparticles for solid phase extraction of plasmid DNA, Anal. Biochem., 2012, 425(2), 125–127. Z. Zhou, U. S. Kadam and J. Irudayaraj, One-stop genomic DNA extraction by salicylic acid-coated magnetic nanoparticles, Anal. Biochem., 2013, 442(2), 249–252.

Functionalized Magnetic Nanoparticles in Sample Pre-treatment

121

172. T. Nakagawa, T. Tanaka, D. Niwa, T. Osaka, H. Takeyama and T. Matsunaga, Fabrication of amino silane-coated microchip for DNA extraction from whole blood, J. Biotechnol., 2005, 116(2), 105–111. 173. Z. Shan, Z. Zhou, H. Chen, Z. Zhang, Y. Zhou, A. Wen, K. D. Oakes and M. R. Servos, PCR-ready human DNA extraction from urine samples using magnetic nanoparticles, J. Chromatogr. B, 2012, 881, 63–68. 174. M. Fuentes, C. Mateo, A. Rodriguez, M. Casqueiro, J. C. Tercero, ´ndez-Lafuente and J. M. Guisa ´n, Detecting minimal H. H. Riese, R. Ferna traces of DNA using DNA covalently attached to superparamagnetic nanoparticles and direct PCR-ELISA, Biosens. Bioelectron., 2006, 21(8), 1574–1580. 175. M. H. Mashhadizadeh, M. Amoli-Diva and K. Pourghazi, Magnetic nanoparticles solid phase extraction for determination of ochratoxin A in cereals using high-performance liquid chromatography with fluorescence detection, J. Chromatogr. A, 2013, 1320, 17–26. 176. R. Keçili and C. M. Hussain, Recent progress of imprinted nanomaterials in analytical chemistry, Int. J. Anal. Chem., 2018, 2018, 8503853. 177. J. Sengupta and C. M. Hussain, Graphene and its derivatives for Analytical Lab on Chip platforms, TrAC, Trends Anal. Chem., 2019, 114, 326–337. 178. Handbook on Miniaturization in Analytical Chemistry: Application of Nanotechnology, ed. C. M. Hussain, Elsevier, 2020. 179. B. A. Sha-Sha, L. I. Zhi, Z. A. Xiao-Huan, W. A. Chun and W. A. Zhi, Graphene-based magnetic solid phase extraction dispersive liquidliquid microextraction combined with gas chromatographic method for determination of five acetanilide herbicides in water and green tea samples, Chin. J. Anal. Chem., 2013, 41(8), 1177–1182. 180. Y. Wang, Y. Sun, Y. Gao, B. Xu, Q. Wu, H. Zhang and D. Song, Determination of five pyrethroids in tea drinks by dispersive solid phase extraction with polyaniline-coated magnetic particles, Talanta, 2014, 119, 268–275. 181. M. Wierucka and M. Biziuk, Application of magnetic nanoparticles for magnetic solid-phase extraction in preparing biological, environmental and food samples, TrAC, Trends Anal. Chem., 2014, 59, 50–58. 182. D. Sharma and C. M. Hussain, Smart nanomaterials in pharmaceutical analysis, Arabian J. Chem., 2020, 13(1), 3319–3343. ¨yu ¨ktiryaki and C. M. Hussain, Advancement in bioana183. R. Keçili, S. Bu lytical science through nanotechnology: Past, present and future, TrAC, Trends Anal. Chem., 2019, 110, 259–276. ¨yu ¨ktiryaki, Y. Su ¨mbelli, R. Keçili and C. M. Hussain, Lab-on-chip 184. S. Bu platforms for environmental analysis, in Encyclopedia of Analytical Science, 2019, pp. 267–273. 185. Handbook of Nanomaterials for Industrial Applications, ed. C. M. Hussain, Elsevier, 2018.

CHAPTER 5

Application of Functionalized Magnetic Nanoparticles for Organic Analyte Extraction ´. GONZA ´LEZ-CURBELO,b ´NEZ-SKRZYPEK,a M. A G. JIME ´LEZ-SA ´LAMO,a,c C. ORTEGA-ZAMORAa AND J. GONZA ´NDEZ-BORGES*a,c J. HERNA a

Departamento de Quı´mica, Unidad Departamental de Quı´mica Analı´tica, Facultad de Ciencias, Universidad de La Laguna (ULL), Avda. Astrofı´sico Fco. ´nchez, s/n1, 38206 San Cristo ´bal de La Laguna, Espan ˜a; b Departamento de Sa ´sicas, Facultad de Ingenierı´a, Universidad EAN, Calle 79 n1 11-45, Ciencias Ba ´ D.C, Colombia; c Instituto Universitario de Enfermedades Tropicales y Bogota ´blica de Canarias, Universidad de La Laguna (ULL), Avda. Astrofı´sico Salud Pu ´nchez, s/n1, 38206 San Cristo ´bal de La Laguna, Espan ˜a Fco. Sa *Email: [email protected]

5.1 Introduction Over the last decades, important advances have been achieved in the introduction of new materials, in particular, nanomaterials, for a wide variety of applications,1–3 including those in the Analytical Chemistry field.4–7 In this last case, magnetic nanoparticles (m-NPs) have found an important place in sample preparation as a result of their high surface-to-volume ratio, high porosity and their ability to establish different types of interactions with the target analytes, which depends on their final coating. Concerning sample preparation, m-NPs have been mostly used in magnetic-dispersive solid-phase extraction (m-dSPE), which is a variant of Analytical Applications of Functionalized Magnetic Nanoparticles Edited by Chaudhery Mustansar Hussain r The Royal Society of Chemistry 2021 Published by the Royal Society of Chemistry, www.rsc.org

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the so-called dispersive SPE (dSPE), for the extraction and preconcentration of the target analytes (organic and inorganic). The first application of magnetic sorbents was proposed by Towler et al. in 1996 for the extraction of radium, lead and polonium from seawater using manganese dioxide magnetite (Fe3O4) as the sorbent.8 However, the term m-dSPE was only proposed ´ et al., when they used copper phthalocyanine three years later by Safarikova dye silanized magnetite and magnetic charcoal for the extraction of dyes.9 In m-dSPE, the sorbent is directly introduced in the sample or extract and, once suitably dispersed, it is retained by an external magnet (see Figure 5.1). Afterward, the adsorbed analytes are normally eluted with an adequate solvent and separated from the magnetic sorbent once more, using a magnet, though in some cases previous washing or drying of the sorbent may be necessary.10,11 m-dSPE can also be used with clean-up purposes, in which case no washing or elution is carried out. The use of m-NPs in m-dSPE has introduced a new horizon in the already well established and mature SPE technique (developed in the 1970s) with the introduction of new magnetic materials and the simplification of the extraction procedure, making it faster since sorbent conditioning and sample loading steps are unnecessary, and no centrifugation or deposition is required for the separation of the sorbent, as it happens in dSPE. Besides, the technique can also be miniaturized, requiring extremely low amounts of extraction sorbents, which is also in compliance with Green Analytical Chemistry principles.12–15 Apart from their application in m-dSPE, few attempts have also been made to apply m-NPs to other sorbent-based microextraction techniques like solidphase microextraction (SPME) or stir-bar sorptive extraction (SBSE) in which the sorbent is disposed as required in both techniques thanks to their magnetic properties.16,17 As previously commented, m-NPs offer multiple advantageous properties for sample preparation; however, due to their tendency to agglomerate and to oxidize, they cannot be normally used directly. In order to avoid these hardships, various organic and inorganic coatings have been used, which improve their stability, offer abundant adsorption sites and a large specific surface area, which finally determine their extraction efficiency and selectivity.5,6,10,11,14,18,19 Coated m-NPs can exhibit different structures (core shell, shell–core–shell, matrix-dispersed and Janus-type), with the most common being those of core–shell type20 in which the core is normally magnetite (Fe3O4), maghemite (g-Fe2O3) or CoFe2O421 (see Figure 5.2). The synthesis of m-NPs, which can be achieved by different methods,20,21 is very frequently of a certain complexity, and should be thoroughly developed and studied. Once a new sorbent is proposed, it should be first characterized using different surface characterization techniques (i.e., X-ray spectroscopy, scan electron or transmission microscopy, thermogravimetric analysis, infrared or Raman spectroscopy, among others) and then the extraction procedure should be optimized. A good validation of the whole

124

Figure 5.1

Functionalized magnetic nanoparticles for organic analyte extraction.

Chapter 5

Application of Functionalized Magnetic Nanoparticles for Organic Analyte Extraction

Schematic representation of a m-dSPE procedure. Figure 5.2

125

126

Chapter 5

method is of high importance, especially the development of a recovery study at different concentration levels and in different matrices. Once developed, the inter-batch reproducibility of the material should also be demonstrated. It should also be taken into account that very frequently, discrete coated m-NPs are not obtained, but the so-called ‘‘composites’’, which have a matrix material (also called the host) which incorporates units with at least one dimension in the size range below 100 nm and combines the properties of both of them, producing new functional materials capable of being used in specific applications (see Figure 5.2). The main role of the matrix is to act as a support that provides stability and processability to the final product.22,23 In this case, it is important to evaluate the extraction capacity of each component separately. From a practical point of view, the materials required to develop a m-dSPE can be found in any analytical laboratory, except for the magnets which are not so common. In this case, permanent magnets with a high energy product are desirable, which are frequently composed of a mixture of neodymium, iron and boron. During the application of such strong magnets, the operator should be aware of not developing the extraction near magnet attracted materials or not wearing them, as well as keeping apart other magnets, in order to avoid possible incidents/accidents in the laboratory. Taking into consideration all the above features of m-dSPE, the aim of this chapter is to review the current state-of-the-art of the application of coated/ functionalized m-NPs in m-dSPE, providing a critical and updated overview of the different m-NPs coatings and their effectiveness for organic analyte extraction.

5.2 Polymeric Magnetic Nanoparticles The use of polymers is probably one of the most common approaches for the protection/coating of m-NPs, during or after their synthesis. In general, polymers can be retained chemically or physically onto m-NPs, forming layers which generate repulsive forces (mainly steric) among the coated m-NPs, preventing their agglomeration2 and reducing the degree of magnetization. The wide variety of polymers that can be used as coatings clearly provides an extremely high number of different m-NPs, each of them with their own selectivity and extraction capacity. Polymers can be categorized according to their nature as natural or synthetic. Natural polymers which can be derived from a wide variety of sources, from plants, animals, and microorganisms, stand out for their biocompatibility,24 however, some of them are water-soluble, lack mechanical strength or are too rigid to be used as m-NPs coatings; cross-linking is used to prevent the coating’s break down but the structure’s mechanical strength remains weak.25 Furthermore, natural polymer coatings tend to be porous (allowing the corrosion of the magnetic core) and, in some occasions, they exhibit non-specific adsorption.26 As for synthetic polymers, they provide an

Application of Functionalized Magnetic Nanoparticles for Organic Analyte Extraction

127

alternative to natural polymers, granting superior mechanical strength and improved stability in water and other solvents,27 nevertheless, some of these polymers exhibit porosity at a molecular level, which exposes the inner magnetic core, and, in some cases, functionalization is strictly limited, due to the lack of anchoring sites.25 The synthesis of polymeric coatings can be achieved through different methods. A common pathway to synthesize polymeric m-NPs is monomer polymerization, which is based on the dispersion of surface-modified m-NPs into a monomer solution and then the polymerization reaction is initiated.28 Nevertheless, polymeric m-NPs synthesized through this method can suffer from deficient coatings (incomplete or non-uniform) affecting the size of the m-NPs and failing to prevent the oxidation of the highly reactive m-NPs, resulting in air instability and leaching under acidic conditions.2,28 In order to face these inconveniences, different methods have been developed, including the following. Dispersion polymerization is a single-step polymerization method which allows the preparation of narrow size coated m-NPs. This method has great interest for industrial synthesis applications due to its simplicity. The synthetic pathway consists of an initiation step (m-NPs are dispersed in the reaction solution, adsorbing monomers, stabilizers, and initiator radicals), a precipitation step (adsorbed radicals grow in length until a critical size is reached, the point at which precipitation occurs) and stable nuclei formation step (unstable coated m-NPs formed during precipitation adsorb the stabilizer and aggregate forming stable coated m-NPs).29,30 Suspension polymerization is a single-step polymerization method that uses mechanical agitation to mix monomers, or a mixture of them, in a liquidphase.31,32 Generally, a mixture of monomers is decanted into a suspension of m-NPs, where polymerization starts, initiating the formation of polymer coated m-NPs. This polymerization method is suitable for massive production because of the smaller amounts of surfactants used33 (compared to emulsion polymerization) to stabilize the microdroplets; nevertheless, its main disadvantage comes from the difficulty of removing all of the residual suspending agents from the synthesized material.31 Emulsion polymerization is a synthetic method with different applications on both industrial and academic scales. The general procedure can be summarized as follows. Synthesized m-NPs are transferred into an organic phase (e.g., oleic acid); then, the prepared organic ferrofluid is emulsified in order to obtain a stable, narrowly size distributed oil-in-water emulsion. After conditioning the emulsified ferrofluid, a mixture containing monomers and an organosoluble initiator is added. Finally, reaction conditions are changed in order to start the reaction and to obtain the polymer coated m-NPs.34 One of the main advantages of the method comes from the possibility of achieving high polymerization rates and weights and the polymers’ high homogeneity and regularity in particle size distribution.32 Nonetheless, emulsion polymerization suffers from similar problems to those observed in suspension polymerization, meaning that the complete

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Chapter 5 31

removal of all surfactant traces is difficult. Miniemulsion polymerization is a particular case of emulsion polymerization that allows the formation of a wide range of functionalized polymers by polymerization or modification of polymers in stable nanodroplets.35,36 This synthetic method combines the advantages of the emulsion polymerization (high polymerization rates, easy thermal control, and high molecular weights, etc.) with the option of using reactants insoluble in water. This method allows the synthesis of a wide range of polymers, that could not be prepared through other methods.37 Emulsifier-free emulsion polymerization is another emulsion polymerization method, in which emulsifiers are not used, which facilitates the separation of the synthesized polymer coated m-NPs.38 Instead, the required colloidal stability for the synthesis is achieved using different reactive compounds (e.g., ionizable initiators, hydrophilic and ionic comonomers) that substitute the function of the emulsifiers,39,40 allowing the preparation of model polymer colloids with narrow particle size distributions and well-characterized surface properties.39 The wide range of existing polymers generates endless possibilities for the extraction of numerous analytes – as the great number of articles published reveals – providing the possibility of even synthesizing molecularly imprinted polymers (MIPs) for highly selective extractions.41–46 MIPs are synthetic polymers designed to selectively retain a target molecule in the presence of other similar compounds. Molecular imprinting proceeds via polymerization of functional and cross-linking monomers around the template molecule (generally the analyte), generating a highly cross-linked three-dimensional (3D) network. This step is followed by the removal of the template, which determines the success or not of the synthesis. The monomer selection has to consider all possible interactions with the analyte’s functional groups, since it determines the recognition process.47–49 Figure 5.341 shows the general procedure for the synthesis of Fe3O4@MIPs: m-NPs were coated through different synthetic steps to stabilize the m-NP, avoid agglomeration and create an adequate anchoring surface for the polymerization of the MIP. The resulting material possessed higher selectivity and binding affinity than the same material with a non-imprinted polymer. Despite their advantages, MIPs face multiple challenges: extensive research is needed to attain optimal synthetic conditions, low specific binding capacity, non-specific binding sites, template leakage, difficult desorption of the analytes, etc.48,49 Table 5.1 shows some recent examples of the application of polymeric m-NPs for the extraction of organic analytes. Among the different organic analytes that they can extract, those to be highlighted are polycyclic aromatic hydrocarbons (PAHs),50 phthalic acid esters (PAEs),51,52 endocrinedisrupting bisphenols (EDBs),53 estrogenic compounds,54–56 endogenous brassinosteroids (BRs),57 antidepressant drugs,58 pesticides (i.e., benzoylurea insecticides (BUs),59 organophosphorus pesticides (OPPs),60,61 triazines,44 etc.), antibiotics (pefloxacin mesylate (PEF-M),41 fluoroquinolones (FQs),62 sulfonamides (SAs),63 etc.), monocyclic aromatic amines (MAAs),64

Synthesis route of magnetic surface imprinted nanoparticles (Fe3O4@MIP) via surface-initiated atom transfer radical polymerization. Reproduced from ref. 41 with permission from Elsevier, Copyright 2012.

Application of Functionalized Magnetic Nanoparticles for Organic Analyte Extraction

Figure 5.3

129

Table 5.1 Some applications of polymer-coated m-NPs in sample treatment.a

Fe3O4@pDA (120 mg)

Fe3O4@CHS@ PANI (15 mg)

Analytes

Matrices (amount)

Previous sample pretreatment

Determination Recovery technique (RSD)

10 PAEs Sea sand and Sea water samples GC–MS sea water (5 g were adjusted to and 1 pH ¼ 6. Sea sand of sand and adipate samples were 50 mL of sea extracted with water) ACN, evaporated to dryness, reconstituted with Milli-Q water and adjusted to pH ¼ 6. HPLC–DAD 3 EDBs Reservoir and Juice samples were filtered. waste waters and grape juice (10 mL)

Fe3O4@PTPA (20 mg)

6 BUs

Tomato, cucumber and watermelon (50 g)

Fe3O4@SiO2@ MIP (8 mg)

PEF-M

Egg (0.4 g)

River and dam Juice samples were filtered. waters and apple, grape and peach juices (50 mL)

GC–FID

Detection limits

Comments

Sea water: Analytes were 0.0018–0.319 desorbed with mg L1 DCM (12 mL). DHP-d4 and Sea sand: 0.020–4 mg kg1 DBP-d4 were used as ISs.

85.0–106.7% 0.10–0.13 mg L1 (r6.6%)

87.7–106.7% 0.05–0.1 mg kg1 (r6.4%)

92.8–96.5% (r4.0%)

0.18 mg L1

88.1–99.2% (r12.3%)

0.1–0.3 mg L1

Reference 51

53 Analytes were desorbed with 0.015 M alkaline MeOH (0.5 mL). 59 Analytes were desorbed with ACN (0.3 mL).

41 Analytes were desorbed with MeOH and HOAc (8 : 2, v/v) (). Analytes were 60 desorbed with DCM (0.2 mL).

Chapter 5

Fe3O4@p(pPDA- 5 OPPs co-Th) (30 mg)

HPLC–MS Samples were washed with distilled water and the edible parts were cut into pieces, homogenized, and centrifuged Eggs were stirred HPLC–UV/Vis to homogenize the albumen and yolk.

65–147% (r21%)

130

Sorbent (amount)

5 FQs

Fe3O4@PpPA (20 mg)

4 MAAs

Fe3O4@CHSPPD (10 mg)

7 PCBs

Fe3O4@SiO2@ p(MAA-coEGDMA) (50 mg)

11 SAs

Fe3O4@SiO2@ p(4-VPBA-coEGDMA) (10 mg)

5 BRs

HPLC–DAD Samples were filtered and adjusted to pH ¼ 6 and 20% ionic strength. GC–FID Tap, river, dam, — well and waste waters and human urine (20 mL) Lake, surface and reservoir waters (50 mL)

86.7–92.8% (r7.7%)

0.007–0.01 mg L1

94–108% (r6%)

0.00011–0.00032 mg L1

87.6–115.6% 0.0005–0.0495 (r10.8%) mg L1

74.0–116.6% 0.00027–0.00129 (r14.8%) mg L1

Analytes were desorbed with MeOH and HOAc (96 : 4, v/v) (0.5 mL). Analytes were desorbed with DCM and chloroform (3 : 1, v/v) (0.25 mL). Analytes were desorbed with acetone and n-hexane (1 : 1, v/v) (10 mL). Analytes were desorbed with acetone with 5% NH4OH (1 mL).

62

64

65

63

57 Elution and derivatization with 3 mg mL1 of 4-DMAPBA– ACN solution with 1% NH4OH (2 mL). BL-d3 and CS-d3 were used as ISs.

131

— GC–MS/MS Aquaculture, livestock breeding and sewage waters (100 mL) Milk (1 mL) Milk samples were HPLC–MS/MS diluted with phosphate buffer (20 mM; pH ¼ 4.0) and centrifuged HPLC–MS/MS Plants Plant tissue (100 mg) samples were frozen in liquid nitrogen, smashed, extracted with ACN, evaporated to dryness and reconstituted with ACN.

52.1–104.5% 0.20–1.46 mg L1 (r12%)

Application of Functionalized Magnetic Nanoparticles for Organic Analyte Extraction

Fe3O4@SiO2@ p(VI-co-DB) (50 mg)

132

Table 5.1

(Continued)

Sorbent (amount)

Analytes

Fe3O4@NH2MER (5 mg)

11 Bile acids

a

Matrices (amount)

Previous sample pretreatment

Determination Recovery technique (RSD)

Detection limits

UHPLC–MS/MS 82.3–108.5% 0.0001–0.005 Human serum Serum samples (r9.5%) mg L1 (1 mL) were mixed with MeOH to precipitate proteins, vortexed and centrifugated. The obtained supernatant was collected, dried and the residue was reconstituted with water.

Comments

Reference

66 Analytes were desorbed with MeOH and acetic acid (95 : 5, v/v) (0.1 mL). An IS (not specified) was used.

Chapter 5

ACN: acetonitrile; BL-d3: [2H3] brassinolide; BRs: brassinosteroids; BUs: benzoylurea insecticides; CS-d3: [2H3] castasterone; CHS: chitosan; DAD: diode array detector; DMAPBA: 4-(N,N-dimethylamino)phenylboronic acid; DBP-d4: di-n-butyl phthalate 2,3,4,5-d4; DCM: dichloromethane; DHP-d4: dihexyl phthalate 3,4,5,6-d4; EDBs: endocrine-disrupting bisphenols; FID: flame ionization detector; FQs: fluoroquinolones; GC: gas chromatography; HOAc: acetic acid; HPLC: high-performance liquid chromatography; ISs: internal standards; LC: liquid chromatography; MAAs: monocyclic aromatic amines; MeOH: methanol; MER: mesoporous epoxy resin; MIP: molecularly imprinted polymer; MOP: magnetic porous organic polymer; MS: mass spectrometry; MS/MS: tandem mass spectrometry; OPPs: organophosphorus pesticides; PAEs: phthalic acid esters; PANI: polyaniline; PCBs: polychlorinated biphenyls; PEF-M: pefloxacin mesylate; pDA: polydopamine; p(MAA-co-EGDMA): poly(methacrylic acid–co–ethyleneglycoldimethacrylate); p(pPDA-co-Th): poly(p-phenylenediamine-co-thiophene); PPD: poly(m-phenylenediamine); PpPA: poly(p-phenylenediamine); PTPA: polytriphenylamine; p(VI-co-DB): poly(vinylimidazole-co-divinylbenzene); p(4-VPBA-co-EGDMA): polymer(4-vinylphenylboronic acid-co-ethylene glycol dimethacrylate); RSD: relative standard deviation; SAs: sulfonamides; UV: ultraviolet; Vis: visible.

Application of Functionalized Magnetic Nanoparticles for Organic Analyte Extraction 65

66

133

polychlorinated biphenyls (PCBs) and bile acids, among others. As also happens with non-magnetic particles, apolar polymers are appropriate for the extraction of non-polar analytes, while if the polarity is increased, then more polar analytes can be extracted. Therefore, during the synthesis procedure (since in general not many m-NPs are currently commercialized) it is important to consider or not the introduction of polar functional groups. Regarding the matrices analyzed, as in the case of analytes, there can be seen a great variability in the nature and complexity of the samples studied. Some examples of liquid samples are biological fluids (e.g., human serum, human urine, human or rat plasma),43,58,64,66 environmental waters (lake, river, reservoir, pond, sea water, wastewater, etc.),50–54,60,62,64,65 drinking water (tap, bottled, etc.),50,52 dairy products such as milk55,63 and fruit juices (i.e., apple, grape, peach).53,60 Concerning solid or semisolid samples, the extraction of soils (i.e., sea sand,51 agricultural soil,44 etc.), foods (vegetables,59 fruits,59 yogurt55 or eggs41), plants (Oryza sativa L.,57 Cortex phellodendri,43 etc.), among others, can also be remarked. In relation to sample preparation prior to the main extraction procedures using polymeric m-NPs, environmental waters and biological samples frequently require filtration to eliminate debris or other interfering elements that could affect the extraction procedure. In the case of juice samples, filtration is frequently applied. When semisolid food samples are considered, homogenization is always required, which could be followed by centrifugation (for supernatant separation), stirring, etc. Solid samples like soils, due to their heterogeneous nature, frequently employ an initial ultrasoundassisted extraction step with organic solvents (e.g., acetonitrile, ACN), which is then followed by an evaporation and reconstitution in a different solvent in which the m-dSPE procedure is applied. Another aspect taken into consideration is the pH of the sample or extract, that for many samples has to be readjusted in order to achieve optimal extraction conditions. Generally, polymeric coatings have been evaluated in different ranges of pH, displaying acceptable stability. As for sorbents, the amounts required are very low, with values lower than 120 mg for the majority of cases. Regarding the recovery values obtained, most works have shown acceptable results, with recoveries higher than 60% and relative standard deviations (RSDs) lower than 20% for most cases, see Table 5.1. An example is the work of Wang et al.59 in which 6 BUs were analyzed in fruits and vegetables using magnetite m-NPs coated with a triphenylamine-based porous organic polymer (Fe3O4@PTPA) via m-dSPE. Reported recovery values (evaluated at two levels of concentration) were within the range of 87.7–106.7% with RSDs lower than 6.4% and the limit of detection (LOD) of the method was 0.05–0.1 ng g1. Separation and determination of the BUs was achieved through high performance liquid chromatography with a mass spectroscopy detector (HPLC–MS). Another example was the work of Liao et al.65 in which 7 PCBs were analyzed in environmental waters, employing chitosan poly(m-phenylenediamine) coated m-NPs (Fe3O4@CHS-PPD). Recovery values (evaluated at three levels of concentration) ranged from

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94–108% with RSDs lower than 6% and LODs from 0.11–0.32 ng L1. Separation and determination of the PCBs was achieved through gas chromatography with a tandem mass spectroscopy detector (GC–MS/MS).

5.3 Magnetic Nanoparticles Based on Allotropic Forms of Carbon In recent years, a wide variety of nanostructured sorbents based on the allotropic forms of carbon has been investigated to coat m-NPs, from unidimensional to tridimensional chemical structures such as carbon nanotubes (CNTs), either single-walled (SWCNTs) or multi-walled (MWCNTs), graphene (G), nanodiamonds (NDs), fullerenes and carbon nanofibers (CNFs).67–70 These nanomaterials have hollow or layered nanosized structures with good thermal conductivity, excellent mechanical, chemical and thermal stability, large surface area and tunable surface properties. These characteristic structures have allowed carbon-based m-NPs to successfully extract traces of many organic compounds through p–p stacking and hydrophobic interactions.71,72 Likewise, these interactions enable quick sorption processes and therefore faster equilibrium and favorable adsorption–desorption kinetics compared to traditional SPE sorbents. However, even in combination with magnetic supports in the m-dSPE mode, these non-polar materials present an aggregation phenomenon and low dispersibility in water, which could make the extraction procedure difficult. Moreover, bare carbon-based-m-NPs have shown low extraction ability and poor selectivity to diverse types of organic analytes, particularly polar ones in complex matrices. Consequently, surface chemical modification is frequently needed to increase their selectivity and extend their applications for more polar analytes via electrostatic forces, Lewis acid–base interactions and hydrogen bonding, as well as making it suitable for subsequent combinations with other types of materials. At the same time, functionalization generally prolongs the shelf life of the sorbents by improving stability toward solvents and acidic/basic solutions. In fact, recent years have witnessed endless advances in research on this field. Table 5.2 summarizes several applications of unmodified and functionalized carbon-based m-NPs for organic analyte extraction. In contrast with SWCNTs, MWCNTs have been widely applied for the m-dSPE extraction of organic analytes. MWCNTs can be described as multiple cylinder-shaped concentric graphite sheets, kept together by van der Waals forces, with outer diameters between 5 nm to a few hundred nanometers.72,87 In most cases, pristine MWCNTs have been assembled on m-NPs via non-covalent interactions due to their lack of functional groups. In this sense, m-MWCNTs can be prepared in two successive stages in which synthesis of m-NPs takes place first and then they are later mixed with MWCNTs to induce the aggregation or directly by mixing MWCNTs with iron salts so that m-NPs synthesis and assembly occurs simultaneously. In the first strategy, m-NPs are encapsulated in the cavity of large pore-size MWCNTs with open ends (endohedral functionalization)88,89 or have been attached on the

Sorbent (amount) Fe3O4@ MWCNTs (20 mg)

Analytes 9 Parabens

23 Phenolic Fe3O4@ compounds MWCNTsCOOH (5 mg)

Fe3O4@ MWCNTsNH2 (20 mg)

7 Multiclass pesticides

Fe3O4@G (7 mg) 5 Carbamate pesticides

Matrices (amount) Human urine and river, harbor, swimming pool, tap and waste water (10 mL)

Sesame oil (0.5 g)

Lake, river, farmland and sewage treatment plant influent and effluent waters (20 mL)

Tomato (2 g)

DeterminaPrevious sample tion technique pretreatment

Recovery (RSD)

Detection limits 1

Comments

Reference

Analytes were desorbed with EtOAc (3 mL).

73

GC–MS

81–119% (r9%)

0.03–2.0 mg L

HPLC–MS/ MS

83.8–125.9% (r13.2%)

0.01–13.60 mg kg1

74 Analytes were desorbed with EtOH (3 mL).

UHPLC– MS/MS

80.4–103.2% (r11.2%)

0.3–1.5 mg L1

Tomatoes were homogenized, centrifuged, and the supernatant

HPLC–DAD 90.3–102.0% (r5.9%)

0.58– 2.06 mg kg1

75 Analytes were desorbed with ACN (5 mL). Fe3O4@ MWCNTs-NH2 showed higher extraction efficiency than Fe3O4@ MWCNTs-COOH. 76 Analytes were desorbed with acetone and HOAc (9 : 1, v/v) (0.2 mL).

135

Water samples were filtered. Urine was frozen and, once thawed, the solid residue was discarded by centrifugation Oil seeds were triturated, squashed and put into an oil presser. The edible oil was diluted with n-hexane Waters were filtered

Application of Functionalized Magnetic Nanoparticles for Organic Analyte Extraction

Table 5.2 Some applications of carbon-based m-NPs in sample treatment.a

Sorbent (amount)

Analytes

136

Table 5.2 (Continued)

Matrices (amount)

DeterminaPrevious sample tion technique pretreatment

Recovery (RSD)

Detection limits

was diluted and adjusted to pH 6.0 CoFe2O4@G (15 mg)

5 SAs

Milk (100 mL)

Fe3O4@GO (20 mg)

5 Flavors and fragrances

Orange juice, chocolate and fruit sugar (2 mL of orange juice and 2 g of chocolate and fruit sugar)

Fe3O4@ GO@MoS2 (2 mg)

3 FQs

Tap water (10 mL)

HPLC–UV Milk was acidified with HClO4 for protein precipitation, diluted and adjusted to pH 4 All samples were HPLC–UV extracted with MeOH, centrifuged and filtered

62.0–104.3% (r14.0%)

1.16–1.59 mg L1

71.5–112.4% (r4.1%)

0.02–0.04 mg L1



85.6–106.1% (r9.5%)

0.00025–0.00050 mg L1

HPLC–UV

Comments

Reference

Fe3O4@G showed higher extraction efficiency than rGO and iron-containing Fe3O4. 77 Analytes were desorbed with MeOH (0.5 mL).

Chapter 5

78 Analytes were desorbed with ACN with 10% HOAc (2 mL). Fe3O4@GO showed higher extraction efficiency than a C18 SPE column. 79 Analytes were desorbed with ACN with 10% HOAc (32 mL). Fe3O4@GO@ MoS2 showed higher extraction efficiency than GO and Fe3O4@GO.

Fe3O4@rGO (5 mg)

Sudan dyes (I, II, III, and IV)

Fe3O4@SiO2@ C60 (40 mg)

16 PAHs

Tea (2.5 g)

Fe3O4@CNFs (10 mg)

3 PAHs

TiO2@Fe3O4@ CNFs (150 mg)

Ibuprofen

GC–FID 90.1–100.9% Tap water, river, (r9.8%) well and waste waters (50 mL) HPLC–DAD 89–105% Lake, sea and waste Water samples (r2.8%) were filtered. waters, human Pharmaceutical urine and tablets were pharmaceutical ground, tablet and syrup extracted with (15 mL of waters, MeOH, diluted 5 mg of and adjusted to pharmaceutical pH 4. tablet and 50 mL of pharmaceutical Pharmaceutical syrup was syrup) diluted and adjusted to pH 4

Tea infusions were prepared in boiling water and filtered —

GC–MS

98.5–106.7% (r10.6%)

1.49 mg L1

80 Analytes were desorbed with EtOH (0.5 mL).

2.5–6.0 mg kg1

Analytes were desorbed with toluene (1 mL). Fe3O4@rGO showed similar extraction efficiency than an alumina-N SPE cartridge. Analytes were desorbed with n-hexane and acetone (1 : 1, v/v) MeOH (1 mL). Analytes were desorbed DCM (1 mL). Analytes were desorbed with acetone (1 mL).

0.0008–0.0143 mg L1

0.000008– 0.00003 mg L1 0.95 mg L1

81

82

83 84

137

Sildenafil citrate

Application of Functionalized Magnetic Nanoparticles for Organic Analyte Extraction

HPLC–DAD 94.0–104.1% Herbal tablets Herbal supple(r7.1%) were ground, mentary products extracted with (1 g) MeOH, centrifuged and filtered HPLC–DAD 79.6–104% Tomato sauce, chili Samples were (r8.6%) extracted with sauce, chili ACN, powder and chili centrifuged flake (2 g) and extracted with ACN twice

Fe3O4@ NDs@GO (30 mg)

138

Table 5.2 (Continued) Sorbent (amount)

DeterminaPrevious sample tion technique pretreatment

Analytes

Matrices (amount)

Fe3O4@g-C3N4 (15 mg)

4 PAEs

Fe3O4@g-C3N4 (4 mg)

3 OH-PAHs

HPLC–UV Lake and tap waters Waters were (100 mL) adjusted at pH ¼ 7 and with 20% w/v NaCl HPLC–FD Human urine (2 mL) Urine was hydrolyzed with bglucuronidase and HOAcsodium acetate buffer solution.

Recovery (RSD)

Detection limits

Comments

79.4–99.4% (r3.8%)

0.05–0.1 mg L1

85 Analytes were desorbed with EtOH (20.5 mL).

Reference

90.1–102% (r8.7%)

0.08 mg L1

Analytes were desorbed with acetone (0.5 mL).

86

a

ACN: acetonitrile; C60: fullerenes; CNFs: carbon nanofibers; DAD: diode array detection; DCM: dichloromethane; EtOAc: ethyl acetate; EtOH: ethanol; FD: fluorescence detector; FID: flame ionization detector; FQs: fluoroquinolones; G: graphene; GC: gas chromatography; g-C3N4: graphitic carbon nitride; GO: graphene oxide; HOAc: acetic acid; HPLC: high-performance liquid chromatography; MeOH: methanol; MS: mass spectrometry; MS/MS: tandem mass spectrometry; MWCNTs: multi-walled carbon nanotubes; NDs: nanodiamonds; PAEs: phthalic acid esters; PAHs: polycyclic aromatic hydrocarbons; rGO: reduced graphene oxide; RSD: relative standard deviation; SPE: solid-phase extraction; SAs: sulfonamides; UHPLC: ultra-high liquid chromatography; UV: ultraviolet.

Chapter 5

Application of Functionalized Magnetic Nanoparticles for Organic Analyte Extraction 90,91

139

surface sites of MWCNTs (exohedral functionalization). Although the later approach is easier, the adsorption capacity of the resulting m-MWCNTs is considerably reduced compared to endohedral functionalization because of the previous occupation of the active surface sites.70 In any case, the simpler in situ synthesis procedure is now the most commonly used to obtain m-MWCNTs.67,70 However, in addition to their low solubility, tendency to agglomeration and weak interactions, only their external surface area interacts with target analytes due to their cylindrical shape. As a consequence, several surface modifications have been developed to improve their binding forces and extend their applications in m-dSPE. In this regard, m-MWCNTs have incorporated polar functional groups such as hydroxyl,92 carboxyl,74 thiol93 and amino.75 Apart from this initial functionalization, MWCNTs have also been combined with other classes to provide m-hybrid materials/m-composites. Such are the cases of m-MWCNTs combined with organic polymers,94,95 MIPs,96,97 ionic liquids (ILs),98 metal organic frameworks (MOFs)99,100 and even other carbon allotropes such as G101 and NFs,102 integrating the advantages of both materials and modulating retention and selectivity. G is a single-/few-layer sheet of carbon atoms arranged in a closely packed two-dimensional honeycomb lattice. Consequently, contrary to what happens for CNTs, this nanosheet structure allows both sides to be accessible for inner and external molecule adsorption, resulting in a much larger theoretical surface area (value up to 2630 m2 g1 vs. 1315 m2 g1).103 Furthermore, G possesses a large delocalized p electron system that provides a strong affinity with the aromatic rings of organic compounds as well as an easy and low-cost synthesis process without residual metallic impurities and versatile surface modification aiming to obtain other selective graphene-based sorbents. These exceptional features of G make it superior to CNTs, and other allotropes and carbonaceous materials, and it is currently the most intensively studied carbon-based nanostructured sorbent for the extraction of organic analytes by m-dSPE.68 Very frequently, this material is obtained from the chemical reduction of graphene oxide (GO, the oxidation of graphite powder), resulting in the so-called reduced GO (rGO), which still contains some polar groups. As similar for CNTs, m-rGO can be synthesized by in situ growth via chemical coprecipitation104 and hydrothermal synthesis,105 or by simple mixing of the m-NPs and the GO,106 but also by chemical bonding.107 As an example, Figure 5.4 shows the procedure followed by Wang et al.107 in which Fe3O4@SiO2–G were synthesized via a chemical bonding method from prepared Fe3O4@SiO2–NH2 and GO, and a final chemical reduction step with hydrazine to obtain the coated rGO, for the extraction of five polycyclic aromatic hydrocarbons (PAHs) from environmental water samples. As can be seen, the authors also used an inert protective silica coating to avoid the oxidation of the magnetite core and prevent loss of magnetism as well as undesirable interactions. As a consequence of such chemical reduction of GO, the resulting m-rGO has properties closer to the reversed-phase, but the presence of residual oxygen groups combines hydrophobic and hydrophilic interactions for the successful extraction of a wide polarity-range of organic analytes. As an example of the

140

Figure 5.4

Chapter 5

Procedures for the preparation of Fe3O4@SiO2–G. Reproduced from ref. 107 with permission from Elsevier, Copyright 2013.

potential of these features, Wang et al.108 demonstrated the better performance of this mixed-mode sorbent. Concretely, Fe3O4@rGO obtained by hydrazinereduction of GO prepared by graphite exfoliation gave higher extraction efficiencies than Fe3O4@GO and Fe3O4@MWCNT for the extraction of analytes containing chloro-substituted phenyl and triazole groups from environmental water samples. However, for some applications, the use of bare m-GO could minimize some inconveniences of bare m-rGO such as the lack of the ability to interact with polar compounds and poor dispersibility in water owing to its high density of polar moieties namely hydroxyl, carboxyl, ketone and epoxy groups. The reason is that m-GO can adsorb oxygen and nitrogen functional groups through electrostatic interactions and hydrogen bonds and exhibits high hydrophilicity and dispersibility in aqueous solution.69 Unfortunately, m-rGO/GO has also evidenced unsatisfactory selectivity and service life. Consequently, different types of organic materials such other carbon-based materials,80,109–111 organic polymers,112,113 ILs,114,115 deep eutectic solvents (DESs),116 MOFs,117,118 ionic surfactants119,120 and MIPs121 have been widely incorporated on these materials to strengthen selectivity. In this sense, the fabrication of 3D rGO/rGO-based m-NPs provides superior properties compared to two-dimensional materials. Such is the case of the very recently work developed by Xiao et al.79 in which a Fe3O4@GO@MoS2 material was used for the extraction of fluoroquinolone (FQ) antibiotics from tap water. Because of the doping of MoS2 into GO, the resulting 3D porous structure exhibited larger specific surface area and adsorption ability compared to GO and Fe3O4@GO. Analogously, Feng et al.122 and Razmi et al.111 fabricated 3D composites by combining Fe3O4, GO and MWCNTs via a solvothermal process in which a hierarchical disposition was obtained with MWCNTs inserted between the GO sheets to prevent their aggregation. Subsequently, the ternary magnetic composites

Application of Functionalized Magnetic Nanoparticles for Organic Analyte Extraction

141

were applied for the extraction of sulfonamides from milk and OPPs from environmental water samples, respectively. In a later work, a synergistic effect between the two carbon allotropes was observed in terms of extraction efficiencies compared to Fe3O4@GO and Fe3O4@MWCNTs alone. Pure and functionalized m-CNTs and m-rGO/GO have been applied for the extraction of a wide range of organic pollutants at trace levels from environmental, biological and food samples, including parabens,73 phenolic compounds,74,123 pesticides,75,76,124–126 veterinary drugs,77–79,127–129 PAEs,130,131 PAHs,132–135 brominated flame retardants (BFRs),136,137 among others, mostly with subsequent chromatographic analysis. Regarding the previous sample pretreatment, liquid samples such as environmental waters or biofluids only require simple filtration and/or dilution,73,75 while solid environmental and food samples require an initial extraction step using organic solvents like ACN81 or MeOH.78,80 With respect to the elution step, each analyte/carbonbased m-NPs combination should be studied, but the majority of studies have used organic solvents such as ACN,75,78,79 EtOAc,73 EtOH74,80 and MeOH.77 Inspired by these applications, other m-NPs based on allotropic forms of carbon such as m-fullerenes and m-CNFs have recently been used for the extraction of organic analytes, but much more sparingly. Despite the fact that fullerenes were discovered in 1985,138 their extremely low solubility in aqueous and organic media have limited their application as sorbent materials. However, Fe3O4@SiO2@C60 and Fe3O4@C60 have been successfully applied for the extraction of PAHs from tea82 and azo dyes from waste waters,139 respectively. Similarly, although CNFs have no aggregation problems due to their linear morphology and specific surface area reported up to 1877 m2 g1,140 m-CNFs have also been rarely used.83,84,110,141

5.4 Metal Organic Framework Coatings MOFs are a special class of 3D highly porous materials resulting from the combination of metal ions or clusters and organic ligands through coordination bonds which, due to the wide variety of both components, enables almost an infinite number of structures.142,143 These crystalline structures have awoken the interest of the scientific community in the last few decades as a consequence of their particular properties, including extraordinary large surface areas (up to E7000 m2 g1), good thermal and chemical stability, possibility of being modified, suitable mechanical resistance, and excellent adsorption capacity, among others.142,143 MOFs have shown an excellent behavior in multiple application fields, and especially in sample preparation. Despite their proven good performance as sorbents, their magnetization has also opened a whole new range of possibilities in which the highest surface areas known are combined with magnetic properties creating one of the most interesting nanocomposites to be applied in sample preparation. It is important to notice that, although they contain metals, as synthesized MOFs are not magnetic and, therefore, a subsequent magnetization step is

142

Chapter 5

needed. In this sense, different strategies can be followed (see Figure 5.5): direct mixing, in which MOF and m-NPs are synthesized separately and then combined under ultrasounds;144 in situ m-NPs growth, in which MOF is introduced in the synthetic medium used to prepare m-NPs;145 single step MOF growth, in which functionalized m-NPs are dispersed into the MOF synthesis solution;146 layer-by-layer MOF growth, in which m-NPs with chelating functional groups or with anion-exchange properties are used as the core to make the MOF grow around it by sequential immobilization of the MOF components;147 and MOF carbonization, in which metal ions or clusters form m-NPs after carbonizing the MOF.148 As an example of this last case, Huo et al.149 carried out the synthesis of MOF MIL-100 through a solvothermal method. Then, a certain amount of MIL-100 was calcined in a furnace under nitrogen gas flow at 415 1C, which was the calcination temperature at which the original structure was unaltered while exhibiting magnetic properties. Then, the magnetic porous material was allowed to cool to room temperature and was washed with ultrapure water and EtOH, and dried under vacuum at 100 1C. This magnetic material was then used as the sorbent for the m-dSPE of 5 PAHs from effluent waste water and river water samples, followed by their GC-FID determination. Recovery values in the range 86–107% and LODs between 4.6 and 8.9 ng L1 were obtained. As a consequence of the good performance and great versatility of this kind of nanocomposite, they have been extensively used for the extraction of a wide variety of organic analytes, including PAHs,149–151 pesticides,152–154 PCBs,17,155 PAEs,156,157 parabens,157 dyes158 or estrogenic compounds,159 among others, although it should be highlighted that they have also been extensively applied to the extraction of heavy metal ions.160,161 Table 5.3 compiles some examples of the applicability of MOF-modified m-NPs for the extraction of organic

Figure 5.5

Schematic representation of different magnetization strategies of MOFs for their application in m-dSPE procedures. Reproduced from ref. 14 with permission from Elsevier, Copyright 2017.

Application of Functionalized Magnetic Nanoparticles for Organic Analyte Extraction

143

compounds from matrices of different kinds, which include drinkable and environmental water,149,150,152,153,156,157 soil,155 beverages,150,153 food17,152,153 or even biological fluids156,159 and cosmetics.157 In general, Fe3O4 m-NPs have been used to provide MOFs with magnetic properties,142,143 probably due to their simple synthetic procedures, their superparamagnetic properties, their high surface-to-volume ratio, as well as their low toxicity, which have made them the preferred option in many applications.162,163 Regarding MOFs, a wide variety of structures can be found, being MIL-100164,165 and MIL-101156,157,166 the most commonly magnetized and applied as extraction sorbents, although others like MOF-5,17,167 HKUST-1,150 UiO-66,155 ZIF-8153,168 or TMU-6152 have also been used in other applications. In this sense, it is worth mentioning the work of Rocı´oBautista and co-workers,150 who carried out the analysis of eight PAHs in water and fruit tea infusions applying Fe3O4@HKUST-1 as the sorbent in a m-dSPE procedure followed by UHPLC–FD determination. In this case, the authors synthesized the Fe3O4 m-NPs and the MOF HKUST-1 separately through very simple methods and then mixed them in a centrifuged tube under vortex agitation. After that, the sample was added and ultrasound was applied, allowing the isolation of the sorbent with an external magnetic field. This very simple, but at the same time highly effective method allowed obtaining high extraction recovery values in water samples, as well as in fruit tea infusions when matrix-matched calibration was used. As it has been shown in the previous example, despite the fact that bare m-NPs without further functionalization can be directly combined with MOFs,150,169 in most cases, m-NPs are previously coated or functionalized. In this sense, SiO2 is one of the most widely applied, either bare158,170 or functionalized.167 However, others such as thioglycolic acid (TGA),152 3-aminopropyltriethoxysilane (APTES)153 or polydopamine (PDA),155 among others, have also been employed in the same way. As an example, Lin et al.155 applied lab-made Fe3O4@PDA@UiO-66-aptamer particles to the m-dSPE of PCB72 and PCB106 from soil samples, followed by their determination by GC–MS. Despite the high surface area of UiO-66, the modification of Fe3O4@PDA@UiO-66 particles with an amino-functionalized aptamer capable of recognizing the target analytes is shown to play a key role, providing much higher extraction efficiency than Fe3O4@PDA@UiO-66–NH2 or Fe3O4@PDA. Regarding the inclusion of other materials during the synthesis of magnetic MOFs, the use of carbon-based nanomaterials must be mentioned in the application of this kind of nanocomposite to the extraction of organic analytes. Thus, GO153 or MWCNTs157 have been included in the synthetic processes with different purposes, although the need of their inclusion is not always clearly justified. In this sense, it is interesting to discuss the work of Jalilian and co-workers,157 who employed Fe3O4@MWCNTs@MIL-101 as the sorbent for the m-dSPE of two parabens and three PAEs from different kinds of water and cosmetic cream samples. In this case, MWCNTs were introduced in order to increase the surface area, resulting in a higher extraction efficiency. The performances of Fe3O4 NPs, MIL-101, Fe3O4@MIL-101 and Fe3O4@MWCNTs@MIL-101 were evaluated, and the

Some applications of MOFs m-NPs in sample treatment.a

Sorbent (amount)

Analytes

Fe3O4@TGA@ TMU-6 (2 mg)

3 OPPs

Fe3O4@APTES-GO/ ZIF-8 (16 mg)

4 Triazole fungicides

Fe3O4@HKUST-1 (B25 mg)

8 PAHs

Magnetic calcined 5 PAHs MIL-100 (12.5 mg)

Fe3O4@MOF-5 (40 mg)

6 PCBs

Matrices (amount)

Previous sample pretreatment

Water samples were Shaft and tap waters and rice filtered. Rice samples were extracted with (25 mL) EtOH, diluted with water and adjusted to pH ¼ 6 Mineral and tap Honey samples were dissolved in water. waters, honey Fruit juices were and mango, centrifuged and the grape and supernatants were orange juices diluted with water (30 mL) Fruit tea infusions were Tap and waste prepared in boiling waters and water and filtered fruit tea infusion (20 mL) Water samples were Effluent waste filtered and adjusted and river to pH ¼ 6 waters (100 mL)

144

Table 5.3

Determination technique

Recovery (RSD)

Detection limits

HPLC–UV

88–107% (r7.1%)

0.5–1 mg L1

152 Analytes were desorbed with 1butanol (0.1 mL).

HPLC–DAD

71–111% (r6.9%)

0.01–0.11 mg L1

Analytes were desorbed with MeOH (0.5 mL).

UHPLC–FD

70–98% (r22%)

0.8–4.6 ng L1 Analytes were desorbed with ACN (0.5 mL).

GC-FID

86–107% (r10%)

149 4.6–8.9 ng L1 MIL-100 was calcined from 300 1C to 700 1C under a nitrogen flow. Analytes were desorbed with ACN (0.5 mL). 0.061–0.096 17 Modified m-NPs mg kg1 were applied in a SBSE procedure. Analytes were desorbed with n-hexane (2.5 mL).

93–97% ()

Reference

153

150

Chapter 5

GC–MS Fish samples were Sneakhead, homogenized and crucian carp extracted with and grass carp n-hexane, filtered and (10 mL) passed through an acidic silica cartridge, dried and reconstituted in water

Comments

2 PCBs

Soil (100 mL)

Fe3O4@MIL-101 (15 mg)

5 PAEs

Fe3O4@ MWCNTs@MIL101 (11.5 mg)

2 Parabens and 3 PAEs

Fe3O4@MOF (20 mg)

7 Estrogenic compounds

GC–MS Water samples were Tap and well filtered. Plasma waters and human plasma samples were deproteinized with (10 mL) HCl and TFA under vortex, centrifuged and diluted with water HPLC–DAD Tap and bottled Water samples were filtered. Cream waters and samples were firstly skin, sunblock dissolved in a mixture and foot of MeOH and water, creams adding HCl, under (18 mL) ultrasound. The solution was diluted with water Urine samples were HPLC–MS/MS Pregnant and diluted with water non-pregnant female urine (20 mL diluted sample)

a

155 A reference material was used to evaluate the accuracy of the methodology. Analytes were desorbed with n-hexane (5 mL). 156 Analytes were desorbed with n-hexane and acetone (1 : 1, v/v) (1 mL).

89–95% (r4%)

0.18–0.25 ng kg1

85–107% ()

0.08–0.15 mg L1

74–97% (r9.1%)

0.03–0.15 mg L1

81–112% (r6.7%)

0.2–7.7 ng L1 Analytes were 159 desorbed with ACN containing 0.01% of NH4OH (0.5 mL).

Analytes were desorbed with ACN (0.1 mL).

157

145

APTES: (3-aminopropyl) triethoxysilane; DAD: diode array detector; FD: fluorescence detector; FID: flame ionization detector; GC: gas chromatography; GO: graphene oxide; HKUST: Hong Kong University of Science and Technology; HPLC: high-performance liquid chromatography; MIL: Material of Institute Lavoisier; MOF: metal-organic framework; MS: mass spectrometry; MS/MS: tandem mass spectrometry; OPPs: organophosphorus pesticides; PAEs: phthalic acid esters; PAHs: polycyclic aromatic hydrocarbons; PCBs: polychlorinated biphenyls; pDA: polydopamine; RSD: relative standard deviation; SBSE: stir bar sorptive extraction; TGA: thioglycolic acid; TFA: trifluoroacetic acid; UHPLC: ultra-high-performance liquid chromatography; UV: ultraviolet; ZIF: zeolite imidazolate framework.

Application of Functionalized Magnetic Nanoparticles for Organic Analyte Extraction

GC–MS Soil samples were extracted with n-hexane, centrifuged, filtered, dried and redispersed in a phosphate buffer

Fe3O4@pDA@ UiO-66@aptamer (30 mg)

146

Figure 5.6

Chapter 5

Effect of the sorbent type on the extraction of parabens and phthalic acid esters from water and cream samples. Extraction conditions: sample pH, 7.0; sorbent amount, 10 mg; sample volume, 5 mL; eluent volume, 100 mL; eluent type, ACN; sorption time, 10 min; desorption time, 2 min; and without addition of NaCl. 1, 2, 3 and 4 refer to Fe3O4 NPs, MIL-101, Fe3O4@MIL-101 and Fe3O4@MWCNTs@MIL-101, respectively. Adapted from ref. 157 with permission from Elsevier, Copyright 2019.

results showed that Fe3O4@MWCNTs@MIL-101 provided the highest extraction efficiency toward the target analytes (Figure 5.6), which was attributed to the better dispersion in aqueous solutions, as well as the higher surface area, both given by the presence of MWCNTs. Finally, it is important to mention that, although magnetic MOFs have been mainly used as sorbents in m-dSPE procedures, they can also be found as coatings in microextraction devices to be applied in SPME16 or SBSE17 procedures. Despite the fact that it is not common to use magnetic nanomaterials in this kind of technique, it is doubtless that their magnetic properties pose an important simplification of the preparation procedure of such devices. This is the case of the work of Lin and co-workers,17 who carried out the synthesis of Fe3O4@MOF-5 and used them as the coating for a Nd–Fe–B rod, which was then used as the stir bar in a SBSE for the analysis six PCBs in sneakhead, crucian carp and grass carp. Despite the good extraction capacity that was shown, with recovery values in the range 93–97%, it is important to highlight that the application of this magnetic sorbent in a SBSE method instead of a m-dSPE one resulted in an increment of the extraction time.

5.5 Covalent Organic Framework Coatings Covalent organic frameworks (COFs) are a new class of highly porous ˆte ´ and co-workers.171 materials synthesized for the first time in 2005 by Co These new materials are ordered crystalline structures composed by the covalent bonding of organic monomers based on light elements (carbon, hydrogen, nitrogen, oxygen, etc.). It is possible to distinguish between two-

Application of Functionalized Magnetic Nanoparticles for Organic Analyte Extraction

147

dimensional (2D) and 3D COFs, depending on the 2D or 3D geometry of the organic monomers,172 with the latest having the higher surface areas, although they generally show lower crystallinities and porous homogeneity.173 Similarly to MOFs, COFs are characterized by very high porosity and high surface areas, which in some cases are comparable to those of MOFs, and the possibility of post-synthesis modification, although in this case lower densities are shown due to the absence of metallic atoms.173 Despite their recent introduction, COFs application has been explored in several fields, among which their use as sorbents has attracted the interest of the scientific community. In this sense, it is important to highlight that their combination with m-NPs to be used in m-dSPE procedures has become the main way of using them. Table 5.4 shows some examples of the application of COFmodified m-NPs as sorbents in sample preparation. As can be seen, despite the short course of this type of magnetic sorbents, the excellent physicochemical properties as well as proven versatility of COFs, have meant that magnetic COFs have been applied to the extraction of a broad spectrum of organic compounds, including PAHs,174–176 PCBs,177 PAEs,178–180 estrogenic compounds,159,181 pesticides182–184 and drugs,185,186 among others. These analytes have been extracted from matrices of a varied nature, including environmental water,175,187,188 soil,189 biological fluids,185,190 beverages180,191 or food,186,188,192 among others. Regarding the magnetization step, a wide number of synthetic routes have been proposed, very similar to the ones previously exposed for magnetic MOFs. Among them, the most popular has been based on in-situ growth strategies by suspending the m-NPs in the COF synthesis media, generally resulting in core–shell structures.177,180,187,198 However, the sequence has been inverted in some cases, and COFs have also been introduced in the m-NPs synthetic media, resulting in a COF with m-NPs distributed by its structure.184,187,195,199 In this sense, despite the fact that Ni,184,195 Fe2O3199 and CoFe2O4196 m-NPs have been used, Fe3O4 m-NPs have been once more the preferred option.192,197,198,200 A common practice involves the previous modification of m-NPs surface to improve the interaction between both COF and m-NPs, which can be achieved with the attachment of NH2 groups,198,201 SiO2187,190,191,198 or even polymeric coatings.179,194,202 In this sense, it is interesting to mention the work of He et al.193 In this case, the authors carried out the synthesis of a 3D bouquet-like COF structure (see Figure 5.7) based on 1,3,5-triformylphloroglucinol (Tp) and p-phenylenediamine (Pa) building blocks and used it as the coating for amino-functionalized Fe3O4 m-NPs. This particular sorbent was applied in a classical m-dSPE procedure for the extraction of six PAHs from river, lake and tap water samples. A combination of ultrasound and shaking guarantees the best dispersion of the sorbent into the sample, together with the higher porosity provided by the particular shape of this bouquet-shaped Fe3O4@NH2@COF, as well as its good extraction capacity and water stability, allowing the authors to obtain recovery percentages over 70% in all cases. Besides, the use of a HPLC–FD system resulted in high sensitivity, with LODs in the range of 0.24–1.01 ng L1.

Table 5.4 Some applications of COFs m-NPs in sample treatment.a Matrices (amount)

Previous sample pretreatment

Determination Recovery technique (RSD)

Detection limits

Fe3O4@ NH2@ COF (5 mg)

6 PAHs

Tap, lake and river waters (200 mL)

Water samples were filtered

HPLC–FD

0.24–1.01 ng L1

Fe3O4@PEI@ pDA@COF (5 mg)

Paclitaxel

Rat plasma (0.5 mL)

Ni/CTF (10 mg)

6 PAEs

Plastic bottles, a disposable plastic cup and boiling water previously contained in the plastic recipients (20 mL)

Fe3O4@COF (5 mg)

15 PAHs

Smoked pork, wild fish, grilled fish, smoked bacon,

HPLC–UV Blood samples were centrifuged. Then plasma was deproteinized with TAC, centrifuged, adjusted to pH ¼ 6 and diluted with a 10 mM phosphate buffer and ACN Plastic bottles or cups GC–FID were firstly cut into small pieces and extracted with MeOH, adjusted to pH ¼ 7 and diluted with water. Boiling H2O was put in contact with plastic containers to let it cool down inside (about 1 h) HPLC–DAD Meat samples were hydrolyzed, extracted with a can and

73–110% (r8%)

99.4–103.7% 0.02 mg L1 (2.3%)

Comments

Reference

193 The synthesis procedure allowed obtaining a bouquet-shaped magnetic COF, with a large surface area and porosity. Analytes were desorbed with ACN (34 mL). 194 7 PAHs were also extracted in order to evaluate the adsorption behavior of the sorbent. Analytes were desorbed with ACN (0.2 mL).

Plastic materials: 85.8–119% (r1.01%) Water: 83.2–113% (r1.01%)

Plastic materials: 0.024–0.085 mg g1 Water: 0.15–0.53 mg L1

195 Analytes were desorbed with acetone (0.15 mL).

84.3  107.1% (r4.3%)

0.83–11.70 ng L1

Analytes were desorbed with ACN (1 mL).

175

Chapter 5

Analytes

148

Sorbent (amount)

CoFe2O4@ CNT@COF (15 mg)

9 HAAs

Analytes were desorbed with MeOH (4 mL).

196

3 Estrogens and 3 phenolic compounds Fe3O4@SiO2@ 6 Nicotinoid Cucumber and COF (10 mg) insecticides lettuce (50 mL extract)

89.6–108.9% 1.4–8.7 mg L1 Analytes were (r6.1%) desorbed with ACN (1 mL).

181

77.5–110.2% 0.02-0.05 (r8.8%) mg L1

Analytes were desorbed with ACN (20.1 mL).

183

Fe3O4@PSA@ 20 OPPs COF (40 mg)

75.9–103.0% 0.002–0.063 (r12.3%) mg kg1

Grape was used as the matrix for method optimization. Analytes were desorbed with ACN (5 mL).

197

Fe3O4@COF (10 mg)

a

HPLC–UV Edible parts of vegetable samples were blended and extracted with ACN thrice UHPLC–MS/ Watermelon, peach Samples were homogenized and MS and orange (40 mL extracted using the extract) first stage of the QuEChERS method (10 g sample, 10 mL ACN, 1.5 g NaCl and 4 g anhydrous MgSO4). Final extract was diluted with water before m-dSPE

73.0–117.0% 0.0058–0.025 (r9.1%) mg kg1

149

ACN: acetonitrile; CNT: carbon nanotube; COF: covalent-organic framework; CTF: covalent triazine framework; DAD: diode array detector; FD: fluorescence detector; FID: flame ionization detector; GC: gas chromatography; HAAs: heterocyclic aromatic amines; HPLC: high-performance liquid chromatography; m-dSPE: magnetic dispersive solid-phase extraction; MeOH: methanol; MS/MS: tandem mass spectrometry; OPPs: organophosphorus pesticides; PAE: phthalic acid ester; PAH: polycyclic aromatic hydrocarbon; pDA: polydopamine; PEI: polyethyleneimine; PSA: N-[3-(trimethoxysilyl)propyl]ethylenediamine; QuEChERS: quick, easy, cheap, effective, rugged, and safe; RSD: relative standard deviation; UHPLC: ultra-high-performance liquid chromatography; TCA: trichloroacetic acid; UV: ultraviolet.

Application of Functionalized Magnetic Nanoparticles for Organic Analyte Extraction

diluted. Coffee samples were put in contact with hot pure water before extraction Samples were cut into UHPLC–MS/ Fried chicken and small pieces, digested MS roast beef (10 mL with NH4OH and extract) MeOH (7 : 3, v/v) thrice and extracted with n-hexane several times Chicken, shrimp and Samples were extracted HPLC–FD pork (10 mL extract) with acetone coffee and river water (10 mL extract)

150

Figure 5.7

Chapter 5

SEM images of the Fe3O4@NH2 (a) and Fe3O4@NH2@COF (c); TEM images of the Fe3O4@NH2 (b) and Fe3O4@NH2@COF (d); (e) photo of gypsophila bouquet; (f) FTIR spectra of the Fe3O4@NH2, COF, and Fe3O4@NH2@COF; (g) nitrogen adsorption– desorption isotherm of the bouquet-shaped Fe3O4@NH2@COF, inset: pore-size distribution of this nanocomposite; (h) magnetization hysteresis loops of the Fe3O4@NH2 and Fe3O4@NH2@COF. Reproduced from ref. 193 with permission from American Chemical Society, Copyright 2017.

Application of Functionalized Magnetic Nanoparticles for Organic Analyte Extraction

151

It is also worth mentioning that although COF-modified m-NPs have shown excellent extraction capacity in multiple applications, they have also been combined with carbon-based nanomaterials in order to take advantage of the already mentioned excellent properties and good behavior as sorbents in sample preparation.179,196 As a good example of that, Liang and co-workers196 proposed the application of CoFe2O4@CNT@COF m-NPs for the extraction of nine heterocyclic aromatic amines (HAAs) from meat samples, and their subsequent determination by UHPLC–MS/MS. For the synthesis of this sorbent, hydroxylated CNTs were suspended in an ethanolic solution of Fe(NO3)3 and Co(NO3)2 and subjected to ultrasound. Then the mixture was dried at 60 1C, increasing the temperature up to 100 1C for 2 h and finally up to 550 1C for a further two hours in order to obtain the CoFe2O4-filled CNTs shown in Figure 5.8, which were the base to obtain the final sorbent via a photochemical method. For this purpose, magnetic CNTs, and the building blocks cyclotricatechylene (CTC) and benzene-1,4-diboronic acid (BDBA) were hermetically sealed in a quartz bottle. Once an inert atmosphere was achieved by flushing nitrogen into the bottle,

Figure 5.8

The SEM (a and b) and TEM (c and d) spectra of CNTs (a), magnetic CNT (c) and CoFe2O4@CNT@COF (b and d). Reproduced from ref. 196 with permission from Elsevier, Copyright 2020.

152

Chapter 5

APTES and a 1,4-dioxane : mesitylene 1 : 1 (v/v) solution were added, applying ultrasound for 1 h and UV radiation during 48 h. Finally, the sorbent was filtered, washed with acetone and dried, obtaining the final sorbent ready to be used. The sorbent was characterized and compared to CTC–COF, observing that CoFe2O4@CNT@COF showed a much higher Brunauer–Emmett–Teller (BET) surface area, presumably due to the presence of CNTs, which also contribute to a better dispersion of the CTC–COF. Regarding the extraction performance, the sorbent showed excellent recovery values (73–117%), obtaining LODs in the range of a few ng g1 in all cases.

5.6 Ionic Liquids Since ILs were first synthesized in 1914 by Paul Walden,203 hundreds of them have been designed, synthesized, analyzed, and used. These compounds constitute a group of salts formed by organic cations and organic or inorganic anions, which have been used as ‘‘green’’ extraction solvents due to their unique physical and chemical properties, such as melting points below 100 1C, good solubility, negligible vapor pressure at room temperature and high thermal stability. In addition, they have excellent solvation properties, a high extraction capacity and easy modification of their structures, which has allowed the synthesis of ILs with specific properties so that they can be used as extraction phases in analytical sample preparation methods.204,205 Very frequently, ILs are in a liquid state, so their combination with other solid materials is required to obtain highly useful sorbents in SPE and also in m-dSPE. For this reason, IL-coated m-NPs (IL-m-NPs), which combine the properties of both elements, have been synthesized. This coating has been made by chemical or physical immobilization methods, but greater stability is achieved through covalent bonds, avoiding their loss in the extraction and elution processes.206 Commonly, once the m-NPs are synthesized, the NPs are first coated with a compound that allows IL binding. For this purpose, SiO2 coatings have been the most used due to its high chemical stability and its great capacity to modify the surface of the NPs with silanol groups that allows the union to different ILs.206–210 Nonetheless, negatively charged polymers like polyaniline (PANI),211 or MOFs like zeolite imidazolate framework-8 (ZIF-8)212 have also been used, since both interact strongly with the cations of ILs211,213 and present some advantages such as good thermal stability, ease of synthesis and commercial availability. Finally, the linking of the ILs takes place, though some works also include a final anion exchange reaction at the end of the procedure.206,208 With regard to the nature of ILs, imidazolium-based ILs have been the most widely used, as can be seen in the studies shown in Table 5.5 (which compile some examples of the application of IL-m-NPs as sorbents)206,208,210,212,214 due to their extensive commercial availability and ease of preparation.204 As an example, Chen and Zhu210 synthesized three ILs including 1-butyl-3methylimidazole hexafluorophosphate ([BMIM]PF6), 1-hexyl-3-methylimidazole hexafluorophosphate ([HMIM]PF6), and 1-octyl-3-methylimidazole hexafluorophosphate ([OMIM]PF6). These IL-coated m-NPs were evaluated by the extraction

Some applications of IL m-NPs in sample treatment.a

Sorbent (amount)

Analytes

Previous sample pretreatment

Determination Recovery technique (RSD)

Detection limits

Tap, river, well and — reservoir waters (100 mL) Milk (20 mL) —

GC–MS

75.0–102.0% 0.04–1.11 (r8.9%) mg L1

UHPLC–MS/ MS

79.0–102.5% 0.0023– (r7.7%) 0.0081 mg L1

HPLC–MS/MS

88.0–99.0% (r8.3%)

4 Pharmaceuticals

— River, sea and swimming pool waters (100 mL) Tap, river and dam — waters (10 mL)

HPLC–UV/FD

84.7–116.2% 3.2–7.2 (r9.9%) mg L1

5 Penicillins

Milk (25 mL)

Fe3O4@SiO2@ 13 PAHs [MIM]PF6 (30 mg) Fe3O4@ZIF-8@ 4 Aflatoxins [BMIM]Br (90 mg) Fe3O4@SiO2@ 11 EDs [MIM]PF6 (10 mg) m-CNP@ [BMIM]PF6 (50 mg m-CNPs plus 150 mL mixture of [BMIM]PF6 (50 mL) and MeOH (100 mL)) Fe3O4@SiO2@ [DABCO-C3OH]Cl (22 mg)

Matrixes (amount)

Milk was acidified UHPLC–MS/ MS with polyhydrated phosphotungstic acid, glacial acetic acid, zinc acetate and ACN for protein precipitation and diluted

0.16–1.21 mg L1

86.9–107.3% 0.03–0.20 (r5.8%) mg kg1

Comments

Reference

Analytes were desorbed with MeOH (0.5 mL). Analytes were desorbed with ACN and DCM (1 : 1, v/v) (21 mL). Analytes were desorbed with MeOH (0.5 mL). Analytes were desorbed with 0.5 M phosphate buffer (0.25 mL).

208

Analytes were desorbed with MeOH 3% formic acid (0.5 mL). PICd5 was used as IS.

209

212

206 214

Application of Functionalized Magnetic Nanoparticles for Organic Analyte Extraction

Table 5.5

153

154

Table 5.5

(Continued)

Sorbent (amount)

Analytes

Matrixes (amount)

Previous sample pretreatment

Determination Recovery technique (RSD)

Linuron

UV spectroLake water, lettuce The water sample metry and apple (40 mL) was filtered. Lettuce and apple were extracted with EtOH, centrifuged and filtered

Fe3O4@PANI@ [DICAT][NTf2] (15 mg)

5 PAHs

River, lake, well, paddy and tap waters, sludge and soil (30 mL)

Fe3O4@SiO2@ poly[VHIM]Br (60 mg)

4 OPPs

The water samples were filtered. The sludge and soil samples were extracted with MeOH, centrifuged, filtered and diluted Green, jasmine and — ice teas (25 mL)

1

95.0–101.0% 5 mg L (2.8%)

GC–MS

80.2–111.9% 0.0008– (r14.9%) 0.2086 mg L1

HPLC–UV

81.4–112.6% 0.01 mg L1 (r11.3%)

Comments

Reference

Analytes were 210 desorbed with EtOH (4 mL). Fe3O4@SiO2@ [OMIM]PF6 showed higher extraction efficiency than Fe3O4, SiO2, Fe3O4@ SiO2, Fe3O4@ SiO2@ [BMIM]PF6 and Fe3O4@ SiO2@ [HMIM]PF6. Analytes were 211 desorbed with ACN (1.5 mL). Fe3O4 @PANI@[DICAT] [NTf2] showed higher extraction efficiency than Fe3O4 and Fe3O4@ PANI. 215 Analytes were desorbed with MeOH (2 mL).

Chapter 5

Fe3O4@SiO2@ [OMIM]PF6 (100 mg)

Detection limits

4 Triazole fungicides

Lake, river and well Samples were waters (50 mL) filtered

Fe3O4@SiO2@ poly[VHIM]Br (50 mg)

Allura red pigment

Candies and fruit juice (40 mL)

Fe3O4@SiO2@ poly[VOIM]PF6 (10 mg)

3 Antidiabetic Human plasma drugs (5 mL)

a

HPLC–DAD

The candy samples Fluorescence spectrowere ground into photometry powder, dissolved and filtered. The fruit juice samples were diluted HPLC–UV The sample was deproteinized with ACN

75.1–120.0% 0.0050– (r10.8%) 0.0078 mg L1

97.4–120.8% 2 mg L1 (0.51%)

– (r8.5%)

0.8–6.0 mg L1

216 Analytes were desorbed with EtOH (0.5 mL). g-MAPS was used to modify the surface of Fe3O4@SiO2 to enhance the stability of PIL coating. 217 Analytes were desorbed with a SDS solution (4 mL). 218 Analytes were desorbed with ACN (20.5 mL).

g-MAPS: 3-(trimethoxysilyl)-propylmethacrylate; ACN: acetonitrile; BMIM: 1-butyl-3-methylimidazole; DABCO-C3OH: 1-(3-hydroxypropyl)-1,4-diazabicyclo[2.2.2]octane; DAD: diode array detection; DB: divinylbenzene; DCM: dichloromethane; DICAT: dicationic ionic liquid; ED: endocrine disrupting compounds ER: extraction recovery; EtOH: ethanol; FD: fluorescence detector; GC: gas chromatography; HMIM: 1-hexyl-3-methylimidazole; HPLC: high-performance liquid chromatography; IS: internal standard; MAI: 1-methyl-3-allylimidazole; m-CNP: magnetic cellulose nanoparticle; MeOH: methanol; MIM: methylimidazole; MS: mass spectrometry; MS/MS: tandem mass spectrometry; ZIF: zeolite imidazolate framework; NTf2: bis(trifluoromethylsulfonyl)imide; OMIM: 1-octyl-3-methylimidazole; OPP: organophosphorus pesticide; PAH: polycyclic aromatic hydrocarbon; PANI: polyaniline; PCP: personal care product; PIC-d5: deuterated piperacillin; PIL: poly(ionic liquid); RSD: relative standard deviation; SDS: sodium dodecyl sulfonate; UHPLC: ultra-high-performance liquid chromatography; UV: ultraviolet; VHIM: 1-vinyl-3-hexylimidazole.

Application of Functionalized Magnetic Nanoparticles for Organic Analyte Extraction

Fe3O4@ SiO2@ MAI-DB (20 mg)

155

156

Chapter 5

of linuron from water and food samples. The results showed higher extraction efficiencies for the target analyte with Fe3O4@SiO2@[OMIM][PF6]. LOD, recovery values and RSDs were found to be 5 mg L1, 95.0–101.0% and 2.8%, respectively. Another example in which the IL is linked to a MOF that acts as an initial coating is the work of Gao and co-workers212 who developed a m-dSPE method to extract 4 aflatoxins from milk samples by UHPLC–MS/MS. They used the IL 1-butyl-3methylimidazolium bromide ([BMIM]Br) to modify magnetic ZIF-8 (m-ZIF-8), obtaining extraction efficiencies for the analytes between 79.0 and 102.5%, with RSDs ranged from 2.5 to 7.7%. The LOD values were determined to be 0.0023–0.0081 mg L1 and the LOQs were 0.0075–0.0267 mg L1. However, other ILs have also been used, such as the dicationic IL synthesized by Shahriman and co-workers211 by reacting 2,5-dichloro-p-xylene and 1-benzylimidazole, with which they subsequently coated the previously synthesized polymeric coated m-NPs, in this case with PANI. With this sorbent they extracted 5 PAHs from environmental water, sludge and soil samples. These solid samples, after air drying, grinding and sieving, were extracted by ultrasound for 10 min using MeOH as the extraction solvent. After centrifugation and filtration, they were analyzed by GC–MS. The developed method provided good LODs (between 0.0008 and 0.2086 mg L1) and extraction recovery values in the range 81.7–104.6% for water samples and 80.2–111.9% for solid samples, with RSDs below 14.9% and 8.7%, respectively. Another example is the eco-friendly IL 1,4-diazabicyclo[2.2.2]octane (DABCO) with which Sahebi and co-workers209 modified m-NPs of Fe3O4 and used 22 mg of this new sorbent for the extraction of 5 penicillins from milk samples. It should be noted that they utilized m-mSPE in the extraction technique, due to the small amounts of sorbent used. The recovery values obtained were between 86.9 and 107.3% with high precision (RSDs in the range 1.9–5.8%). The sensitivity of the developed method was evaluated, obtaining LOD values ranging from 0.03 to 0.20 mg kg1. In addition, some derivatives of ILs have been designed, such as polymeric ILs (PILs) and magnetic ILs (m-ILs), with the aim of expanding the field of application of these compounds by combining the characteristics of ILs with those of other materials. PILs are stable structures made up of hundreds of covalently bonded monomers, which have also been used as sorbents in m-dSPE,216,218 with the most used being the monomer IL 1-vinyl-3hexylimidazolium bromide.215,217 This innovative class of polyelectrolytes combines the properties of ILs and polymers215 and is generally synthesized directly on the m-NPs by free radical copolymerization methods.215–218 Table 5.5 shows some examples of the application of PIL-coated m-NPs for the extraction of organic analytes, such as fungicides,216 drugs,218 OPPs,215 or pigments,217 in different matrices (environmental waters,216 human plasma,218 teas,215 and candies217). On the other hand, m-ILs were first generated relatively recently, since the first m-IL synthesized was 1-butyl-3methylimidazolium tetrachloroferrate [BMIM]FeCl4 in 2001,219 but its magnetic properties were not known until 2004.220 These materials have a metal ion incorporated into the structure of the ILs. Therefore, when they are subjected to an external magnetic field, they exhibit paramagnetic behavior,

Application of Functionalized Magnetic Nanoparticles for Organic Analyte Extraction

157 221,222

so that their adsorption on magnetic materials is not necessary. However, it is thought that m-NPs can be added to increase the magnetic properties of m-ILs.223 Some studies in which ILs and PILs have been used to functionalize m-NPs have also carried out sorbent reutilization studies. In IL-based m-NPs, between 5209,211 and 10208,210 cycles of the m-dSPE procedure are indicated without significant losses in adsorption capacity, while with PIL-based m-NPs, up to 14218 and 20215 cycles are achieved. However, special care must be taken with the possible carry-over effects that may arise from the reuse of sorbents.

5.7 Miscellaneous In addition to all the compounds previously described for the functionalization of m-NPs, surfactants, inorganic coatings, aptamers and g-C3N4, among others, they have also been used in a good number of occasions. Surface-active agents or surfactants are adsorbed on the m-NPs through electrostatic attraction or hydrophobic interactions and they can be anionic, like sodium dodecyl sulfate (SDS),224,225 cationic, like cetyltrimethylammonium bromide (CTAB)226,227 and cetylpyridinium chloride (CPC),228 or non-ionic,229 being the most used cationic surfactants and, in particular, CTAB. Surfactantcoated m-NPs have been employed in the determination of various target analytes, such as emerging micropollutants,230 selective serotonin reuptake inhibitor,224 chlorophenols,227 parabens,229 phenolic compounds,228 and nonsteroidal anti-inflammatory drugs (NSAIDs),226 from aquatic224,227–230 and biological samples,224–226 as can be seen in Table 5.6. Inorganic materials can also act as a protective cover of m-NPs, which is why m-NPs have been functionalized with silicon dioxide, the most common, because it forms an inert layer with a high chemical stability. It also has a high mechanical and thermal stability, it is biocompatible, has low toxicity, and is capable of adding other specific binders due to the fact that it functionalizes the surface of the m-NPs with silanol groups that allow it to have a wide application in different fields.207 On the other hand, metallic oxide/sulfides and metals have also been used as coatings, which show different effects on the magnetization saturation value of m-NPs depending on the metal used.207 Recently, aptamer-based coating sorbents have also had important development and application in this field. Aptamers are artificial, specific, single-stranded nucleic acids (DNA or RNA) that show a high selective extraction of analytes because they have a certain sequence of bases, which can be bonded programmatically and arbitrarily modified.231 Some examples where aptamer functionalized m-NPs have been used are the extraction and preconcentration of mycotoxins from food samples,232,233 bisphenol A (BPA) and PCBs from biological fluids,177,234 or PCBs from soils,235 as can be seen in Table 5.6. Another material that is now emerging as a promising coating of m-NPs is g-C3N4, which is a G analog made of layered sheets of tris-triazine connected double-sided polyaromatic scaffold, which results in a defect-rich

Table 5.6

Some applications of different m-NPs in sample treatment.a

Analytes

Sample pretreatment

The water samples Tap and river were filtered. The waters and urine samples human urine were centrifuged (50 mL) and diluted Samples were 4 Chlorophe- River, tap, Fe3O4@CTAB filtered nols waste and (100 mg m-NPs ground and 60 mg CTAB) waters (700 mL) Samples were Tap, ground, Fe3O4@SiO2@CPC 3 Phenolic filtered compounds river and (100 mg m-NPs waste waters and 50 mg CPC) (800 mL)

Fe3O4@SDS (11.5 mg m-NPs and 5 mg SDS)

Fluoxetine

Mefenamic Fe3O4@CTAB acid (50 mg m-NPs and 15 mg CTAB)

Recovery (RSD)

Detection limits 1

Comments

Reference

Fluorescence spectrophotometry

80.0–104.0% (1.4%)

20 mg L

Analytes were desorbed 224 with MeOH (1.5 mL).

HPLC–UV

83.0–98.0% (r5.9%)

0.11–0.15 mg L1

Analytes were desorbed 227 with MeOH (31.5 mL).

HPLC–FD

66.0–106.0% (r6.0%)

0.007–0.020 mg L1

HPLC–UV

92.2–99.1% (r4.1%)

0.087–0.097 mg L1

Analytes were desorbed 228 with ACN 1% HOAc (31 mL). Fe3O4@SiO2@CPC showed slightly higher extraction efficiency than Fe3O4@SiO2@CTAB. Analytes were desorbed 226 with MeOH (21 mL).

Fluorescence spectrophotometry

79.4–90.4% (r3.6%)

0.74–0.85 mg L1

Analytes were desorbed 225 with MeOH (5 mL).

Chapter 5

Propranolol Fe3O4@SDS (0.02 mg m-NPs and 0.13 mg SDS)

Human plasma The blood samples were centrifuged and urine and plasma was (200 mL) withdrawn. Urine samples were centrifuged. If necessary, both samples were diluted Human plasma The blood samples were centrifuged and urine and plasma was (1.0 mL of withdrawn. Urine plasma and samples were 0.5 mL of centrifuged urine)

Determination technique

158

Sorbent (amount)

Matrixes (amount)

2.4–6.3 mg L1

HPLC–FD Human serum Samples were vortexed and and urine centrifuged with b(0.5 mL of glucosidase and serum and 1 mL of urine) sulfatase HPLC–MS Human serum The sample was (1 mL) diluted with a mixture of water/ formic acid/2propanol (50 : 40 : 10, v/v/v) for protein denaturation

90.8–92.3% (r7.3%)

1.0–2.0 mg L1

87.7–101.5% (r0.8%)

0.0021 mg L1

Cornmeal (15 g)

91.3–99.1% (r4.2%)



4 Parabens

River, sea and lake waters (80 mL)

Fe3O4@SiO2@ ssDNA (5 mg)

BPA

Fe3O4@SiO2@ COF@ Apt-15 (30 mg)

2-OH-CB 124

Fe3O4@CTS@AptNP (0.1 g)

Ochratoxin A

Samples were filtered



HPLC–UV

HPLC–FD

Analytes were desorbed 229 with MeOH(0.28 mL). Fe3O4@SiO2@ DC193C showed slightly higher extraction efficiency than Fe3O4 and Fe3O4@SiO2. Analytes were desorbed 234 with ACN and TE buffer (1 : 1, v/v) (1 mL).

159

Analytes were desorbed 177 with hexane and ethyl acetate (1 : 1, v/v) (0.4 mL). Fe3O4@ SiO2@COF@Apt-15 showed slightly higher extraction efficiency than Fe3O415, Fe3O4-150 and Fe3O4@SiO2@COF@ Apt-150. 2-OH-CB 124 showed superior extraction efficiency compared to other three OH-PCBs. Analytes were desorbed 232 with MeOH/Tris– EDTA buffer/HCl (70 : 28 : 2, v/v/v) (3 mL). Sample cleaned-up by immunoaffinity chromatography was also performed. No significant differences were

Application of Functionalized Magnetic Nanoparticles for Organic Analyte Extraction

86.0–118.0% (r15.9%)

Fe3O4@SiO2@ DC193C (20 mg)

Table 5.6

(Continued)

Analytes

Fe3O4@SiO2@AptNP (8 mg)

Aflatoxin M1

Milk (3 mL)

Fe3O4@AuNPs@HB-Apt (10 mg)

2 PCBs

Soil (10 g)

a

Sample pretreatment

Determination technique

Milk was mixed with HLPC–FD hexane and MeOH/water 8 : 2 (2 mM NaCl), shaken and filtered GC–MS The sample was dried at room temperature, pulverized and made into a powder of about 200 mesh

Recovery (RSD)

Detection limits

97.0–116.0% (r14.0%)

0.0002 mg L1

90.4–96.4% (r6.53%)

0.003–0.005 mg kg1

Comments

Reference

160

Sorbent (amount)

Matrixes (amount)

found in the ERs, but the extraction time was much shorter in the magnetic separation. Analytes were desorbed 233 with DCM/MeOH/ HOAc (80 : 19 : 1, v/v/v) (2 mL). Analytes were desorbed 235 with EtOH (1 mL). HS-SBSE was performed. The coating could be reused at least 60 times before recovery values of the PCBs dropped below 90%. Fe3O4@Au-NPs@HBApt showed higher extraction efficiency than and Fe3O4, Fe3O4@AuNPs@primer and Fe3O4@Au-NPs@Apt.

Chapter 5

2-OH-CB 124: hydroxy-2 0 ,3 0 ,4 0 ,5,5 0 -pentachlorobiphenyl; ACN: acetonitrile; Apt: aptamer; BPA: bisphenol A; COF: covalent organic framework; CPC: cetylpyridinium chloride; CTAB: cetyltrimethylammonium bromide; CTS: chitosan; DC193C: silicone–ethylene-oxide copolymer; DCM: dichloromethane; EDTA: ethylenediaminetetraacetic acid; ER: extraction recovery; EtOH: ethanol; FD: fluorescence detector; GC: gas chromatography; HOAc: acetic acid; HB-Apt: hyperbranched aptamer; HPLC: high-performance liquid chromatography; HS-SBSE: headspace bar sorptive extraction; MeOH: methanol; m-NPs: magnetic nanoparticles; MS: mass spectrometry; NP: nanoparticle; PCBs: polychlorinated biphenyls; RSD: relative standard deviation; SDS: sodium dodecyl sulfate; ssDNA: single-strand deoxyribonucleic acid; TE: Tris-EDTA; UV: ultraviolet.

Application of Functionalized Magnetic Nanoparticles for Organic Analyte Extraction

161

and N-bridged molecular structure. Therefore, g-C3N4 exhibits Lewis base behavior, hydrogen bonding and an extensive p-electron system for adsorption of organic analytes in both sides of the planar sheets. Moreover, it shows better solubility with aqueous phases and good stability at extreme pH. Fe3O4@g-C3N4 has been synthetized from simple precursors under ambient conditions at low cost via coprecipitation,236,237 simple physically blending238 or solvothermal strategy.86 Due its advantages, Fe3O4@g-C3N4 has exhibited very recent and increasingly extractability for the extraction of PAEs,85 PAHs,86,236,239,240 PCBs237 and BFRs241 in various organic analysis fields. Since Fe3O4@g-C3N4 offered a good performance, it has great potential in the fabrication of related functionalized or hybrid materials for the extraction of other organic analytes from complex matrices. Apart from the previously mentioned functionalized/coated m-NPs it should be highlighted that some of them have also been combined with different materials forming the so-called magnetic nanocomposites.242 As previously mentioned, it should be taken into account that when composites are used as sorbents, it is necessary to first evaluate the extraction capacity of each of its components separately.

5.8 Conclusions Nowadays, it is without doubt that m-NPs play an important role in the analytical chemistry field, especially in sample preparation, due to the fact that they simplify enormously this sometimes tedious and extremely timeconsuming step. The fact that a wide variety of coatings, as well as a good number of composites, can be relatively easily obtained, has clearly widened their application to the extraction of a large variety of analytes (especially organic compounds) and matrices. The application of m-NPs in sample preparation requires suitable characterization of the sorbents using different surface characterization techniques, and the demonstration of the extraction efficiency of such materials, including inter-batch studies, which are crucial. Of particular importance is also the demonstration of the effectiveness of a composite compared to their constituents which is not so frequently tackled in the literature. Polymeric coatings are amongst the most popular ones as a result of their varied nature, followed by those based on the allotropic forms of carbon, which have also been highly used, though mainly for the extraction of apolar analytes. MOFs and COFs coatings, together with those based on ILs, are also gaining importance, and soon, it is quite probable that more new approaches will also appear with interesting and challenging applications, since this is a hot and dynamic research field.

Abbreviations ACN APTES

acetonitrile (3-aminopropyl) triethoxysilane

162

BDBA BET BMIM BPA BRs BUs CHS CNFs CNTs COFs CPC CTAB CTC DABCO DES dSPE EDBs FQs G GC g-C3N4 GO HAAs HMIM HPLC ILs LOD MAAs m-ILs m-NPs m-G m-GO MOFs m-rGO MS MS/MS m-dSPE m-MWCNTs MWCNTs NDs NSAIDs OMIM OPPs PAEs PAHs PANI

Chapter 5

benzene-1,4-diboronic acid Brunauer–Emmett–Teller 1-butyl-3-methylimidazolium bisphenol A endogenous brassinosteroids benzoylurea insecticides chitosan carbon nanofibers carbon nanotubes covalent organic frameworks cetylpyridinium chloride cetyltrimethylammonium bromide cyclotricatechylene 1,4-diazabicyclo[2.2.2]octane deep eutectic solvent dispersive solid-phase extraction endocrine-disrupting bisphenols fluoroquinolones graphene gas chromatography graphitic carbon nitride graphene oxide heterocyclic aromatic amines 1-hexyl-3-methylimidazole high-performance liquid chromatography ionic liquids limit of detection monocyclic aromatic amines magnetic ionic liquids magnetic nanoparticles magnetic graphene magnetic graphene oxide metal organic frameworks magnetic reduced graphene oxide mass spectrometry tandem mass spectrometry magnetic dispersive solid-phase extraction magnetic multiwalled carbon nanotubes multiwalled carbon nanotubes nanodiamonds anti-inflammatory drugs 1-octyl-3-methylimidazole organophosphorus pesticides phthalic acid esters polycyclic aromatic hydrocarbons polyaniline

Application of Functionalized Magnetic Nanoparticles for Organic Analyte Extraction

PCBs PDA PEF-M PILs PPD PTPA RSD rGO SAs SBSE SPME SWCNTs TGA UHPLC

163

polychlorinated biphenyls polydopamine pefloxacin mesylate polymeric ionic liquids poly(m-phenylenediamine) triphenylamine based porous organic polymer relative standard deviation reduced graphene oxide sulfonamides stir-bar sorptive extraction solid-phase microextraction single-walled carbon nanotubes thioglycolic acid ultra-high-performance liquid chromatography

Acknowledgements J.G.S. would like to thank ‘‘Cabildo de Tenerife’’ for the Agustı´n de Betancourt contract at the Universidad de La Laguna.

References 1. W. Park, H. Shin, B. Choi, W.-K. Rhim, K. Na and D. Keun Han, Prog. Mater. Sci., 2020, 114, 100686. ¨th, Angew. Chem., Int. Ed., 2007, 46, 2. A.-H. Lu, E. L. Salabas and F. Schu 1222–1244. 3. A. A. Nayl, A. I. Abd-Elhamid, A. Y. El-Moghazy, M. Hussin, M. A. Abu-Saied, A. A. El-Shanshory and H. M. A. Soliman, Trends Environ. Anal. Chem., 2020, 26, e00087. 4. L. Xu, X. Qi, X. Li, Y. Bai and H. Liu, Talanta, 2016, 146, 714–726. ´lez-Sa ´lamo, J. Herna ´ndez-Borges and 5. B. Socas-Rodrı´guez, J. Gonza ´. Rodrı´guez-Delgado, TrAC, Trends Anal. Chem., 2017, 96, 172–200. M. A ´. Gonza ´lez-Sa ´lamo, D. A. Varela-Martı´nez, C. Cairo ´s, M. A ´lez6. J. Gonza ´ndez-Borges, LG-GC North Am., 2019, 37, 22–27. Curbelo and J. Herna ¨yu ¨ktiryaki, R. Keçili and C. M. Hussain, ed. C. M. Hussain, 7. S. Bu Elsevier, 2020, pp. 29–40. 8. P. H. Towler, J. D. Smith and D. R. Dixon, Anal. Chim. Acta, 1996, 328, 53–59. ´ and I. ˇ 9. M. ˇ Safarˇ´kova ı Safarˇ´k, ı J. Magn. Magn. Mater., 1999, 194, 108–112. ´n Bernardo, 10. A. I. Corps Ricardo, F. Abujaber, F. J. Guzma ´. Rı´os, Trends Environ. Anal. R. C. Rodrı´guez Martı´n-Doimeadios and A Chem., 2020, 27, e00097. 11. H.-L. Jiang, N. Li, L. Cui, X. Wang and R.-S. Zhao, TrAC, Trends Anal. Chem., 2019, 120, 115632.

164

Chapter 5

´ski, A. M. Bevanda, S. Talic´, 12. A. Kurowska-Susdorf, M. Zwierz˙dz˙yn ´ A. Ivankovic and J. P"otka-Wasylka, TrAC, Trends Anal. Chem., 2019, 111, 185–196. 13. A. Ga"uszka, Z. Migaszewski and J. Namies´nik, TrAC, Trends Anal. Chem., 2013, 50, 78–84. ¨yu ¨ktiryaki, I_ . Dolak and C. M. Hussain, ed. C. M. 14. R. Keçili, S. Bu Hussain, Elsevier, 2020, pp. 75–95. 15. A. K. da Silva, T. G. Ricci, A. L. de Toffoli, E. V. S. Maciel, C. E. D. Nazario and F. M. Lanças, ed. C. M. Hussain, Elsevier, 2020, pp. 77–98. 16. H. Lan, N. Gan, D. Pan, F. Hu, T. Li, N. Long, H. Shen and Y. Feng, J. Chromatogr. A, 2014, 1365, 35–44. 17. S. Lin, N. Gan, L. Qiao, J. Zhang, Y. Cao and Y. Chen, Talanta, 2015, 144, 1139–1145. ¨yu ¨ktiryaki, R. Keçili and C. M. Hussain, TrAC, Trends Anal. Chem., 18. S. Bu 2020, 127, 115893. 19. C. M. Hussain, in Advanced Environmental Analysis: Applications of Nanomaterials, The Royal Society of Chemistry, 2017, vol. 2, pp. 1–13. 20. W. Wu, Z. Wu, T. Yu, C. Jiang and W.-S. Kim, Sci. Technol. Adv. Mater., 2015, 16, 23501. 21. X.-S. Li, G.-T. Zhu, Y.-B. Luo, B.-F. Yuan and Y.-Q. Feng, TrAC, Trends Anal. Chem., 2013, 45, 233–247. 22. L. Xie, R. Jiang, F. Zhu, H. Liu and G. Ouyang, Anal. Bioanal. Chem., 2014, 406, 377–399. 23. F. Ridi, M. Bonini and P. Baglioni, Adv. Colloid Interface Sci., 2014, 207, 3–13. 24. M. Eid, J. Polym. Res., 2013, 20, 112. 25. S. C. McBain, H. H. P. Yiu and J. Dobson, Int. J. Nanomed., 2008, 3, 169– 180. ¨llner and G. Gauglitz, Surf. Coatings 26. G. Markovic, T. Mutschler, K. Wo Technol., 2006, 201, 1282–1288. 27. M. Mohiti-Asli and E. G. Loboa, ed. M. S. Ågren, Woodhead Publishing, 2016, pp. 483–499. 28. R. Y. Hong, B. Feng, X. Cai, G. Liu, H. Z. Li, J. Ding, Y. Zheng and D. G. Wei, J. Appl. Polym. Sci., 2009, 112, 89–98. ´k, J. Polym. Sci., Part A: Polym. Chem., 2001, 39, 3707–3715. 29. D. Hora ´k, M. Trchova ´, M. J. Benesˇ, M. Veverka and E. Pollert, Polymer, 30. D. Hora 2010, 51, 3116–3122. 31. M. B. Hocking, Handbook of Chemical Technology and Pollution Control, 3rd edn, 2005. 32. F. Shakerian, K.-H. Kim, E. Kwon, J. E. Szulejko, P. Kumar, S. Dadfarnia and A. M. Haji Shabani, TrAC, Trends Anal. Chem., 2016, 83, 55–69. 33. Y. Lee, J. Rho and B. Jung, J. Appl. Polym. Sci., 2003, 89, 2058–2067. 34. F. Montagne, O. Mondain-Monval, C. Pichot and A. Elaı¨ssari, J. Polym. Sci., Part A: Polym. Chem., 2006, 44, 2642–2656.

Application of Functionalized Magnetic Nanoparticles for Organic Analyte Extraction

165

35. D. Crespy and K. Landfester, Beilstein J. Org. Chem., 2010, 6, 1132– 1148. 36. C. Kaewsaneha, P. Tangboriboonrat, D. Polpanich, M. Eissa and A. Elaissari, J. Polym. Sci., Part A: Polym. Chem., 2013, 51, 4779–4785. 37. J. M. Asua, Prog. Polym. Sci., 2002, 27, 1283–1346. 38. N. Pimpha, S. Chaleawlert-umpon and P. Sunintaboon, Polymer, 2012, 53, 2015–2022. 39. N. Sharifi-Sanjani, M. Soltan-Dehghan, N. Naderi and A. Ranji, J. Appl. Polym. Sci., 2004, 94, 1898–1904. 40. Y.-M. Wang and C. Y. Pan, Colloid Polym. Sci., 1999, 277, 658–665. 41. Y. Liu, Y. Huang, J. Liu, W. Wang, G. Liu and R. Zhao, J. Chromatogr. A, 2012, 1246, 15–21. 42. H. Li, T. Xie, L. Ye, Y. Wang and C. Xie, Microchim. Acta, 2017, 184, 1011–1019. 43. J. Meng, W. Zhang, T. Bao and Z. Chen, J. Sep. Sci., 2015, 38, 2117–2125. ´lvarez and A. Martı´n-Esteban, J. Mol. ˜o-Ropero, M. Dı´az-A 44. M. J. Patin Recognit., 2017, 30, e2593. 45. A. Mehdinia, T. Baradaran Kayyal, A. Jabbari, M. O. Aziz-Zanjani and E. Ziaei, J. Chromatogr. A, 2013, 1283, 82–88. 46. R. Keçili and C. M. Hussain, Int. J. Anal. Chem., 2018, 2018, 8503853. 47. X. Song, S. Xu, L. Chen, Y. Wei and H. Xiong, J. Appl. Polym. Sci., 2014, 131, 40766. 48. G. Li and K. H. Row, Sep. Purif. Rev., 2018, 47, 1–18. 49. E. Abdollahi, M. Abdouss, M. Salami-Kalajahi and A. Mohammadi, Polym. Rev., 2016, 56, 557–583. 50. M. Hesampour, M. Ali Taher and M. Behzadi, New J. Chem., 2017, 41, 12910–12919. ´nez-Skrzypek, J. Gonza ´lez-Sa ´lamo, D. A. Varela-Martı´nez, 51. G. Jime ´. Gonza ´lez-Curbelo and J. Herna ´ndez-Borges, J. Chromatogr. A, M. A 2019, 1611, 460620. ´lez-Sa ´lamo, B. Socas-Rodrı´guez, J. Herna ´ndez-Borges and 52. J. Gonza ´. Rodrı´guez-Delgado, J. Chromatogr. A, 2017, 1530, 35–44. M. A 53. X. Jiang, J. Cheng, H. Zhou, F. Li, W. Wu and K. Ding, Talanta, 2015, 141, 239–246. ´ndez-Borges, P. Salazar, M. Martı´n and 54. B. Socas-Rodrı´guez, J. Herna ´. Rodrı´guez-Delgado, J. Chromatogr. A, 2015, 1397, 1–10. M. A ´lez-Sa ´lamo, B. Socas-Rodrı´guez, J. Herna ´ndez-Borges and 55. J. Gonza ´. Rodrı´guez-Delgado, Food Chem., 2017, 215, 362–368. M. A 56. Q. Li, M. H. W. Lam, R. S. S. Wu and B. Jiang, J. Chromatogr. A, 2010, 1217, 1219–1226. 57. J. Ding, L.-J. Mao, N. Guo, L. Yu and Y.-Q. Feng, J. Chromatogr. A, 2016, 1446, 103–113. 58. A. A. Asgharinezhad, S. Karami, H. Ebrahimzadeh, N. Shekari and N. Jalilian, Int. J. Pharm., 2015, 494, 102–112. 59. Q. Wang, J. Wu, L. Hao, Q. Wu, C. Wang and Z. Wang, J. Sep. Sci., 2018, 41, 3285–3293.

166

Chapter 5

60. A. Targhoo, A. Amiri and M. Baghayeri, Microchim. Acta, 2017, 185, 15. ´-Icardo, 61. S. Meseguer-Lloret, S. Torres-Cartas, M. Catala ´ ´nez, E. F. Simo-Alfonso and J. M. Herrero-Martı Anal. Bioanal. Chem., 2017, 409, 3561–3571. 62. X. Huang, Y. Wang, Y. Liu and D. Yuan, J. Sep. Sci., 2013, 36, 3210– 3219. 63. Q. Gao, D. Luo, J. Ding and Y.-Q. Feng, J. Chromatogr. A, 2010, 1217, 5602–5609. 64. A. Amiri, M. Baghayeri and S. Nori, J. Chromatogr. A, 2015, 1415, 20–26. 65. Q. G. Liao, D. G. Wang and L. G. Luo, Anal. Bioanal. Chem., 2014, 406, 7571–7579. 66. L. Sun, R. Duan, Y. Fan, X.-Z. Chen, C. Peng, C. Zheng, L.-Y. Dong and X.-H. Wang, J. Chromatogr. A, 2020, 1609, 460448. ˜ a67. C. Herrero-Latorre, J. Barciela-Garcı´a, S. Garcı´a-Martı´n, R. M. Pen ´rola-Jime ´nez, Anal. Chim. Acta, 2015, 892, 10–26. Crecente and J. Ota 68. N. Li, H.-L. Jiang, X. Wang, X. Wang, G. Xu, B. Zhang, L. Wang, R.-S. Zhao and J.-M. Lin, TrAC, Trends Anal. Chem., 2018, 102, 60–74. 69. N. Manousi, E. Rosenberg, E. Deliyanni, G. A. Zachariadis and V. Samanidou, Molecules, 2020, 25, 1148. 70. W. Li and Y. Shi, TrAC, Trends Anal. Chem., 2019, 118, 652–665. 71. B.-T. Zhang, X. Zheng, H.-F. Li and J.-M. Lin, Anal. Chim. Acta, 2013, 784, 1–17. ´. Gonza ´lez-Curbelo, J. Herna ´ndez-Borges 72. A. V. Herrera-Herrera, M. A ´. Rodrı´guez-Delgado, Anal. Chim. Acta, 2012, 734, 1–30. and M. A ˜ as and 73. M. Pastor-Belda, L. Marı´n-Soler, N. Campillo, P. Vin ´ndez-Co ´rdoba, J. Chromatogr. A, 2018, 1564, 102–109. M. Herna 74. R. Wu, F. Ma, L. Zhang, P. Li, G. Li, Q. Zhang, W. Zhang and X. Wang, Food Chem., 2016, 204, 334–342. 75. J. Dong, Z. Feng, S. Kang, M. An and G. Wu, Anal. Methods, 2020, 12, 2747–2756. 76. N. Li, J. Chen and Y.-P. Shi, Talanta, 2015, 141, 212–219. 77. Y. Li, X. Wu, Z. Li, S. Zhong, W. Wang, A. Wang and J. Chen, Talanta, 2015, 144, 1279–1286. 78. R. Xiao, X. Zhang, X. Zhang, J. Niu, M. Lu, X. Liu and Z. Cai, Talanta, 2017, 166, 262–267. 79. R. Xiao, S. Wang, M. H. Ibrahim, H. I. Abdu, D. Shan, J. Chen and X. Lu, J. Chromatogr. A, 2019, 1593, 1–8. ¨ . Demir and M. Soylak, J. Chromatogr. B, 2018, 80. E. Yilmaz, H. I_ . Ulusoy, O 1084, 113–121. 81. M.-Y. Zhang, M.-M. Wang, Y.-L. Hao, X.-R. Shi and X.-S. Wang, J. Sep. Sci., 2016, 39, 1749–1756. 82. D.-B. Zhou, X. Sheng, F. Han, Y.-Y. Hu, L. Ding, Y.-L. Lv, W. Song and P. Zheng, J. Chromatogr. A, 2018, 1578, 53–60. 83. A. Sarafraz-Yazdi, T. Rokhian, A. Amiri and F. Ghaemi, New J. Chem., 2015, 39, 5621–5627.

Application of Functionalized Magnetic Nanoparticles for Organic Analyte Extraction

167

84. E. Yilmaz, S. Salem, G. Sarp, S. Aydin, K. Sahin, I. Korkmaz and D. Yuvali, Talanta, 2020, 213, 120813. 85. M. Wang, X. Yang and W. Bi, J. Sep. Sci., 2015, 38, 445–452. 86. Q. Nian, X. Wang, M. Wang and G. Zuo, Microchim. Acta, 2019, 186, 497. ´. Gonza ´lez Curbelo and J. 87. A. Herrera-Herrera, M. Asensio-Ramos, M. A ´ndez-Borges, in Applications of Carbon Nanotubes, 2013. Herna 88. G. Korneva, H. Ye, Y. Gogotsi, D. Halverson, G. Friedman, J.-C. Bradley and K. G. Kornev, Nano Lett., 2005, 5, 879–884. 89. J. Jin, R. Li, H. Wang, H. Chen, K. Liang and J. Ma, Chem. Commun., 2007, 386–388. 90. Y. Deng, C. Deng, D. Yang, C. Wang, S. Fu and X. Zhang, Chem. Commun., 2005, 5548–5550. 91. V. Georgakilas, V. Tzitzios, D. Gournis and D. Petridis, Chem. Mater., 2005, 17, 1613–1617. 92. H.-F. Zhang and Y.-P. Shi, Anal. Chim. Acta, 2012, 724, 54–60. 93. A. N. M. Nasir, N. Yahaya, N. N. M. Zain, V. Lim, S. Kamaruzaman, B. Saad, N. Nishiyama, N. Yoshida and Y. Hirota, Food Chem., 2019, 276, 458–466. ´s, A. Rı´os and M. Zougagh, Electrophoresis, 94. K. Murtada, F. de Andre 2018, 39, 1808–1815. 95. N. Jalilian, H. Ebrahimzadeh and A. A. Asgharinezhad, J. Chromatogr. A, 2017, 1499, 38–47. 96. M. Hashemi and Z. Nazari, J. Food Compos. Anal., 2018, 69, 98–106. 97. Y. Yin, L. Yan, Z. Zhang and J. Wang, Talanta, 2015, 144, 671–679. 98. M. Luo, D. Liu, L. Zhao, J. Han, Y. Liang, P. Wang and Z. Zhou, Anal. Chim. Acta, 2014, 852, 88–96. 99. W. Li, H. Zhang and Y. Shi, J. Chromatogr. B, 2017, 1059, 27–34. 100. W. K. Li, J. Chen, H. X. Zhang and Y. P. Shi, Talanta, 2017, 168, 136– 145. 101. K. Chen, R. Jin, C. Luo, G. Song, Y. Hu and H. Cheng, J. Sep. Sci., 2018, 41, 1847–1855. 102. A. D. Purceno, A. P. C. Teixeira, N. J. de Souza, L. E. Fernandez-Outon, J. D. Ardisson and R. M. Lago, J. Colloid Interface Sci., 2012, 379, 84–88. 103. A. L. de Toffoli, E. V. S. Maciel, B. H. Fumes and F. M. Lanças, J. Sep. Sci., 2018, 41, 288–302. 104. G. Zhao, S. Song, C. Wang, Q. Wu and Z. Wang, Anal. Chim. Acta, 2011, 708, 155–159. 105. Q. Wu, C. Feng, C. Wang and Z. Wang, Colloids Surf., B, 2013, 101, 210–214. 106. Y.-B. Luo, Z.-G. Shi, Q. Gao and Y.-Q. Feng, J. Chromatogr. A, 2011, 1218, 1353–1358. 107. W. Wang, R. Ma, Q. Wu, C. Wang and Z. Wang, J. Chromatogr. A, 2013, 1293, 20–27. 108. W. Wang, X. Ma, Q. Wu, C. Wang, X. Zang and Z. Wang, J. Sep. Sci., 2012, 35, 2266–2272.

168

Chapter 5

109. Y. Sun, J. Tian, L. Wang, H. Yan, F. Qiao and X. Qiao, J. Chromatogr. A, 2015, 1422, 53–59. 110. M. Rezvani-Eivari, A. Amiri, M. Baghayeri and F. Ghaemi, J. Chromatogr. A, 2016, 1465, 1–8. 111. H. Razmi and M. Jabbari, Int. J. Environ. Anal. Chem., 2015, 95, 1353– 1369. 112. H. Lin and C. Deng, Talanta, 2016, 149, 91–97. 113. X. Wang, G. Song and C. Deng, Talanta, 2015, 132, 753–759. 114. E. Kazemi, A. M. Haji Shabani, S. Dadfarnia, A. Abbasi, M. R. Rashidian Vaziri and A. Behjat, Anal. Chim. Acta, 2016, 905, 85–92. 115. M. Ghorbani, M. Chamsaz and G. H. Rounaghi, J. Sep. Sci., 2016, 39, 1082–1089. 116. Y. Huang, Y. Wang, Q. Pan, Y. Wang, X. Ding, K. Xu, N. Li and Q. Wen, Anal. Chim. Acta, 2015, 877, 90–99. 117. X. Wang and C. Deng, Talanta, 2015, 144, 1329–1335. 118. G. Cheng, Z.-G. Wang, S. Denagamage and S.-Y. Zheng, ACS Appl. Mater. Interfaces, 2016, 8, 10234–10242. 119. S. Zhang, W. Wu and Q. Zheng, Anal. Methods, 2015, 7, 9587–9595. 120. Q. Liu, J. Shi, T. Wang, F. Guo, L. Liu and G. Jiang, J. Chromatogr. A, 2012, 1257, 1–8. 121. J. Luo, Y. Gao, K. Tan, W. Wei and X. Liu, ACS Sustain. Chem. Eng., 2016, 4, 3316–3326. 122. Y. Feng, X. Hu, F. Zhao and B. Zeng, J. Sep. Sci., 2019, 42, 1058–1066. 123. L. Liu, T. Feng, C. Wang, Q. Wu and Z. Wang, Microchim. Acta, 2014, 181, 1249–1255. 124. H. R. Nodeh, W. A. Wan Ibrahim, M. A. Kamboh and M. M. Sanagi, RSC Adv., 2015, 5, 76424–76434. 125. S. Mahpishanian and H. Sereshti, J. Chromatogr. A, 2016, 1443, 43–53. 126. X. Wang, H. Wang, M. Lu, X. Ma, P. Huang, X. Lu and X. Du, J. Sep. Sci., 2016, 39, 1734–1741. ´ndez-Borges, M. M. Afonso, 127. A. V. Herrera-Herrera, J. Herna ´. Rodrı´guez-Delgado, Talanta, 2013, 116, 695– J. A. Palenzuela and M. A 703. 128. X. He, G. N. Wang, K. Yang, H. Z. Liu, X. J. Wu and J. P. Wang, Food Chem., 2017, 221, 1226–1231. 129. Y. Wang, L. Liu, C. Xiao, L. Chen, P. Yang, Q. Liu, J. Wang and X. Liu, Food Anal. Methods, 2016, 9, 2521–2530. 130. Y. Jiao, S. Fu, L. Ding, Q. Gong, S. Zhu, L. Wang and H. Li, Anal. Methods, 2012, 4, 2729–2734. 131. L. Hao, C. Wang, X. Ma, Q. Wu, C. Wang and Z. Wang, Anal. Methods, 2014, 6, 5659–5665. 132. L. Pang, W. Zhang, W. Zhang, P. Chen, J. Yu, G.-T. Zhu and S. Zhu, RSC Adv., 2017, 7, 53720–53727. 133. M. Moazzen, R. Ahmadkhaniha, M. E. Gorji, M. Yunesian and N. Rastkari, Talanta, 2013, 115, 957–965.

Application of Functionalized Magnetic Nanoparticles for Organic Analyte Extraction

169

134. L. Zhu and H. Xu, J. Sep. Sci., 2014, 37, 2591–2598. 135. Q. Han, Z. Wang, J. Xia, S. Chen, X. Zhang and M. Ding, Talanta, 2012, 101, 388–395. 136. J. Yang, J. Li, J. Qiao, S. Cui, H. Lian and H. Chen, Appl. Surf. Sci., 2014, 321, 126–135. 137. J. Yang, J. Qiao, S. Cui, J. Li, J. Zhu, H. Yin, C. Zhan and H. Lian, J. Sep. Sci., 2015, 38, 1969–1976. 138. H. W. Kroto, J. R. Heath, S. C. O’Brien, R. F. Curl and R. E. Smalley, Nature, 1985, 318, 162–163. 139. J. A. Rodriguez, I. S. Ibarra, J. M. Miranda, E. Barrado and E. M. Santos, Anal. Methods, 2016, 8, 8466–8473. 140. N.-N. Bui, B.-H. Kim, K. S. Yang, M. E. Dela Cruz and J. P. Ferraris, Carbon N. Y., 2009, 47, 2538–2539. 141. P. Li, D. Huang, J. Huang, J. Tang, P. Zhang and F. Meng, J. Chromatogr. A, 2020, 1625, 461305. ´lez-Herna ´ndez, V. Pino, J. Pasa ´n and 142. P. Rocı´o-Bautista, P. Gonza A. M. Afonso, TrAC, Trends Anal. Chem., 2017, 90, 114–134. 143. F. Maya, C. Palomino Cabello, R. M. Frizzarin, J. M. Estela, `, TrAC, Trends Anal. Chem., 2017, 90, G. Turnes Palomino and V. Cerda 142–152. 144. S.-H. Huo and X.-P. Yan, Analyst, 2012, 137, 3445–3451. 145. M. Saikia, D. Bhuyan and L. Saikia, New J. Chem., 2015, 39, 64–67. ´llez and J. Coronas, Chem. Commun., 2012, 146. S. Sorribas, B. Zornoza, C. Te 48, 9388–9390. ¨ll, 147. M. E. Silvestre, M. Franzreb, P. G. Weidler, O. Shekhah and C. Wo Adv. Funct. Mater., 2013, 23, 1210–1213. 148. N. L. Torad, M. Hu, S. Ishihara, H. Sukegawa, A. A. Belik, M. Imura, K. Ariga, Y. Sakka and Y. Yamauchi, Small, 2014, 10, 2096–2107. 149. S.-H. Huo, H.-Y. An, J. Yu, X.-F. Mao, Z. Zhang, L. Bai, Y.-F. Huang and P.-X. Zhou, J. Chromatogr. A, 2017, 1517, 18–25. ´n, C. Ruiz-Pe ´rez and 150. P. Rocı´o-Bautista, V. Pino, J. H. Ayala, J. Pasa A. M. Afonso, J. Chromatogr. A, 2016, 1436, 42–50. 151. Q. Zhou, M. Lei, Y. Wu and Y. Yuan, J. Chromatogr. A, 2017, 1487, 22–29. 152. M. Shakourian, Y. Yamini and M. Safari, Talanta, 2020, 218, 121139. 153. I. A. Senosy, H.-M. Guo, M.-N. Ouyang, Z.-H. Lu, Z.-H. Yang and J.-H. Li, Food Chem., 2020, 325, 126944. 154. X. M. Wang, H. Kou, J. Wang, R. Teng, X. Du and X. Lu, J. Porous Mater., 2020, 27, 1171–1177. 155. S. Lin, N. Gan, Y. Cao, Y. Chen and Q. Jiang, J. Chromatogr. A, 2016, 1446, 34–40. 156. R. Dargahi, H. Ebrahimzadeh, A. A. Asgharinezhad, A. Hashemzadeh and M. M. Amini, J. Sep. Sci., 2018, 41, 948–957. 157. N. Jalilian, H. Ebrahimzadeh and A. A. Asgharinezhad, J. Chromatogr. A, 2019, 1608, 460426. 158. Y. Xu, J. Jin, X. Li, Y. Han, H. Meng, C. Song and X. Zhang, Microchim. Acta, 2015, 182, 2313–2320.

170

Chapter 5

159. L. Chen, M. Zhang, F. Fu, J. Li and Z. Lin, J. Chromatogr. A, 2018, 1567, 136–146. 160. Y. Wang, H. Chen, J. Tang, G. Ye, H. Ge and X. Hu, Food Chem., 2015, 181, 191–197. 161. S. Rezabeyk and M. Manoochehri, Microchim. Acta, 2018, 185, 365. ´lez-Sa ´lamo, A. V. Herrera-Herrera, C. Fanali and 162. J. Gonza ´ndez-Borges, LC GC Eur., 2016, 29, 180–193. J. Herna ´lez-Sa ´lamo, B. Socas-Rodrı´guez, J. Herna ´ndez-Borges and 163. J. Gonza ´. Rodrı´guez-Delgado, TrAC, Trends Anal. Chem., 2016, 85, 203–220. M. A ˜a-Me ´ndez, R. M. Mawale, J. E. Conde-Gonza ´lez, 164. E. M. Pen ´rez, Talanta, 2020, B. Socas-Rodrı´guez, J. Havel and C. Ruiz-Pe 207, 120275. 165. T. Khezeli and A. Daneshfar, RSC Adv., 2015, 5, 65264–65273. 166. Y.-F. Huang, M. Liu, Y.-Q. Wang, Y. Li, J.-M. Zhang and S.-H. Huo, RSC Adv., 2016, 6, 15362–15369. 167. Y. Hu, Z. Huang, J. Liao and G. Li, Anal. Chem., 2013, 85, 6885–6893. 168. H. Su, Y. Lin, Z. Wang, Y.-L. E. Wong, X. Chen and T.-W. D. Chan, J. Chromatogr. A, 2016, 1466, 21–28. 169. S. Zhang, Z. Jiao and W. Yao, J. Chromatogr. A, 2014, 1371, 74–81. 170. J. Ma, Z. Yao, L. Hou, W. Lu, Q. Yang, J. Li and L. Chen, Talanta, 2016, 161, 686–692. ˆte ´, A. I. Benin, N. W. Ockwig, M. O’Keeffe, A. J. Matzger and 171. A. P. Co O. M. Yaghi, Science, 2005, 310, 1166 LP–1161170. 172. J. Xin, X. Wang, N. Li, L. Liu, Y. Lian, M. Wang and R.-S. Zhao, Food Chem., 2020, 330, 127255. ´lez-Sa ´lamo, G. Jime ´nez-Skrzypek, C. Ortega-Zamora, 173. J. Gonza ´. Gonza ´lez-Curbelo and J. Herna ´ndez-Borges, Molecules, 2020, M. A 25, 3288. 174. W. Zhang, T. Liu, H. Dong, H. Bai, F. Tian, Z. Shi, M. Chen, J. Wang, W. Qin and X. Qian, Anal. Chem., 2017, 89, 5810–5817. 175. N. Li, D. Wu, N. Hu, G. Fan, X. Li, J. Sun, X. Chen, Y. Suo, G. Li and Y. Wu, J. Agric. Food Chem., 2018, 66, 3572–3580. 176. X. Shi, N. Li, D. Wu, N. Hu, J. Sun, X. Zhou, Y. Suo, G. Li and Y. Wu, Anal. Methods, 2018, 10, 5014–5024. 177. D. Jiang, T. Hu, H. Zheng, G. Xu and Q. Jia, Chem. – Eur. J., 2018, 24, 10390–10396. 178. L. Liu, W.-K. Meng, Y.-S. Zhou, X. Wang, G.-J. Xu, M.-L. Wang, J.-M. Lin and R.-S. Zhao, Chem. Eng. J., 2019, 356, 926–933. 179. Y. Lu, B. Wang, C. Wang, Y. Yan, D. Wu, H. Liang and K. Tang, Chromatographia, 2019, 82, 1089–1099. 180. Y.-H. Pang, Q. Yue, Y. Huang, C. Yang and X.-F. Shen, Talanta, 2020, 206, 120194. 181. N. Li, D. Wu, J. Liu, N. Hu, X. Shi, C. Dai, Z. Sun, Y. Suo, G. Li and Y. Wu, Microchem. J., 2018, 143, 350–358. 182. X.-M. Wang, W.-H. Ji, L.-Z. Chen, J.-M. Lin, X. Wang and R.-S. Zhao, J. Chromatogr. A, 2020, 1619, 460916.

Application of Functionalized Magnetic Nanoparticles for Organic Analyte Extraction

171

183. J. Lu, R. Wang, J. Luan, Y. Li, X. He, L. Chen and Y. Zhang, J. Chromatogr. A, 2020, 1618, 460898. 184. W. Zhao, X. Wang, J. Guo, Y. Guo, C. Lan, F. Xie, S. Zong, L. He and S. Zhang, J. Chromatogr. A, 2020, 1618, 460847. 185. M. Wang, M. Gao, K. Zhang, L. Wang, W. Wang, Q. Fu, Z. Xia and D. Gao, Microchim. Acta, 2019, 186, 827. 186. A. Wen, G. Li, D. Wu, Y. Yu, Y. Yang, N. Hu, H. Wang, J. Chen and Y. Wu, J. Chromatogr. A, 2020, 1612, 460651. 187. J. Fan, Z. Liu, J. Li, W. Zhou, H. Gao, S. Zhang and R. Lu, J. Chromatogr. A, 2020, 1619, 460950. 188. J. Zhang, Z. Chen, S. Tang, X. Luo, J. Xi, Z. He, J. Yu and F. Wu, Anal. Chim. Acta, 2019, 1089, 66–77. 189. R. Wang and Z. Chen, Microchim. Acta, 2017, 184, 3867–3874. 190. Y. Wang, S. Wu, D. Wu, J. Shen, Y. Wei and C. Wang, Anal. Chim. Acta, 2020, 1093, 61–74. 191. S. Li, Q. Liang, S. A. H. Ahmed and J. Zhang, Food Anal. Methods, 2020, 13, 1111–1118. 192. N. Li, D. Wu, X. Li, X. Zhou, G. Fan, G. Li and Y. Wu, Food Chem., 2020, 306, 125455. 193. S. He, T. Zeng, S. Wang, H. Niu and Y. Cai, ACS Appl. Mater. Interfaces, 2017, 9, 2959–2965. 194. Y. Chen and Z. Chen, Talanta, 2017, 165, 188–193. 195. Z. Yan, M. He, B. Chen, B. Gui, C. Wang and B. Hu, J. Chromatogr. A, 2017, 1525, 32–41. 196. R. Liang, Y. Hu and G. Li, J. Chromatogr. A, 2020, 1618, 460867. 197. X. Lin, X. Wang, J. Wang, Y. Yuan, S. Di, Z. Wang, H. Xu, H. Zhao, P. Qi and W. Ding, Anal. Chim. Acta, 2020, 1101, 65–73. 198. M. Zhang, J. Li, C. Zhang, Z. Wu, Y. Yang, J. Li, F. Fu and Z. Lin, J. Chromatogr. A, 2020, 1615, 460773. 199. J.-Y. Ren, X.-L. Wang, X.-L. Li, M.-L. Wang, R.-S. Zhao and J.-M. Lin, Anal. Bioanal. Chem., 2018, 410, 1657–1665. 200. M. Pham, T.-C. Wen, H.-C. Li, P.-H. Hsieh, Y.-R. Chen, H.-C. Chang and C.-C. Han, Materials, 2016, 9, 385. 201. M.-R. Lee, F.-Y. Lai, J. Dou, K.-L. Lin and L.-W. Chung, Anal. Lett., 2011, 44, 676–686. 202. Y. Yan, Y. Lu, B. Wang, Y. Gao, L. Zhao, H. Liang and D. Wu, ACS Appl. Mater. Interfaces, 2018, 10, 26539–26545. 203. P. Walden, Bull. Acad. Imper. Sci., 1914, 8, 405–422. ´rrez-Serpa, P. I. Napolitano-Tabares, J. ˇ 204. A. Gutie Sulc, I. Pacheco´ndez and V. Pino, Separations, 2020, 7, 37. Ferna 205. K. Yavir, K. Konieczna, Marcinkowski and A. Kloskowski, TrAC, Trends Anal. Chem., 2020, 130, 115994. ´n, R. Lucena, S. Ca ´rdenas 206. F. A. Casado-Carmona, M. del, C. Alcudia-Leo ´rcel, Microchem. J., 2016, 128, 347–353. and M. Valca 207. S. Liu, B. Yu, S. Wang, Y. Shen and H. Cong, Adv. Colloid Interface Sci., 2020, 281, 102165.

172

Chapter 5

´n-Cano, M. del Carmen Alcudia-Leo ´n, R. Lucena, S. Ca ´rdenas 208. F. Gala ´ and M. Valcarcel, J. Chromatogr. A, 2013, 1300, 134–140. 209. H. Sahebi, E. Konoz, A. Ezabadi, A. Niazi and S. H. Ahmadi, Microchem. J., 2020, 154, 104605. 210. J. Chen and X. Zhu, Spectrochim. Acta Part A Mol. Biomol. Spectrosc., 2015, 137, 456–462. 211. M. S. Shahriman, M. R. Ramachandran, N. N. M. Zain, S. Mohamad, N. S. A. Manan and S. M. Yaman, Talanta, 2018, 178, 211–221. 212. S. Gao, Y. Wu, S. Xie, Z. Shao, X. Bao, Y. Yan, Y. Wu, J. Wang and Z. Zhang, J. Chromatogr. B, 2019, 1128, 121778. 213. X.-L. Sun, W.-H. Deng, H. Chen, H.-L. Han, J. M. Taylor, C.-Q. Wan and G. Xu, Chem. – Eur. J., 2017, 23, 1248–1252. ´. Rı´os, F. J. Guzma ´n Bernardo and 214. F. Abujaber, M. Zougagh, S. Jodeh, A R. C. Rodrı´guez Martı´n-Doimeadios, Microchem. J., 2018, 137, 490–495. 215. X. Zheng, L. He, Y. Duan, X. Jiang, G. Xiang, W. Zhao and S. Zhang, J. Chromatogr. A, 2014, 1358, 39–45. 216. C. Liu, Y. Liao and X. Huang, J. Chromatogr. A, 2017, 1524, 13–20. 217. A. A. A. Bakheet and X. S. Zhu, J. Mol. Liq., 2017, 242, 900–906. 218. S. Badragheh, M. Zeeb and M. R. Talei Bavil Olyai, RSC Adv., 2018, 8, 30550–30561. 219. M. S. Sitze, E. R. Schreiter, E. V. Patterson and R. G. Freeman, Inorg. Chem., 2001, 40, 2298–2304. 220. S. Hayashi and H. Hamaguchi, Chem. Lett., 2004, 33, 1590–1591. 221. M. J. Trujillo-Rodrı´guez, O. Nacham, K. D. Clark, V. Pino, J. L. Anderson, J. H. Ayala and A. M. Afonso, Anal. Chim. Acta, 2016, 934, 106–113. 222. M. Sajid, TrAC, Trends Anal. Chem., 2019, 113, 210–223. 223. P. Tashakkori, P. Erdem and S. Seyhan Bozkurt, J. Liq. Chromatogr. Relat. Technol., 2017, 40, 657–666. 224. H. Bagheri, O. Zandi and A. Aghakhani, Anal. Chim. Acta, 2011, 692, 80–84. 225. A. Bavili Tabrizi, N. Dehghani Teymurlouie, A. Bavili Tabrizi and N. Dehghani Teymurlouie, J. Mex. Chem. Soc., 2016, 60, 108–116. 226. A. Beiraghi, K. Pourghazi, M. Amoli-Diva and A. Razmara, J. Chromatogr. B, 2014, 945–946, 46–52. 227. J. Li, X. Zhao, Y. Shi, Y. Cai, S. Mou and G. Jiang, J. Chromatogr. A, 2008, 1180, 24–31. 228. X. Zhao, Y. Shi, T. Wang, Y. Cai and G. Jiang, J. Chromatogr. A, 2008, 1188, 140–147. 229. M. M. Ariffin, A. H. M. Azmi, N. M. Saleh, S. Mohamad and S. K. M. Rozi, Microchem. J., 2019, 147, 930–940. 230. E. M. M. Wanda, H. Nyoni, B. B. Mamba and T. A. M. Msagati, Phys. Chem. Earth, Parts A/B/C, 2018, 108, 28–47. 231. M. Yu, L. Wang, L. Hu, Y. Li, D. Luo and S. Mei, TrAC, Trends Anal. Chem., 2019, 119, 115611.

Application of Functionalized Magnetic Nanoparticles for Organic Analyte Extraction

173

232. S. Wang, R. Niu, Y. Yang, X. Zhou, S. Luo, C. Zhang and Y. Wang, Int. J. Biol. Macromol., 2020, 153, 583–590. 233. M. Khodadadi, A. Malekpour and M. A. Mehrgardi, J. Chromatogr. A, 2018, 1564, 85–93. 234. Y. Su, C. Shao, X. Huang, J. Qi, R. Ge, H. Guan and Z. Lin, Anal. Bioanal. Chem., 2018, 410, 1885–1891. 235. J. Zeng, Q. Wang, J. Gao, W. Wang, H. Shen, Y. Cao, M. Hu, W. Bi and N. Gan, J. Chromatogr. A, 2020, 1614, 460715. 236. M. Zhang, G. Huang, J. Huang and W. Chen, Microchem. J., 2018, 142, 385–393. 237. D. Li, J. Zhu, M. Wang, W. Bi, X. Huang and D. D. Y. Chen, J. Chromatogr. A, 2017, 1491, 27–35. 238. H.-B. Zheng, J. Ding, S.-J. Zheng, G.-T. Zhu, B.-F. Yuan and Y.-Q. Feng, Talanta, 2016, 148, 46–53. 239. M. Rajabi, A. G. Moghadam, B. Barfi and A. Asghari, Microchim. Acta, 2016, 183, 1449–1458. 240. M. Wang, S. Cui, X. Yang and W. Bi, Talanta, 2015, 132, 922–928. 241. M. Wang, H. Yuan, W. Deng, W. Bi and X. Yang, J. Chromatogr. A, 2015, 1412, 12–21. 242. S. Behrens and I. Appel, Curr. Opin. Biotechnol., 2016, 39, 89–96.

CHAPTER 6

Graphene-based Sorbents for Modern Magnetic Solid-phase Extraction Techniques FERNANDO MAURO LANÇAS,* DEYBER ARLEY VARGAS MEDINA, NATALIA GABRIELLY PEREIRA DOS SANTOS AND MARCELA JORDAN SINISTERRA ˜o Paulo, Institute of Chemistry at Sa ˜o Carlos, Brazil University of Sa *Email: [email protected]

6.1 Introduction Graphene (G) is a two-dimensional allotropic form of carbon composed of monoatomic thickness layers of sp2 hybridized carbon atoms, assembled in a honeycomb-like lattice.1 Discovered by Novoselov et al. in 2004 at Manchester University,2,3 graphene was the first stable two-dimensional crystal isolated, and its remarkable properties have made it one of the most promissory materials of modern nanotechnology. The robust structure generated by s-bonds between the carbon atoms in the 2D plane confers to graphene a high stiffness and mechanical resistance, and it is considered to be a material up to 200 times stronger than steel, lighter, and with a significantly higher Young’s modulus.4 Simultaneously, the long conjugated p electrons system of the sp2 honeycomb structure provides important optical properties and excellent thermal and electric conductivity (B3000 W mK1 and 104 O1 cm1, respectively). Hence, graphene is an ideal material for producing electronic devices,5 but also its transparency and its impermeability to gases have several other relevant applications.6 Analytical Applications of Functionalized Magnetic Nanoparticles Edited by Chaudhery Mustansar Hussain r The Royal Society of Chemistry 2021 Published by the Royal Society of Chemistry, www.rsc.org

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In analytical chemistry, graphene emerged as a potential sorbent for the solid-phase extraction of a wide variety of analytes from diverse and complex matrices in many scientific areas.1,5,7 The first applications of graphene in sample preparation were published in 2011,8,9 and since then, the interest in the development and application of its composites as sorbents to modern extraction techniques has been continuously growing. From the sample preparation point of view, graphene is especially interesting due to the large surface area (ca. 2630 m2 g1) of the nanosheets and its adeptness to provide analyte–sorbent interaction sites on both sides of the lattice. In terms of chemical interactions, graphene is a non-polar and hydrophobic adsorbent, whose long delocalized p-electron provides good affinity for molecules containing aromatic moieties, through strong p–p stacking, cation–p, and electrostatic interactions. On the other hand, the lack of functional groups in graphene limits its range of applicability. Graphenebased sorbent preparation is typically mediated by the formation of graphene oxide (GO), a very reactive intermediary product of its chemical exfoliation.10 The older methods of obtaining graphene were based on the graphite top-down mechanical exfoliation with an adhesive tape (peeling method), and the chemical vapor deposition (CVD) method, in which the decomposition of carbon precursors at high temperatures is induced by metallic catalysts.4 Although both methods can generate good quality materials, they can result in laborious, non-reproducible, and low yield. Nowadays, graphene is mainly obtained by chemical exfoliation of graphite in liquid solutions; the Hummers method is the most widely used. In short, after the graphite oxidation, the ultrasound-assisted exfoliation results in graphene oxide (GO) (Figure 6.1).11 Other alternatives for GO synthesis include the Staudenmaier and Hofmann methods, among many others, as described by Poh and co-workers.12 All these oxidative processes occur with the change of the configuration of several atoms sp2 to sp3 and the consequent incorporation of oxygenated groups, such as COC, C–OH, and –COOH. This modification offers new interaction mechanisms through hydrogen bonding, electrostatic interactions, and dative bonding, extending the applicability scope to the adsorption of diverse inorganic and non-aromatic organic species containing polar functional groups.13 GO can be used as an extraction phase or chemically reduced to produce reduced graphene oxide (rGO), a material with less remaining oxygenated groups, which is more suitable for the extraction of less polar compounds. Finally, the remaining oxygenated groups can be used to bond GO or rGO into another support material such as aminopropyl silica (NH2–Si), providing graphene functionalized silica particles (Si@G), enabling the use of graphene used in sample preparation techniques based on the use of sorbent packed-beds.14,15 Another relevant advantage of incorporating oxygenated groups to graphene is the lattice’s endowment with reactive sites for further modification with diverse functional groups, improving the sorbent capacity, and tuning its selectivity.7 A great diversity of modified graphene-based sorbents can be

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Figure 6.1

Chapter 6

Schematic of the synthesis route to obtain GO, rGO from graphite, as well as graphene silica derived composites. Reproduced from ref. 93 with permission from Elsevier, Copyright 2016.

synthesized, including various chemical functionalities, such as ionic surfactants, ionic liquids, metal–organic frameworks (MOFs), nanoparticles (NPs), and molecular recognition functionalities such as molecularly imprinted polymers (MIPs), aptamers, and supramolecules, such as cyclodextrins, among many others.16 All the potentialities mentioned above have skyrocketed the application of graphene-based sorbents in sample preparation, which, allied to the broad toolkit of modern techniques, provides a wide spectrum of possibilities for solid-phase microextraction of diverse organic compounds from environmental, biological, forensic, and food-surveillance samples,1,5,7 such as those illustrated in Figure 6.2. GO, rGO and Si@G-derived composites have been used as sorbents and coatings in immobilized support techniques such as stir bar sorptive extraction (SBSE),17,18 and fiber,17,18 and in-tube17,18 formats of solid-phase microextraction (SPME). Likewise, multiple applications in techniques based on packed-formats, such as conventional solid-phase extraction (SPE),19,20 and its miniaturized version – microextraction by packed sorbent (MEPS)21,22 – have been widely described in recent years.

Graphene-based Sorbents for Modern Magnetic Solid-phase Extraction Techniques

Figure 6.2

177

Schematic representation of the graphene-based sorbents toolkit for modern sample preparation.

Nevertheless, graphene-based sample preparation can be susceptible to some drawbacks. For example, in immobilized supported coating-based techniques, the glue and polymers employed can suffer leaching under organic solvent conditions, causing interference in the instrumental analysis, especially when chromatographic and mass spectrometry techniques are used. Also, in packed-bed formats, graphene-based columns and extraction devices are susceptible to clogging and excessive back-pressure. Sorbent exfoliation can occur under high-pressure conditions, releasing graphene nanosheets, obstructing the frit’s pores in the extraction devices. Besides, sorbent swelling can also occur for continuous water/solvent deposition between the graphene nanosheets, contributing to the extraction device clogging.23,24 Dispersive solid-phase microextraction (DSPME) is one alternative to overcome those drawbacks. In this technique, there is no need for packed or coated extraction devices, and the process is usually speedy and efficient due to the enhanced analyte–sorbent interaction provided by the dispersion mechanism. Nevertheless, the small size and density of the graphene nanosheets make it challenging to recover the sorbent from the sample solution, even after intensive filtration or centrifugation stages.5,25 An advantageous alternative to overcome this limitation is magnetic solid-phase extraction (MSPE),26 a modern extraction strategy based on the use of sorbents supported over magnetic carries, which can be smoothly and efficiently collected from the sample bulk by application of an external magnetic field.27,28 Graphene-based magnetic sorbents (GMS) can be easily prepared by coordination of the oxygenated groups in the lattice surface with metallic atoms of magnetic carries such as the nanoparticles of magnetite (Fe3O4)

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and maghemite (g-Fe2O3). The use of magnetic graphene-based sorbents excludes the clogging difficulties of the packed device and efficiently addresses the limitations of the additional centrifugation and filtration steps of the conventional dispersive extractions.16 Hence, MSPE is nowadays the predominant technique in the exploitation of graphene-based sorbents. At present, most of the reported graphene applications in sample preparation correspond to MSPE of organic and inorganic analytes from several complex samples, including the treatment of solid matrices.30

6.2 Graphene-based Magnetic Sorbents Graphene-based magnetic sorbents (GMS) are characterized by a nanoparticle containing a magnetic core of metals such as nickel (Ni), cobalt (Co), iron (Fe), or oxides of magnetite (Fe3O4) and maghemite (g-Fe2O3) covered by graphene sheets that guarantees the selectivity of the material.31 This configuration aims to overcome each material’s limitations individually once the magnetic nanoparticles tend to undergo oxidation and form agglomerates.32 Furthermore, on the other hand, graphene sheets tend to aggregate due to their hydrophobic character and the strong van der Waals interactions existing between their sheets.16,33 Therefore, these new materials (GMS) present adequate extraction capacity, combining the affinity of graphene with several organic compounds through p–p stacking, electrostatic interactions, hydrogen bonds, and hydrophobic interactions, with the superparamagnetism of the nanoparticles, allowing the separation of the sorbent and sample by an external magnetic field.16 Although the GMS has an adequate extraction capacity, its hydrophobic character is not compatible with polar and ionic compounds and has little dispersivity in water, which impairs its performance.16 Allied to these limitations, nanoparticle incorporation reduces the graphene’s surface area and, consequently, decreases the material’s loadability.34 Some alternatives to overcome these barriers are to use graphene oxide, which has a more hydrophilic character, and therefore greater dispersivity in water,34,35 being suitable for the extraction of polar and ionic compounds. Besides, oxidation allows the functionalization of graphene with other organic groups, increasing its selectivity and surface area.16,36

6.2.1

Preparation of Graphene-based Magnetic Sorbents

The production of GMS mainly involves the Hummers method, by which graphene oxide is obtained from graphite. GO is characterized by having many chemical groups containing oxygen, such as hydroxyls, carbonyls, and epoxy.37 These are the same groups that favor the functionalization of other materials on the GO surface, which can later be reduced to graphene. Therefore, GMS might involve sorbents based on G or even GO.

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Several approaches are utilized to introduce nanoparticles in the G or GO sheets, such as synthesis hydrothermal, solvothermal, sonochemical, coprecipitation, and direct magnetization methods.16

6.2.1.1

Direct Magnetization

This approach consists of obtaining the GMS through the electrostatic interactions between the GO sheet’s negatively charged surface and the nanoparticle’s positively charged surface (iron oxides). Therefore, it is necessary to prepare a GO dispersion by ultrasound and iron oxide dispersion with an acid. These solutions are mixed for a specific time until a homogeneous solution is obtained containing the GO sheets bound to the iron oxide nanoparticles. The material is separated by centrifuging and applying an external magnetic field, followed by drying in an oven under vacuum.38 This methodology is outlined in Figure 6.3.

6.2.1.2

Coprecipitation Method

The coprecipitation method is one of the most common approaches for obtaining nanoparticles linked to G/GO. In this procedure, the iron oxide nanoparticles are generated in situ over the G/GO sheets. Therefore, FeCl2 and FeCl3 salts in an experimentally determined molar ratio are mixed with GO’s aqueous solution. The salts coprecipitation (eqn (6.1)) occurs by the addition of ammonia, under vigorous stirring (Figure 6.4). Graphene oxide can be further reduced with hydrazine hydrate to obtain G.39 FeCl2 þ 2FeCl3 þ 8NH4OH-Fe3O4 (on GO) þ 8NH4Cl þ 4H2O

(6.1)

Despite the simplicity of the method, it is difficult to have control of the shape and size of these nanoparticles, since this method is influenced by a series of parameters, such as the pH of the solution, the types of iron salts used, the molar proportion of the salts, temperature and ionic strength. Another limitation of the method is that the nanoparticles can be

Figure 6.3

Schematic representation of the process of obtaining Fe3O4/GO by direct magnetization. Reproduced from ref. 38 with permission from Elsevier, Copyright 2012.

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Figure 6.4

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(a) Schematic representation of obtaining Fe3O4/GO (MGO) by the coprecipitation approach. (b) Photograph of the GO and iron salts solutions, and the new sorbent. Reproduced from ref. 39 with permission from Springer Nature, Copyright 2018.

distributed unevenly under the G/GO sheets, generating agglomerates or reducing the binding sites of the resulting material.16

6.2.1.3

Hydrothermal Method

Hydrothermal synthesis consists of the oxidation of Fe21 ions over the GO sheets, in an alkaline medium and under high temperatures. A FeSO4 solution must be prepared and added to an aqueous solution of GO, followed by the addition of NaOH. The resulting solution must be vigorously mixed for a determined time and then transferred to an autoclave, where the formation of nanoparticles occurs under the GO sheets.40 If the interest is to obtain rGO leaves, a reducing agent such as hydrazine hydrate, or even glucose, should be introduced. This latter approach employs a more environmentally friendly reducing agent with a high capacity to reduce GO to rGO under hydrothermal conditions. The methodology is the same as that reported above; however, hydrazine or glucose should be introduced into the solution (Figure 6.5).41

6.2.1.4

Solvothermal Method

The solvothermal approach is similar to hydrothermal synthesis, with the difference of using an organic solvent.42–44 This type of synthesis is often performed together with obtaining GO by exfoliating graphite oxide with diethylene glycol. This solution should be added to a solution containing Fe31 salt

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Figure 6.5

Hydrothermal synthesis of Fe3O4/G using glucose as a reducing agent. Reproduced from ref. 41 with permission from Elsevier, Copyright 2011.

Figure 6.6

Solvothermal synthesis of Fe3O4/G. Reproduced from ref. 44 with permission from American Chemical Society, Copyright 2015.

and sodium acetate dissolved in diethylene glycol. After homogenization of the resulting solution, the formation of nanoparticles on the GO occurs in an autoclave. Sodium acetate is used in this method for electrostatic stabilization of nanoparticles under GO, and diethylene glycol acts as a solvent and reducing agent (Figure 6.6).

6.2.1.5

Sonochemical Method

The sonochemical approach is a methodology that has been stimulating the fields of organic synthesis, nanomaterials, organometallic chemistry, among

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other fields. Its superiority is in applying ultrasound to chemical reactions since ultrasound can generate the appropriate temperature and pressure conditions, in addition to its ability to heat and cool down quickly.45 The use of ultrasound can replace methods that require higher temperatures, such as solvothermal and hydrothermal synthesis, which are performed in an autoclave.46 Just adjust the ultrasound source to an appropriate frequency and power. It can also be used for the in situ coprecipitation method of iron salts under the G sheets.47,48

6.3 Functionalization of Graphene-based Magnetic Sorbents As previously mentioned, GMS can be derived with a great diversity of chemistry functionalities capable of providing improved sorbent selectivity and retention capability. Hence, GMS are frequently anchored to boronate affinity materials (BAM), ionic surfactants (ISs), ionic liquids (ILs), metal– organic frameworks (MOFs), and molecular recognition functionalities such as molecularly imprinted polymers (MIPs), aptamers, and supramolecules, such as cyclodextrins, between many others.16 Several different approaches for functionalizing the G/GO sheets with the same chemical group will be found in the literature. We herein discuss these methodologies in general, so that the reader can choose the methodology to fit their purposes. Modification with aptamers and boronate affinity materials (BAM) involves covalent functionalization.49–51 Therefore, the GMS is subjected to some chemical modifications of its surface that will allow it to link the chemical group of interest. After that, the GMS and the chemical group are incubated together for an appropriate amount of time and at the appropriate temperature. The addition of IL to the GMS can be done by mixing both in an ultrasound bath, followed by reflux with adequate time and temperature.52 Functionalization with MOF involves the self-assembly approach of organic ligands and metal ions under the GMS’s surface.53,54 For this, the GMS is first mixed with a solution of metal ions under mechanical agitation for a specified time. It is then introduced into a solution containing the organic ligands, and the process takes place in the same way. This process is repeated several times. The addition of MIPs can be done by the surface imprinting technique.55–58 In this case, the GMS is mixed with a solution containing: monomers, crosslinker, initiator, and the template molecule, for an appropriate time and temperature. Then, the MIP@GMS must be washed with an organic solvent to remove the template molecules. Another approach is the sol–gel method, in which the GMS is mixed with the template molecules under an ultrasound bath for a stipulated time, and then the monomers are added with pH adjustment so that polymerization occurs. Modification with carbon nanotubes can be carried out in several ways, such as pyrolysis of the GMS with urea (carbon source) and microwave radiation; a one-step reaction with the dissolution of GO with a carbon source, source of iron ions under microwave radiation, among other approaches.59

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Other functionalization methods can be found directly in GMS preparation articles with the reader’s chemical group of interest.

6.3.1

Molecularly Imprinted Polymers (MIPs)

Molecularly printed polymers (MIPs) consist of a synthetic polymer containing cavities with the appropriate size, shape, and functional groups to recognize a specific organic compound.16,58 They are highly selective materials, with low cost and ease of preparation,56 and therefore encourage the scientific community to search for new supports using this type of material. Graphene and graphene oxide are suitable supports for MIPs due to their high surface area. As a result, a MIPs@GMS has high adsorptive specificity, adsorption capacity, and faster dynamics of adsorption and desorption.58 This sorbent development requires the optimization of several variables, such as the number of monomers, model molecule, and polymerization time.58

6.3.2

Metal–Organic Frameworks (MOFs)

Metal–organic frameworks (MOFs) are designated as organic–inorganic supramolecular materials derived from the coordination of metal ions or agglomerates with multidentate ligands. They have exciting properties such as high surface area, adjustable polarity and pore size, and thermal stability.60 GMS’s functionalization with MOFs improves the properties of dispersibility, reuse, pore-volume, and mechanical resistance, leading to the development of a sorbent with unique properties.61,62 Thus, a sorbent with a high surface area, hydrophobic, and metal ion affinity is obtained. Together with the adjustable pores property, these characteristics allow the selective retention of target molecules, while macromolecules present in the sample are eliminated. Therefore, MOFs@GMS are widely used to enrich peptides through their reversible affinity with metal ions.53

6.3.3

Ionic Liquids (ILs) and Deep Eutectic Solvents (DESs)

Ionic liquids (ILs) are a class of organic salts seen as an alternative to current organic solvents.37 Their composition involves organic cations (e.g., imidazole, pyridinium, pyrrolidinium, tetraalkyl ammonium, tetraalkyl phosphonium, and sulfonium) and inorganic or organic anions (e.g., tetrafluoroborate, bromide, and hexafluorophosphate).16 Their extraction capacity combined with other physical and chemical properties such as a wide temperature range in the liquid state, high viscosity, affinity for organic and inorganic compounds, low vapor pressure, and wide range of solubility, and polarity, makes ILs attractive composites for GMS functionalization. The development of functionalized GMS with polymeric ionic liquids (ILs@GMS) revealed an increase in the adsorption sites and improved the hydrophobicity of graphene in water.63

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Despite the diverse eminent qualities of ILs, their high cost and toxicity limit their development and application. Thus, a new alternative is the deep eutectic solvents (DESs), which constitute a eutectic mixture between a Lewis or Bronsted acid and a base,64 such as choline chloride (ChCl), a quaternary ammonium salt widely applied due to its low cost and toxicity, ease of synthesis, biocompatibility, and biodegradability. This DES@GMS is widely used in protein enrichment.65,66

6.3.4

Boronate Affinity Materials (BAM)

GMS functionalized with boronate affinity materials (BAM@GMS) have high selectivity with cis-diol molecules (e.g., saccharides, glycans, glycoproteins, and nucleotides)67 and interact through the reversible formation of cyclic esters.16 Figure 6.7 shows the mechanism involved in the molecular interactions between these sorbents and the target analytes. Under conditions of pH above the pKa of boronic acid (BAM), that is, under alkaline conditions, the boron atom takes an anionic form (sp3 configuration), and therefore can react with cis-diol molecules, forming cyclic esters of five or six members. However, when the pH is changed to an acidic condition, boronic acid tends to dissociate from the cis-diol molecule; under these conditions, it is in the sp2 configuration.67

Figure 6.7

Interaction mechanism between BAM and cis-diol molecules. Reproduced from ref. 67 with permission from the Royal Society of Chemistry.

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Therefore, extraction with BAM@GMS requires control of pH conditions to ensure the selectivity of the sorbent. The appropriate pH can be predicted by the pKa value of the constituent boronic acid; however, this property may vary due to the anchoring in the GMS.67

6.3.5

Supramolecules

Supramolecules are a new set of large molecules with remarkable molecular recognition capabilities, interacting with organic compounds by forming a host–guest inclusion complex. Due to the cavity structure, supramolecules (crown ethers, calixarenes, cucurbiturils, pillararenes, and cyclodextrins) act as the host, capturing their guest (organic compound), which must have spatial correspondence with the cavity, and be able to establish hydrophobic and van der Waals interactions.16 Among the supramolecules mentioned, cyclodextrins are one of the most used in functionalization with GMS. An example of this class is the betacyclodextrins (b-CD).68,69 This type of cyclic polysaccharide is formed by seven D-glucopyranose units with glycosidic bonds of the a-1,4 type. Its cyclic structure allows forming a cone-like cavity (Figure 6.8), with a hydrophobic inner surface and a hydrophilic outer surface, owing to the direction of the hydroxyl group that forms the D-glucopyranose units. With this configuration, b-CDs are highly soluble in aqueous media, which increases the dispersion of GMS. Therefore, b-CD@GMS sorbents have a large surface area due to graphene presence, combined with the tremendous molecular recognition of supramolecules and their enrichment capacity.69

6.3.6

Aptamers

Aptamers (Apt) are small single strands (oligonucleotides) of DNA or RNA that can recognize a wide range of target analytes from small molecules, proteins, cells, and tissues, through hydrogen bonds, van der Waals interactions, among others. These interactions allow the aptamer to bind to the target compound and fold into specific shapes.16

Figure 6.8

Schematic representation of a b-CD@GMS and demonstration of the capture of a target analyte in its cavity. Adapted from ref. 69 with permission from Elsevier, Copyright 2017.

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Apt@GMS combines the high surface area of graphene with the high specificity and stability characteristics of aptamers. Besides, these materials are inexpensive, non-toxic, and easy to synthesize. This sorbent can selectively extract a target analyte in a shorter time than conventional extraction processes. For example, an Apt@GMS was used to purify histone from nucleoproteins with the same quality as the acid extraction that consumes in about two hours.50

6.3.7

Miscellaneous Functionalities

Other categories of GMS involve functionalization with ionic surfactants (sodium dodecyl sulfate, cetyltrimethylammonium bromide, octadecyl trimethyl ammonium), which are capable of forming hemimicelles/admicelles on the surface of the GMS containing a charge opposite to that of the surfactant.70 Therefore, pH changes are necessary to change the surface load of the GMS for further functionalization. The presence of ionic tails on the surfactants allows the new sorbent to interact with polar and ionic compounds.16 Several polymers have also been introduced in GMS, such as polythiophene, polyacrylic acid, chitosan, polypyrrole, and polydopamine. This last polymer is the most used among those mentioned. Its hydrophilic nature due to the presence of the hydroxyl groups helps graphene interact with aromatic analytes through p–p stacking interactions. Other chemical groups that have been little explored for functionalization with GMS are carbon nanotubes (CNTs) that have a high adsorption capacity, and microporous organic polymers (MOPs), which as the name suggests, have a high surface area and well-defined pores.37

6.4 Characterization of Graphene-based Magnetic Sorbents Once synthesized, graphene-based magnetic sorbents are typically characterized by techniques such as X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM), Fourier transform infrared spectroscopy (FTIR), and diffuse reflectance ultraviolet–visible spectrophotometry (DRS), Raman spectroscopy, vibrating-sample magnetometer (VSM), thermogravimetric analysis (TGA), transmission electron microscopy (TEM), and zeta potential measurement. The GMS crystal structure, Figure 6.9, generally exhibits a characteristic diffraction peak at 2y ¼ 26.21 corresponding to the reflection (002) of graphene; in addition significant diffraction peaks are observed for the Fe3O4 crystal planes (2y ¼ 30.21, 35.61, 43.31, 53.71, 57.31 and 62.81), assigned to (2 2 0) (3 1 1) (4 0 0) (4 2 2) (5 1 1) and (4 0 0) respectively.71 Of the SEM images obtained from this type of sorbents, one is presented in Figure 6.10. Characteristics of graphene sheets are observed; these are wrinkled sheets of carbon in the form of silk waves, being coated by iron

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Figure 6.9

187

Illustrative example of X-ray diffraction pattern of G (a) and G/Fe3O4 (b). Reproduced from ref. 71 with permission from Elsevier, Copyright 2011.

oxide nanoparticles, which were distributed over the entire surface, some of them presenting a certain degree of saturation.71 The expected band’s presence in a typical FT-IR spectrum of the magnetic sorbents is shown in Table 6.1. UV–vis analysis shows a characteristic absorption peak of GO at 230 nm corresponding to the p–p* transition of C–C aromatic bonds. When the magnetic nanohybrid is formed, this peak tends to move to 277 nm, confirming the formation of the magnetic sorbent [email protected] In a Raman spectrum, the change in structure can be observed after the self-assembly and reduction process (Figure 6.11), in which two peaks were obtained at 1340 (D) and 1590 (G) cm1, with band D being the product of the disorder associated with structural defects, while G is characteristic of the sp2 hybridization of C–C bonds. Therefore, the intensity ratios of these two bands are used to compare different carbon structures, being found in the literature as ID/IG or I(D)/I(G). The increase in the ID/IG value confirms the reduction and magnetization of the sorbent under study.73 Another critical characterization parameter is the evaluation of the superparamagnetic properties of the GMS. This can be evaluated through a graph in which the magnetization is a function of the magnetic field at 298 K (Figure 6.12), showing whether they have sufficient saturation intensity for magnetic separation with a conventional magnet.71 The thermogravimetric analysis allows the content of each component of the magnetic sorbent, Figure 6.13, to be determined by oxidative decomposition. Generally, three weight loss processes occur, one at approximately 120 1C, attributed to the evaporation of adsorbed water molecules. A second process between 120–350 1C due to the elimination of labile oxygen-containing functional groups, such as CO, CO2, and H2O, thanks to the destruction of oxygenated functional groups. Finally, the TGS/DSC spectra have a characteristic weight/peak at 350–520 1C. A robust exothermic peak is observed in the DSC curve at 430 1C, due to the carbon skeleton decomposition. Then, at 520 1C, no representative weight loss is observed,

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Figure 6.10

Chapter 6

SEM of G (a) and G/Fe3O4 composite (b). Reproduced from ref. 71 with permission from Elsevier, Copyright 2011.

indicating that approximately 85.1% of the weight of the metallic oxide is deposited on the graphene’s surface, which is expected.74 The zeta potential is a property of a material that can measure the particle’s stability dispersed on the surface. For this reason, Fe3O4 nanoparticles are usually found to be positively charged in magnetic materials, while GO is negatively charged due to the presence of carboxyl, hydroxyl, and epoxy

Graphene-based Sorbents for Modern Magnetic Solid-phase Extraction Techniques Table 6.1

189

Characteristic FT-IR bands of graphene-based magnetic sorbents.

Assignation

Wave number (cm1)

O–H stretching vibration due to partial reduction of CQO to C–OH. Broad absorption. O–H stretch due to hydroxyl groups on the surface of nanoparticles. O–H angular vibration Fe3O4–rGO Stretch vibration CQC GO completely reduced Paramagnetic adsorption peak of Fe3O4 particles. Fe–O stretching.

3410.98

Figure 6.11

3396.20 1622.28 1622.11 562.34

Raman spectrum of GO (lower curve) and 3D-G–Fe3O4 (upper curve). Reproduced from ref. 73 with permission from Elsevier, Copyright 2018.

groups. Therefore, self-assembly of the GO on the surface of the nano-Fe3O4 can be easily obtained through electrostatic interactions.75

6.5 Modern Applications of Graphene-based Magnetic Sorbents Due to the material’s mentioned potentialities, GMS is being used in countless applications to extract organic compounds from biomolecules and metal ions in different matrices. This can be observed in Figure 6.14; the

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Figure 6.12

VSM magnetization curves of Fe3O4 and G/Fe3O4. Reproduced from ref. 71 with permission from Elsevier, Copyright 2011.

Figure 6.13

TG/DSC curves of FGC in an air atmosphere. Reproduced from ref. 74 with permission from Elsevier, Copyright 2011.

data were obtained from the Web of Science database. ‘‘Graphene-based sorbents’’ and ‘‘magnetic solid-phase extraction’’ were used as keywords. In the last 5 years, the number of publications on this subject has been increasing; from 2019 until the middle of 2020, over 50% of the total number of publications was reported to include these subjects. This allows us to predict that the trend will continue.

Graphene-based Sorbents for Modern Magnetic Solid-phase Extraction Techniques

Figure 6.14

191

Scientometric distribution of the recent publications containing graphene-based sorbents; (a) distribution by year of publication; (b) classification of the publication by subject area.

Among a large number of applications, the work carried out by Luo et al. in which sulfonamides were extracted from water samples by physical immobilization of graphene nanospheres on silica-coated magnetite, Fe3O4@ SiO2/G, is highlighted. In this report, it is evident why the preferred synthetic method when working with these sorbent materials is the chemical bond of graphene to silanol groups, since the researchers obtained the particles by dispersion, through a sonication process for several hours, resulting in useful but not reusable particles as they are not stable enough.76 Thus, it is clear that the magnetic particles absorption capacity is due to the hydrophobic interactions of the honeycomb network of carbon atoms. Therefore, for the extraction of polar or ionic compounds by MSPE, bare graphene magnetic particles as an extracting sorbent are not suitable. This chapter will compile recent applications of graphene-based magnetic graphene composites to detect organic pollutants (pesticides, drugs, among others), inorganic pollutants, and biological macromolecules.

6.5.1

Applications on the Extraction of Organic Pollutants

Pesticides are one of the most controversial compounds due to the need to use them to protect crops, but at the same time due to the damage they cause both environmentally and in human health since their use is so widespread that it is currently common to find residues of these compounds in soils, bodies of water, and foodstuffs. Their general carbon ring-based structure is extensively studied by applying graphene-based magnetic sorbents, always seeking to obtain more effective, highly selective, and environmentally friendly analytical methods. Nevertheless, despite the already demonstrated disadvantages regarding the use of bare graphene magnetic particles, this is still one of the most used sorbents due to its fast and straightforward preparation compared to other sorbents.16

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Another class of organic pollutants is drug residues (human and veterinary), which can be caused both by unreasonable emissions from hospitals and factories and by residues remaining in the human or animal body after consumption or eliminated through their droppings. However, despite their low concentrations, it is necessary to detect and quantify them. It is essential to carry out sample pre-treatment to achieve the desired quantification; this pre-treatment can be done using G/GO magnetic materials, obtaining efficient extractions and reasonably low LOD. A good example is a work published by Yilmaz and Sharp for the detection of Ibuprofen in pharmaceutical, ambient water, and synthetic urine samples, using a fast and efficient preconcentration method using the mentioned graphene-like two-dimensional transition metal dichalcogenides such as MoS2, MoSe2, MoTe2, NbS2, NbSe2, WS2, WSe2, TaS2 and TaSe2.77 The nanoflowers obtained (MoS2@Fe3O4@C-dot NFs) were synthesized employing a simple green hydrothermal synthesis procedure, with the carbon points (C points) obtained from cow’s milk. Thanks to the structure of the MoS2 in the form of interleaved layers, many magnetic C-points can quickly enter the spaces between the layers, and in turn, these magnetic C points (Fe3O4@C) prevent the MoS2 layers from clumping together, the latter acting as protective layers by its chemical stability. Finally, the –OH and –COOH groups at points C improve the extraction efficiency by forming hydrogen bonds with Ibuprofen. Thus, these new sorbents are showing excellent extraction yields when used in the MSPE process. Another important application of the GMS is found in the determination of drugs in food surveillance. For example, the European Union and other government organizations have established maximum limits for some contaminants in food, such as 100 mg kg1 for sulfonamides, 100 mg kg1 for ciprofloxacin in milk or meat, 10 mg kg1 for sarafloxacin in chicken, among many others.78 He and collaborators determined those drug residues with fluoroquinolone in foods of animal origin. The authors obtained high absorption capacities (46800 ng) and high enrichment factors (68–79 times) for the 7 fluoroquinolones studied, in addition to the sorbent being able to be used at least 40 times.79 Another exciting application of MSPE based on graphene has to do with the so-called endocrine disruptors. Despite being exogenous compounds, which behave like natural hormones, they can have adverse effects on the reproductive system, growth, metabolism, the cardiovascular system, and even on the human immune system. This suggests that the study of analytes such as phthalates, phenols, and estrogens is essential, focusing mainly on environmental sample analysis. Shah and Jan proposed a method in which the sorbent is a non-toxic chemical composed of crosslinked alginate encapsulated magnetic graphene oxide beads, revealing the functional groups of alginate and graphene oxide on the surface of the beads, which through p–p, n–p, and hydrogen bonding interactions, effectively adsorb Bisphenol A (6.73 mg g1) and Epichlorohydrin (7.01 mg g1).80

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The GMS used in MSPE has also been used to analyze compounds such as polycyclic aromatic hydrocarbons (PAHs), dyes, additives, brominated flame retardants, among many others.16 Additives are compounds that have been gaining considerable interest in the food industry since they improve the appearance, taste, and structure of foods. The drawback is the excessive use that is often given to them, so the study of these substances has gained a lot of interest in guaranteeing the quality of food.78 In work presented by Yu and Fan, an MSPE extraction method was developed using magnetic nanoparticles coated with graphenemodified tetraethyl orthosilicate and 3-aminopropyltriethoxysilane to study Allura Red, an additive frequently used in beverages, sweets, and gelatin. It mainly comes from oil and has given a negative response for in vitro genotoxicity, as well as for long-term carcinogenic studies, so both JECFA and the European Union Scientific Committee for Food (SCF) established a maximum concentration of 0–7 mg kg1 body weight (bw) dia1.81 Mycotoxins are other investigated compounds in food samples because these are secondary metabolites produced by toxigenic fungi in growing plants, which can accumulate in the human body due to the intake of foods such as grains, oil, milk, and meat, affecting human health.78 Magnetic graphene oxide (MGO) nanocomposites have been used for the adsorption of these compounds, as proposed by Pirouz et al., who managed to reduce the Fusarium mycotoxins in palm kernel cake (PKC), which is naturally contaminated. Among these, the mycotoxins investigated were zearalenone (ZEA), the fumonisins (FB1 and FB2), and trichothecenes (deoxynivalenol toxins (DON), HT-2 and T-2). The best results were obtained at a pH of 6.2.82

6.5.2

Applications on the Extraction of Inorganic Pollutants

Another controversial issue is the environmental contamination by heavy metals due to their high toxicity, although only traces of them are detected since they accumulate in living organisms causing severe disorders and diseases. Their study using G-based MSPE has become popular mainly for the analysis of Cd(II), Zn(II), As(II) and As(IV), Hg(II), and Cr(VI). The magnetic sorbent easily absorbs these metals through cationic, electrostatic, hydrogen bonding, and additive bonding interactions.16 A super important parameter is the pH of the sample solutions since the zeta potentials of the G/GO sorbents vary with pH. This was demonstrated in work published by Zhou et al., in which for the elimination of Cr(VI), they used graphene oxide/F3O4 reduced by hydrothermal self-assembly, where the maximum adsorption capacity was recorded in acid and neutral medium. However, it decreased drastically in alkaline medium, attributed to the change in load and the sorbent.83 Seeking to improve the selectivity of the sorbent against Cr(VI), Chen et al. synthesized triethylenetetramine–magnetite reduced graphene oxide (TET–MRGO), also achieving excellent results in the elimination of Cu(II), thanks to the high affinity of nitrogen atoms and Cu(II) ions.84,85

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Another metal also studied is Co(II), which was successfully adsorbed by a zero-valence iron-modified magnetic graphene sorbent, proposed by Xing et al.86 Next, they worked with magnetic cobalt and nickel ferrites (CoFe2O4 and NiFe2O4) to synthesize graphene nanocomposites (CoFe2O4–G and NiFe2O4–G) through a solvothermal process to study Pb(II) and Cd(II) in water samples.87 A study carried out by Qi et al. reduced magnetite/reduced graphene oxide (MRGO) nanocomposites by different methods (solvothermal, hydrothermal, and coprecipitation). The authors demonstrate that according to the method of preparation, sorbents present certain functional groups on the surface, specific particle size, and a particular morphology, which leads to a certain affinity toward a metal ion, a drug, or a dye,88 being extremely important to study the preparation method before applying to obtain the best results.

6.5.3

Applications on the Extraction of Biological Macromolecules

Another relevant application using G-based MSPE is the study of so-called biological macromolecules, such as proteins and peptides, due to their essential relationship in detecting diseases such as cancer.16 Lu and his colleagues proposed an MSPE method with Fe3O4/graphene/TiO2 to extract phosphopeptides from biological samples, considering that these macromolecules are quite relevant in regulating biological pathways in cancer cells. Therefore, when modifying the sorbent with TiO2, graphene gained high adsorption selectivity, and the results were very satisfactory.89 Subsequently, Yin et al. obtained magnetic graphene double-sided mesoporous nanocomposites (maggraphene@mSiO2) to study endogenous peptides. This material presented a large surface area and, therefore, a large volume of pores that allowed efficient adsorption of the target molecules by hydrophobic–hydrophilic interactions. Fe3O4 particles on both sides of the material enriched the extraction process.90 Another work to be highlighted is that of Shi et al., in which they worked with hydrophilic polydopamine-coated magnetic graphene nanocomposites (MG@PDA) which not only managed to immobilize a large amount of trypsin but also, thanks to the presence of PDA, presented outstanding biocompatibility against the substances of interest; this work paved the foundations for high-performance proteomic studies.91 Most recent work includes that of Liu et al., in which DNA was extracted using MSPE with nano-compounds of magnetic chitosan modified with guanidine ionic fluid/graphene oxide (GIL–MCGO); the collection was done using an external magnet, of the monocaterian DNA or the sodium DNA salts. These nanocomposites are highly efficient in extracting DNA from complex matrices such as salmon sperm, human blood, and E. coli cell lysate.92

6.6 Conclusion The association between graphene and magnetic nanoparticles is currently one of the most explored sample preparation insights. The synergetic

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properties of these materials enable the development of new, efficient, and diversified sample treatment strategies, which can supply many modern analytical chemistry challenges. Graphene is a modern nanomaterial with growing interest and application in many scientific and technological areas. In analytical chemistry, graphenebased extraction sorbent development has aroused particular interest because of its great superficial area, providing multiple analyte interaction sites. Besides its hydrophobic character, graphene can be oxidized incorporating oxygenated functional groups, which offer a polar character and reactive sites to anchor more diversified chemical functionalities, which can confer improved selectivity and analyte uptake. Hence, graphene-based sorbents can have incorporated diverse molecular recognition functionalities, supramolecular moieties, and a wide diversity of organic functional groups able to provide analyte–sorbent interaction through a wide diversity of mechanisms. Once the final sorptive capacities depend on the nature and amount of functional moieties incorporated over the graphene sorbent, material characterization is also an essential step in producing and using a determined graphene-based sorbent. Several instrumental techniques, such as elemental analysis, XDR, FTIR, SEM, and DTA, among many others, can provide valuable qualitative and quantitative information, which allows relating the sorbent capacity with the sorbent constitution. Among the several modern sample preparation techniques, the MSPE reveals especially attention for exploiting graphene-based sorbents. This technique efficiently addresses the agglomeration, solvent/water incorporation, and good dispersion, frequently present when graphene-based sorbents are employed in packed, immobilized, and dispersive sample preparation formats. Hence, from the first description almost ten years ago, the development and application of graphene-based MSPE methods have been under continuous development. Its demand will continue due to its great applicability in studying environmental, forensic, clinical, and food interest samples in the coming years.

Acknowledgements The authors acknowledge the financial support from grant #2010/19910-9, ˜o Paulo Research grant # #2017/02147-0, and grant #2019/22724-7, from Sa Foundation (FAPESP). We also acknowledge grants 308843/2019-3, #459326/ 2014-7, #307293/2014-9, and #311300/2015-4 from CNPq. This study was ˜o de Aperfeiçoamento de Pessoal de financed in part by the Coordenaça Nı´vel Superior - Brasil (CAPES) – Finance Code 001.

References 1. H. Grajek, J. Jonik, Z. Witkiewicz, T. Wawer and M. Purcha"a, Crit. Rev. Anal. Chem., 2020, 50, 445. 2. K. S. Novoselov, Science, 2004, 306, 666.

196

Chapter 6

3. K. S. Novoselov, D. Jiang, F. Schedin, T. J. Booth, V. V. Khotkevich, S. V. Morozov and A. K. Geim, Proc. Natl. Acad. Sci., 2005, 102, 10451. 4. M. J. Allen, V. C. Tung and R. B. Kaner, Chem. Rev., 2010, 110, 132. 5. X. Hou, S. Tang and J. Wang, TrAC, Trends Anal. Chem., 2019, 119, 115603. 6. A. K. Geim, Science, 2009, 324, 1530. 7. A. L. de Toffoli and F. M. Lanças, J. Sep. Sci., 2018, 41, 288. 8. H. Zhang and H. K. Lee, J. Chromatogr. A, 2011, 1218, 4509. 9. Y.-B. B. Luo, J.-S. S. Cheng, Q. A. Ma, Y.-Q. Q. Feng and J.-H. H. Li, Anal. Methods, 2011, 3, 92. 10. E. V. S. Maciel, K. Mejı´a-Carmona, M. Jordan-Sinisterra, L. F. da Silva, D. A. Vargas, Medina and F. M. Lanças, Front. Chem., 2020, 8, 664. 11. W. S. Hummers and R. E. Offeman, J. Am. Chem. Soc., 1958, 80, 1339. ˇk, A. Ambrosi, G. Zhao, Z. Sofer and M. Pumera, 12. H. L. Poh, F. ˇ Sane Nanoscale, 2012, 4, 3515. 13. A. T. Smith, A. M. LaChance, S. Zeng, B. Liu and L. Sun, Nano Mater. Sci., 2019, 1, 31. 14. Q. Liu, J. Shi, J. Sun, T. Wang, L. Zeng and G. Jiang, Angew. Chem., Int. Ed., 2011, 50, 5913. 15. A. Speltini, M. Sturini, F. Maraschi, L. Consoli, A. Zeffiro and A. Profumo, J. Chromatogr. A, 2015, 1379, 9. 16. N. Li, H. Jiang, X. Wang, X. Wang, G. Xu, B. Zhang, L. Wang, R. Zhao and J. Lin, TrAC, Trends Anal. Chem., 2018, 102, 60. 17. K. Mejı´a-Carmona and F. M. Lanças, J. Chromatogr. A, 2020, 1621, 461089. 18. A. L. De Toffoli, B. H. Fumes and F. M. Lanças, J. Environ. Sci. Health, Part B, 2018, 53, 434. ´s, J. Food 19. R. Mateos, S. Vera, A. M. Dı´ez-Pascual and M. P. San Andre Compos. Anal., 2017, 62, 223. 20. W. A. W. Ibrahim, H. R. Nodeh and M. M. Sanagi, Crit. Rev. Anal. Chem., 2016, 46, 267. 21. B. H. Fumes and F. M. Lanças, J. Chromatogr. A, 2017, 1487, 64. ´cia de Toffoli 22. E. Vasconcelos Soares Maciel, B. Henrique Fumes, A. Lu and F. Mauro Lanças, Electrophoresis, 2018, 39, 2047. 23. A. Iakunkov, J. Sun, A. Rebrikova, M. Korobov, A. Klechikov, A. Vorobiev, N. Boulanger and A. V. Talyzin, J. Mater. Chem. A, 2019, 7, 11331. 24. S. Zheng, Q. Tu, J. J. Urban, S. Li and B. Mi, ACS Nano, 2017, 11, 6440. 25. F. Li, Y. Huang, K. Huang, J. Lin and P. Huang, Int. J. Mol. Sci., 2020, 21, 390. ´ and I. ˇ 26. M. ˇ Safarˇ´kova ı Safarˇ´k, ı J. Magn. Magn. Mater., 1999, 194, 108. 27. S. E. Kepekci-Tekkeli and Z. Durmus, J. Chil. Chem. Soc., 2019, 64, 4448. ´n-Vidal, A. Cepeda and 28. I. S. Ibarra, J. A. Rodriguez, C. A. Gala J. M. Miranda, J. Chem., 2015, 2015, 1. 29. A. Laura, C. Chiara, C. Giorgia, L. Barbera, C. Maria, M. Susy and `, Chromatographia, 2019, 82, 1251. A. Lagana

Graphene-based Sorbents for Modern Magnetic Solid-phase Extraction Techniques

197

30. B. Feriduni, A. Mohebbi, M. A. Farajzadeh and M. Namvar, Food Anal. Methods, 2019, 12, 2742. 31. B. Hu, M. He and B. Chen, in Solid-Phase Extraction, ed. C. F. Poole, Elsevier, Amsterdam, 2020, p. 235. 32. T. Jamshaid, E. T. T. Neto, M. M. Eissa, N. Zine, M. H. Kunita, A. E. El-Salhi and A. Elaissari, TrAC, Trends Anal. Chem., 2016, 79, 344. 33. M. Khan, M. N. Tahir, S. F. Adil, H. U. Khan, M. R. H. Siddiqui, A. A. Al-Warthan and W. Tremel, J. Mater. Chem. A, 2015, 3, 18753. 34. T. Chatzimitakos and C. Stalikas, Separations, 2017, 4, 14. 35. S. Su, B. Chen, M. He, B. Hu and Z. Xiao, Talanta, 2014, 119, 458. 36. I. Ali, A. A. Basheer, X. Y. Mbianda, A. Burakov, E. Galunin, I. Burakova, E. Mkrtchyan, A. Tkachev and V. Grachev, Environ. Int., 2019, 127, 160. 37. N. Manousi, E. Rosenberg, E. Deliyanni, G. A. Zachariadis and V. Samanidou, Molecules, 2020, 25, 1148. 38. Q. Han, Z. Wang, J. Xia, S. Chen, X. Zhang and M. Ding, Talanta, 2012, 101, 388. 39. S. Pu, S. Xue, Z. Yang, Y. Hou, R. Zhu and W. Chu, Environ. Sci. Pollut. Res., 2018, 25, 17310. 40. T. Qi, C. Huang, S. Yan, X. J. Li and S. Y. Pan, Talanta, 2015, 144, 1116. 41. J. Shen, M. Shi, H. Ma, B. Yan, N. Li and M. Ye, Mater. Res. Bull., 2011, 46, 2077. 42. H. Sun, L. Cao and L. Lu, Nano Res., 2011, 4, 550. 43. G. Vinodhkumar, J. Wilson, S. S. R. Inbanathan, I. V. Potheher, M. Ashokkumar and A. C. Peter, Phys. B Condens. Matter, 2020, 580, 411752. 44. S. Zhan, D. Zhu, S. Ma, W. Yu, Y. Jia, Y. Li, H. Yu and Z. Shen, ACS Appl. Mater. Interfaces, 2015, 7, 4290. 45. X. Hangxun, B. W. Zeiger and K. S. Suslick, Chem. Soc. Rev., 2013, 42, 2555. 46. S. Zhu, J. Guo, J. Dong, Z. Cui, T. Lu, C. Zhu, D. Zhang and J. Ma, Ultrason. Sonochem., 2013, 20, 872. 47. M. P. Deosarkar, S. M. Pawar and B. A. Bhanvase, Chem. Eng. Process. Process Intensif., 2014, 83, 49. 48. G. Park, L. Bartolome, K. G. Lee, S. J. Lee, D. H. Kim and T. J. Park, Nanoscale, 2012, 4, 3879. 49. J. Su, X. He, L. Chen and Y. Zhang, Talanta, 2018, 180, 54. 50. Y. Chen, B. Jiang, Y. Hu, N. Deng, B. Zhao, X. Li, Z. Liang, L. Zhang and Y. Zhang, Electrophoresis, 2019, 40, 2135. 51. Y. Xiong, C. Deng and X. Zhang, Talanta, 2014, 129, 282. 52. L. Gholami-Bonabi, N. Ziaefar and H. Sheikhloie, Water Sci. Technol., 2020, 81, 228. 53. G. Cheng, Z. G. Wang, S. Denagamage and S. Y. Zheng, ACS Appl. Mater. Interfaces, 2016, 8, 10234. 54. Y. Zheng, S. Zheng, H. Xue and H. Pang, Adv. Funct. Mater., 2018, 28, 1. 55. J. Guo, Y. Wang, Y. Liu, C. Zhang and Y. Zhou, Talanta, 2015, 144, 411.

198

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56. F. Ning, H. Peng, J. Li, L. Chen and H. Xiong, J. Agric. Food Chem., 2014, 62, 7436. 57. F. Tan, M. Liu and S. Ren, Sci. Rep., 2017, 7, 1. 58. J. Luo, Y. Gao, K. Tan, W. Wei and X. Liu, ACS Sustainable Chem. Eng., 2016, 4, 3316. 59. V. K. Sharma, T. J. McDonald, H. Kim and V. K. Garg, Adv. Colloid Interface Sci., 2015, 225, 229. 60. H. Furukawa, K. E. Cordova, M. O’Keeffe and O. M. Yaghi, Science, 2013, 341, 1230444. 61. F. Pourbahman, M. Zeeb, A. Monzavi and S. S. Homami, Chem. Pap., 2019, 73, 3135. 62. X. Cao, Z. Jiang, S. Wang, S. Hong, H. Li, Y. Shao, Y. She, J. Wang, F. Jin and M. Jin, J. Sep. Sci., 2017, 40, 4747. 63. Y. Chen, S. Cao, L. Zhang, C. Xi, X. Li, Z. Chen and G. Wang, J. Chromatogr. A, 2016, 1448, 9. 64. E. L. Smith, A. P. Abbott and K. S. Ryder, Chem. Rev., 2014, 114, 11060. 65. Y. Huang, Y. Wang, Q. Pan, Y. Wang, X. Ding, K. Xu, N. Li and Q. Wen, Anal. Chim. Acta, 2015, 877, 90. 66. K. Xu, Y. Wang, X. Ding, Y. Huang, N. Li and Q. Wen, Talanta, 2016, 148, 153. 67. D. Li, Y. Chen and Z. Liu, Chem. Soc. Rev., 2015, 44, 8097. 68. D. Wang, L. Liu, X. Jiang, J. Yu and X. Chen, Colloids Surf., A, 2015, 466, 166. 69. S. Mahpishanian and H. Sereshti, J. Chromatogr. A, 2017, 1485, 32. ´. Rı´os and M. Zougagh, TrAC, Trends Anal. Chem., 2016, 84, 72. 70. A 71. C. Wang, C. Feng, Y. Gao, X. Ma, Q. Wu and Z. Wang, Chem. Eng. J., 2011, 173, 92. 72. M. Z. Kassaee, E. Motamedi and M. Majdi, Chem. Eng. J., 2011, 172, 540. 73. A. Rahimi, M. A. Zanjanchi, S. Bakhtiari and M. Dehsaraei, Food Chem., 2018, 262, 206. 74. Y. Yao, S. Miao, S. Liu, L. P. Ma, H. Sun and S. Wang, Chem. Eng. J., 2012, 184, 326. 75. H. Ravishankar, J. Wang, L. Shu and V. Jegatheesan, Process Saf. Environ. Prot., 2016, 104, 472. 76. Y. B. Luo, Z. G. Shi, Q. Gao and Y. Q. Feng, J. Chromatogr. A, 2011, 1218, 1353. 77. E. Yilmaz and G. Sarp, Anal. Methods, 2020, 12, 1570. 78. X. Hou, S. Tang and J. Wang, TrAC, Trends Anal. Chem., 2019, 119, 115603. 79. X. He, G. N. Wang, K. Yang, H. Z. Liu, X. J. Wu and J. P. Wang, Food Chem., 2017, 221, 1226. 80. Tasmia, J. Shah and M. R. Jan, Ecotoxicol. Environ. Saf., 2020, 190, 110099. 81. Y. Yu and Z. Fan, Food Addit. Contam., Part A, 2016, 33, 1527.

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82. A. A. Pirouz, J. Selamat, S. Z. Iqbal, H. Mirhosseini, R. A. Karjiban and F. A. Bakar, Sci. Rep., 2017, 7, 1. 83. W. Du, C. Lei, S. Zhang, G. Bai, H. Zhou, M. Sun, Q. Fu and C. Chang, J. Pharm. Biomed. Anal., 2014, 91, 160. 84. J. H. Chen, H. T. Xing, X. Sun, Z. B. Su, Y. H. Huang, W. Weng, S. R. Hu, H. X. Guo, W. B. Wu and Y. S. He, Appl. Surf. Sci., 2015, 356, 355. 85. Y. Chen, B. Pan, H. Li, W. Zhang, L. Lv and J. Wu, Environ. Sci. Technol., 2010, 44, 3508. 86. M. Xing, L. Xu and J. Wang, J. Hazard. Mater., 2016, 301, 286. 87. C. Santhosh, P. Kollu, S. Felix, V. Velmurugan, S. K. Jeong and A. N. Grace, RSC Adv., 2015, 5, 28965. 88. T. Qi, C. Huang, S. Yan, X. J. Li and S. Y. Pan, Talanta, 2015, 144, 1116. 89. J. Lu, C. Deng, X. Zhang and P. Yang, ACS Appl. Mater. Interfaces, 2013, 5, 7330. 90. P. Yin, N. Sun, C. Deng, Y. Li, X. Zhang and P. Yang, Proteomics, 2013, 13, 2243. 91. C. Shi, C. Deng, Y. Li, X. Zhang and P. Yang, Proteomics, 2014, 14, 1457. 92. M. Liu, X. Ding, X. Wang, J. Li, H. Yang and Y. Yin, RSC Adv., 2019, 9, 23119. 93. C. E. D. Nazario, B. H. Fumes, M. R. da Silva and F. M. Lanças, J. Chromatogr. B: Anal. Technol. Biomed. Life Sci., 2017, 1043, 81.

CHAPTER 7

Magnetic Nanoparticles as an Efficient Tool for Analyte Extraction: Challenges and New Opportunities M. RAPA,a L. MADDALONI,a R. RUGGIERI,a I. FRATODDIb AND G. VINCI*a a

Department of Management, Sapienza University of Rome, via del Castro Laurenziano 9 00161, Rome, Italy; b Department of Chemistry, Sapienza University of Rome, Piazzale Aldo Moro 5, 00185, Rome, Italy *Email: [email protected]

7.1 Introduction During history, many inventions have promoted the evolution of society. The first millennium was characterized by paper, algebra and gunpowder inventions. The second millennium saw the introduction of the printing press, steam and fuel engines, vaccines, relativity theory and atomic energy. In the current millennium, together with laser, smartphone, USB technology, GPS and 3D printing, the development of nanomaterials has found great applicability in industrial and research fields.1 Nanomaterials are introducing changes in many industrial areas, allowing some particular characteristics such as the type of material, and the size, shape, morphology, chemical composition and molecular configuration of the materials to be managed. Moreover, the use of nanomaterials has expanded rapidly, from the first applications in the materials field, to multiple sectors Analytical Applications of Functionalized Magnetic Nanoparticles Edited by Chaudhery Mustansar Hussain r The Royal Society of Chemistry 2021 Published by the Royal Society of Chemistry, www.rsc.org

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such as medical and pharmaceutical, biological, environmental, electronic and recently agro-food.2 Among the different types of nanomaterials, including nanotubes, nanocluster and nanowires, the use of nanoparticles, generally functionalized, has increased in the last decades. The functionalization type is chosen according to many variables, such as the interaction required, the application fields and ease of synthesis. Within this framework, the synergic collaboration of research in analytical chemistry and materials sciences has developed several methods for the efficient and rapid determination of analytes, especially in complex matrices.3,4 Magnetic Nanoparticles (MNPs) can be involved in all the analytical steps, starting from the sample pretreatment, the chromatographic techniques, the membrane application, moving to the lab-on-chip or the Artificial Intelligence (AI) tools.5 In this chapter MNPs as an efficient tool for analyte extraction are analyzed by highlighting the challenges and new opportunities that this application can bring. Since the 2000s, MNPs have been used in the analyte extraction field. By analyzing literature through the Scopus database, it is possible to highlight that the number of papers published on the use of MNPs for analyte extraction has increased since 2015 and then remained constant (about 170 per year) until 2020 (see Figure 7.1). Therefore, the application of MNPs as an extraction tool has grown by about 150% over the past two decades, to a total of more than 700 publications. The distribution of authors by country was assessed. Again, for this evaluation, the Scopus database was examined. The country with the most contributions was China with 490 papers representing 42% of the total

Figure 7.1

Trend of papers published on MNPs as an extraction tool (2001–2019). Source: Scopus.

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Figure 7.2

Papers published on MNPs as an extraction tool in terms of the author’s country. Source: Scopus.

Figure 7.3

The papers published on MNPs as an extraction tool for 108 inhabitants in the author’s country. Source: Scopus.

number. In second place was Iran, followed by the USA, Spain, India, Turkey, Germany, Canada, Malaysia and Brazil (see Figure 7.2). In addition, the number of papers per one hundred million of the country’s population was determined. From this perspective, the Iranians were the researchers that published more than the other countries (41 papers per 108 inhabitants). China, which was the first in terms of number of papers, in this classification placed 6th (see Figure 7.3).

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Indeed, the development of MNPs applications for analyte extraction is widespread throughout the world6. So, the research in this field is continuing to speed up in all continents with the leadership of Asiatic researchers.

7.2 Sample Pre-treatment: A Key Step in Analytical Determination Despite the fact that the currently available analytical instrumentation has reached very high levels of sensitivity, it is necessary to extract and contextually pre-concentrate an analyte, starting from the matrix in which it is dissolved.7 For these reasons, sample pre-treatment is typically considered one of the key-steps in all analytical procedures, except for non-destructive methods.8 Pre-treatment can be carried out through many approaches, which can be divided into two large categories, flow-through and batch. In the flow-through approach the analyte solution flows continuously on/through the tool intended to concentrate it, while in the batch approach the extraction tool is introduced into the analyte solution.9 Each category is divided into many types, depending on whether the analyte is to be extracted completely or partially.10 The subdivision of the most used extraction techniques is shown in Figure 7.4. Solid-Phase Extraction (SPE) is a technique characterized by a solid extraction phase, packed in a cartridge, on which the analyte solution is passed.11 Usually, the extraction procedure is preceded by an activation step with specific solvents. Accelerated Solvent Extraction (ASE) employs solvents at high temperatures and pressures but maintains their liquid state during extraction procedure. In this state, the solvent physicochemical properties change enhancing the mass transfer rates and increasing the solubility of analytes. This allows the solvent to penetrate more easily and deeper into the solid matrix being extracted and a higher extraction yield is achieved. A similar performance is obtained in Supercritical Fluid Extraction (SFE).12

Figure 7.4

Subdivision of extraction techniques according to flow-through and batch categories.

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The volatile compounds are usually extracted with the Head Space (HS) or the Purge & Trap extraction methods. In the HS method, the analyte solution is placed in a vial and it is heated to a constant temperature to favor the passage of the compounds in phase steam. The headspace is then saturated with volatile components initially present in the sample. In the Purge & Trap method, also known as Dynamic Head Space, the volatile analytes are extracted continuously by bubbling of an inert and pure gas (such as He or N2). The analytes present in the gas phase are captured on an adsorption trap and then removed by thermal desorption directly in the determination instrument.13 Liquid–Liquid Extraction (LLE) is based on the partition of an analyte between two immiscible phases and it can distribute itself in a certain ratio thanks to the different affinity for the two solutions. The evolutions of the LLE are Microwave Assisted Extraction (MAE) and Ultrasound Assisted Extraction (UAE), in which to achieve better extraction a physical approach is used. The Soxhlet extractor is a tool able to continuously separate analytes by a solid or semisolid matrix through a defined volatile extraction phase.14 The Solid-Phase Micro Extraction (SPME) technique is based on the extraction by a material for which the analyte has an affinity, typically deposited on a fiber or inside a silica capillary (in-tube SPME). Usually, MNPs are involved as the extraction tool in SPME.15 Nevertheless, MNPs are used in all the methods mentioned above.

7.3 MNPs for Analyte Extraction In an analytical protocol, in addition to the analyte type, the matrix in which it is dispersed is a principal component. The matrix is defined as everything that is part of a sample, but which is not subject to analytical examination. The matrix is the ‘‘basic material’’ of which the sample is composed and in which the analytes are dissolved or dispersed.16 The composition of the sample can be somewhat complex and influence the instrumental response. The influences can be chemical or physical, such as complexation of the analytes, formation of ‘‘masking’’ compounds, change in activity, pH alteration or changes in the physical properties. Therefore, the matrix in which the analytes are dispersed can be a solution with a high solute concentrations (discharges, brackish waters, brines, sugary drinks, etc.), water-solvent organic mixtures (industrial processes, wines, alcoholic drinks, etc.), solutions with high protein content (biological fluids, food, etc.) or solutions with high acidity (discharges, extraction of metals from solid matrices, etc.). Therefore, the use of MNPs as the extraction tool can be applied in all the matrices.17,18 From a literature review using the Scopus database, we found that the main application of MNPs in the extraction step is in the environmental field19,20 (see Figure 7.5) such as in river water, lake water or industrial discharge samples. Other applications have been found in the food sector and biological analysis, such as in urine or blood samples.21,22 The small size of MNPs and their high surface area/volume ratio has led to high sensitivity and high extraction efficiency.23 Moreover, the magnetism of

Magnetic Nanoparticles as an Efficient Tool for Analyte Extraction

Figure 7.5

205

Distribution of MNP application in the literature. Source: Scopus.

these NPs simplifies the separation of the extraction tools from the matrix and can improve the rate of separation.24–26 Indeed, the application of this kind of NP enhances the extraction step faster than traditional methods, by a few minutes or even seconds.27,28 Despite the proprieties of the magnetic core of MNPs, the real extraction is operated by the functionalizing layer, which is ‘‘ad hoc’’ functionalized.29 The matrix involved with the specific MNPs used will be addressed in the following paragraphs.

7.3.1

Environmental Applications

The analytical determination in the environmental field gives an evaluation of a specific compartment, such as air, soil, or water. These are the main targets of the pollution coming from anthropic activities or natural sources. In the environmental analyses, the analytes are usually found in low concentrations (103–1012 per kg), so the methods involved should have high sensitivity.30 Moreover, a pollutant can be present in various forms with different chemical–physical characteristics and toxicities, this phenomenon is known as speciation, and all the species must be determined.31 Sampling should be statistically significant and should not affect the sample, especially if the results are used for environmental hygiene certification. In this regard, the application of MNPs in the extraction procedure has been applied to different environmental samples such as water (river, lake, pond, bathing, etc.),31–39 soil,34,40,41 plants,42 and wastewater.36 Many analytes have been detected thanks to MNPs, usually metals or heavy metals,32,33,35,37,38,40,41 pesticides,43 organic pollutants30,34,42 but also colorants36 and UV filters.31 In Table 7.1 the main applications of MNPs in the environmental field are reported. The MNPs applied in the environmental field are usually based on iron oxides such as Fe3O4 or Fe2O4. Some MNPs are also base on silica32,33,35 or use the magnetic proprieties of Cobalt.31,32 The magnetic proprieties of NPs are

MNP application as an extraction tool in the environmental field.

MNPs

Functionalizing layer

Fe3O4

Sodium hexanoate

Fe3O4@SiO2 1,5-diphenylcarbazide Co@SiO2 [P66614]1[BEHPA] Sodium oleate Fe3O4

MNPs size —

Matrix

Analyte

Atrazine, Simazine, Terbuthylazine 22 nm Water Cr(VI), Cr(III) 300–400 nm Water Pb 27 nm Soil Polychlorinated leachates biphenyls (PCBs) — Soil Pd(II)

Fe3O4@SiO2 Sodium dodecyl sulfate, 2-(5-bromo-2-pyridylazo)5-diethyl aminophenol Polyaniline-dicationic 7.5 nm Fe3O4 ionic liquid

Water

Water, sludge, and soil

Polyethylenimine Sodium dodecyl sulfate

20 nm 84 nm

Fe3O4

1,5-bis(di-2pyridil)methylene thiocarbohydrazide Uncoated Metal–organic-framework

15–20 nm

— 60–80 nm

Soil Plants

Water Mine stone, road dust and water Bathing UV filters waters

Fe3O4 Fe3O4 Fe3O4 Fe3O4

Metal–organic-framework Murexide, 3-aminopropyl triethoxysilane

70 nm 45–60 nm

CoFe2O4

Oleic acid



Pd Organochlorine pesticides Phthalate esters Ag(I), Au(III), Pd(II)

Time of Extraction extraction efficiency

LOD

Reference 1

20 mg



81.4–96.7%

100–130 ng L

44

100 mg 1.5 mg 50 mg

60 min 10 min 10 min

94% 90% 78–98%

— 10 ng L1 0.7–2.2 ng L

33 32 30

15 mg

10 min

96.7–104.0%

120 ng L1

40

15 mg

20 min

80.2–111.9%

0.8–208.6 ng L1

34

20 mg 24 min 87.15 mg 4 min

82.7–98.3% 98–99%

2 ng L1 700 ng L1

35 36

50 mg

2 min

97–107%.

7.8 ng L1

37

50 mg 50 mg

30 s 70 s

90–101% 6.4 ng L1 81.46–113.59% 620–3920 ng kg1

15 mg 10 mg

25 min 8.0 min

85.1–106.7% 95–104%

80000–150000 ng L1 39 60–250 ng L1 38

25 mg

30 min

80–116%

13–148 ng L1

41 42

31

Chapter 7

Fe@SiO2 Fe3O4

Polycyclic Aromatic Hydrocarbons (PAHs) Water As(III), As(V) Wastewater Rhodamine-B, Rhodamine-6G Water Hg

MNPs amount

206

Table 7.1

Magnetic Nanoparticles as an Efficient Tool for Analyte Extraction

207

exploited to give a quick and easy extraction, especially for removing the extracting phase by a magnet. The real role of the extractor is exercised by the functionalizing layer, which is chosen ‘‘ad hoc’’ and chemically bound to MNPs. Subsequently, for each analyte a specific chemical species can be implemented as the functionalizing layer. The compounds involved in this scope are different, i.e., fatty acids,30,36,44,45 ionic liquid32 and polar compounds. Rarely do the MNPs occur uncoated,41 this type of application might be favored for facilitated synthesis of MNPs but it only has an acceptable efficiency for very few compounds. The size of MNPs used ranges from a few nm to 500 nm, they are distributed into 3 large populations (7–25 nm, 40–80 nm and 300–400 nm). The extraction period varies according to all the characteristics discussed above (analyte, matrices, MNPs, layer, etc.), so the extraction time can be a few seconds (30 s)41 or hours.33 To evaluate the accuracy of the extraction tools used, the recovery of analyte was evaluated and expressed as the extraction efficiency. Generally, two approaches are used. Samples were analyzed with the ‘‘traditional’’ extraction and with the MNPs extraction tool and the quality of both methods was compared. In the other approach, a well-known amount of analyte standard was added to a blank matrix and the determination was performed directly with the MNPs. It was possible to obtain a good extraction efficiency of the MNPs tools, generally around 80–100%, depending on the combination of analyte/matrix. Moreover, the limit of detection (LOD) of the method associated with MNPs extraction was comparable to the ‘‘traditional’’ methods that were on the order of ng L1. An interesting application of MNPs as extraction tools was to incorporate MNPs in an effervescence tablet.44 The magnetic effervescence tablet was composed of citric acid, sodium hexanoate, sodium bicarbonate, and Fe3O4 nanoparticles. The reaction between citric acid, sodium hexanoate and sodium bicarbonate generates hexanoic acid and CO2. The CO2 bubbles assisted the contact of MNPs and hexanoate with the analyte, and the extractant was then isolated by an external magnet. Therefore, this application combined extractant generation, dispersion, and magnetic recovery into one step.44 Another application to be counted, is the use of MNPs for the UV filter detection in sea water and bathing water.31 The UV filters are employed in sunscreen and belong to the following chemical classes: benzophenones, salicylates, p-aminobenzoic acid and derivatives, benzimidazole derivatives, triazines, benzotriazoles, dibenzoylmethane derivatives, cinnamates and camphor derivatives.46 The effects of dispersing these compounds in the marine environment are quite serious. At first, thanks to their lipophilic characteristic, they tend to bio-accumulate in aquatic environments and the food chains originating from them.47 In addition, some of the UV filters have bleaching effects on coral, an endangered and protected species.48

7.3.2

Food Applications

The analytical determination in the food sector involves the analysis of nutrients, such as proteins, lipids, vitamins, etc. (Table 7.2). Moreover, great

208

Table 7.2 MNPs Fe3O4 Fe3O4

MNP application as an extraction tool in the food sector. Functionalizing layer

MNPs size Matrix

Zr-Fe3O4

Oleic acid 8–10 nm 1-(2,3-dihydroxypropyl)- 32 nm 1,4-diazabicyclo[2.2.2] octanylium chloride Uncoated 300 nm

Fe3O4

Graphene



Fe3O4

Uncoated

— 40 nm

Pistachio Milk

Fe3O4



Candies, Beverages

91.6–99.6% 73.4–96.5%

LOD

Reference 1

21 ng L 20–1180 ng kg1

53 56

20 mg

5 min

74.13–92.9% 2680 ng L1

5 mg

7 min

79.6–108%

3000–6000 ng kg1 60

50 mg

6 min

78.3–93.8%

45000 ng kg1

55



11 min

91–99%

1000 ng L1

58

30 ng 10 mg

10 min 2 min

94% 98–105%

20 ng L1 5090 ng L1

54 61

Polychlorinated 10 mg biphenyls (PCBs) 30 mg Amaranth, Ponceau 4R, Sunset yellow, Allure red

10 min

70.4–108.0% 2.1–54 ng L

59

20 min

93.3–110.5% 150–200 ng L

63

Fruit, Vegetable Pyrethroids residues

13–16 nm Milk 15 nm Cotton candy, Saffron spray — Fruit juice

MNPs Time of Extraction amount extraction efficiency

Aflatoxins 60 mg 5 min Cephalosporins 65.5 mg 8 min

Animal-derived Ribavirin foods Tomato sauce, Sudan dyes (I, II, III, Chiliand IV) containing foods Wheat flour Deoxynivalenol

Fe3O4@SiO2 Dimethyl octadecyl [3-(trimethoxysilyl) propyl] ammonium chloride Fe3O4 Dopamine Co-Fe2O4@ Polyethyleneimine SiO2 Cellulose Co-Fe2O4

Polydopamine, polyethyleneimine

Analyte

Ochratoxin A Tartrazine

57

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209

attention is focused on the determination of food quality and safety markers.49 These markers are specific compounds characteristic of a product and/ or a production process. The chemical species usually involved in food quality assessment can give information about the origin of food or can be used for fraud detection.50,51 Indeed, food safety is ascertained by the absence of intrinsic components associated with a risk of damage to health. Therefore, for food safety the determination of chemical or biological contaminants is required. To consider food of high quality, it is necessary to ensure its safety.52 For this reason, food safety is widely considered as a prerequisite for food quality. MNPs as extraction tools are mainly applied for the detection of chemical and microbiological contaminants. In this context, MNPs are used to detect mycotoxins (such as aflatoxin and ochratoxin),53–55 residues of veterinary drugs56,57 or pesticides,58 pollutants59 and dyes.60–62 The matrices in which these analytes are dispersed can be essentially any; starting from fruit and vegetables,53,58–60 to cereals,55 animal-derived food,54,56,57 beverages63 and candies.61,63 Also in this field, ferrite is usually chosen for magnetic separation, even if in some cases it is assisted by Zr57 or Co.59,61 The size of MNPs herein applied range from 10 to 300 nm, and the amount used is between 5 and 60 mg. The extraction procedure is very quick in this sector, with a maximum of 20 min required.63 The extraction efficiency of the evaluated results is very successful, each method reaches at least 90% of recovery. LODs also give good results (ng L1) and they were in accordance with the existing literature. Also, in this area many functionalizing layers were used, even if some MNPs have been applied uncoated. This is the case for the Zr–Fe3O4 MNPs, that have been used to detect ribavirin in animal-derived foods.57 It’s noteworthy that ribavirin is a powerful antiviral and it is generally used for animal diseases. Furthermore, this antiviral was successfully used again COVID-19, during the worldwide pandemic64.

7.3.3

Biological Applications

The analysis of biological fluids is essential for healthcare, but also for the applications in the forensic area. The MNPs, based on Fe3O4, are applied to extract amino acid metabolites,65 medicine residues,66 toxic compounds67,68 and drugs or their metabolites (Table 7.3).69,70 A specific functionalizing layer has been chosen, but some papers use uncoated MNPs69 or an extracting phase is typically used, such as C-18 functionalization70 or just carbon.66 The size of MNPs used has a great variance, from 8 to 300 nm. On the other hand, the amount of MNPs required is extremely low. The maximum quantity used was 20 mg, but some papers reported the use of just 3 mg of MNPs.70 The detection limits (LOD) ranged from ng mL1 to ng L1 orders, with extraction efficiencies not really suitable in some cases.66 Nevertheless, for certain applications the extraction was very quick, even just a single minute.68

210

Table 7.3 MNPs Fe3O4

MNP application as an extraction tool in the biological field.

Functionalizing layer

MNPs size 8 nm

Fe3O4

Aminophenylboronic acid C18

Fe3O4

Poly(E-caprolactone)

50 nm

Matrix Urine

200–300 nm Urine

Fe3O4@ Ethidium bromide SiO2

250 nm

Blood serum, Urine Urine

Fe3O4

20 nm

Plasma

500 nm

Urine

Carbon

Fe3O4@ Uncoated SiO2

Analyte

MNPs Time of Extraction amount extraction efficiency

LOD

Reference 1

Catecholamines 5 mg

5 min

92–108%

2.0–7.9 ng mL

3 mg

5 min

72.3–83.6%

0.5–20 ng mL1

70

15 mg

35 min

82.8–104.9%

1.00 ng mL1

67

1 min

93.3–121.3%

0.0030–0.0096 ng mL1 68

20 min

56.35–66.43% 0.09–0.69 ng mL1

40 min

77.1–94.7%.

Cocaine, codeine, morphine, methadone Progesterone

10 mg Hydroxylated polycyclic aromatic hydrocarbons (hydro-PAHs) 20 mg Losartan, Carvedilol, Amlodipine besylate Cocaine and its 20 mg 7 metabolites

0.23–1.5 ng mL1

65

66

69

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Magnetic Nanoparticles as an Efficient Tool for Analyte Extraction

211

7.4 Conclusions Magnetic Nanoparticles (MNPs) can be involved in all analytical steps, including sample pre-treatment, chromatographic techniques, membrane application, and then the lab-on-chip or AI tools. Nowadays, more than 700 publications have been found on the use of MNPs as an extraction tool, a growth of about 150% over the past two decades. From a literature review using the Scopus database, it was determined that the main application of MNPs in the extraction step was in the environmental field such as in river water, lake water or industrial discharge samples. Other applications have been found in food and biological analysis, such as in urine or blood samples. Indeed, the magnetism of these NPs simplifies the separation of the extraction tools from the matrix and can improve the rate of separation. Moreover, the application of this kind of NPs enhances the extraction step faster than the traditional methods, by involving only a few minutes or even seconds. In addition, the same MNPs can be used for several cycles, without any loss in extraction efficiency and sensitivity. These features make the use of MNPs more sustainable than the traditional methods, according to the green chemistry principles.

References 1. T. Nevzorova and E. Karakaya, Explaining the drivers of technological innovation systems: The case of biogas technologies in mature markets, J. Cleaner Prod., 2020, 259, 120819. 2. G. Vinci and M. Rapa, Noble Metal Nanoparticles Applications: Recent Trends in Food Control, Bioengineering, 2019, 6(1), 1. 3. A. Bearzotti, A. Macagnano, S. Pantalei, E. Zampetti, I. Venditti, I. Fratoddi and M. V. Russo, J. Phys.: Condens. Matter, 2008, 20, 474207. 4. F. Vitale, R. Vitaliano and C. Battocchio, et al., Synthesis and Microstructural Investigations of Organometallic Pd(II) Thiol-Gold Nanoparticles Hybrids, Nanoscale Res. Lett., 2008, 3, 461. ¨yu ¨ktiryaki, I. Dolak and C. M. Hussain, Handbook of 5. R. Keçili, S. Bu Nanomaterials in Analytical Chemistry: Modern Trends in Analysis, 2019. 6. S. Bisht, M. Mizuma, G. Feldmann, N. A. Ottenhof, S. M. Hong, D. Pramanik, V. Chenna, C. Karikari, R. Sharma, M. G. Goggins, M. A. Rudek, R. Ravi, A. Maitra and A. Maitra, Systemic administration of polymeric nanoparticle-encapsulated curcumin (NanoCurc) blocks tumor growth and metastases in preclinical models of pancreatic cancer, Mol. Cancer Ther., 2010, 9(8), 2255–2264. 7. F. Chemat, M. Abert Vian, A.-S. Fabiano-Tixier, M. Nutrizio, A. Rezˇek Jambrak, P. E. S. Munekata, J. M. Lorenzo, F. J. Barba, A. Binello and G. Cravotto, A review of sustainable and intensified techniques for extraction of food and natural products, Green Chem., 2020, DOI: 10.1039/c9gc03878g. 8. Q. W. Zhang, L. G. Lin and W. C. Ye, Techniques for extraction and isolation of natural products: a comprehensive review, Chin. Med., 2018, 13, 20.

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9. P. Bagga, T. M. Ansari and H. H. Siddiqui, et al., Bromelain capped gold nanoparticles as the novel drug delivery carriers to aggrandize effect of the antibiotic levofloxacin, EXCLI J., 2016, 15, 772–780. 10. F. Chemat, N. Rombaut, A. Meullemiestre, M. Turk, S. Perino, A. S. Fabiano-Tixier and M. Abert-Vian, Innov. Food Sci. Emerg. Technol., 2017. 11. K. Bielicka-Daszkiewicz, Extraction techniques based on solid state and connected with liquid chromatography, J. Liq. Chromatogr. Relat. Technol., 2016, 39(10), 477–487. ´rdenas and R. Lucena, Separations, Recent Advances in Extraction 12. S. Ca and Stirring Integrated Techniques, Separations, 2017, 4(1), 6. 13. B. Nouri, B. Fouillet, G. Toussaint, R. Chambon and P. Chambon, Complementarity of purge-and-trap and head-space capillary gas chromatographic methods for determination of methyl-tert.-butyl ether in water, J. Chromatogr. A, 1996, 726(1–2), 153–159. ˙ y"kiewicz, Crit. Rev. 14. L. Trzonkowska, B. Les´niewska and B. Godlewska-Z Anal. Chem., 2016. 15. G. Ouyang and J. Pawliszyn, SPME in environmental analysis, Anal. Bioanal. Chem., 2006, 386, 1059–1073. 16. H. Filik and A. A. Avan, Nanostructures for nonlabeled and labeled electrochemical immunosensors: Simultaneous electrochemical detection of cancer markers: A review, Talanta, 2019, 205, 120153. 17. F. Gao, An Overview of Surface-Functionalized Magnetic Nanoparticles: Preparation and Application for Wastewater Treatment, ChemistrySelect, 2019, 4(22), 6805–6811. 18. J. Sengupta and C. M. Hussain, Graphene and its derivatives for Analytical Lab on Chip platforms, TrAC, Trends Anal. Chem., 2019, 114, 326–337. ¨yu ¨ktiryaki, Y. Su ¨mbelli, R. Keçili and C. M. Hussain, Encycl. Anal. 19. S. Bu Sci., 2019. 20. C. M. Hussain and R. Keçili, Modern Environmental Analysis Techniques for Pollutants, 2019. 21. D. Sharma and C. M. Hussain, Smart nanomaterials in pharmaceutical analysis, Arabian J. Chem., 2020, 13(1), 3319–3343. ¨yu ¨ktiryaki and C. M. Hussain, TrAC, Trends Anal. Chem, 22. R. Keçili, S. Bu 2019. 23. K. K. Kefeni and B. B. Mamba, Photocatalytic application of spinel ferrite nanoparticles and nanocomposites in wastewater treatment: Review, Sustainable Mater. Technol., 2020, 23, e00140. 24. K. K. Kefeni, T. A. M. Msagati and B. B. Mamba, Ferrite nanoparticles: synthesis, characterisation and applications in electronic device, Mater. Sci. Eng., B, 2017, 215, 37–55. 25. R. Kecili and C. M. Hussain, Recent Progress of Imprinted Nanomaterials in Analytical Chemistry, Int. J. Anal. Chem., 2018, DOI: 10.1155/2018/ 8503853. 26. C. M. Hussain, Nanomaterials in Chromatography: Current Trends in Chromatographic Research Technology and Techniques, 2018.

Magnetic Nanoparticles as an Efficient Tool for Analyte Extraction

213

27. A. Mirabi, A. S. Rad and F. Divsalar, et al., Application of SBA-15/Diphenyl Carbazon/SDS Nanocomposite as Solid-Phase Extractor for Simultaneous Determination of Cu(II) and Zn(II) Ions, Arabian J. Sci. Eng., 2018, 43, 3547–3556. 28. W. A. Wan Ibrahim, H. R. Nodeh, H. Y. Aboul-Enein and M. M. Sanagi, Magnetic solid-phase extraction based on modified ferum oxides for enrichment, preconcentration, and isolation of pesticides and selected pollutants, Crit. Rev. Anal. Chem., 2015, 270–287. 29. I. Fratoddi, M. Rapa, G. Testa, I. Venditti, F. A. Scaramuzzo and G. Vinci, Gold nanoparticles-based extraction of phenolic compounds from olive mill wastewater: A rapid and sustainable method, Microchem. J., 2018, DOI: 10.1016/j.microc.2018.01.043. ´rez, B. Albero, J. L. Tadeo, E. Molero and C. Sa ´nchez-Brunete, 30. R. A. Pe Application of magnetic iron oxide nanoparticles for the analysis of PCBs in water and soil leachates by gas chromatography-tandem mass spectrometry, Anal. Bioanal. Chem., 2015, DOI: 10.1007/s00216014-8409-0. ´, A. Chisvert, D. L. Giokas and A. Salvador, Determination of 31. J. L. Benede ultraviolet filters in bathing waters by stir bar sorptive–dispersive microextraction coupled to thermal desorption–gas chromatography–mass spectrometry, Talanta, 2016, 147, 246–252. 32. S. Hosseinzadegan, W. Nischkauer, K. Bica and A. Limbeck, FI-ICP-OES determination of Pb in drinking water after pre-concentration using magnetic nanoparticles coated with ionic liquid, Microchem. J., 2019, 146, 339–344. 33. N. Assi, P. Aberoomand Azar, M. Saber Tehrani, S. W. Husain, M. Darwish and S. Pourmand, In Situ Remediation of Groundwater Contaminated by Heavy- and Transition-Metal Ions by Selective Ion-Exchange Methods, Int. J. Environ. Sci. Technol., 2019, DOI: 10.1007/s13762018-1868-7. 34. S. F. F. Syed Yaacob, M. A. Kamboh, W. A. Wan Ibrahim and S. Mohamad, New sporopollenin-based b-cyclodextrin functionalized magnetic hybrid adsorbent for magnetic solid-phase extraction of nonsteroidal anti-inflammatory drugs from water samples, R. Soc. Open Sci., 2018, 5(7), 171311. 35. Q. Zhou, Z. Zheng, J. Xiao and H. Fan, Label-Free SERS Monitoring of Chemical Reactions Catalyzed by Small Gold Nanoparticles Using 3D Plasmonic Superstructures, Talanta, 2016, DOI: 10.1016/j.talanta.2016. 05.024. 36. E. Ranjbari, M. R. Hadjmohammadi, F. Kiekens and K. De Wael, Anal. Chem., 2015, 87, 7894–7901. ´n and 37. E. V. Alonso, M. L. Guerrero, P. C. Cueto, J. B. Benı´tez, J. M. C. Pavo A. G. de Torres, Development of an on-line solid phase extraction method based on new functionalized magnetic nanoparticles. Use in the determination of mercury in biological and sea-water samples, Talanta, 2016, 153, 228–239.

214

Chapter 7

38. S. Karami, H. Ebrahimzadeh and A. A. Asgharinezhad, A simple and fast method based on functionalized magnetic nanoparticles for the determination of Ag(i), Au(iii) and Pd(ii) in mine stone, road dust and water samples, Anal. Methods, 2017, DOI: 10.1039/c7ay00596b. 39. R. Dargahi, H. Ebrahimzadeh, A. A. Asgharinezhad, A. Hashemzadeh and M. M. Amini, Magnetic solid-phase extraction of phthalate esters from environmental water samples using fibrous phenyl-functionalized Fe3O4@SiO2@KCC-1, J. Sep. Sci., 2017, DOI: 10.1002/jssc. 201700700. 40. M. Wang, L. Wu, Q. Hu and Y. Yang, Environ. Sci. Pollut. Res., 2018, 25, 8340–8349. ¨ zkan, et al., Determination of palladium 41. N. Aylin Kasa, S. Sel and B. Ç. O in soil samples by slotted quartz tube-flame atomic absorption spectrophotometry after vortex-assisted ligandless preconcentration with magnetic nanoparticle–based dispersive solid-phase microextraction, Environ. Monit. Assess., 2019, 191, 692. 42. B. E. Meteku, J. Huang, J. Zeng, F. Subhan, F. Feng, Y. Zhang, Z. Qiu, S. Aslam, G. Li and Z. Yan, Magnetic metal–organic framework composites for environmental monitoring and remediation, Coord. Chem. Rev., 2020, 413, 213261. 43. J. He, W. Xu, Y. Shang, P. Zhu, X. Mei, W. Tian and K. Huang, Development and optimization of an efficient method to detect the authenticity of edible oils, Food Control, 2013, 31(1), 71–79. 44. X. Jing, X. Cheng, W. Zhao, H. Wang and X. Wang, Magnetic effervescence tablet-assisted switchable hydrophilicity solvent-based liquid phase microextraction of triazine herbicides in water samples, J. Mol. Liq., 2020, 306, 112934. ˜ as, N. Campillo and M. Herna ´ndez-Co ´rdoba, Food 45. M. Pastor-Belda, P. Vin Chem., 2017, 221, 76–81. ´, Organic UV filters and 46. M. S. Dı´az-Cruz, M. Llorca and D. Barcelo their photodegradates, metabolites and disinfection by-products in the aquatic environment, TrAC, Trends Anal. Chem., 2008, 27(10), 873–887. ¨ller and T. Poiger, Occurrence 47. M. E. Balmer, H. R. Buser, M. D. Mu of Some Organic UV Filters in Wastewater, in Surface Waters, and in Fish from Swiss Lakes, Environ. Sci. Technol., 2005, DOI: 10.1021/ es040055r. 48. R. Danovaro, L. Bongiorni, C. Corinaldesi, D. Giovannelli, E. Damiani, P. Astolfi, L. Greci and A. Pusceddu, Sunscreens Cause Coral Bleaching by Promoting Viral Infections, Environ. Health Perspect., 2008, DOI: 10.1289/ehp.10966. 49. R. Preti, M. Rapa and G. Vinci, Effect of Steaming and Boiling on the Antioxidant Properties and Biogenic Amines Content in Green Bean (Phaseolus vulgaris) Varieties of Different Colours, J. Food Qual., 2017, DOI: 10.1155/2017/5329070. 50. L. Gobbi, S. Ciano, M. Rapa and R. Ruggieri, Beverages, 2019, 5, 40.

Magnetic Nanoparticles as an Efficient Tool for Analyte Extraction

215

51. M. Rapa, S. Ciano, A. Rocchi, F. D’Ascenzo, R. Ruggieri and G. Vinci, Hempseed Oil Quality Parameters: Optimization of Sustainable Methods by Miniaturization, Sustainability, 2019, DOI: 10.3390/su11113104. 52. G. Vinci and M. Rapa, Noble Metal Nanoparticles Applications: Recent Trends in Food Control, Bioengineering, 2019, DOI: 10.3390/ bioengineering6010010. 53. Z. Taherimaslak, M. Amoli-Diva, M. Allahyari, K. Pourghazi and M. H. Manafi, Low density solvent based dispersive liquid–liquid microextraction followed by vortex-assisted magnetic nanoparticle based solid-phase extraction and surfactant enhanced spectrofluorimetric detection for the determination of aflatoxins in pistachio nuts, RSC Adv., 2015, DOI: 10.1039/c4ra11484a. 54. A. Sargazi, A. Aliabadi, A. Rahdari, S. Allahdini-Hesaroiyeh, M. NejatiYazdinejad and M. H. Majd, A Simple and Fast Method for Magnetic Solid Phase Extraction of Ochratoxin A, J. Braz. Chem. Soc., 2017, DOI: 10.21577/0103-5053.20160245. 55. R. Karami-Osboo, M. Maham and M. Mirabolfathy, Magnetic nanoparticle solid phase extraction-HPLC-UV for determination of deoxynivalenol in wheat flour, Anal. Methods, 2015, DOI: 10.1039/c5ay02502h. 56. H. Sahebi, E. Konoz and A. Ezabadi, New J. Chem., 2019, DOI: 10.1039/ c9nj02200g. 57. M. Qie, S. Zheng, B. Xiaoyun, Z. Bo, F. Guozhen and W. Shuo, Specific recognition of ribavirin in animal-derived foods by high performance liquid chromatography combined with magnetic solid-phase extraction based on highly selective Zr-Fe3O4, J. Sep. Sci., 2016, DOI: 10.1002/ jssc.201900245. 58. H. Bagheri, Y. Yamini, M. Safari, H. Asiabi, M. Karimi and A. Heydari, Simultaneous determination of pyrethroids residues in fruit and vegetable samples via supercritical fluid extraction coupled with magnetic solid phase extraction followed by HPLC-UV, J. Supercrit. Fluids, 2016, 107, 571–580. 59. F. Abujaber, M. Zougagh, S. Jodeh, A. Rios, F. J. G. Bernardo and R. C. R. Martı´n-Doimeadios, Magnetic cellulose nanoparticles as sorbents for stir bar-sorptive dispersive microextraction of polychlorinated biphenyls in juice samples, Talanta, 2019, 201, 266–270. 60. M. Y. Zhang, M. M. Wang, Y. L. Hao, X. R. Shi and X. S. Wang, Comparison of critical methods developed for fatty acid analysis: A review, J. Sep. Sci., 2016, DOI: 10.1002/jssc.201600167. 61. H. R. Noormohamadi, M. R. Fat’hi and M. Ghaedi, Fabrication of polyethyleneimine modified cobalt ferrite as a new magnetic sorbent for the micro-solid phase extraction of tartrazine from food and water samples, J. Colloid Interface Sci., 2018, 531, 343–351. 62. W. Chai, H. Wang, Y. Zhang and G. Ding, Talanta, 2016, 149, 13–20. 63. H. Chen, X. Deng, G. Ding and Y. Qiao, The synthesis, adsorption mechanism and application of polyethyleneimine functionalized magnetic nanoparticles for the analysis of synthetic colorants in

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66.

67.

68.

69.

70.

Chapter 7

candies and beverages, Food Chem., 2019, DOI: 10.1016/j.foodchem. 2019.04.111. L. Li, R. Li, Z. Wu, X. Yang, M. Zhao, J. Liu and D. Chen, Therapeutic strategies for critically ill patients with COVID-19, Ann. Intensive Care, 2020, 1–9. L. Jiang, Y. Chen, Y. Luo, Y. Tan, M. Ma, B. Chen, Q. Xie and X. Luo, Determination of catecholamines in urine using aminophenylboronic acid functionalized magnetic nanoparticles extraction followed by highperformance liquid chromatography and electrochemical detection, J. Sep. Sci., 2014, DOI: 10.1002/jssc.201400920. H. Heidari and B. Limouei-Khosrowshahi, Magnetic Particles: Their Applications from Sample Preparations to Biosensing Platforms, J. Chromatogr. B: Anal. Technol. Biomed. Life Sci., 2019, DOI: 10.1016/ j.jchromb.2019.03.025. Z. Es’haghi, A. Nezhadali and A. D. Khatibi, Magnetically responsive polycaprolactone nanoparticles for progesterone screening in biological and environmental samples using gas chromatography, Anal. Bioanal. Chem., 2016, 408, 5537–5549. W. Zhang, Y. Zhang, G. Zhang, J. Liu, W. Zhao, W. Zhang, K. Hu, F. Xie and S. Zhang, Facile preparation of a cationic COF functionalized magnetic nanoparticle and its use for the determination of nine hydroxylated polycyclic aromatic hydrocarbons in smokers’ urine, Analyst, 2019, DOI: 10.1039/c9an01188a. F. Yang, Y. Zou, C. Ni, R. Wang, M. Wu, C. Liang, J. Zhang, X. Yuan and W. Liu, Magnetic dispersive solid-phase extraction based on modified magnetic nanoparticles for the detection of cocaine and cocaine metabolites in human urine by high-performance liquid chromatography–mass spectrometry, J. Sep. Sci., 2017, DOI: 10.1002/jssc. 201700457. ¨s, C. Aguilar and M. Calull, Capillary T. Baciu, F. Borrull, C. Neusu electrophoresis combined in-line with solid-phase extraction using magnetic particles as new adsorbents for the determination of drugs of abuse in human urine, Electrophoresis, 2016, DOI: 10.1002/elps. 201500515.

CHAPTER 8

Functionalized Magnetic Nanoparticles for Solid-phase Extraction EVRIM UMUT Dokuz Eylul University, School of Healthcare, Department of Medical Imaging Techniques, 35330, Balçova, Izmir, Turkey Email: [email protected]

8.1 Introduction As an analytical procedure, sample preparation for the detection and quantification of particular substances, called ‘‘analytes’’, is an important and challenging step, since most of the samples concerned in biological, pharmaceutical, environmental and food applications are complex solutions/dispersions including only trace amounts of target analytes and many interfering substances (impurities) as well. Solid phase extraction (SPE) stems from the isolation of these analytes from sample solution matrices and preconcentrating them to a level detectable by analytical instruments.1–5 However, this separation and enrichment of target analytes using traditional on-column SPE methods followed by subsequent centrifugation and filtration steps can be quite time consuming depending on the complexity of the samples. Moreover, during the multistep process some extent of existing analytes can be lost and/or the sample can be contaminated, which eventually may lead to the misinterpretation of the final analysis result. Therefore, development of modern SPE techniques with high capture efficiency and detection specificity is highly needed.6–8 In recent years, mostly based Analytical Applications of Functionalized Magnetic Nanoparticles Edited by Chaudhery Mustansar Hussain r The Royal Society of Chemistry 2021 Published by the Royal Society of Chemistry, www.rsc.org

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on the automation and miniaturization of several stages in SPE, different modifications of the SPE technique were discovered (see Figure 8.1) such as thin-film microextraction (TFME), polymer monolith microextraction (PMME), solid-phase microextraction (SPME), micro-solid phase extraction (m-SPE), magnetic solid phase extraction (MSPE) and dispersive (micro) solid phase extraction (d-SPE), in which the type of solid sorbent bed and absorbent materials show differences.9 This chapter particularly focuses on magnetic solid phase extraction (MSPE) and its applications, while detailed reviews and textbooks about other types of SPE techniques can be found in

Figure 8.1

Recently developed SPE methods for the extraction of metals and organic compounds. Reproduced from ref. 9 with permission from the Royal Society of Chemistry.

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10–13

the literature. The chapter is organized as follows: In Section 8.2 the basic principles of the MSPE procedure are explained. Next in Section 8.3, criteria for the selection of suitable magnetic materials, their surface coating and different designs of the nanomaterials used in MSPE are discussed. Finally, in Section 8.4 the real-world applications of MSPE are summarized.

8.2 Principles and Methods As is the case in many nanostructured materials, magnetic nanoparticles (MNPs) have unique physical properties revealed in the nanoscale and due to the high surface-to-volume ratio, which make them useful in a large variety of biomedical applications such as magnetic resonance imaging,14–18 targeted drug delivery,19 hyperthermia20,21 and technological applications i.e., magnetic recording,22 and magnetic refrigeration.23 MNPs smaller than one magnetic domain possess superparamagnetic behavior so that they can be instantly magnetized in the presence and demagnetized in the absence of an external magnetic field. This magnetic responsiveness, when combined with the unique size advantages of MNPs i.e., enhanced surface-to-volume ratio and comparable dimensions with many analytes of interest (for example molecules in analytical chemistry, enzymes/proteins in biology and pollutant metal ions in environmental science), give them the possibility to be used as sorbents in SPE applications by exerting a magnetic force. In particular, analytes adsorbed on added MNPs are separated from sample solution/suspension by the application of a magnetic field in an ‘‘action at a distance’’ manner24 (see Figure 8.2). Thereafter, by the addition of suitable solvents, the analytes are desorbed (elution), recovered and concentrated for the analysis. SPE guided with MNPs or magnetic solid phase extraction (MSPE) is named after ˇ Safarˇ´k ı and ˇ Safarˇ´kova ı in their pioneering work, where they separated copper phthalocyanine dyes immobilized on magnetite nanoparticles,25 and offers: (i) rapid separation with eliminated centrifugation and filtration steps, (ii) high extraction amounts thanks to the MNP’s large interaction surface with analytes, (iii) reusability of sorbent MNPs after elution for further analysis, and (iv) high selectivity since most of the interfering substances in samples are non-magnetic and do not respond to the magnetic field. Moreover, the method can be applied to almost all solutions since the magnetic forces are not affected by the chemical properties like pH, concentration, polarity and surface charges. Regarding the magnetically induced motion of MNPs in liquid samples (called magnetophoresis), collecting the MNPs, and therefore the attached analytes, by handling of a strong magnet next to the sample container (as shown in Figure 8.2) is the most basic approach, which works most of the time. However, for MNPs with relatively low saturation magnetization the magnetic force exerted on them becomes weak and the separation process can be very time consuming, especially when the particles are well dispersed throughout the sample (here we assume that the magnetic drift forces also

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Figure 8.2

Chapter 8

Schematic representation of magnetic solid phase extraction. Reproduced from ref. 24 with permission from the Royal Society of Chemistry.

do not dominate the electrostatic and steric interactions between particles, which are responsible for the colloidal stability). For this reason, different procedures such as magnetic field flow fractionation (MgFFF), being one of the implementations of many other FFF techniques, were introduced26–29 in which the experimental setups are equipped either with a superconducting magnet30 or quadrupolar electromagnets.31 In the MgFFF application, MNP including the sample is flown through a capillary column perpendicular to the applied field (see Figure 8.3), and thereafter, in the basic operation (normal) mode they are trapped on column walls and subsequently eluted for removing the extraction phase.32 Based on the fact that different sized MNPs have different flow rates and different accelerations under a magnetic field, MgFFF allows size selection/sorting of polydispersed MNPs, hence separation of different analytes of interest which are attached to different monodisperse fractions of MNPs in the same sample. As a leading study showing the feasibility of MNP assisted separation by a MgFFF method, C. T. Yavuz and colleagues performed a size-dependent separation of a mixture of 4 nm and 12 nm iron oxide nanocrystals and by using these MNPs they efficiently removed arsenic (99.2%) from waste water in a column magnetic separator with packed steel wool filters at a flow rate of 20 mL per min and under a low magnetic field gradient (o1 T cm1).33 Different groups proposed and demonstrated that by varying the applied magnetic field strength, a more efficient separation of MNP mixtures can be achieved in a ‘‘catch–drag–release’’ manner.34,35 Here one has to state that

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Figure 8.3

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Sketch of the cross section of a capillary column used in MgFFF showing the laminar flow of sample including different sized MNPs. Reproduced from ref. 32 with permission from the Royal Society of Chemistry. Adapted from ref. 26 with permission from American Chemical Society, Copyright 2005.

depending on the value of magnetic field strength, in the literature the technique is also often classified as and called ‘‘low gradient magnetic separation (LGMS)’’ and ‘‘high gradient magnetic separation (HGMS)’’,36–40 the latter of which is generally applied successfully with microparticles but results in low separation efficiencies with nanosized particles due to the clustering of highly magnetized particles with dipolar interactions. In particular, under the intense magnetic field applied during HGMS, the dipole– dipole interaction dominates steric and electrostatic forces, so that the particles lose their colloidal stability and get agglomerated which results in a lower specific surface area required for efficient separation of analytes. In the literature there are comprehensive reviews focusing on this problem.41,42

8.3 Material Selection and Design 8.3.1

Magnetic Core

The performance of MSPE applications in terms of the separation speed i.e., sensitivity to the external magnetic field gradient, depends on the physicochemical properties of the magnetic core. In the selection of the magnetic core, the most important parameters to be considered are the size, magnetic anisotropy and the saturation magnetization, where the latter two are characteristics of the kind of magnetic ion, but are also influenced by the size and shape of the magnetic core.43 The most commonly studied MNPs in MSPE are transition metals such as Fe, Ni, and Co; metal oxides MFe2O4 where M: Zn, Mn, Ni, or Co and metallic alloys like FePt, and CoPt. The magnetic core should be smaller than the critical size i.e., the size of one magnetic domain is such that at room temperature MNPs show superparamagnetic behavior, which is the key requirement for MSPE ensuring that the MNPs are instantly magnetized/demagnetized by the switching

222 Table 8.1

Chapter 8 Several important magnetic parameters (room temperature saturation magnetization, superparamagnetic critical size, and magnetic anisotropy constant) of magnetic core materials used in MSPE.

Magnetic RT saturation First order magnetic Superparamagnetic core magnetization anisotropy constant critical size K1 (104 J m3) DSP (nm) References material Ms (emu g1) Fe Fe3O4 CoFe2O4 MnFe2O4 NiFe2O4 FePt

220 90–100 80–94 80 56 75

4.5  1.2 18–39  0.25  0.68 11

9 25 14 25 28 2–3

48, 49, 50 51, 52, 53 54, 55, 56, 57 58, 59, 60, 61 62, 63, 64 65, 66

on/off of the external magnetic field. The superparamagnetic critical size for the ferrites is generally between 15–30 nm, whereas it can be as low as 3 nm for FePt particles.43–47 The fact that the superparamagnetic MNPs don’t possess any residual magnetization, is also important since before adding them into the samples for extraction, they can be readily dispersed in a carrier liquid without attracting each other and forming clusters/agglomerates. Furthermore, the MNPs should ideally have low magnetic anisotropy and high saturation magnetization providing that they are easily magnetized under reasonable field strengths and experience large magnetic forces enough to drift them in liquid sample in the direction of the magnetic field source (magnet). Monometallic nanoparticles such as Fe and Co offer the highest saturation magnetization, however they are not stable and are immediately oxidized under ambient conditions, therefore metal oxides like FeO, NiO or ferrites are more commonly employed in MSPE. Table 8.1 summarizes the saturation magnetization, magnetic anisotropy energy density and the critical size of most commonly studied magnetic compounds.

8.3.2

Particle Coating and Functionalization

Although the implementation of MNPs in SPE applications is very useful, they do not solely have enough functionality to interact with target analytes. For this reason, the magnetic core of the MNPs is coated by an organic or inorganic layer, and the surfaces are generally further functionalized with site specific ligands, peptides or antibodies. In this respect, the inner layer of the organic/inorganic coating actually plays a double role; first by surrounding the magnetic core it prevents the agglomeration of the particles and ensures the stability of them in a liquid environment, and second it stems as a base (bed) that the functional groups can be grafted on to (see Figure 8.4).67 In MPSE, the type of the interaction between the molecular analytes and the functionalized MNP surface depends on the hydrophilicity and polarity of the surface. In the case of nonpolar or weakly polar surface coatings the retention of the analytes is due to van der Waals forces, whereas for polar surfaces it is mediated by dipole–dipole, p–p interactions or

Functionalized Magnetic Nanoparticles for Solid-phase Extraction

Figure 8.4

223

Synthesis of silica coated Fe3O4 (as MNPs) functionalized with guanidine-based triazabicyclodecene (TBD) for the preconcentration of soybean oil as a biodiesel. Adapted from ref. 67 with permission from the Royal Society of Chemistry.

hydrogen bonding, while strong covalent bonds are not preferred due to irreversible attachment.68 MNPs can be synthesized by several physical techniques i.e., mechanical milling,69 spray pyrolysis,70 sol–gel71 or wet chemical procedures like high temperature hydrothermal chemical decomposition72–74 or the coprecipitation method.75,76 Both chemical approaches are based on the decomposition of organometallic salts in the liquid phase and have advantages/disadvantages of their own. S. Sun and co-workers published a series of papers, where they showed for the first time that by following a high temperature hydrothermal route one can produce magnetite Fe3O4,72 other transition metal oxides MFe2O4 (M: Fe, Co, Mn)73 and FePt nanoparticles74 with high crystallinity and monodispersity (size distribution standard deviation sB%10). On the other hand, in the surfactant assisted co-precipitation method the size control during particle growth is more difficult, but the method allows MNPs to be obtained at milder conditions with larger yields and in situ coating of magnetic cores with chemical moieties introduced during synthesis. One should point out that, the introduced organic/ inorganic coatings can sometimes dramatically change the magnetic properties of MNPs by modifying the surface spin arrangement of magnetic cores and consequently affecting their performance in MPSE applications. In particular, the periodical bonds between magnetic ions, which are terminated at the surface due to the formation of new types of bonding with coating material atoms77 or the mechanical stress induced by the coating78 give rise to the broken symmetry and frustration of surface spins at the magnetic core. This kind of disordered spin layer is often called ‘‘magnetically dead’’ since it does not contribute to the particle magnetization as the interior spins do, and eventually the saturation magnetization of the MNPs is decreased as compared to the uncoated ones.79 This coating effect, which should not be confused with finite size effects20,76,80 commonly observed in MNPs, obviously depends on the type of the coating material and the nature of the chemical interaction used in the linkage of this material on the magnetic core surface.

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In the literature there are numerous MPSE studies introducing very different designs of MNPs mostly using Fe3O4 as the magnetic core and employing a wide variety of coating materials including organic/inorganic molecules, ionic liquids (IL),81 carbonaceous nanomaterials,82–84 molecularly-imprinted polymers (MIP)85,86 and metal organic frameworks (MOF).87 But among them the most commonly used are silica, graphene, carbon nanotubes (CNT), layered double hydroxide (LDH), b-cyclodextrine and chitosan, which will be mentioned here and the interested reader should refer to more dedicated reviews published in the literature about MPSE with the other above-mentioned coating materials.88–91 Silica (SiO2) is maybe the most commonly chosen material for the coating of MNPs due to its availability, chemical stability and presence of silane groups on its surface, which can strongly react with many surface ligands including amine, thiol and carboxylic ends. As mentioned earlier, since in MPSE the immobilized analytes need to be easily recovered from the MNP surface by elution, generally the silica surface is modified by replacing free silane groups with amine groups or octadecylsilane (ODS) in order to provide weaker linkage with non-polar or weakly polar analytes.92–94 The silica ¨ber method,95 which is based on coating is mostly done by following the Sto the condensation of tetraethylorthosilicate (TEOS) in sol–gel form on preformed MNPs and by governing these reactions in micelles one can control the thickness of the silica shell on MNPs.96 Another frequently studied coating material is layered double hydroxide (LDH), which is an anionic clay having parallel aligned layers with large interlayer spaces.97–99 Hence their attachment on MNPs, especially in brush like orientation (see Figure 8.5) offers further enhancement of the surface area in contact with analytes and thanks to the exchangeable anions in their structure, they act as excellent sorbents for metal ion removal in water.100 M. Shao et al. synthesized silicacoated Fe3O4 MNPs, whose surface is decorated with LDH nanoplatelets in a flowerlike morphology reaching a surface area of 83 m2 g1 and showed their application for the separation of histidine-tagged proteins.101,102 A second advantage of using LDHs in MPSE exists in the elution step such that, since the retention of the target analytes on LDH are mediated by ionic interactions they can be easily released back in a solvent with adjustable pH.

Figure 8.5

Different orientations (horizontal (a), vertical (b) and mixed (c)) of LDH attached on MNPs. Adapted from ref. 102 with permission from the Royal Society of Chemistry.

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LDHs can be synthesized by sol–gel, hydrothermal and co-precipitation methods, which are the most followed approaches for the formation of LDHs on already existing MNPs. In the opposite way, MNPs can be also embedded on an LDH surface either by chemical bonding or physical attachment.103 Another equally important coating material is cyclodextrin (CD), which is a cyclic oligosaccharide composed of 6 (a-CD), 7 (b-CD) or 8 (g-CD) glucose subunits, where b-CD is the most preferred one due to the easiness of production. The forthcoming property of CD making it popular in MPSE is its molecular morphology with hydrophilic exterior and hydrophobic cavity, which can encapsulate a large variety of appropriately sized organic compounds as analytes.104–106 CD is synthesized by the enzymatic conversion from starch, and its attachment on MNPs is supplied by hydrogen bonding with multiple hydroxyl groups on the hydrophilic side. Similarly, chitosan, as a natural polysaccharide cationic polymer, is widely used in MSPE applications.107–111 One of the earliest studies was done by Y. Chang and D. Chen, in which they reported very quick and efficient removal of Cu(II) ions from water by using chitosan coated Fe3O4 MNPs as sorbents. In this work chitosan was first carboxymethylated and then covalently bound on the surface of preformed magnetite nanoparticles via carbodiimide activation.112 Since their discovery, carbon-based nanomaterials, namely graphene (G) and carbon nanotubes (CNTs), have drawn tremendous attention due to their outstanding electrical, thermal and mechanical properties.113 As is well known, graphene is a two-dimensional layer of hexagonal carbon lattice with one atomic thickness. Its large specific area combined with unpaired electrons positioned throughout the 2-D carbon network allows high capacity adsorption of almost any kind of analyte on both sides via p–p, van der Waals, hydrophobic, and electrostatic interactions and hydrogen bonding.87,114 Due to the same reasons, its further functionalization and attachment of MNPs in order to bring magnetic responsiveness for MSPE application is also easily achievable.115–117 Graphene can be produced from its multilayer bulk form ‘‘graphite’’ or from its influential intermediate ‘‘graphene oxide (GO)’’, which possess highly reactive epoxy, hydroxyl, and carboxyl groups and is very soluble in water or other organic solvents on the contrary to graphene. For this reason, functionalized graphene oxide (fGO) is more intensively studied in dispersive MSPE.118–122 On the other hand, carbon nanotubes (CNTs), as the curled version of graphene that exists in two different forms as single-walled (SWCNT) and multi-walled (MWCNT) carbon nanotubes have more applicability due to further modification possibilities.123–125 The immobilization of MNPs on CNT (either as entrapment in the cylindrical cavity between the inner wall(s) or decoration on the outer wall(s)) can be realized with an in situ one step functionalization reaction, which is based on the electrostatic interaction of metal precursors with oxidized CNT followed by the deposition of metal-oxide MNPs with a common co-precipitation method.126 In summary, depending on the specific needs of the MSPE application we see plenty of studies in the literature, where the above-mentioned materials are combined in a smart way. Table 8.2 lists some recent examples of such studies in different MPSE applications.

226 Table 8.2

Chapter 8 Some MSPE studies utilizing different combinations of functionalized coating materials: IL – ionic liquid, MIP – molecularly imprinted polymers, MOF – metal organic framework.

Magnetic adsorbent

Analyte

Tetrabromobisphenol A Fe3O4@SiO2@MIPs GO/MWCNT/Fe3O4/SiO2 Paracetamol, caffeine NiFe2O4@PDA@Mg/Al–LDH Organophosphorus pesticides Fe3O4@ILs–b-CD–CP Mn(II), Mn(VII) ions CoFe2O4/chitosan Indigotine blue dye MOF-1210(Zr/Cu)–Fe3O4 Benzophenone Estrogens rGO/ZnFe2O4 Fe3O4@VTEO@IL–MIPs Lysozyme Fe3O4@MOFs Blood lipid regulators

Sample matrix

Reference

Water 127 Urine, wastewater 128 Fruit juice 64 Water Water Soil Water, soil, fish Chicken egg Water

81 129 130 131 132 133

8.4 Applications of MSPE 8.4.1

Environmental Applications

Environmental pollutants include heavy metal ions and organic contaminants such as dyes, pesticides, algal toxins, volatile organic compounds (VOCs) (i.e., polycyclic aromatic hydrocarbons (PAH)), flame retardants, hormones and pharmaceuticals, which are released into water, air and soil by domestic, agricultural and industrial activities.5,134–136 Among all the metal ions, arsenic As(III)/As(V), lead Pb(II), cadmium Cd(II) and mercury(II) are extremely toxic and threaten the human body even at trace concentrations, while in the second rank chromium Cr(III)/Cr(VI), antimony Sb(V), manganese Mn(II), nickel Ni(II) and copper Cu(II) can reach hazardous levels through bioaccumulation.114 Similarly, organic pollutants can damage biochemical pathways of living organisms. Nevertheless, preconcentration and removal of these pollutants are obligatory not only due to environmental legislation but also due to ecological health concerns. P. H. Towler et al. for the first time showed the recovery of Ra, Pb and Po from seawater samples using MnO2-coated Fe3O4 nanoparticles as sorbents.137 Since then, many different designs of MNPs conjugated with functional polymers such as poly(aminoamide) dendrimers (PAMAM),138 2-acrylamido-2-methyl-1-propansulfonic acid (AMPS)-based hydrogels,139 aminopropyltriethoxysilane (APS), copolymers of acrylic acid (AA) and crotonic acid (CA),140 polyrhodanine,141 and chitosan112 were reported for metal ion removal from water samples. Dyes,129 pesticides,64 hormones,131 and pharmaceuticals128 were successfully isolated from environmental samples by MSPE. F. Chen and co-workers have separated six triazole fungicides i.e., penconazole (Pen), tebuconazole (TEB), epoxiconazole (Epo), bitertanol (Bit), fenbuconazole (Fen) and difenoconazole (Dif) from environmental water by using ionic liquid-based carbon nanotube-coated MNPs as sorbents.142 In this work, 1-(3-aminoproyl)imidazole ILs were attached on the outer wall of MWCNTs, whose surface was further decorated by magnetite Fe3O4 nanoparticles resulting in IL–Fe3O4@MWCNT sorbents (see Figure 8.6).

Functionalized Magnetic Nanoparticles for Solid-phase Extraction

Figure 8.6

8.4.2

227

Synthesis route of IL–Fe3O4@MWCNT sorbents for the MSPE of triazole fungicides from environmental water. Reproduced from ref. 142 with permission from the Royal Society of Chemistry.

Food Applications

Food quality and safety is one of the most important aspects regarding public health. In addition to pollutants like polychlorinated dioxins, PAHs, pesticides, and veterinary drugs which contaminate foods through ecological cycles, there are also additives commonly used in the food industry in order to increase the shelf life of foodstuffs and also natural toxins (mycotoxin, phycotoxins, phytotoxins) included in food products.68 As regulated by law, the amounts of these chemical compounds must be monitored regularly to check whether they meet the allowed limitations put in place by health authorities such as the FDA (U. S. Food and Drug Administration). However, most of the analyzed food products have a high degree of complexity and the naturally occurring lipids, fat acids, proteins, sugars and pigments interfere with the above-mentioned target analytes, hence careful sample

228

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pre-treatment with clean-up of these interferents followed by the preconcentration and enrichment of the analytes is needed with efficient separation techniques such as MSPE.143 Different food products such as milk,144 eggs,132 honey,145 tea146 and fruit juices64 have been studied with MSPE, where again a diverse combination of coating materials (LDH, b-CD, GO, ILs, MIPs etc.) with MNPs were used as magnetic sorbents. As an example, S. Wang et al. reported selective binding of quercetin, which is a plant flavonol that exists in many fruits, vegetables and seeds, on Fe3O4–bCD@MIP sorbents.147 In the preparation of these sorbents, the surface of the PEGylated Fe3O4 MNPs were first modified by b-CD, which is then imprinted with baicalein (BAI) in the presence of crosslinkers (see Figure 8.7).

8.4.3

Biological and Pharmaceutical Applications

Implementation of MSPE to biological samples such as human blood serum,148 urine,149 saliva150 and sperm find many applications in biotechnology, medicine and pharmaceutics.151,152 In molecular biology and genetics studies the isolation/purification of ribonucleic acid (RNA) and deoxyribonucleic acid (DNA) is needed for use in further analysis such as polymerase chain reaction (PCR) amplification or DNA hybridization. MSPE offers faster, more sensitive and efficient separation as compared to phenol/ chloroform extraction of DNA and therefore is widely used in modern DNA extraction kits. For a long time, silica-coated MNPs were employed as magnetic sorbents for DNA,68 however in this approach the negatively charged surface of silica (attributed to deprotonated silanol groups) should be densely modified with chaotropic salts to ‘‘shield’’ the electrostatic repulsion between silica and polyanionic DNA in neutral conditions (see Figure 8.4). Alternatively, at lower pH a surface treatment with amino groups (or functionalization with an amino-reach polymer like PEI) can promote electrostatic interactions between protonated amino groups on silica and DNA.6 MNPs are also used in immunoassays, which is the procedure for the identification of cells,153 proteins154/peptides and biomacromolecules based on antibody affinity. Antibodies permit specific recognition of cell types by binding to a cell-surface receptor. In their immobilization on MNPs, usually some crosslinkers such as N-succinimidyl 3-(2-pyridyldithio) propionate (SPDP), 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide hydrochloride (EDCI) and N,N 0 -methylene bis acrylamide (MBA) are also involved. One should note here that in practice, although the targeted cell population is recognized with high specificity, only a low fraction of targeted cells interacts with the antibody attached MNPs, where actually at this point the cell membrane plays a crucial role in MNP–cell interactions.43 In pharmaceutical science MSPE is used for the determination of drug molecules in biological fluids. This is required for toxicology, therapeutic drug monitoring as well as the development of new drugs. After the administration of drugs into the body either through injection or oral methods, following its biodistribution and processing by the metabolism, monitoring

Functionalized Magnetic Nanoparticles for Solid-phase Extraction

Figure 8.7

229

Schematic showing the synthesis steps of Fe3O4–b-CD@MIP as a sorbent of quercetin. Reproduced from ref. 147 with permission from the Royal Society of Chemistry.

the low concentration residuals in blood and/or urine is important for pharmacokinetic studies and bioequivalence tests. Many different drugs such as antibiotics,155 analgesics,156 anti-inflammatory,157 antidepressants,158 steroids159 or supplements like hormones149 were isolated from biological matrices by using MSPE, in which MNPs conjugated with a combination of ILs, MIPs, GOs, and CNTs were used as magnetic sorbents. For example, S. Badragheh and colleagues synthesized silica coated magnetite nanoparticles functionalized with 1-vinyl-3-octylimidazolium bromide (VIOM–Br) as ionic liquids, where Br anions were further replaced with PF6. They showed that the resulting Fe3O4@SiO2@PILs nanoparticles can be used to extract antidiabetic drugs from human plasma160 (see Figure 8.8).

230

Figure 8.8

Chapter 8

Schematic diagram showing the preparation of Fe3O4@SiO2@PILs and its application magnetic isolation of target drugs. Reproduced from ref. 160 with permission from the Royal Society of Chemistry.

Abbreviations AA AMPS APS CA CD CNT EDCI FFF GO HGMS IL LDH LGMS MBA MgFFF MIP MNP MOF MSPE MWCNT ODS PAH PAMAM PCR

Acrylic acid 2-Acrylamido-2-methyl-1-propanesulfonic acid Aminopropyltriethoxysilane Crotonic acid Cyclodextrine Carbon nanotube 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide hydrochloride Field flow fractionation Graphene oxide High gradient magnetic separation Ionic liquid Layered double hydroxide Low gradient magnetic separation N,N 0 -methylene bis acrylamide Magnetic field flow fractionation Molecularly imprinted polymers Magnetic nanoparticle Metal organic framework Magnetic solid phase extraction Multi-walled carbon nanotube Octadecylsilane Polycyclic aromatic hydrocarbons Poly(aminoamide) dendrimer Polymerase chain reaction

Functionalized Magnetic Nanoparticles for Solid-phase Extraction

PEG PEI rG SPDP SPE SWCNT TBD VOC

231

Polyethylene glycol Polyethylenimine Reduced graphene N-succinimidyl 3-(2-pyridyldithio) propionate Solid phase extraction Single-walled carbon nanotube Triazabicyclodecene Volatile organic compound

References 1. N. J. K. Simpson, Solid-Phase Extraction: Principles, Techniques and Applications, Marcel Dekker Inc, New York-Basel, 2000. 2. B. Buszewski and M. Szultka, Crit. Rev. Anal. Chem., 2012, 42, 198. ´n and S. C. G. N. Braga, 3. F. Augusto, L. W. Hantao, N. G. S. Mogollo TrAC, Trends. Anal. Chem., 2013, 43, 14. ´ska, M. de la Guardia and J. Namies´nik, 4. J. P. Wasylka, N. Szczepan TrAC, Trends. Anal. Chem, 2016, 77, 23. ´n, E. Ballesteros, M. Zhang 5. A. Azzouz, S. K. Kailasa, S. S. Lee, A. J. Rasco and K. H. Kim, TrAC, Trends. Anal. Chem., 2018, 108, 347. 6. J. Kudr, Y. Haddad, L. Richtera, Z. Heger, M. Cernak, V. Adam and O. Zitka, Nanomaterials, 2017, 7, 243. 7. J. S. Beveridge, J. R. Stephens and M. E. Williams, Ann. Rev. Anal. Chem., 2011, 4, 251. 8. M. Faraji, Nanochem. Res., 2016, 1, 264. 9. P. Baile, E. Fernandez, L. Vidal and A. Canals, Analyst, 2019, 144, 366. ¨yu ¨ktiryaki, R. Keçili and C. M. Hussain, TrAC, Trends Anal. Chem., 10. S. Bu 2020, 127, 115893. 11. C. M. Hussain, Nanomaterials in Chromatography: Current Trends in Chromatographic Research Technology and Techniques, Elsevier, Amsterdam, 2018. 12. C. M. Hussain, Handbook of Nanomaterials in Analytical Chemistry: Modern Trends in Analysis, Elsevier, Amsterdam, 2019. 13. C. M. Hussain, Handbook on Miniaturization in Analytical Chemistry: Application of Nanotechnology, Elsevier, Amsterdam, 2020. 14. E. Umut, F. Pineider, P. Arosio, C. Sangregorio, M. Corti, F. Tabak, A. Lascialfari and P. Ghigna, J. Magn. Magn. Mater., 2012, 324, 2373. ¨denler, M. Basini, M. F. Casula, E. Umut, C. Go ¨sweiner, 15. M. Bo A. Petrovic, D. Kruk and H. Scharfetter, J. Magn. Reson., 2018, 290, 68. 16. Y. X. J. Wang, Quant Imaging Med. Surg., 2011, 1, 35–40. 17. Q. L. Vuong, P. Gillis, A. Roch and Y. Gossuin, Wiley Interdiscip. Rev.: Nanomed. Nanobiotechnol., 2017, 9, 1. 18. J. W. M. Bulte, Adv. Drug Delivery Rev., 2019, 138, 293. 19. S. Palanisamy and Y. M. Wang, Dalton Trans., 2019, 48, 9490. ¨ngu ¨nes- , J. Colloid 20. E. Umut, M. Cos- kun, F. Pineider, D. Berti and H. Gu Interface Sci., 2019, 550, 199.

232

Chapter 8

21. Z. Hedayatnasap, F. Abnisa and W. M. A. W. Daud, Mater. Des., 2017, 123, 174. 22. M. L. Plumer, J. Van Ek and D. Weller, The Physics of Ultra-High-Density Magnetic Recording, Springer-Verlag, Berlin, 2012. 23. N. R. Ram, M. Prakash, U. Naresh, N. S. Kumar, T. S. Sarmash, T. Subbarao, R. J. Kumar, G. R. Kumar and K. C. B. Naidu, J. Supercond. Novel Magn., 2018, 31, 1971. 24. Y. Zou, Y. Chen, Z. Yan, C. Chen, J. Wang and S. Yao, Analyst, 2013, 138, 5904. 25. M. ˇ Safarˇıkova and I. ˇ Safarˇık, J. Magn. Magn. Mater., 1999, 194, 108. 26. A. H. Latham, R. S. Freitas, P. Schiffer and M. E. Williams, Anal. Chem., 2005, 77, 5055. 27. T. M. Vickrey and J. A. Garcia-Ramirez, Sep. Sci. Technol., 1980, 15, 1297. 28. P. Reschiglian, A. Zattoni, B. Roda, E. Michelini and A. Roda, Trends Biotechnol., 2005, 23, 475. 29. S. K. R. Williams, J. R. Runyon and A. A. Ashames, Anal. Chem., 2011, 83, 634. 30. O. Tsukamoto, T. Ohizumi, T. Ohara, S. Mori and Y. Wada, IEEE Trans. Appl. Supercond., 1995, 5, 311. 31. F. Carpino, M. Zborowski and P. S. Williams, J. Magn. Magn. Mater., 2007, 311, 383. 32. M. Iranmanesh and J. Hulliger, Chem. Soc. Rev., 2017, 46, 5925. 33. C. T. Yavuz, J. T. Mayo, W. W. Yu, A. Prakash, J. C. Falkner, S. Yean, L. Cong, H. J. Shipley, A. Kan, M. Tomson, D. Natelson and V. L. Colvin, Science, 2006, 314, 964. 34. J. S. Beveridge, J. R. Stephens, A. H. Lantham and M. E. Williams, Anal. Chem., 2009, 81, 9618. 35. Y. Bi, X. Pan, L. Chen and Q. H. Wan, J. Chromatogr. A, 2011, 1218, 3908. 36. P. F. Garcia, M. Brammen, M. Wolf, S. Reinlein, M. F. von Roman and S. Berensmeier, Sep. Purif. Technol., 2015, 150, 29. 37. S. Mirshahghassemi, A. D. Ebner, B. Cai and J. R. Lead, Sep. Purif. Technol., 2017, 179, 328. 38. Z. Kheshti, K. A. Ghajar, A. Altaee and M. R. Kheshti, Sep. Purif. Technol., 2019, 212, 650. 39. W. Ge, A. Encinas, E. Araujo and S. Song, Results Phys., 2017, 7, 4278. 40. S. S. Leong, Z. Ahmad, S. C. Low, J. Camacho, J. Faraudo and J. Lim, Langmuir, 2020, 36, 8033. 41. J. Lim, S. P. Yeap and S. C. Low, Sep. Purif. Technol., 2014, 123, 171. 42. S. P. Yeap, J. Lim, B. S. Ooi and A. L. Ahmad, J. Nanopart. Res., 2017, 19, 368. 43. E. Umut, in Modern Surface Engineering Treatments, ed. M. Aliofkhazraei, Intech Publisching Inc., Croatia, 2013. 44. A. Goldmann, Modern Ferrite Technology, Springer, USA, 2006. 45. R. H. Kodama, J. Magn. Magn. Mater., 1999, 200, 359. 46. S. Sun, H. Zeng, D. B. Robinson, S. Raoux, P. M. Rice, S. X. Wang and G. Li, J. Am. Chem. Soc., 2004, 126, 273.

Functionalized Magnetic Nanoparticles for Solid-phase Extraction

233

47. S. Sun, S. Anders, T. Thomson, J. E. E. Baglin, M. F. Toney, H. F. Hamann, C. B. Murray and B. D. Terris, J. Phys. Chem. B, 2003, 107, 5419. 48. N. Li, J. Chen and Y. P. Shi, Talanta, 2015, 141, 212. 49. Q. Zhou, M. Lei, J. Li, K. Zhao and Y. Liu, J. Chromatogr. A, 2016, 1441, 1. 50. Q. Zhou, M. Lei, Y. Liu, Y. Wu and Y. Yuan, Talanta, 2017, 175, 194. 51. E. Tahmasebi, Y. Yamini, M. Moradi and A. Esrafili, Anal. Chim. Acta, 2013, 713, 68. 52. S. Sadeghi, H. Azhdari, H. Arabi and A. Z. Moghaddam, J. Hazard. Mater., 2012, 215–216, 208. 53. S. Zhang, H. Niu, Z. Hu, Y. Cai and Y. Shi, J. Chromatogr. A, 2010, 1217, 4757. ˇ as, N. Campillo and M. Herna ´ndez-Co ´rdoba, 54. M. Pastor-Belda, P. Vin Food Chem., 2017, 221, 76. 55. F. S. Dias, M. E. P. A. Guarino, A. L. C. Pereira, P. P. Pedra, M. A. Bezerra and S. G. Marchetti, Microchem. J., 2019, 146, 1095. 56. Y. Li, X. Wu, Z. Li, S. Zhong, W. Wang, A. Wang and J. Chen, Talanta, 2015, 144, 1279. 57. K. Ma, M. Zhang, S. Miao, X. Gu, N. Li, S. Cui and J. Yang, J. Sep. Sci., 2018, 41, 3441. 58. J. H. Lo and G. Chen, Langmuir, 2005, 24, 11173. 59. R. Wu and J. Qu, J. Chem. Technol. Biotechnol., 2005, 80, 20. 60. N. U. Yamaguchi, R. Bergamasco and S. Hamoudi, Chem. Eng. J., 2016, 295, 391. 61. Z. S. Kardar, M. H. Beyki and F. Shemirani, Food Chem., 2016, 209, 241. 62. A. A. Ensafi, S. Rabiei, B. Rezaei and A. R. Allafchian, Anal. Methods, 2013, 5, 3903. 63. S. H. Hashemi, M. Kaykhaii, A. J. Keikha and E. Mirmoradzehi, Spectrochim. Acta, Part A, 2019, 213, 218. 64. L. Du, X. Wang, T. Liu, J. Li, J. Wang, M. Gao and H. Wang, Microchem. J., 2019, 150, 104128. 65. P. Hashemi, H. Bagheri, A. Afkhami, A. Amidi and T. Madrakian, Talanta, 2018, 176, 350. 66. R. Nakao, Y. Matuo, F. Mishima, T. Taguchi and S. Nishijima, J. Phys.: Conf. Ser., 2009, 156, 012032. 67. E. C. S. Santos, T. C. dos Santos, R. B. Guimaraes, L. Ishida, R. S. Freitas and C. M. Ronconi, RSC Adv., 2015, 5, 48031. 68. M. Wierucka and M. Biziuk, TrAC, Trends. Anal. Chem., 2014, 59, 50. 69. W. Liu, M. Yue, B. Cui and G. C. Hadjipanayis, Rev. Nanosci. Nanotechnol., 2014, 3, 259. 70. S. Rajput, L. P. Singh, C. U. Pittman and D. Mohan, J. Colloid Interface Sci., 2017, 492, 176. 71. K. Atrak, A. Ramazani and S. T. Fardood, J. Mater. Sci.: Mater. Electron., 2018, 29, 6702. 72. S. Sun and H. Zeng, J. Am. Chem. Soc., 2002, 124, 8204. 73. S. Sun, H. Zeng, D. B. Robinson, S. Raoux, P. M. Rice, S. X. Wang and G. Li, J. Am. Chem. Soc., 2004, 126, 273.

234

Chapter 8

74. S. Sun, S. Anders, T. Thomson, J. E. E. Baglin, M. F. Toney, H. F. Hamann, C. B. Murray and B. D. Terris, J. Phys. Chem. B, 2003, 107, 5419. 75. N. A. Yazid and Y. C. Joon, AIP Conf. Proc., 2019, 2124, 020019. 76. E. Umut and Hittite, J. Sci. Eng., 2019, 6, 243. ´rez-Landaza ´bal, J. M. Pastor and C. Go ´mez-Polo, 77. S. Larumbe, J. I. Pe J. Appl. Phys., 2012, 111, 103911. 78. X. Sun, Y. Q. Ma, S. T. Xu, Y. F. Xu and B. Q. Geng, Mater. Charact., 2015, 107, 343. 79. M. Unni, A. M. Uhl, S. Savliwala, B. H. Savitzky, R. Dhavalikar, N. Garraud, D. P. Arnold, L. F. Kourkoutis, J. S. Andrew and C. Rinaldi, ACS Nano, 2017, 11, 2284. 80. V. N. Nikiforov, A. N. Ignatenko and V. Y. Irhin, Bull. Russ. Acad. Sci.: Phys., 2014, 78, 1081. 81. S. Chen, X. Qin, W. Gu and X. Zhu, Talanta, 2016, 161, 325. 82. S. Farhad and K. Fatemeh, J. Nanosci. Nanotechnol., 2020, 20, 5433. 83. Q. Han, Z. Wang, J. Xia, S. Chen, X. Zhang and M. Ding, Talanta, 2012, 101, 388. 84. S. Li, Y. Gong, Y. Yang, C. He, L. Hu, L. Zhu, L. Sun and D. Shu, Chem. Eng. J., 2015, 260, 231. 85. A. Zengin, E. Yıldırım, U. Tamer and T. Caykara, Analyst, 2013, 138, 7238. 86. R. Keçili and C. M. Hussain, Int. J. Anal. Chem., 2018, 8503853. 87. Y. Wang, J. Xie, Y. Wu and X. Hu, Microchim. Acta, 2014, 181, 949. 88. N. Li, H. L. Jiang, X. Wang, X. Wang, G. Xu, B. Zhang, L. Wang, R. S. Zhao and J. M. Lin, TrAC, Trends. Anal. Chem., 2018, 102, 60. 89. F. Maya, C. P. Cabello, R. M. Frizzarin, J. M. Estela, G. T. Palomino and V. Cerd, TrAC, Trends. Anal. Chem., 2017, 90, 142. 90. M. Dinç, C. Esen and B. Mizaikoff, TrAC, Trends. Anal. Chem., 2019, 114, 202. 91. C. S. Jon, L. Y. Meng and D. Li, TrAC, Trends. Anal. Chem., 2019, 120, 115641. 92. M. Mostafaei, S. N. Hosseini, M. Khatami, A. Javidanbardan, A. A. Sepahy and E. Asadi, Protein Expression Purif., 2018, 145, 1. 93. N. B. Caon, C. S. Cardoso, F. L. Faita, L. Vitali and A. L. Parize, J. Environ. Chem. Eng., 2020, 8, 104003. 94. N. C. C. Lobato, A. M. Ferreira, P. G. Weidler, M. Franzreb and M. B. Mansur, Sep. Purif. Technol., 2019, 229, 115839. ¨ber, A. Fink and E. Bohn, J. Colloid Interface Sci., 1968, 26, 62. 95. W. Sto 96. S. Santra, R. Tapec, N. Theodoropoulou, J. Dobson, A. Hebard and W. Tan, Langmuir, 2001, 17, 2900. 97. D. Yang, X. Li, D. Meng, M. Wang and Y. Yang, Food Chem., 2017, 237, 870. 98. H. Palza, K. Delgado and J. Govan, Appl. Clay Sci., 2019, 183, 105350. 99. J. Sun, Y. Chen, H. Yu, L. Yan, B. Du and Z. Pei, J. Colloid Interface Sci., 2018, 532, 474. 100. S. H. Lee, H. Choi and K. W. Kim, J. Geochem. Explor., 2018, 184, 247. 101. M. Shao, F. Ning, J. Zhao, M. Wei, D. G. Evans and X. Duan, J. Am. Chem. Soc., 2012, 134, 1071.

Functionalized Magnetic Nanoparticles for Solid-phase Extraction

102. 103. 104. 105. 106. 107.

108. 109. 110. 111. 112. 113. 114. 115. 116. 117. 118. 119. 120. 121. 122. 123.

124. 125. 126. 127. 128. 129. 130. 131. 132.

235

Z. Gu, J. J. Atherton and Z. P. Xu, Chem. Commun., 2015, 51, 3024. D. Jiang, X. Li and Q. Jia, ACS Sustainable Chem. Eng., 2019, 7, 421. A. Gentili, J. Chromatogr. A, 2020, 1609, 460654. J. H. Lee and S. Y. Kwak, Appl. Surf. Sci., 2019, 467–468, 178. K. V. Ragavan and N. K. Rastogi, Carbohydr. Polym., 2017, 168, 129. M. Omidinasab, N. Rahbar, M. Ahmadi, B. Kakavandi, F. Ghanbari, G. Z. Kyzas, S. S. Martinez and N. Jaafarzadeh, Environ. Sci. Pollut. Res., 2018, 25, 34262. T. Tolessa, X. X. Zhou, M. Amde and J. F. Liu, Talanta, 2017, 169, 91. A. Feizbakhsh and S. Esteshami, Chromatographia, 2016, 79, 1177. M. K. Moazen and H. A. Panahi, J. Sep. Sci., 2017, 40, 1019. J. Shah and M. R. J. Tasmia, Carbohydr. Polym., 2018, 199, 461. Y. C. Chang and D. H. Chen, J. Colloid Interface Sci., 2005, 283, 446. ¨ . B. Mergen, E. Umut, E. Arda and S. Kara, Polym. Test., 2020, 90, 106682. O M. Hemmati, M. Rajabi and A. Asghari, Microchim. Acta, 2018, 185, 160. S. Mahpishanian and H. Sereshti, J. Chromatogr. A, 2016, 1443, 43. M. Musa, W. A. W. Ibrahim, F. M. Marsin, A. S. A. Keyon and H. R. Nodeh, Food Chem., 2018, 265, 165. H. You, X. F. Wang, J. Y. Li, H. T. Fan, H. Shen and Q. Zhang, J. Ind. Eng. Chem., 2019, 70, 346. L. P. Lingamdinne, J. R. Koduru and R. R. Karri, J. Environ. Manage., 2019, 231, 622. J. Sun, Q. Liang, Q. Han, X. Zhang and M. Ding, Talanta, 2015, 132, 557. Y. X. Ma, D. Xing, W. J. Shao, X. Y. Du and P. Q. La, J. Colloid Interface Sci., 2017, 505, 352. M. Yan, Q. Liang, W. Wan, Q. Han, S. Tan and M. Ding, RSC Adv., 2017, 7, 30109. J. Sengupta and C. M. Hussain, TrAC, Trends Anal. Chem., 2019, 114, 326. M. Melchionna, A. Beltram, A. Stopin, T. Montini, R. W. Lodge, A. N. Khlobystov, D. Bonifazi, M. Prato and P. Fornasiero, Appl. Catal., B, 2018, 227, 356. Y. Liu, L. Guo, H. Huang, J. Dou, Q. Huang, D. Gan, J. Chen, Y. Li, X. Zhang and Y. Wei, J. Colloid Interface Sci., 2019, 545, 8. A. I. C. Ricardo, A. Sanchez-Cachero, M. Jimenez-Moreno, F. J. G. Bernardo, R. C. R. Martin-Doimeadios and A. Rios, Talanta, 2018, 179, 442. C. Herrero-Latorre, J. Barciela-Garcı´a, S. Garcia-Martı´n, R. Pena´nez, Anal. Chim. Acta, 2015, 892, 10. Crecente and J. Otarola-Jime Q. Wu, M. Li, Z. Huang, Y. Shao, L. Bai and L. Zhou, J. Ind. Eng. Chem., 2018, 60, 268. H. I. Ulusoy, E. Yılmaz and M. Soylak, Microchim. J., 2019, 145, 843. J. M. N. dos Santos, C. R. Pereira, L. A. A. Pinto, T. Frantz, E. C. Lima, E. L. Foletto and G. L. Dotto, Carbohydr. Polym., 2019, 217, 6. W. Li, R. Wang and Z. Chen, J. Chromatogr. A, 2019, 1607, 460403. W. Li, J. Zhang, W. Zhu, P. Qin, Q. Zhou, M. Lu, X. Zhang, W. Zhao, S. Zhang and Z. Cai, Talanta, 2020, 208, 120440. W. Xu, Q. Dai, Y. Wang, X. Hu, P. Xu, R. Ni and J. Meng, RSC Adv., 2018, 8, 21850.

236

Chapter 8

133. E. M. Pena-Mendez, R. M. Mawale, J. E. Conde-Gonzalez, B. SocasRodriguez, J. Havel and C. Ruiz-Perez, Talanta, 2020, 207, 120275. 134. C. M. Hussain, in Advanced Environmental Analysis-application of Nanomaterials, ed. C. M. Hussain and B. Kharisov, The Royal Society of Chemistry, Cambridge, 2017. ¨yu ¨ktiryaki, Y. Su ¨mbelli, R. Keçili and C. M. Hussain, in Encyclo135. S. Bu pedia of Analytical Science, ed., P. Worsfold, C. Poole, A. Townshend and ´, Elsevier, Amsterdam, 2019, vol. 5. M. Miro 136. C. M. Hussain and R. Keçili, Modern Environmental Analysis Techniques for Pollutants, Elsevier, Amsterdam, 2019. 137. P. H. Towler, J. D. Smith and D. R. Dixon, Anal. Chim. Acta, 1996, 328, 53. 138. C. M. Chou and H. L. Lien, J. Nanopart. Res., 2011, 13, 2099. 139. O. Ozay, S. Ekici, Y. Baran, N. Aktas and N. Sahiner, Water Res., 2009, 43, 4403. 140. F. Ge, M. M. Li, H. Ye and B. X. Zhao, J. Hazard. Mater., 2012, 211, 366. 141. J. Song, H. Kong and J. Jang, J. Colloid Interface Sci., 2011, 359, 505. 142. F. Chen, Z. Song, J. Nie, G. Yu, Z. Li and M. Lee, RSC Adv., 2016, 6, 81877. 143. A. Andrade-Eiroa, M. Canle, V. Leroy-Cancellieri and V. Cerda, TrAC, Trends. Anal. Chem., 2016, 80, 641. 144. Y. Zhao, Y. C. Yuan, X. L. Bai, Y. M. Liu, G. F. Wu, F. S. Yang and X. Liao, Food Chem., 2020, 305, 125429. 145. S. Mahpishanian and H. Sereshti, J. Chromatogr. A, 2017, 1485, 32. 146. Y. Shi, H. Wu, C. Wang, X. Guo, J. Du and L. Du, Food Chem., 2016, 199, 75. 147. S. Wang, B. Wang, H. Si, J. Shan and X. Yang, RSC Adv., 2015, 5, 8028. 148. W. Wu, F. Lin, X. Yang, B. Wang, X. Lu, Q. Chen, F. Ye and S. Zhao, Talanta, 2020, 207, 120284. 149. L. Chen, M. Zhang, F. Fu, J. Li and Z. Lin, J. Chromatogr. A, 2018, 1567, 136. 150. Y. Cui, D. Liu, M. Zhao, J. Li, Y. Yang, M. Li, J. Gao and Y. Jiang, J. Pharm. Biomed. Anal., 2020, 189, 113414. 151. D. Sharma and C. M. Hussain, Arabian J. Chem., 2020, 13, 3319. ¨yu ¨ktiryaki and C. M. Hussain, TrAC, Trends Anal. Chem., 152. R. Keçili, S. Bu 2019, 110, 259. 153. H. Xu, Z. P. Aguilar, L. Yang, M. Kuang, H. Duan, Y. Xiong, H. Wei and A. Wang, Biomaterials, 2011, 32, 9758. 154. Q. Wen, Y. Wang, K. Xu, N. Li, H. Zhang, Q. Yang and Y. Zhou, Talanta, 2016, 160, 481. 155. S. Wei, J. Li, Y. Liu and J. Ma, J. Chromatogr. A, 2016, 1473, 19. 156. T. Madrakian, F. Fazl, M. Ahmadi and A. Afkhami, New J. Chem., 2016, 40, 122. 157. H. Alinezhad, A. Amiri, M. Tarahomi and B. Maleki, Talanta, 2018, 183, 149. 158. M. Safari, M. Shahlaei, Y. Yamini, M. Shakorian and E. Arkan, Anal. Chim. Acta, 2018, 1034, 204. 159. X. An, W. Chai, X. Deng, H. Chen and G. Ding, J. Sep. Sci., 2018, 41, 2774. 160. S. Badragheh, M. Zeeb and M. R. T. B. Olyai, RSC Adv., 2018, 8, 30550.

Section 3: Functionalized Magnetic Nanoparticles in the Separation/ Identification Stage of Analysis

CHAPTER 9

Use of Functionalized Magnetic Nanoparticles in Modern Separation Techniques SAURABH SHUKLA,a RAMSHA KHAN,*a ABHISHEK SAXENAa AND CHAUDHERY MUSTANSAR HUSSAIN*a,b a

Faculty of Civil Engineering, Institute of Technology, Shri Ramswaroop Memorial University, Barabanki-225003, UP, India; b Department of Chemistry and Environmental Science, New Jersey Institute of Technology, University Heights, Newark, NJ 07102, USA *Emails: [email protected]; [email protected]

9.1 Introduction The sustenance of our society in coherence with sustainable development is directly proportional to our advancements in managing the decreasing environmental quality.1 The hazards related to human health in terms of the possible entrance of heavy metals (HMs) into the food chain/web (biomagnification) presents a worrisome picture.2 The pressure for increasing crop production has resulted into immense application of inorganic fertilizers which contain huge concentrations of nitrogen. Such activities have led to the pollution of underground water sources which may cause several diseases in human beings including ‘blue baby syndrome’ in infants.3,4 The field of nanoparticles has been widely accepted throughout the globe owing to the unique physico-chemical properties related to their shape and size.5 The term ‘nanotechnology’ relatively defines the processes related to structures with sizes in the range of 1–100 nm.6 The broad spectrum of applications includes Analytical Applications of Functionalized Magnetic Nanoparticles Edited by Chaudhery Mustansar Hussain r The Royal Society of Chemistry 2021 Published by the Royal Society of Chemistry, www.rsc.org

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the areas of chemistry, biochemistry, medicine, biotechnology and biomedics.7 The conjunction of nanotechnology with analytical chemistry has provided new pathways to researchers for exploring the efficacy and employability of these two fields in coherence. The advantages associated with NPs include their enhanced reactivity owing to greater ratio between surface area and volume when compared to their heavier counterparts.8 The role of NPs in analytical processes in sample preparation has emerged to be very effective. The implementation of NPs in the preparation of samples is about 30% of the utilization of nanomaterials (NMs). The increasing use of NMs as stationary phases in chromatographic techniques includes in liquid chromatography (LC) and gas chromatography (GC). The increased productivity and simplification of sample preparation through the use of NMs have been witnessed, considering the complexities associated with the process.9 The use of NMs in sample preparation is illustrated in Figure 9.1. An important class of NPs which has gained high impetus owing to its exemplary properties is magnetic nanoparticles (MNPs). MNPs have presented excellent potential applicability in the field of biomedicines.10 The application of MNPs in various diagnostic and therapeutic techniques has had a vital impact. The unique abilities of MNPs to perform at cellular and molecular levels for biological processes have led to their use as catalysts and contrast agents in imaging techniques including magnetic resonance imaging (MRI).11 The application of MNPs as vehicles for targeted drug delivery,12 detection and treatment of critical diseases such as cancer,13 neurological illnesses,14 and cardiovascular diseases15 has gained popularity owing to their efficient performance. MNPs owing to their unique properties have widely been employed in the field of separation, drug delivery and catalysis. MNPs can be separated from environmental and biological samples using an external magnetic field. Therefore, the need for additional steps of filtration centrifugation is terminated. Some of the considerable physical properties of MNPs which promote their employability in the field of biomedicine are illustrated in Figure 9.2.

Figure 9.1

Use of NMs in sample preparation.

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Figure 9.2

241

Properties of MNPs affecting their use in biomedicine.

These properties of MNPs and the effect on their use in biomedicines are discussed below. (a) Controllable sizes: The size range of MNPs is relatively smaller or comparable to that of a cell (10–100 mm), virus (20–450 nm) or gene (2 nm wide and 10–100 nm long) etc. This comparable size of MNPs assists their movement into the vicinity of the required biological target. A layer or coating of other biological molecules can be applied to promote their interaction or binding with the biological target, making addressing the target very convenient. (b) MNPs obey Coulomb’s Law: These NPs being magnetic in nature follow the Coulomb’s law thereby making their working controllable through a fluctuating external magnetic field. The conjunction of penetrability of magnetic fields into human cells with optimal working at a controlled distance has widened the applications of MNPs in targeted drug delivery. Thus, the transportation of any substance, delivery of cancer treatment drugs to a targeted part (tumor, lesion) in the human body can be achieved with great convenience. (c) Ability of MNPs to resonantly respond to a fluctuating magnetic field: This ability of MNPs provides the benefit of energy transfer from the excited magnetic field to the NP. Let us consider a case of heating up the MNP, leading to its employment as a hyperthermia agent which provides a noxious quantity of thermal energy to targeted areas in the body including tumors. They are often used as agents for the enhancement of radiotherapy and chemotherapy techniques, as an average amount of heating is optimal for termination of virulent cells or tissues. Although MNPs offer many benefits, the issue of their instable nature as a result of their size range which causes clustering is problematic. Moreover,

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the vulnerable metallic NPs lose their magnetism due to the occurrence of oxidization owing to reactivity. Thus, functionalization of NPs by surface modification through fusion of bioparticles including antibodies, folic acid, etc. and chemicals16 is a method to overcome the shortcomings of NPs. The optimal properties of functionalized NPs including non-clustering, and non-abrasive nature in conjunction with various physical properties have promoted the employment and potential exploration by researchers.17 The application of NPs in chromatographic techniques has been very popular and is an area of extended investigation owing to its broad spectrum of applications. The NPs varying in the size range of 1–2 nm have wide applications in open tubular columns for gas chromatography (GC), and highperformance liquid chromatography (HPLC) systems as well.18 In the science of separation, the analytical performance of any technique is quantified based on the selectivity of analyte and efficiency of separation parameters. The separation is dependent upon the characteristics of stationary phases. The NPs in unchanged and hybrid forms including functionalized MNPs etc. have emerged as novel stationary phases for efficient chromatographic selectivity and retention. In general, four types of interparticle forces exist in MNPs, including van der Waals forces, magnetic forces, electrostatic repulsion forces, and steric hindrance. The van der Waals forces and magnetic forces cause agglomeration of MNPs while electrostatic repulsion forces and steric hindrance provide enhanced stability and are advantageous. MNPs in spite of various benefits carry some shortcomings including agglomeration of the particles and stability concerns. The naked metallic NPs are chemically active and are easily oxidized leading to loss of their magnetic features. Thus, for the preservation of their stability various coatings with silica, carbon, or polymers are applied. The surface modification techniques include introduction of shielding molecules on the surface of the particle to enhance the repulsive force between particles. This also causes reduction in the surface energy, and improvement in the hydrophilic/hydrophobic properties. The introduction of various functional groups including sulfonic acid, amino, and hydroxyl into MNPs is an efficient method of surface modification. The coating of materials on the surface of particles including quantum dots, silicon dioxide, and metal oxides is a technique to adjust the selectivity of the sorbent. Moreover, the surface modification techniques include both physical modification and chemical bonding in coherence. The technique of physical modification employs physical means including adsorption, and coating, through methods like surface adsorption and surface deposition. The surface modification of MNPs through plasma and ultraviolet radiation is a physical modification while chemical modification includes modification in the surface state of MNPs.19 The concept of magnetic particles design workflow and the possible modification and functionalization of magnetic particles are illustrated in Figure 9.3.

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Figure 9.3

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Concept of magnetic particles design workflow and possible modification and functionalization of magnetic particles. Reproduced from ref. 20, https://doi.org/10.3390/nano7090243, under the terms of the CC BY 4.0 license https://creativecommons.org/licenses/ by/4.0/.

9.2 Synthesis of MNPs The possibilities of advancements in the properties of MNPs led to the development of various methods for the synthesis of MNPs. Some of these methods are illustrated in Figure 9.4.

9.2.1

Thermal Decomposition Technique

The synthesis of MNPs through thermal decomposition of metal predecessors like metal carbonyls such as Ni(CO)4, CO2(CO)8, and Fe(CO)5, and metal oleates is performed in reactors or autoclaves through application of high temperature and pressure.22 This technique provides products with optimal control over particle size, efficient monodispersity, and restricted size distribution, with notable crystallinity of iron oxide MNPs. The associated disadvantages of the thermal decomposition technique include the requirement of high temperature at the time of synthesis, employment of noxious organic chemicals, huge costs, and the transformation for the enhancement of biocompatibility of the synthesized MNPs including Fe3O4 NPs.23 The synthetization of various magnetic metal nanoparticles has been achieved through this method through the application of the metal carbonyl precursors Fe(CO)5, and CO2(CO)8.24 The advancements in water-soluble MNPs through the controlled size of particles have led to more efficient synthetization results.24 The application of watersoluble MNPs at 245 1C developed through a one-pot preparation technique as contrast agents in magnetic resonance imaging (MRI) for the detection of cancer tissues has proven to be very effective.25

9.2.2

Sol–Gel Synthesis

This technique of synthetization of MNPs includes the introduction of a hydroxyl group (–OH) into an organic compound also termed as ‘hydroxylation’,

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Figure 9.4

Synthesis of MNPs.21

and condensation of reactants to be employed for acquiring the sol of NPs. The process of condensation leads to the development of a three-dimensional network metal oxide gel. The developed gel is transformed to the crystalline state through heating, in which the structure and performance efficacy can be managed. The control over these parameters is obtained through optimal management of conditions related to hydroxylation and condensation including temperature and pH of the channel along with the level of salt precursors.26 This method of synthetization has proved to be very effective, through providing the benefits of uniform mixing, lower processing temperature, and higher reactivity. However, the issue of coagulation of the synthesized MNPs after the treatment needs to be addressed.

9.2.3

Hydrothermal Synthesis

Hydrothermal synthesis of MNPs includes the use of an aqueous medium at high temperature and pressure conditions to promote the rate of nucleation and addition of novel NPs for the development of smaller sized particles.26 The process of synthetization with hydrothermal conditions can be achieved through hydrolysis, oxidation and even neutralization of hybrid metal hydroxides.

9.2.4

Coprecipitation Technique

This technique of synthetization for the development of iron oxides with possible structures of g-Fe2O3 or Fe3O4 depends upon the occurrence of chemical reactions in the aqueous solution, in which the processes of

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nucleation and development of iron hydroxide nuclei occur in coherence.27 The primary benefit with the application of a coprecipitation technique is the availability of magnetic iron oxide nanoparticles on a mass scale. The maintenance of optimal conditions is required which results in a wider size distribution of MNPs. The first successfully implemented synthetization of iron oxide MNPs was performed through coprecipitation of FeCl2, and FeCl3 with alkaline conditions by Massart and Cabuil.21

9.2.5

Microemulsion-based Synthesis

Microemulsion-based synthesis incorporates the previously discussed reactions like coprecipitation or decreasing the microemulsions for management of the size of the developed MNPs. The synthetization of monodispersing MNPs with various structures and sizes through a microemulsion-based methodology. The primary issue associated with this technique is the broad rate of organic solvent utilization at the time of the production process with comparatively smaller production.

9.2.6

Flow Injection Synthesis

This method of synthetization is very efficient for application in MNPs with narrow size distribution. This method employs application of laminar flow through a capillary reactor for proper mixing of the chemical reagents. The synthetization of magnetic Fe3O4 NPs with narrow size distribution ranging between 2 and 7 nm has been effectively done through flow injection methodology.28 The benefits of flow injection synthesis include homogenous mixing and optimal reproducibility owing to laminar plug-flow conditions.

9.2.7

Aerosol/Vapor-phase-based Synthesis

These techniques include a spray approach and laser pyrolysis which have proven to be quite optimal owing to the high synthetization rate in the chemical processes.29 The spray pyrolysis technique consists of a solution composed of an organic reducing agent and ferric salts which are dispersed into a series of reactors succeeded by condensation of the aerosol solute and evaporation of solvent. The dry residues are changed to MNPs, where the preliminary size of droplets is the deciding factor for the size of NPs. The laser pyrolysis technique is an emerging methodology employed for the preparation of MNPs. The approach of laser heating a gaseous composite of iron precursor like iron pentacarbonyl is employed for reduction of the reaction time at the time of production. The reaction for synthetization is constantly kept going for a higher yield of MNPs. The implementation of the laser pyrolysis technique has proved to be efficient in the synthetization of small, narrow size distribution, and non-aggregated MNPs. The MNPs with crystal size and narrow size distribution varying between 2 and 7 nm can be effectively manufactured under suitable conditions.

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9.3 Chromatography: An Overview Chromatography can be defined as an analytical tool which supports the separation of an individual element from a mixture of multiple compounds. The basic concept of chromatography includes the movement of a sample in free phase which is termed as the ‘mobile phase’ over a fixed sample free phase referred to as the stationary phase. The passage of the sample under analysis over the mobile phase leads to interaction between the stationary and mobile phases. The elements with greater distribution ratio during the interaction between stationary and mobile phases take a longer duration of time in the stationary phase for their passage through the system.30 The technique of chromatography is a conventional analytical tool which consists of the separation of different elements, semi-volatile or volatile in nature. The differential separation of analytes occurs between a stationary phase and a mobile phase which is usually an inert gas like He, H2, or N2. The technique of chromatography has gained relevant significance in the fields of analytical chemistry, biotechnology, biomedicines, toxicologists, etc. Its use as an efficient tool of separation by chemical analysts is noteworthy. The need for constant developments in the field of separation has led to amalgamation of nanotechnology with separation science. This conjunction has provided efficient results reducing the complexities associated with the segregation of samples in any state (solid, liquid or gaseous) from mixtures of various components. The unique properties of NMs include magnetic, thermal, electrical, and optical features owing to their size. The NMs in natural and modified forms (through functionalization) have provided significant results with high efficacy through improvement in the range of detection, increased affinity toward target components, enriched magnification accuracy, and enhanced sensitivity.31 The factors affecting the classification of chromatographic separation depend upon various factors which are illustrated in Figure 9.5. Usually, the stationary phase is in the solid state, or possibly a liquid film protected by a solid support while the mobile phase is in the liquid or gaseous state. The referral of chromatographic methods is usually done through integrating the mobile phase accompanied by the stationary phase. One of the most widely and primarily used chromatographic separation techniques is gas chromatography. Gas chromatography is an efficient method of separation in which the mobile phase exists in the gaseous state for the detection of volatile organic compounds (VOCs).32 The process of gas chromatography consists of a column which acts as a passage for the mobile phase in the gaseous state, the column is either capillary or packed. The mobile phase gas (argon, nitrogen, or helium) is usually decided by the detector being used. The set-up works at a required temperature based on the volatility of the components. The samples are segregated between a stationary phase (liquid) and a mobile phase (gaseous). The primary aim in the process is the vaporization of the sample which is attained through injection of the sample in the gaseous state or maintenance of the temperature of the point of injection above the boiling point of the components.

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Figure 9.5

247

Factors affecting the classification of chromatographic separation.30

Moreover, the sample vapor is cleared through the column partially as a gas and in part disintegrated as the liquid phase. The volatile components in the gaseous state pass at a rapid speed through the column owing to their low partition coefficient in comparison to other components with higher boiling points. The movement of effluent across the detector initiates an electric signal with reference to the levels of volatile components. The levels of compounds and retention time can be quantified through the chromatogram developed by the electrical signal for distinction of compounds.30 Gas chromatography also includes injection of a sample and vaporization up to the head of the separation column, where its walls are coated with a stationary phase including silica, porous polymers, or activated carbons. However, to achieve efficient separation within a given reasonable timeframe and at high resolutions, the physical and/or chemical affinity between the sorbate and sorbent should be highly favorable.33,34 The chromatographic separation technique can also be used involving the intercommunication of stationary and mobile phases. The concept of thin layer chromatography involves a solid phased adsorbent which can possibly present selectivity segregated owing to the differences in the elution rate. Thus, the firmness and weakness of the adsorbent vary for all mixtures. The method of paper chromatography consists of components to be segregated being passed through a stationary phase (optimal quality paper) and a liquid mobile phase. This causes the upward movement of samples accompanied by the developing solution. The advantage of paper chromatography includes optimal time and materials requirement.35

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Another technique of chromatographic separation is based upon the principles incorporating the processes of, (a) absorption, (b) partition, and (c) ion exchange/size exclusion. The process of absorption chromatography involves segregation of solutes from a solid stationary phase depending on the absorption ability. Whereas the technique of partition chromatography involves segregation based on the contrast between the partition coefficient of the stationary and mobile phase, being a thin liquid film covered on a solid surface. Moreover, the ionic solutes are attached to the stationary phase where a cationic or anionic functional group is linked to a solid support. These ions are segregated through electrostatic forces in ionexchange chromatography. It can be inferred that these chromatographic methods have proven to be very effective in separation, isolation, and purification of chemicals. The application of chromatography in the analytical processes has gained huge momentum in recent times. The previous studies on chromatographic techniques have also faced analytical issues in chromatographic instruments. The chromatographic techniques, specifically liquid chromatography (LC) and gas chromatography (GC) systems, are being employed for the smallest ions to the largest molecules. The chromatographic techniques have proved to be efficient analytical tools in a variety of fields including food, environmental, toxicological, biological, industrial, clinical, forensic, agricultural, and organic synthesis.36 The necessity for reduction in analysis time, cost incurred in the development of green analytical methods along with the need for enhancement of resolution and sensitivity of the analysis have increased at a rapid pace. The development of efficient separation techniques is associated with physical, chemical, and technical issues in the fabrication of columns. The advancements in chromatographic developments are also associated with the development of novel varieties of columns along with improving the existing column reliability, efficiency, and reproducibility. The analytical column is the smallest component of the chromatographic system, but it is the most vital of the system considering that the separation of the analyte mixture occurs in it. The stationary phase materials are the vehicles that cause separation, which therefore make the properties of the column packing materials vital for conduction of optimum separations. The column efficiency, capacity and selectivity are affected by the nature of the packing material. The employment of functionalized MNPs in separation science initiated with the evolution of nanotechnology, in spite of suggestions for their use in analytical chemistry since 1982.37 The use of NMs in chromatography and separation science has grown and is expected to be widespread in the future. The development of analytical sciences has proven to be supportive for regulatory authorities who require detection at the nanoscale. This conjunction has been very successful in medical, biological, and pharmaceutical industries. The separation and identification of various components in environmental and biological samples at the nanogram level have emerged as a

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challenge in chromatography areas. The researchers have increased their nanoscale analysis for dealing with this challenge. The nanoscale efficiency of chromatographic techniques has also proved to be an optimal option for such variants of analysis with the primary objective of optimization of design methodologies for nano chromatography. The nanocolumn is useful for mass sensitivity in comparison to traditional columns with multiple benefits of managing low sample volumes at low flow rates. Various other factors such as low requirement of solvent and additives for elution, and easier separation control temperature due to the faster and efficient heat transfer in nanophases make this technology very adaptable and easy to use. In the nano chromatographic techniques, the size of (nanoscale) the sorbent particles contributes toward the very high separation efficiency and high capacities (in stationary phases), as compared to micro chromatography. These techniques also result in an increased pressure drop through the column. This pressure drop is inversely proportional to the square of the diameter of the sorbent particle. Moreover, an additional issue is encountered while fabricating the nano dimensions of these sorbent particles, which is the extra-column band broadening. Here the size of the column is reduced and in turn the peak volume decreases sharply. However, the separation efficiencies achieved through these nanocolumns may decrease rapidly due to the introduction of extra-column void volume. It is important to note here that a problem can also be faced with establishment of the terminology of nano chromatographic systems. For example, nanocolumns can be confused with capillary tubes or nanoscale capillary columns. Since nano chromatography is the latest and best available method of chromatographic miniaturization, it is prudent that nano chromatographic techniques might have huge potential for application in research and development in the future. The small detection sizes of these separation instruments play a crucial role in research and development science. In modern times, the need of the hour is for the industrial methodologies to be sensitive enough that they can detect substances present even in small samples. Nano chromatography offers state-of-the-art designs for these low-concentration substances with exceptional detectability and absolute identification. However, a major and key limitation in the use of nano chromatographic techniques is their higher price compared to that of the conventional techniques in use. Nevertheless, the modern research and innovation in the fabrication of new equipment can overcome this limitation and result in a large-scale expansion of nano chromatography to be adapted in routine laboratory and industrial analysis. It could be concluded that innovations in nanomaterials have escalated in the recent past for chromatographic techniques and devices to be incorporated at the laboratory and industrial level. Hence, it is very much expected that very soon nanomaterials will be the critical components for chromatographic techniques and devices not only at the laboratory scale but also at the commercial level leading to more accurate and reliable analysis.31

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9.3.1

Considerations for an Effective Chromatographic Separation

The theoretical considerations which must be incorporated to establish rapid and effective separations through the technique of chromatography include the van Deemter equation. This equation while considering the thermodynamic, kinetic, and physical properties of the process devises the relation between the variance per unit length of a separation column with linear mobile phase velocity. The van Deemter equation explains the inverse proportionality relation between column efficiency and size of sorbent (eqn (9.1)). H ¼A þ

B þ Cv v

(9:1)

where  A is the eddy diffusion parameter which is related to the diameter of the packing material (dp),  is the coefficient of diffusion for eluting particles in the longitudinal direction,  C is the resistance to the mass transfer coefficient of the analyte correlated to the decrement in size of particle size (d2p). It also explains that the decrease in the size of sorbent results in a decrease in the height of the plate,  v is the linear velocity,  H is the plate height. The following eqn (9.2) illustrates the effect of the decrease in size of particle (d2p) on analysis time: ta ¼

ð1 þ kÞNh 2 dp vDm

(9:2)

where      

ta is the time required by the analyte to proceed in the column, k is the retention factor, Dm is the diffusion coefficient of the mobile phase, n is the reduced linear velocity, N is the number of theoretical plates, h is the reduced plate height.

Furthermore, the pressure required during the packing and operation of the columns can be evaluated using eqn (9.3): DP ¼

jZuL dp2

(9:3)

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251

where     

DP is the pressure drop, L is the length of the column,38,39 Z is the viscosity, j is the flow resistance factor, u is the linear velocity.

The retention factor (K) from eqn (9.1) is also referred to as the partition factor or capacity factor. It is the ratio of time spent by the solute in the stationary and mobile phases (eqn (9.4)). It also provides the relative retention information: k¼

tR  tM tM

(9:4)

where  tR is the retention time,  tM is the total retention time of an unretained compound. The retention time is the time spent by a solute in a column (both stationary and mobile phases). It depends upon the interaction between analyte and stationary phase. Stronger interaction results in a longer interaction time, and subsequently an increase in the retention time. The efficiency (N) of the operation is calculated using eqn (9.5) and (9.6): N ¼ 5.545 (tR/wH)2

(9.5)

N ¼ 16 (tR/wB)2

(9.6)

where    

N is the number of theoretical plates (N/m), tR is the retention time, wH is the peak width at half height, wB is the peak width at base.

9.3.2

Functionalized MNPs in GC

The various NMs used in chromatographic techniques include graphene, FNs single-walled carbon nanotubes (SWCNTs), and multiwalled carbon nanotubes (MWCNTs).40 The primary goal of employing graphene, metal-oxide NPs, CNTs, and FNs as the stationary phase is to increase the contact surface area with the solute. Thereby enhancing the efficiency of separation and selectivity of GC and LC columns. Some of the remarkable properties of CNTs are, (a) strong affinity toward hydrophobic molecules, (b) thermal and mechanical stability, (c) ability to establish p–p electrostatic interactions, and (d) large surface area for the adsorption of analytes.41 Graphene which is a vital building block of carbon-based NMs with a honeycomb structure

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possesses optimal thermal, electrical, mechanical, and optical properties.42 The p–p electrostatic stacking property of graphene has created huge scope for its use as a sorbent material.43 The unique characteristics possessed by graphene has led to its employment as an adsorbent in various sample preparation techniques. The use of graphene for the magnetic extraction of sulfonamide from water samples has also been done.44 The technique for the fabrication of graphene is comparatively simple compared to that of CNTs.45 Moreover, various studies have employed the use of CNTs in the chromatographic techniques for the segregation of various constituents. An example being, the purification of MWCNTs (30 cm0.3 mm) as a stationary phase in gas chromatography used in the separation of halogenated hydrocarbons, C1–C4 alcohols, esters, and ketones.46 In the study, the CNT column showed a better retention time and a greater number of symmetrical peaks, as compared to graphitized columns. The reason behind this might be the presence of cavities and hydrophilic groups on CNTs. These hydrophilic groups slow down the diffusion rate of solutes and decrease the theoretical plate number. Few other studies have also reported the successful separation of argon, carbon dioxide, hydrogen, C1–C6 hydrocarbon, C1–C3 alcohols, and polycyclic aromatic hydrocarbons (PAHs), making use of SWCNTs and MWCNTs as a stationary phase in GC. Purified CNTs were also found to be useful during the separation of isomers of primary and secondary alcohol, whereas contrary results were obtained for the separation of the same compounds by f-CNTs. Compounds like f-CNTs and CNTs in combination with ionic liquids (ILs) have gained a lot of significance in the separation processes recently. An advantage being that the immobilization of ILs on the inner wall of the SWCNT capillary column provides a higher surface area for the analytes. Despite their remarkable properties, pure CNTs have poor dispersion rates in most of the solvents and also form aggregates. Hence, the functionalization of CNTs is very essential to impart better selectivity and prevent the formation of aggregates. Moreover, the amine-f-CNTs have been used to selectively separate the alcohols with a good degree of correlation between retention time and the physico-chemical qualities of the analyte. Oxidized CNTs with a carboxylic group on their surface have also been found to be very helpful in enhancing the retention and separation of alcohols to a great extent.

9.3.3

Liquid Chromatography (LC)

Various NMs have found application in the field of liquid chromatography separation techniques. The monolithic columns which are utilized in LC due to their high porosity cause higher permeability, and hence result in a lower pressure drop, which thereby makes them comparatively more efficient in comparison to the traditional columns. NM altered polymer and silica-based monolithic columns have also attracted huge momentum as stationary phases with a large specific surface area, high porosity, and wide surface chemistry enhancing chromatographic separations.47

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Monolithic columns have been used by many researchers around the world. In a study the monolithic column was employed through utilization of ethylene glycol dimethacrylate as the cross-linker, 2-propanol, vinylbenzyl chloride as the monomer, and SWCNTs as the porogen with increased retention of small neutral molecules owing to hydrophobic interaction between the analyte and SWCNTs.48 It was found in the study that the addition of SWCNTs in silica LC column causes segregation of 12 peptides in 8 min of height in equivalence to the theoretical plate (HETP) value of 7.10 mm, which is not viable through C18 column49 with a HETP value of 11.5 mm. A composite mixture of phenols and ketones was segregated through incorporation of MWCNTs in a benzyl methacrylate monolithic column.36 The separation of solutes is caused by the enhancement in the resolution of the efficacy of columns with the incorporation of MWCNTs in the monolithic column. The predominant supporting material in traditional HPLC has been silica. The segregation of toluene, benzene, and p-xylene has been efficiently done in a column of MWCNT-grafted silica microspheres with polybutadiene having a retention factor in the range of 2–5 and retention time of 6–13 min.50 The role of herbicides for increasing the crop yield toward a sufficient food supply across the globe also has associated hazards. The toxic nature of atrazine and simazine needs to be assessed. Various research studies have previously highlighted their quantification through HPLC, HPLC–MS, GC, and GC–MS.51,52 The HPLC–MS technique is common owing to its ability of higher characterization. The coherent quantification of 10 triazine herbicides in rice samples through high-resolution and optimal mass accuracy hybrid linear ion trap (Orbitrap) mass spectrometer within 12 min has also been done in a study by Mau et al.53 The technique was validated with reference to limits of detection quantification with a correlation coefficient 40.9975. The extraction of selected herbicides has also been done through a new solid-phase membrane tip extraction employing MWCNTs as the adsorbent. This method proved to be facile, feasible, economic and improved results were also obtained in comparison to the commercially available SPE-MIP method for triazine extraction with a relative standard deviation of 6–8%, recovery of 95–101%, linearity in the range of 1–100 g L1, and limit of detection (LOD) of 0.2–0.5 g L1, respectively.54 The large surface area and optimal adsorption properties have increased the use of carbon nanostructure materials as sorbents in SPE and magnetic SPE for the segregation of organic compounds.55 The application of porous graphitized carbon in HPLC and GC as effective stationary phases for chromatographic segregations was also previously reported.56 The separation of nucleosides, dihydroxyl benzenes, amino acids and isomeric alkylbenzenes has been reported through a GO NPs/silica hybrid as the stationary phase in reversed-phase LC and hydrophilic interaction LC.57 The high surface-area-to-volume ratios have also led to an increased importance of NPs in the field of capillary electrochromatography (CEC), HPLC, and GC for the segregation of both low and high molecular weight compounds. These are employed as the stationary phase in CEC, GC, and LC and

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as the pseudo stationary phase in micellar electrokinetic chromatography.58 The use of poly(diallyldimethylammonium chloride)-GNP-modified glass chip for optimal segregation of aminophenols has also been done.59 The modified GNPs were also applied for the CE separation of proteins and DNA fragments with high resolution, good separation efficiency and repeatability, longer shelf life, and easy automation. The applications of GNPs in HPLC are much less than in CE and CEC. One of the studies reported the application of gold microparticles modified with n-octadecanethiol in capillary LC column for the separation of organic compounds. Kobayashi et al. demonstrated the separation of phenanthrene and anthracene by using a column of thiol-modified gold-coated poly (methyl methacrylate)-based stationary phases. Modified GNPs were also used for the separation of chiral analytes, dansyl-D and L-norvaline, on an HPLC column.59

9.4 Application of Functionalized MNPs in Separation Techniques 9.4.1

Magnetic Solid Phase Extraction (MSPE)

The unique properties of MNPs have resulted in their application in multidisciplinary fields and sample preparation is one of them. The addition of functionalized MNPs to sample matrices for extraction and preconcentration of samples is used in magnetic SPE (MSPE). The incubation and centrifugation of samples until the analytes are adsorbed by MNPs are performed for a known amount of time. The ease of isolating the functionalized MNPs through the application of an external magnetic field from the solution is noteworthy. Suitable solutions are used for desorption of analytes and the isolated MNPs can be easily reused. The rapid process of separation of suspended MNPs from the samples through the application of an external magnetic field is a major benefit. The magnetic SPE sorbents for distribution of magnetism contain Fe3O4 as the primary material. A variety of NPs have been suggested for the extraction of materials in MSPE. Studies have shown that the extraction and preconcentration of non-metabolized PAHs from urine samples can be achieved through application of super paramagnetic Fe3O4 diphenyl NPs with a mean diameter of 200 nm.60 The preconcentration of PAHs from environmental samples for gas chromatography–mass spectrometry (GC–MS) analysis was done through the application of a magnetic SPE sorbent made of a carbon– ferromagnetic nanocomposite designed with a hydrophobic sublayer and a hydrophilic surface.9 The dual functionality characteristic provides the sorbent with the ability for optimal extraction of PAHs in suitable coherence with the sample matrix. The use of hexane as the desorption solvent under sonication without the requisite of sample shaking. The resultant enrichment factors were 35–133 times for the targeted analytes. The core shell structured carbonencapsulated MNPs (CMNPs) had been employed for preconcentration of bisphenol A, dipropyl phthalate, diethyl phthalate, dibutyl phthalate, sulfonamide, quinolones antibiotics organic compounds, dioctyl phthalate, and

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tetracyclines from water samples with quantification through HPLC with a photodiode array detector (HPLC–PDA) and HPLC with fluorescence detector (HPLC–FLD).61 The interaction between the sorbent and analytes occurred through a hydrophobic interaction, p–p stacking interaction, and hydrogen bonding. The removal ability of CMNPs depends greatly on the levels of oxygen-containing species and graphitized carbon on the carbon shell.61 The temperature maintained during the sorbent preparation in turn controls the sorbent content of oxygen-containing species and graphitization, which subsequently regulates the extent of sorbent hydrophobicity. Studies have suggested CMNP preparation at 850 1C followed by high graphitization (80%) has been proven to have a strong adsorption affinity toward highly polar and moderately polar analytes. Moreover, the reasonable extraction of nonpolar and moderately nonpolar compounds was also achieved with CMNPs prepared at 300–500 1C along with the graphitization efficiency of carbon shell lower than 50%. These prepared CMNPs sorbents had abundant oxygen-containing species (80%) on its surface at a heating temperature of 200 1C. It also favored the extraction of quinolones antibiotics over various other analytes present. In another study, a magnetic carbon nanomaterial for Fe3O4 enclosure hydroxylated multiwalled carbon nanotubes (Fe3O4-EC-MWCNTs-OH) was utilized for magnetic SPE of aconitines (aconitine, hypaconitine, and mesaconitine) extracted from human serum samples and followed by their quantitation by HPLC with a diode array detector (HPLC–DAD).62 The results showed that under the optimized experimental conditions, the achieved recoveries of spiked serum samples were between 98.0% and 103.0%.

9.4.1.1

Magnetic Solid-phase Extraction: Environmental Samples

The application of MSPE for environmental samples through employment of MNPs has gained momentum. The development of MNPs for the preconcentration of atrazine from water samples has also been attempted. The results obtained from the analytical response of the prepared NPs were found to be linear over a range of 0.1–50 mg L1 with a limit of detection (LOD) of 0.033 mg L1 through the application of high-performance liquid chromatography under optimal conditions. The enrichment factor obtained was 268 for atrazine in the study.63 The magnetic Fe3O4/dithiocarbamate/SiO2 NPs were used for the effective removal of Cu21 and Ni21 ions from solutions in a study by Dai and colleagues.64 The affinity of prepared MNPs toward target ions was seen in the output results. The binding capacity values for Cu21 and Ni21 ions were obtained as 230.49 and 235.23 mg g1, respectively.

9.4.1.2

Magnetic Solid-phase Extraction for Food and Beverage Samples

MNPs have been used in the sample preparation for the analysis of food and beverage samples by Li and colleagues.65 The magnetic Fe3O4 NPs were

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coated with a polyvinyl alcohol layer and synthetized for selective extraction of aminoglycoside antibiotics including dihydrostreptomycin, streptomycin, and kanamycin in honey samples. The prepared MNPs were used to extract the aminoglycoside antibiotics in a very small time of 30 s. The detection limit values for dihydrostreptomycin, streptomycin, and kanamycin were found to be 0.913, 0.993, and 1.23 mg kg1, respectively.

9.4.1.3

Magnetic Solid-phase Extraction for Biological Samples

The application of MSPE in biological samples including blood plasma, urine, etc. has gained momentum as a use for MNPs. A study based on the modification of magnetic Fe3O4 NPs with carbon was conducted by Heidari and colleagues66 to extract pharmaceutical compounds (besylate, amlodipine, losartan, and carvedilol) from plasma samples. The increased implementation of functionalized MNPs in MSPE processes, owing to their unique properties including selectivity in the rate of extraction from complex matrices including food, beverage, biological, and environmental samples. The studies discussed above for sample preparation applications through utilization of MNPs have gained momentum during recent decades. MNPs possess unique properties including huge surface area, small size, and active surface which can be transformed accordingly (superparamagnetic, low toxicity, etc.). The properties possessed by MNPs have led to their selection in SPE processes. The shortcomings of traditional techniques have been overtaken by MNPs owing to their quick dispersion in the sample solutions thereby enhancing and quickening the rate of extraction of the targets. The optimal efficiency in extraction of the target compound/s through MNPs has also terminated the effects of the matrix associated with traditional methods.

9.5 Conclusion The present chapter discusses the usefulness of various nanomaterials that help in improving the chemical stability, enrichment capability, offer a large window of selectivity, enhanced efficiency of separation, and the availability of suitable derivatization and detection systems in various chromatographic methods in detail. In modern times, carbon-based nanomaterials are being comprehensively used primarily because of their unique size, shape, and hydrophobic surface. These properties play a critically important role in the fields of optical, electrochemical, and adsorption processes. Moreover, the hydrophobic surface of these nanomaterials helps in accelerating the optimal mass transfer and it is also helpful in creating the interactions between the analytes and nanomaterials. Besides, owing to their special properties these nanomaterials can also be used in different sample preparation technologies such as sorbent or SPE and SPME fibers, demonstrating their excellent extraction efficiencies. It can also be seen that when compared with graphitized or activated carbon, these carbon nanomaterials have provided exceptional

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results in terms of retention time, selectivity, and resolution. In addition to their use in separation processes, these nanomaterials have also been used in designing the pumping system in capillary LC, which has been proved to be very useful in terms of the stability and reproducibility of the results. It is expected that in the coming years the novel techniques and technological advancements will enhance the use of nanomaterials in separation techniques. It can be said that, in the near future, the development of novel stationary phases of functionalized nanomaterials containing selective and appropriate chemical moieties will lead to increasingly interesting analytical applications. These applications will help in opening various doors of opportunities for these nanomaterials to develop into a mature and independent field and promote our existing scientific knowledge and resources.

References 1. S. Shukla, R. Khan and C. M. Hussain, Nanoremediation, in The Handbook of Environmental Remediation, Royal Society of Chemistry, 2020, ch. 16, pp. 443–467. 2. R. Khan, A. Saxena and S. Shukla, Evaluation of heavy metal pollution for River Gomti, in parts of Ganga Alluvial Plain, India, SN Appl. Sci., 2020, 2(8), 1451. 3. S. Shukla and A. Saxena, Sources and leaching of nitrate contamination in groundwater, Curr. Sci., 2020, 118(6), 883–891. 4. S. Shukla and A. Saxena, Groundwater quality and associated human health risk assessment in parts of Raebareli district, Uttar Pradesh, India, Groundwater Sustainable Dev., 2020, 100366. 5. S. Gul, S. B. Khan, I. U. Rehman, M. A. Khan and M. I. Khan, A Comprehensive Review of Magnetic Nanomaterials Modern Day Theranostics, Front Mater., 2019, 6(July), 1–15. 6. E. Guihen, Nanoparticles in modern separation science, TrAC, Trends Anal. Chem., 2013, 46, 1–14. 7. C. R. Martin, Membrane-based synthesis of nanomaterials, Chem. Mater., 1996, 8, 1739–1746. 8. F. D. Guerra, G. D. Smith, F. Alexis and D. C. Whitehead, A Survey of VOC Emissions from Rendering Plants, Aerosol Air Qual. Res., 2017, 17(1), 209–217. 9. R. N. Rao and S. S. Albaseer, Nanomaterials in chromatographic sample preparations [Internet], Nanomaterials in Chromatography: Current Trends in Chromatographic Research Technology and Techniques, Elsevier Inc., 2018, vol. 7, pp. 201–231. Available from: http://dx.doi.org/10.1016/B9780-12-812792-6/00007-8. 10. Q. A. Pankhurst, J. Connolly, S. K. Jones and J. Dobson, Applications of magnetic nanoparticles in biomedicine, J. Phys. D Appl. Phys., 2003, 36(13), R167–R181. 11. Z. Li, L. Wei, M. Gao and H. Lei, One-pot reaction to synthesize biocompatible magnetite nanoparticles, Adv. Mater., 2005, 17(8), 1001–1005.

258

Chapter 9

12. J. Dobson, Magnetic nanoparticles for drug delivery, Drug Dev. Res., 2006, 67, 55–60. 13. M. Ferrari, Cancer nanotechnology: Opportunities and challenges, Nat. Rev. Cancer, 2005, 5, 161–171. 14. J. S. Weinstein, C. G. Varallyay, E. Dosa, S. Gahramanov, B. Hamilton and W. D. Rooney, et al., Superparamagnetic iron oxide nanoparticles: Diagnostic magnetic resonance imaging and potential therapeutic applications in neurooncology and central nervous system inflammatory pathologies, a review, J. Cereb. Blood Flow Metab., 2010, 30, 15–35. 15. S. A. Wickline, A. M. Neubauer, P. M. Winter, S. D. Caruthers and G. M. Lanza, Molecular imaging and therapy of atherosclerosis with targeted nanoparticles, J. Magn. Reson. Imaging, 2007, 25, 667–680. 16. F. Herranz and J. Pellico, Covalent Functionalization of Magnetic Nanoparticles for Biomedical Imaging, 2012, https://spie.org/news/4473covalent-functionalization-of-magnetic-nanoparticles-for-biomedicalimaging?SSO=1. 17. R. Subbiah, M. Veerapandian and S. K. Yun, Nanoparticles: Functionalization and Multifunctional Applications in Biomedical Sciences, Curr. Med. Chem., 2011, 17(36), 4559–4577. ´rvo ¨lgyi, Z. Juvancz and A. Dallos, 18. G. Tolnai, G. Alexander, Z. Ho Stabilization of gas chromatographic stationary phases with nanosized particles, Chromatographia, 2001, 53(1–2), 69–75. 19. B. Hu, M. He and B. Chen, Magnetic nanoparticle sorbents, Solid-Phase Extraction, Elsevier, 2019, pp. 235–284. 20. J. Kudr, Y. Haddad, L. Richtera, Z. Heger, M. Cernak and V. Adam, et al., Magnetic nanoparticles: From design and synthesis to real world applications, Nanomaterials, 2017, 7(9), 243. ¨yu ¨ktiryaki, I. Dolak and C. M. Hussain, The use of mag21. R. Keçili, S. Bu netic nanoparticles in sample preparation devices and tools, in Handbook of Nanomaterials in Analytical Chemistry: Modern Trends in Analysis, Elsevier, 2019, pp. 75–95. 22. L. Gao, J. Wu, S. Lyle, K. Zehr, L. Cao and D. Gao, Magnetite nanoparticle-linked immunosorbent assay, J. Phys. Chem. C, 2008, 112(44), 17357–17361. 23. S. Behrens, Preparation of functional magnetic nanocomposites and hybrid materials: Recent progress and future directions, Nanoscale, 2011, 3, 877–892. 24. F. X. Redl, K. S. Cho, C. B. Murray and S. O’Brien, Three-dimensional binary superlattices of magnetic nanocrystals and semiconductor quantum dots, Nature, 2003, 423(6943), 968–971. 25. F. Hu, L. Wei, Z. Zhou, Y. Ran, Z. Li and M. Gao, Preparation of biocompatible magnetite nanocrystals for in vivo magnetic resonance detection of cancer, Adv. Mater., 2006, 18(19), 2553–2556. 26. F. Chen, Q. Gao, G. Hong and J. Ni, Synthesis and characterization of magnetite dodecahedron nanostructure by hydrothermal method, J. Magn. Magn. Mater., 2008 Jun, 320(11), 1775–1780.

Use of Functionalized Magnetic Nanoparticles in Modern Separation Techniques

259

27. L. H. Reddy, J. L. Arias, J. Nicolas and P. Couvreur, Magnetic nanoparticles: Design and characterization, toxicity and biocompatibility, pharmaceutical and biomedical applications, Chem. Rev., 2012, 112, 5818–5878. 28. G. Salazar-Alvarez, M. Muhammed and A. A. Zagorodni, Novel flow injection synthesis of iron oxide nanoparticles with narrow size distribution, Chem. Eng. Sci., 2006 Jul, 61(14), 4625–4633. 29. R. Strobel and S. E. Pratsinis, Direct synthesis of maghemite, magnetite and wustite nanoparticles by flame spray pyrolysis, Adv. Powder Technol., 2009, 20(2), 190–194. 30. B. S. Hameed, C. S. Bhatt, B. Nagaraj and A. K. Suresh, Chromatography as an efficient technique for the separation of diversified nanoparticles, Nanomaterials in Chromatography: Current Trends in Chromatographic Research Technology and Techniques, Elsevier Inc., 2018, pp. 503–518. Available from: http://dx.doi.org/10.1016/B978-0-12-812792-6/00019-4. 31. C. M. Hussain, Nanochromatography—Concluding Account, Nanomaterials in Chromatography, Elsevier Inc., 2018, ch. 20, pp. 519–523. Available from: http://dx.doi.org/10.1016/B978-0-12-812792-6/00020-0. 32. M. R. Siddiqui, Z. A. AlOthman and N. Rahman, Analytical techniques in pharmaceutical analysis: A review, Arabian J. Chem., Elsevier B.V., 2017, vol. 10, pp. S1409–S1421. 33. C. Saridara and S. Mitra, Chromatography on self-assembled carbon nanotubes, Anal. Chem., 2005, 77(21), 7094–7097. 34. C. I. L. Justino, T. A. P. Rocha-santos and A. C. Duarte, Nanomaterials in Lab-on-Chip Chromatography, Nanomaterials in Chromatography, Elsevier Inc., 2018, ch. 14, pp. 387–400. Available from: http://dx.doi.org/ 10.1016/B978-0-12-812792-6/00014-5. 35. F. Ramezani, Protein Bands Detection by Nanoparticles after Paper Chromatography, Int. J. Nanosci. Nanotechnol., 2012, 8(3), 181–184. 36. A. Aqel, Using of nanomaterials to enhance the separation efficiency of monolithic columns, Nanomaterials in Chromatography: Current Trends in Chromatographic Research Technology and Techniques, Elsevier Inc., 2018, pp. 299–322. Available from: http://dx.doi.org/10.1016/B978-0-12812792-6/00010-8. 37. T. S. Stevens and M. A. Langhorst, Agglomerated Pellicular AnionExchange Columns for Ion Chromatography, Anal. Chem., 1982, 54(6), 950–953. 38. Organo-silica nano-particles used in ultrahigh-pressure liquid chromatography – Analyst (RSC Publishing), [cited 2020 Sep 1], Available from: https://pubs.rsc.org/ko/content/articlelanding/2002/an/b203236h# !divAbstract. ´n, Ultrahigh-pressure liquid 39. J. A. Anspach, T. D. Maloney and L. A. Colo chromatography using a 1-mm id column packed with 1.5-mm porous particles, J. Sep. Sci., 2007, 30(8), 1207–1213. ´rcel, S. Ca ´rdenas and B. M. Simonet, Role of carbon nanotubes 40. M. Valca in analytical science [Internet], Anal. Chem., 2007, 79, 4788–4797.

260

Chapter 9

´ndez-Borges, L. M. Ravelo-Pe ´rez and 41. M. Asensio-Ramos, J. Herna ´ ´guez-Delgado, M. A. Rodrı Simultaneous determination of seven pesticides in waters using multi-walled carbon nanotube SPE and NACE, Electrophoresis, 2008, 29(21), 4412–4421. 42. W. Yang, K. R. Ratinac, S. R. Ringer, P. Thordarson, J. J. Gooding and F. Braet, Carbon nanomaterials in biosensors: Should you use nanotubes or graphene [Internet], Angew. Chem., Int. Ed., 2010, 49, 2114–2138. 43. Y. B. Luo, Z. G. Shi, Q. Gao and Y. Q. Feng, Magnetic retrieval of graphene: Extraction of sulfonamide antibiotics from environmental water samples, J. Chromatogr. A, 2011, 1218(10), 1353–1358. 44. J. Ding, Q. Gao, X. S. Li, W. Huang, Z. G. Shi and Y. Q. Feng, Magnetic solid-phase extraction based on magnetic carbon nanotube for the determination of estrogens in milk, J. Sep. Sci., 2011, 34(18), 2498–2504. 45. W. L. Zhang and H. J. Choi, Silica-graphene oxide hybrid composite particles and their electroresponsive characteristics, Langmuir, 2012, 28(17), 7055–7062. 46. Q. Li and D. Yuan, Evaluation of multi-walled carbon nanotubes as gas chromatographic column packing, J. Chromatogr. A, 2003, 1003(1–2), 203–209. 47. S. Tong, S. Liu, H. Wang and Q. Jia, Recent advances of polymer monolithic columns functionalized with micro/nanomaterials: Synthesis and application [Internet], Chromatographia, 2014, 77, 5–14. ´th, et al., 48. Y. Li, Y. Chen, R. Xiang, D. Ciuparu, L. D. Pfefferle and C. Horva Incorporation of single-wall carbon nanotubes into an organic polymer monolithic stationary phase for m-HPLC and capillary electrochromatography, Anal. Chem., 2005, 77(5), 1398–1406. ´, R. Aljhani, T. Gharbi and Y. C. Guillaume, Incorporation of 49. C. Andre carbon nanotubes in a silica HPLC column to enhance the chromatographic separation of peptides: Theoretical and practical aspects, J. Sep. Sci., 2011, 34(11), 1221–1227. 50. A. Aqel, K. Yusuf, Z. A. Al-Othman, A. Y. Badjah-Hadj-Ahmed and A. A. Alwarthan, Effect of multi-walled carbon nanotubes incorporation into benzyl methacrylate monolithic columns in capillary liquid chromatography, Analyst, 2012, 137(18), 4309–4317. 51. J. Cheng, M. Liu, X. Zhang, L. Ding, Y. Yu and X. Wang, et al., Determination of triazine herbicides in sheep liver by microwave-assisted extraction and high performance liquid chromatography, Anal. Chim. Acta, 2007, 590(1), 34–39. 52. V. W.-H. Tsang, N.-Y. Lei and M. H.-W. Lam, Determination of Irgarol1051 and its related s-triazine species in coastal sediments and mussel tissues by HPLC–ESI-MS/MS, Mar. Pollut. Bull., 2009, 58(10), 1462–1471. 53. R.-X. Mou, M.-X. Chen, Z.-Y. Cao and Z.-W. Zhu, Simultaneous determination of triazine herbicides in rice by high-performance liquid chromatography coupled with high resolution and high mass accuracy hybrid linear ion trap-orbitrap mass spectrometry, Anal. Chim. Acta, 2011, 706(1), 149–156.

Use of Functionalized Magnetic Nanoparticles in Modern Separation Techniques

261

54. H. H. See, M. Marsin Sanagi, W. A. W. Ibrahim and A. A. Naim, Determination of triazine herbicides using membrane-protected carbon nanotubes solid phase membrane tip extraction prior to micro-liquid chromatography, J. Chromatogr. A, 2010, 1217(11), 1767–1772. ´rez, A. V. Herrera-Herrera, J. Herna ´ndez-Borges and 55. L. M. Ravelo-Pe ´. Rodrı´guez-Delgado, Carbon nanotubes: Solid-phase extraction M. A [Internet], J. Chromatogr. A, 2010, 1217, 2618–2641. 56. J. H. Knox, B. Kaur and G. R. Millward, Structure and performance of porous graphitic carbon in liquid chromatography, J. Chromatogr. A, 1986, 352(C), 3–25. 57. S. Choudhury, E. Duffy, D. Connolly, B. Paull and B. White, Graphene oxide nanoparticles and their influence on chromatographic separation using polymeric high internal phase emulsions, Separations, 2017, 4(1), 5. 58. C. Nilsson and S. Nilsson, Nanoparticle-based pseudostationary phases in capillary electrochromatography [Internet], Electrophoresis, 2006, 27, 76–83. 59. M. Pumera, J. Wang, E. Grushka and R. Polsky, Gold nanoparticleenhanced microchip capillary electrophoresis, Anal. Chem., 2001, 73(22), 5625–5628. 60. F. Bianchi, V. Chiesi, F. Casoli, P. Luches, L. Nasi and M. Careri, et al., Magnetic solid-phase extraction based on diphenyl functionalization of Fe 3O 4 magnetic nanoparticles for the determination of polycyclic aromatic hydrocarbons in urine samples, J Chromatogr. A, 2012, 1231, 8–15. 61. H. Niu, Y. Wang, X. Zhang, Z. Meng and Y. Cai, Easy synthesis of surfacetunable carbon-encapsulated magnetic nanoparticles: Adsorbents for selective isolation and preconcentration of organic pollutants, ACS Appl. Mater. Interfaces, 2012, 4(1), 286–295. 62. H.-F. Zhang and Y.-P. Shi, Preparation of Fe3O4 nanoparticle enclosure hydroxylated multi-walled carbon nanotubes for the determination of aconitines in human serum samples, Anal Chim Acta, 2012, 724, 54–60. 63. S. A. Haeri and S. Abbasi, New strategy for the biosorption of atrazine after magnetic solid-phase extraction from water followed by highperformance liquid chromatography analysis, J. Sep. Sci., 2016, 39(14), 2839–2845. 64. Y. Dai, L. Niu, J. Zou, T. Chen, H. Liu and Y. Zhou, Preparation of core-shell magnetic Fe3O4@ SiO2-dithiocarbamate nanoparticle and its application for the Ni21, Cu21 removal, Chin. Chem. Lett., 2018, 29, 887–891. 65. D. Li, T. Li, L. Wang and S. Ji, A polyvinyl alcohol-coated core-shell magnetic nanoparticle for the extraction of aminoglycoside antibiotics residues from honey samples, J. Chromatogr. A, 2018, 1581–1582, 1–7. 66. H. Heidari and B. Limouei-Khosrowshahi, Magnetic solid phase extraction with carbon-coated Fe3O4 nanoparticles coupled to HPLC-UV for the simultaneous determination of losartan, carvedilol, and amlodipine besylate in plasma samples, J. Chromatogr. B, 2019, 1114–1115, 24–30.

CHAPTER 10

Chromatographic Applications of Functionalized Magnetic Nanoparticles ¨ STEM KEÇILI,a I_ BRAHIM DOLAK,b GURBET CANPOLATc RU AND CHAUDHERY MUSTANSAR HUSSAIN*d a

Anadolu University, Yunus Emre Vocational School of Health Services, 26470 Eskis- ehir, Turkey; b Dicle University, Vocational School of Technical Sciences, 21280 Diyarbakır, Turkey; c Siirt University, Department of Chemistry, 56100, Siirt, Turkey; d New Jersey Institute of Technology, Department of Chemistry and Environmental Science, Newark N J 07102, USA *Email: [email protected]

10.1 Introduction Functionalized magnetic nanoparticles (MNPs) are nanoscale in size and exhibit a magnetic feature. Thus, they can effectively be manipulated by using external magnetic field stimulation.1 Functionalized MNPs have magnetic elements including iron, cobalt, nickel and their oxides such as maghemite, magnetite, and cobalt ferrite. Although a number of pure phases of iron oxide are naturally available, the most widely used MNPs are Fe3O4 and g-Fe2O3. However, they display different physico-chemical features because of the difference in their iron oxidation states. The mostly studied one is Fe3O4, also called ‘‘magnetite’’, which is a ferromagnetic black colored iron oxide of Fe(II) and Fe(III). The reason for the magnetite being the preferred type is that the Fe21 state is available with the potential of acting as an electron donor.2 Analytical Applications of Functionalized Magnetic Nanoparticles Edited by Chaudhery Mustansar Hussain r The Royal Society of Chemistry 2021 Published by the Royal Society of Chemistry, www.rsc.org

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Functionalized MNPs have received great interest from scientists from different fields of science.3–21 Because these unique nanomaterials show excellent superparamagnetic properties, they can be easily removed from complex matrices by using a magnet. Therefore, there is no need to apply a filtration or centrifugation step during the separation processes. Even though MNPs have a number of advantages, they exhibit various disadvantages including their instability and agglomeration issues. In addition, naked metallic NPs display high chemical activity, and they are oxidized easily which can cause loss of magnetism of the MNPs. Therefore, the development of efficient protection techniques to stabilize the naked MNPs is crucial. For example, the surface of the NPs can be coated with carbon, silica or surfactants or polymeric materials to form a layer on the NP surface.22 In this chapter, an overview of the latest developments in the chromatographic applications of functionalized MNPs is provided. The chapter starts with the preparation techniques used for MNPs. Then, chromatographic applications of MNPs including capillary electrochromatography (CEC) and chip-based chromatography are demonstrated. Figure 10.1 shows a schematic depiction of the progress made with the various chromatographic applications of functionalized MNPs.

10.2 Preparation Techniques for MNPs There are several popular approaches for the efficient preparation of stable, monodisperse, and shape-controllable NPs with magnetic features including the thermal decomposition approach, co-precipitation approach, sol–gel process, hydrothermal technique, microemulsion technique, flow injection technique and aerosol/vapor-phase-based approaches.

10.2.1

Thermal Decomposition Approach

MNPs are effectively synthesized by applying thermal decomposition of metal precursors such as metal carbonyls (i.e., Fe(CO)5, Co2(CO)8 and

Figure 10.1

A schematic depiction of the progress of the various chromatographic applications of functionalized MNPs.

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Ni(CO)4) and metal oleates at high temperature and pressure.23 This approach yields MNPs which exhibit high monodispersity, great control in particle size and narrow size distribution of the MNPs. The major disadvantages of this technique are the requirement for extreme temperature values for the preparation of MNPs, high process costs and the use of hazardous organic chemicals, as well as the need for extra steps to improve the biocompatibility of the prepared MNPs such as magnetic Fe3O4 NPs.24 Various metal NPs were successfully prepared by using the thermal decomposition method by using Fe(CO)5 and Co2(CO)8.25,26 Magnetic metal NPs are also synthesized via decomposition of low-valent alkene or polyene metal complexes at room temperature.27,28 Lee et al. synthesized water-soluble MNPs with a narrow size distribution with controllable particle size. In a crucial research conducted by Lee et al.,29 Fe3O4 NPs were efficiently synthesized by applying high temperature. In their research, the researchers efficiently used the synthesized MNPs as contrast agents and molecular imaging probes for the magnetic resonance applications and biosensing applications, respectively. In another important research reported by Hu and co-workers,30 an effective approach of one-pot preparation of water-soluble MNPs at 245 1C was developed. In this research, the prepared MNPs were successfully employed as contrast agents for magnetic resonance imaging applications.

10.2.2

Co-precipitation Approach

This approach is an effective and straightforward route for the synthesis of magnetic iron oxides with either g-Fe2O3 or Fe3O4 structures. In this approach, the process is mainly based on the chemical reactions occurring in an aqueous solution with the process of both the nucleation and growth of iron hydroxide nuclei.31 The co-precipitation process of Fe21/Fe31 salts is conducted at ambient temperature under alkaline conditions. The synthesis of Fe3O4 NPs with an appropriate diameter can be performed by the optimization of process parameters (i.e., temperature and pH, etc.).32 The following equation represents the chemical reaction of the preparation of Fe3O4 nanoparticles. Fe21 þ 2Fe31 þ 8OH-Fe3O4 þ 4H2O

(10.1)

One of the major advantages of this technique is that magnetic Fe3O4 NPs can be effectively prepared on a large scale.33 However, process conditions should be carefully determined in this technique and general NPs with a wide size distribution are obtained. The first successful preparation of magnetic Fe3O4 NPs was performed by Massart and Cabuil through co-precipitation of FeCl2 and FeCl3.34 In this work, the prepared MNPs were roughly spherical and exhibited an average diameter of ca. 8 nm.

Chromatographic Applications of Functionalized Magnetic Nanoparticles

10.2.3

265

Sol–Gel Process

For the preparation of MNPs applying this technique, the hydroxylation and condensation processes of the reactants in solutions are conducted to prepare a sol of NPs. In the further step, a gel with a 3D structure of metal oxide is synthesized via a condensation process. On the other hand, the crystalline state is achieved by using temperature.35 The structure of the obtained gel and its performance can be controlled by changing the experimental conditions of hydroxylation and condensation processes.36 The sol–gel process is an effective and simple technique and displays great superiorities including the need for lower temperature values, excellent reaction activity and high mixing uniformity. However, one of the drawbacks of this approach is a coagulation problem during the post-treatment step for the preparation of MNPs.

10.2.4

Hydrothermal Technique

In this approach, the preparation of MNPs in aqueous medium is successfully conducted at extreme experimental conditions (i.e., applying high pressure and high temperature).37 The use of high temperature for the preparation of the MNPs is very beneficial and important for the rate of nucleation and accelerates the growth of the new MNPs that lead to obtaining NPs with a small size. Hydrolysis and oxidation processes are major routes for the effective preparation of MNPs under hydrothermal conditions.

10.2.5

Microemulsion Technique

A microemulsion is an isotropic transparent liquid system composed of oil, water and amphiphile.38 For the preparation of MNPs by applying a microemulsion technique, the process is mainly performed by accomplishing the aforementioned chemical reactions including reduction or co-precipitation in microemulsion systems for the efficient control of the size of the MNPs to be obtained. The process is carried out by the reaction of either two reactants lying in two separate micellar systems through mixing and coalescence or reactants inside a single micelle through thermalinitiation.39 This technique can be successfully employed for the synthesis of monodisperse MNPs. The major drawbacks of the microemulsion approach are low yield and consumption of a high volume of organic solvents during the MNPs preparation process.40

10.2.6

Flow Injection Technique

Another powerful and efficient technique for the preparation of MNPs is the flow injection approach. This approach enables researchers to obtain MNPs with a narrow particle size distribution. In this technique, a laminar flow is applied during the preparation of the MNPs. In a work carried out by Alvarez et al.,41 magnetic Fe3O4 NPs in the range from 2 to 7 nm were efficiently prepared by using a flow injection technique. This technique has a number of advantages including great mixing homogeneity and high reproducibility.

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Aerosol/Vapor-phase-based Approaches

Aerosol/vapor-phase-based approaches including spray pyrolysis technique and laser pyrolysis are other effective approaches for the preparation of MNPs since these techniques provide a high rate of synthesis in continuous chemical processes.42 For the preparation of MNPs by employing this technique, a solution composed of ferric salts and a reducing agent is sprayed into a number of reactors followed by condensing of the aerosol solute and evaporation of the solvent. Then, the dried residues are transformed into the obtained MNPs. The laser pyrolysis approach is another effective technique which is successfully employed for the preparation of MNPs. In this approach, laser heating a gaseous mixture of iron precursor (i.e., iron pentacarbonyl) is used for reducing the reaction time during the preparation of MNPs. The laser pyrolysis approach is effectively employed for the preparation of small, non-aggregated and narrow size-distributed MNPs. MNPs with a narrow size distribution can be effectively prepared by applying the laser pyrolysis approach.43

10.3 Chromatographic Applications of Functionalized Magnetic Nanoparticles (MNPs) Functionalized MNPs exhibit a number of superiorities including compatibility with various materials, simplicity of application, ease of surface modification, fast isolation and excellent recovery of the target compound/s by applying an external magnetic field, which are crucial in separation applications. To increase the adsorption features of MNPs, different inorganic or organic NMs (i.e., silica, metal and metal oxides, graphene, carbon nanotubes (CNTs), molecularly imprinted polymers (MIPs) and ionic liquids, etc.) were successfully combined with the MNPs such as magnetite (Fe3O4) and maghemite (g-Fe2O3) to obtain composite NMs having magnetic features. These functionalized composite MNPs can be successfully employed in chromatographic separation applications. An effective separation process by applying functionalized MNPs mainly depends on the target compound/s, the type of the magnetic nanoadsorbent and the interaction of the target compound/s with the functional groups on the surface of the NMs that may be due to various interactions such as hydrogen bonding, dipole–dipole and ionic interactions, etc. In the following sub-sections, capillary electrochromatography (CEC) and chip-based chromatography applications of functionalized MNPs are discussed and various examples reported in the literature are demonstrated.

10.3.1

Capillary Electrochromatography (CEC)

In CEC applications, the chromatographic process for the design and development of effective stationary phases exhibits a substantial impact on the separation efficiency. Because of their unique features, functionalized MNPs can usually improve the selectivity of the separation, and the efficiency of the capillary column.

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In an interesting research study carried out by Zhu and co-workers,44 various open-tubular CEC columns having magnetic stationary phases were successfully prepared by using functionalized MNPs. For this purpose, new open-tubular CEC columns were fabricated by using magnetic core–shell nanoparticles conjugated with C18 and NH2 groups. These magnetic core– shell nanoparticles were effectively immobilized in the CEC columns with magnets (see Figure 10.2). The developed magnetic core-shell nanoparticleimmobilized open-tubular CEC columns were successfully employed for the efficient separation of various organic acids such as salicylic acid, isophthalic acid, phthalic acid, anthranilic acid and benzoic acid. In addition, these opentubular CEC columns were also tested for the separation of the aqueous extract of Rhizoma gastrodiae. The achieved results confirmed that the large specific surface area of the MNPs immobilized in the column and multiple separation mechanisms significantly increased the efficiency of the CEC column. In another crucial work,45 the same research group reported the design and preparation of a N-(3-(trimethoxysilyl)-propyl)-ethylenediamine (PEDA)-coated

Figure 10.2

A schematic demonstration of the preparation of various stationary phases in the CEC column. (a) Placement of magnets, (b) loading of magnetic Fe3O4@SiO2 nanoparticles bearing the NH2 group, (c) loading of magnetic Fe3O4@SiO2 nanoparticles having C18, (d) cleaning of the CEC column, and (e) electric balance. Solid balls demonstrate the magnetic Fe3O4@SiO2 nanoparticles bearing the NH2 group while hollow balls demonstrate the magnetic Fe3O4@SiO2 nanoparticles having C18. Reproduced from ref. 44 with permission from Elsevier, Copyright 2013.

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and functionalized MNP-immobilized open-tubular CEC column for the efficient separation of 5 different compounds including sulfanilic acid, benzoic acid, cinnamic acid, p-aminobenzoic acid and isophthalic acid. The prepared capillary column having magnetic Fe3O4@SiO2 nanoparticles displayed a great separation performance toward the target compounds. On the other hand, the developed CEC column was also used for the analysis of the aqueous extract of Rhizoma gastrodiae. 23 compounds in the extract were effectively eluted from the capillary column within a short time (30 min). Yang et al. developed an open-tubular CEC column having b-cyclodextrinfunctionalized MNPs.46 In their study, MNPs conjugated with b-cyclodextrin and mono-6-deoxy-6-(1-methylimidazolium)-b-cyclodextrin tosylate, which is an ionic liquid, were efficiently coated on the inner surface of the capillary column. The developed open-tubular CEC column having b-cyclodextrinfunctionalized MNPs was employed for the enantioseparation of various dansylated amino acids including the DL-forms of leucine, alanine, isoleucine, methionine, valine and glutamic acid. The achieved results indicated that the use of MNPs as coating materials in capillary columns is a promising and powerful approach in the chiral separation field. In a work conducted by Carrasco–Correa and colleagues,47 a monolithic column having functionalized MNPs was prepared for the CEC-based separation of various alkyl benzenes (i.e., toluene, thiourea, propyl benzene, ethylbenzene, butyl benzene, hexylbenzene and pentyl benzene) and organophosphorous pesticides such as quinalphos, fensulfothion, malathion, profenofos, dialifos, methylchlorpyrifos, chlorpyrifos and sulprofos. In this work, magnetic Fe3O4 NPs were first modified with vinyl groups and then incorporated into polymethacrylate monolithic columns. The CEC-based separation performance of the developed monolithic columns having MNPs was tested using alkyl benzenes and organophosphorous pesticides. By applying CEC, separation efficiencies of the target compounds, using the developed monolithic column having MNPs, of up to 130 000 plates per m were obtained. The increase of the specific surface area of the monolithic columns due to the incorporation of MNPs led to an increase in the retention time for the target compounds and an enhancement of the separation efficiency. Lei and colleagues prepared different hybrid monolithic columns having NPs for CEC applications.48 To take both the advantages of NPs and monolithic columns in this study, different types of NPs including magnetic Fe3O4@SiO2 NPs functionalized with NH2 groups, and mesoporous SBA-15 silica NPs with both hexagonal and wormlike shapes were successfully incorporated into the polymethacrylate monolithic columns, respectively. Polymethacrylate monolithic columns were prepared by using butyl methacrylate (BMA) and ethylene glycol dimethacrylate (EDMA). The separation performance of the prepared hybrid monolithic columns having NPs toward various organic acids (i.e., isophthalic acid, phthalic acid, sulfanilic acid, salicylic acid and o-iodobenzoic acid) was investigated. In addition, the monolithic capillary column incorporated with magnetic Fe3O4@SiO2 NPs functionalized with NH2 groups (poly(BMA–EDMA–Fe3O4@SiO2/NH2) was

Chromatographic Applications of Functionalized Magnetic Nanoparticles

Figure 10.3

269

Separation of the compounds in an aqueous extract of Rhizoma gastrodiae using poly(BMA–EDMA) and poly(BMA–EDMA–Fe3O4@SiO2/NH2) columns. Reproduced from ref. 48 with permission from Elsevier, Copyright 2012.

also employed for the separation of the compounds in an aqueous extract of Rhizoma gastrodiae. The target compounds in the extract, including citric acid (1), gastrodin (2) and vanillyl alcohol (3), were effectively separated by using the poly(BMA–EDMA–Fe3O4@SiO2/NH2) capillary column (see Figure 10.3). As can be seen from the figure, incorporation of the magnetic Fe3O4@SiO2/NH2 NPs into the polymethacrylate monolithic capillary column considerably increased the separation efficiency. Wang et al. synthesized magnetic silica particles having octadecylsilane (ODS) in the CEC column.49 An external magnetic field was applied for the efficient immobilization of magnetic silica particles in the surface of the capillary column. The images of the capillary column packed with magnetic silica particles are given in Figure 10.4. The developed capillary column having magnetic silica particles modified with ODS was successfully applied for the effective separation of various neutral compounds including anthracene, toluene, fluorine, naphthalene and thiourea. Wang and co-workers50 developed an open-tubular CEC column having Fe3O4 MNPs modified with carboxyl groups. In their study, carboxyl groupmodified Fe3O4 MNPs were efficiently immobilized on the surface of a capillary column which had positively charged poly(diallydimethylammonium chloride) by applying an electrostatic self-assembly technique. After characterization by using electroosmotic flow measurements and scanning

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Figure 10.4

(a) Images of a capillary column packed with magnetic silica particles. (b) Magnified (160) images of packed capillary sections (inlet, middle and outlet of the column). Reproduced from ref. 49 with permission from American Chemical Society, Copyright 2007.

electron microscopy (SEM), the prepared open-tubular capillary column having Fe3O4 MNPs modified with carboxyl groups was successfully employed for the effective separation of various dipeptides (i.e., glycyl-Lphenylalanine, glycyl-L-tyrosine hydrate and glycyl-L-tryptophan hydrate), amino acids (i.e., phenylalanine, tryptophan and tyrosine) and proteins (i.e., bovine serum albumin, conalbumin, a-lactalbumin and b-lactoglobulin).

10.3.2

Chip-based Chromatography

Chip-based chromatography is extensively employed for the efficient separation of chiral compounds because of its many superiorities including low sample and solvent consumption, excellent separation efficiency, short processing time and rapid equilibration of the chromatographic system.51,52 For the fabrication of chip systems, poly(dimethylsiloxane) (PDMS) is the widely used polymeric material because of its advantages such as ease of fabrication, low cost, high optical transparency and oxygen permeability.53,54 In a crucial work performed by Liang et al.,51 chip-based chromatographic enantioseparation of D- and L-tryptophan was successfully carried out. In this

Chromatographic Applications of Functionalized Magnetic Nanoparticles

Figure 10.5

271

A schematic representation of the chip-based chromatographic enantioseparation of D- and L-tryptophan. Reproduced from ref. 51 with permission from Elsevier, Copyright 2012.

study, a magnetic nanocomposite composed of Fe3O4 NPs, graphene oxide (GO) and b-cyclodextrin (b-CD) was prepared as a stationary phase. For this purpose, the magnetic Fe3O4/GO nanocomposite was firstly prepared and b-CD was then conjugated to the prepared magnetic nanocomposite. Finally, the prepared magnetic nanocomposite was successfully immobilized into the PDMS microchannels of the chip system by applying an external magnetic field (see Figure 10.5). The achieved results confirmed that the efficient baseline enantioseparation of D- and L-tryptophan was obtained within a very short time (less than 50 s) with a good resolution factor (1.65) by using the developed chip. Qu and co-workers reported the development of a microfluidic system integrated with molecularly imprinted MNPs as the stationary phase for the efficient enantioseparation of R,S-ofloxacin by capillary electrochromatography.55 For this purpose, superparamagnetic NPs were firstly functionalized with 3-(methacryloyloxy)propyltrimethoxysilane. Then, molecularly imprinted NPs were synthesized on the surface of functionalized MNPs. For the preparation of selective molecularly imprinted NPs, S-ofloxacin, methacrylic acid (MAA) and ethylene glycol dimethacrylate (EDMA) were chosen as the template, functional monomer and cross-linker, respectively. Figure 10.6 shows the schematic depiction of the enantioseparation of R,S-ofloxacin by using the developed microfluidic system integrated with molecularly imprinted MNPs as the stationary phase.

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Figure 10.6

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The schematic depiction of the enantioseparation of R,S-ofloxacin by using the developed microfluidic system integrated with molecularly imprinted MNPs as the stationary phase. BR, SR, DR, WE, RE and AE represent the buffer reservoir, sample reservoir, detection reservoir, working electrode, reference electrode and auxiliary electrode, respectively. Reproduced from ref. 55 with permission from Elsevier, Copyright 2010.

The obtained results showed that the enantioseparation of R,S-ofloxacin was successfully performed by employing the prepared microfluidic system integrated with molecularly imprinted MNPs as the stationary phase. The limit of detection values for R- and S-ofloxacin were achieved as 0.4 mM and 2.0 mM, respectively, that were much lower than the previously reported values (17.5 mM and 22.2 mM) for R,S-ofloxacin in the literature, obtained by using an open tubular molecularly imprinted capillary column.56 Another chip-based chromatographic separation of chiral compounds using functionalized MNPs was reported by Wu et al.57 In their research, a facile and fast approach was developed for the efficient separation of chiral compounds based on a poly(dimethylsiloxane) (PDMS) microchip modified with molecularly imprinted functionalized MNPs. Histidine and mandelic acid enantiomers were chosen as model compounds to investigate the chiral stationary phase. For the preparation of molecularly imprinted MNPs, norepinephrine and Fe3O4 NPs were used as the functional monomer and supporting substrate, respectively. The schematic demonstration of the magnetic molecularly imprinted Fe3O4@polynorepinephrine NPs modifiedPDMS microfluidic system and enantioseparation of mandelic acid is given in Figure 10.7. The achieved results indicated that the developed microchip modified with molecularly imprinted MNPs can be successfully employed for the fast and efficient separation of chiral compounds. In a study carried out by Kabiri and colleagues,58 an effective frit-free polydimethylsiloxane (PDMS) microfluidic system packed with diatomaceous earth (DE) microparticles as the stationary phase using magnetic Fe3O4 NPs was developed. The fabrication of a PDMS microfluidic device having MNPs and diatomaceous earth (DE) is schematically represented in Figure 10.8. The fabricated microfluidic device was efficiently employed for

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Figure 10.7

A schematic demonstration of the magnetic molecularly imprinted Fe3O4@polynorepinephrine NPs modified-PDMS microfluidic system and enantioseparation process. Reproduced from ref. 57 with permission John Wiley & Sons, Copyright r 2017 WILEY–VCH Verlag GmbH & Co. KGaA, Weinheim.

Figure 10.8

(A) A schematic representation of the fabrication of the PDMS microfluidic device having MNPs and diatomaceous earth (DE). P1 and P2 represent sample entries, and P3 is the exit. (B) The flow of DE, MNPs and DE particles embedded with MNPs. (C) Magnetically arresting the flowing particles. (D) The slight expansion of the PDMS microfluidic channel because of the hydrodynamic pressure. (E) The formation of a stable microfluidic channel with DE particles upon drying and is then ready for the separation process. Reproduced from ref. 58 with permission from the Royal Society of Chemistry.

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the chromatographic separation of two food dyes FD&C Blue No. 1 (Brilliant blue) and FD&C Yellow No. 5 (Tartrazine). Wang et al. developed a magnetic molecularly imprinted polymer as the stationary phase of the PDMS-based chip for the enantioseparation of D,Ltryptophan, D,L-tyrosine, Gly-D-Phe and Gly-L-Phe and R,S-ofloxacin.59 For this purpose, magnetic Fe3O4 NPs, dopamine and enantiomers were used as the supporting substrate, functional monomer and template compounds, respectively. The molecularly imprinted MNPs were packed in the surface of PDMS microchannels by applying an external magnetic field. The developed molecularly imprinted magnetic Fe3O4 NPs-based chip system was efficiently employed for the enantioseparation of the target compounds.

10.4 Conclusions Functionalized MNPs are highly stable materials and offer high separation efficiency in chromatographic applications due to their unique features such as high surface-area-to-volume ratio and extremely small size. In addition, they can be efficiently synthesized and modified with various functional groups. The application of functionalized MNPs in chromatographic separation processes especially chip-based chromatographic applications considerably reduces the process time, cost and volume of sample and reagents. Likewise, MNPs open a green chemistry-based processes in analytical chemistry since these nanomaterials can significantly decrease the use of toxic solvents, and thus restricts the generation of hazardous waste.

References 1. F. Zhao, B. Zhang and L. Feng, Mater. Lett., 2012, 68(1), 112. 2. V. V. Mody, A. Cox, S. Shah, A. Singh, W. Bevins and H. Parihar, Appl. Nanosci., 2013, 4(4), 385. 3. C. M. Hussain, Magnetic Nanomaterials for Environmental Analysis, Advanced Environmental Analysis-Application of Nanomaterials, ed., C. M. Hussain and B. Kharisov, The Royal Society of Chemistry, 2017. 4. R. Keçili and C. M. Hussain, Int. J. Anal. Chem., 2018, 8503853. ¨yu ¨ktiryaki, Y. Su ¨mbelli, R. Keçili and C. M. Hussain, Lab-On-Chip 5. S. Bu Platforms for Environmental Analysis, ed. P. Worsfold, C. Poole, ´, Encyclopedia of Analytical Science, A. Townshend and M. Miro Academic Press, 3rd edn, 2019, pp. 267–273. ¨yu ¨ktiryaki and C. M. Hussain, TrAC, Trend Anal. Chem., 6. R. Keçili, S. Bu 2019, 110, 259–276. 7. K. Zhou, X. Zhou, J. Liu and Z. Huang, J. Pet. Sci. Eng., 2020, 188, 106943. 8. L. Mohammed, H. G. Gomaa, D. Ragab and J. Zhu, Particuology, 2017, 30, 1. 9. D. Song, R. Yang, F. Long and A. Zhu, J. Environ. Sci., 2019, 80, 14. ¨yu ¨ktiryaki, R. Keçili and C. M. Hussain, TrAC, Trend Anal. Chem., 10. S. Bu 2020, 127, 115893.

Chromatographic Applications of Functionalized Magnetic Nanoparticles

11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41.

275

M. Iranifam, TrAC, Trend Anal. Chem., 2013, 51, 51. ´ka ´s, D. Bica and M. V. Avdeev, China Particuol., 2007, 5, 43. L. Ve A. S. Teja and P.-Y. Koh, Prog. Cryst. Growth Charact. Mater., 2009, 55, 22. M. Wierucka and M. Biziuk, TrAC, Trend Anal. Chem., 2014, 59, 50. M. Angelakeris, Biochim. Biophys. Acta, Gen. Subj., 2017, 1861, 1642. D. Sharma and C. M. Hussain, Arabian J. Chem., 2020, 13, 3319. J. Sengupta and C. M. Hussain, TrAC, Trend Anal. Chem., 2019, 114, 326. C. M. Hussain, Nanomaterials in Chromatography: Current Trends in Chromatographic Research Technology and Techniques, Elsevier, 2018. C. M. Hussain and R. Keçili, Modern Environmental Analysis Techniques for Pollutants 1st edn, 2019, Elsevier. C. M. Hussain, Handbook of Nanomaterials in Analytical Chemistry: Modern Trends in Analysis, Elsevier, 2019. C. M. Hussain, Handbook on Miniaturization in Analytical Chemistry: Application of Nanotechnology, Elsevier, 2020. A. H. Lu, E. L. Salabas and F. Schuth, Angew. Chem., Int. Ed., 2007, 46, 1222. L. Z. Gao, J. M. Wu, S. Lyle, K. Zehr, L. L. Cao and D. Gao, J. Phys. Chem. C, 2008, 112, 17357. S. Behrens, Nanoscale, 2011, 3, 877. ¨m, Proc. Natl. Acad. Sci. U. S. A., A. Ahniyaz, Y. Sakamoto and L. Bergstro 2007, 104, 17570. F. X. Redl, K. S. Cho, C. B. Murray and S. O’Brien, Nature, 2003, 423, 968. T. O. Ely, C. Amiens, B. Chaudret, E. Snoeck, M. Verelst, M. Respaud and J. Broto, Chem. Mater., 1999, 11, 526. J. Osuna, D. de Caro, C. Amiens, B. Chaudret, E. Snoeck, M. Respaud, J. Broto and A. Fert, J. Phys. Chem. C, 1996, 100, 14571. J. H. Lee, Y. M. Huh, Y. Jun, J. Seo, J. Jang, H. T. Song, S. Kim, E. J. Cho, H. G. Yoon, J. S. Suh and J. Cheon, Nat. Med., 2006, 13, 95. F. Q. Hu, L. Wei, Z. Zhou, Y. L. Ran, Z. Li and M. Y. Gao, Adv. Mater., 2006, 18, 2553. L. H. Reddy, J. L. Arias, J. Nicolas and P. Couvreur, Chem. Rev., 2012, 112, 5818. R. Massart, IEEE Trans. Magn., 1981, 17, 1247. J. Liu, S. Z. Qiao, Q. H. Hu and G. Q. Lu, Small, 2011, 7, 425. R. Massart and V. Cabuil, J. Chim. Phys. PCB, 1987, 84, 967. H. Itoh and T. Sugimoto, J. Colloid Interface Sci., 2003, 265, 283. C. Cannas, D. Gatteschi, A. Musinu, G. Piccaluga and C. Sangregorio, J. Phys. Chem. B, 1998, 102, 7721. F. Chen, Q. Gao, G. Hong and J. Ni, J. Magn. Magn. Mater., 2008, 320, 1775. I. Danielsson and B. Lindman, Colloids Surf., 1981, 3, 391. C. Petit, A. Taleb and M. P. Pileni, J. Phys. Chem. B, 1999, 103, 1805. D. H. Chen and S. H. Wu, Chem. Mater., 2000, 12, 1354. G. Salazar-Alvarez, M. Muhammed and A. A. Zagorodni, Chem. Eng. Sci., 2006, 61, 4625.

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42. R. Strobel and S. E. Pratsinis, Adv. Powder Technol., 2009, 20, 190. 43. S. Veintemillas-Verdaguer, Y. Leconte, R. Costo, O. Bomati-Miguel, ´rez-Rial, I. Rodriguez B. Bouchet-Fabre, M. P. Morales, P. Bonville, S. Pe and N. Herlin-Boime, J. Magn. Magn. Mater., 2007, 311, 120. 44. Y. Zhu, L. Zhang, J. Qian and W. Zhang, Talanta, 2013, 104, 173. 45. Y. Zhu, Z. Zhou, S. Qin, Z. Ren, L. Zhang, H. Fu and W. Zhang, Electrophoresis, 2012, 33, 340. 46. X. Yang, X. Sun, Z. Feng, Y. Du, J. Chen, X. Ma and X. Li, Microchim. Acta, 2019, 186, 244. 47. E. J. Carrasco-Correa, G. Ramis-Ramos and J. M. Herrero-Martı´nez, J. Chromatogr. A, 2015, 1385, 77. 48. W. Lei, L.-Y. Zhang, L. Wan, B.-F. Shi, Y.-Q. Wang and W.-B. Zhang, J. Chromatogr. A, 2012, 1239, 64. 49. Y. Wang, Z. Zhang, L. Zhang, F. Li, L. Chen and Q.-H. Wan, Anal. Chem., 2007, 79, 5082. 50. W. Wang, X. Xiao, J. Chen and L. Jia, J. Chromatogr. A, 2015, 1411, 92. 51. R.-P. Liang, C.-M. Liu, X.-Y. Meng, J.-W. Wang and J. D. Qiu, J. Chromatogr. A, 2012, 1266, 95. 52. N. Chiem and D. J. Harrison, Anal. Chem., 1997, 69, 373. 53. R. S. Martin, A. J. Gawron, S. M. Lunte and C. S. Henry, Anal. Chem., 2000, 72, 3196. 54. J. A. Vickers, M. M. Caulum and C. S. Henry, Anal. Chem., 2006, 78, 7446. 55. P. Qu, J. Lei, L. Zhang, R. Ouyang and H. Ju, J. Chromatogr. A, 2010, 1217, 6115. 56. S. A. Zaidi, K. M. Han, S. S. Kim, D. G. Hwang and W. J. Cheong, J. Sep. Sci., 2009, 32, 996. 57. L.-L. Wu, R.-P. Ling, J. Chen and J.-D. Qiu, Electrophoresis, 2018, 39, 356. 58. S. Kabiri, M. D. Kurkuri, T. Kumeria and D. Losic, RSC Adv., 2014, 4, 15276. 59. X.-N. Wang, R.-P. Liang, X.-Y. Meng and J. D. Qiu, J. Chromatogr. A, 2014, 1362, 301.

Section 4: Functionalized Magnetic Nanoparticles in Detection Stage of Analysis/Miniturization devices

CHAPTER 11

Functionalized MNPs in Detection Stage of Analysis/ Miniaturization Devices MOJTABA BAGHERZADEH Reactor and Nuclear Safety School, Nuclear Science and Technology Research Institute, 81465-1589, Isfahan, IR, Iran Email: [email protected]

In recent years, superparamagnetic iron oxide nanoparticles have shown great potential in many applications related to biotechnology and nanomaterials, such as antibacterial,1 corrosion,2,3 MRI, efficient enzyme or protein immobilization as an ELISA test, magnetically controlled transport of drugs,4 and more recently in sensing5–8 and catalytic applications.9–11 Most functionalized superparamagnetic nanoparticles (MNPs) are synthesized directly at the oxide surface (Fe3O4 or Fe2O3), but the key to their recent development has been the tremendous progress made in the surface chemistry of these nanomaterials, along with surface functionality requirements and biocompatibility purposes for biotechnology applications. Surface modification of MNPs is a critical step in terms of their surface charge, hydrodynamic size, and biological properties. Importantly, a molecular level surface modification strategy is a key aspect of designing and fabricating high-performance MNPs for the desired applications. The use of a variety of surface functional groups such as hydroxyl, carboxyl, boronic, amine, hydroxamic, sulfate, and others has been described for molecular level surface modification in the literature.12–18

Analytical Applications of Functionalized Magnetic Nanoparticles Edited by Chaudhery Mustansar Hussain r The Royal Society of Chemistry 2021 Published by the Royal Society of Chemistry, www.rsc.org

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The most common coating materials for the application of MNPs in analytical chemistry are polymeric materials such as polystyrene, polysaccharides, polyethylene glycol, peptides, and phospholipids,19–25 and inorganic materials such as silica, porous carbon, and graphene-based materials.26–30 However, surface modification and coating of MNPs are usually performed through two routes: (i) physical,21–25,31 and (ii) chemical19,20,25,31–36 routes. The physical route is a method for encapsulation of MNPs in a polymer shell without physical or chemical binding. This method is convenient to make microcapsules loaded with MNPs and other substances (for example, drugs).24,25,37 Usually, a mixture of components is squeezed through the nozzle of a certain size (related to the desired size of microcapsules) into an environment that produces rapid polymerization of the cell material (solvent, air, radiation, environment at polymerization temperature, etc.).21,22 Using standard nozzles of different sizes, it is possible to produce narrowly sizedistributed microspheres. Perhaps the simplest route is physical adsorption, but this approach is reversible in nature and can ultimately lead to loss of the surface adsorbed targeting function. More robust coupling strategies are based on covalent chemical binding. Chemical binding is the most commonly used technique. Modification of the MNP surface with the desired functional groups allows numerous kinds of surface engineering.38,39 The dominant reaction chemistry for MNP functionalization has been carbodiimide and/or N–hydroxysuccinimide (NHS) ester-mediated amide bond formation between carboxylates on the MNP and amines on the targeting ligand, or vice versa7,40 (Figure 11.1). While these covalent amide bonds provide highly stable linkages, they offer little to no control over the molecular orientation of the targeting ligand on the surface. Particularly in the case of targeting proteins, there exists a multitude of free reactive amines and carboxylates distributed across the protein surface, and inevitably some proportion of the coupled ligands is oriented with its binding site occluded. To improve MNP conjugation and targeting efficiency, a variety of sitespecific conjugation strategies have been developed and implemented. One approach to site-specific MNP functionalization relies on noncovalent but high-affinity interactions. For example, NHS ester reactions have been used to covalently couple diethylenetriaminepentaacetic acid (DTPA) to MNPs (Figure 11.2).7 Similarly, graphene oxide nanosheets can be functionalized with MNPs via NHS ester coupling.40 The easiest and most widely used way to start MNP functionalization is coating the MNPs with amorphous silica. After the silica coating, surfacereactive groups such as tetraethyl orthosilicate (TEOS) and aminopropyltriethoxysilane (APTMES) are added to MNPs and kept for 2–72 h at 100–120 1C either in a sonic bath or mechanically stirred/shaken.19,32–35 The surface-reactive groups facilitate the stability and allow the design of multifunctional MNPs. Synthesis in a polymer matrix is a one-pot chemical method of producing coated MNPs.36 Polymers like saccharides, polysaccharides, polysaccharides derivatives, and other polymers could be used

Functionalized MNPs in Detection Stage of Analysis/Miniaturization Devices

Figure 11.1

281

Schematic representation of a mechanism for coupling of graphene oxide nanosheets with MNPs by using EDC/NHS. Reproduced from ref. 40 with permission from the Royal Society of Chemistry.

for this purpose. The sizes of the magnetic crystals formed using this process are normally 1–3 nm. When larger sizes of crystals and/or aggregation are desired, hydrothermal growth can be used.

11.1 Transduction Methods in Sensing Based on MNPs Sensing strategies based on MNPs offer advantages in terms of analytical figures of merit, such as enhanced sensitivity, low limit of detection (LOD), high signal-to-noise ratio, and shorter time of analysis compared with nonMNP-based strategies.41,42 In sensing applications, MNPs are used through direct application of tagged supports to the sensor, being integrated into the transducer materials, and/or dispersion of the MNPs in the sample followed by their attraction by an external magnetic field onto the active detection surface of the (bio)sensors. Table 11.1 shows examples of MNP-based sensors and biosensors for the detection of several analytes in different samples,43–76 taking into consideration their analytical figures of merit, such as LOD and linear range. Table 11.1 shows that these sensors and biosensors are based on different transduction principles (electrochemical, optical, piezoelectric and magnetic field), which

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Figure 11.2

Schematic representation of a mechanism for coupling of DTPA to MNPs by using EDC/NHS and its application in electrochemical determination of Cu21 and Pb21 ions. Reproduced from ref. 7 with permission from Elsevier, Copyright 2013.

are presented and discussed in the following sub-sections according to their classification.

11.1.1

Electrochemical

Electrochemical (EC) devices measure EC signals (current, voltage, and impedance) induced by the interaction of analytes and electrodes that can be coated with chemicals, biochemical materials or biological elements to improve their surface activity.78,79 EC devices possess advantages of rapidity, high sensitivity, low cost and easy miniaturization and operation, so being attractive in applications, such as clinical, environmental, biological and pharmaceutical.78,80 EC devices can be classified as amperometric, potentiometric, voltammetric, chemiresistive, and capacitive, according to their working principles.79 The EC immunosensors, and enzyme, tissue and DNA biosensors are designed through immobilizing biological-recognition elements of antibodies, enzyme, tissue and DNA, respectively, on the working electrode surface. To improve the sensitivity of EC devices, signal amplification has been attempted using MNPs. MNPs can be used in EC devices through their contact with the electrode surface, transport of a redoxactive species to the electrode surface, and formation of a thin film on the electrode surface. For MNP-based EC biosensors.43–46,51–58 Table 11.1 shows

Some examples of sensors and biosensors based on magnetic nanoparticles.a

Transduction principle

Sensor type

Electrochemical Voltammetry Voltammetry Voltammetry Voltammetry Voltammetry Voltammetry

Type of magnetic nanoparticles

Analyte

Reference

Core–shell Au–Fe3O4 Fe3O4 Au nanoparticles Au–Fe3O4 composite nanoparticles Fe3O4 Au nanoparticles Core–shell Fe3O4@SiO2 Fe3O4 anchored on reduced graphene oxide Fe3O4@Au-MWCNT-chitosan Core–shell Fe3O4@SiO2/MWCNT Core–shell Au–Fe3O4@SiO2 Fe3O4@SiO2/MWCNT Magnetic beads Dynabeads Protein G

Carcinoembryonic antigen Clenbuterol (pork) Organochloride pesticides (cabbage) H2O2 (contact lens care solution) Metronidazole (milk, honey) Cr(III)

44 45 43 46 47 48

Streptomycin Uric acid (blood serum, urine) Glucose (human serum) Glucose (glucose solution) Zearalenone (maize certified reference material, baby food cereal, wheat, rice, maize, barley, oats, sorghum, rye, soya flour) Potentiometry Core–shell Fe3O4 Glucose (human serum) Electrochemoluminescent Core–shell Fe3O4 Au nanoparticles a-fetoprotein (human serum) Electrochemoluminescent Core–shell Fe3O4@Au Cry1Ac Electrochemical Iron oxide carboxyl-modified magnetic Ochratoxin A (wine) impedance nanoparticles Electrochemical Fe@Au nanoparticles-2DNA impedance aminoethanethiolfunctionalized graphene nanoparticles Voltammetry Voltammetry Amperometry Amperometry Potentiometry

Optical

SPR

54 55 56 57 58

b-human chronic gonadotropin

59

a-fetoprotein Thrombin Dog IgG

60 77 61

283

SPR SPR SPR

Magnetic nanoparticles (fluidMAGARA) with iron oxide core Fe3O4@Au magnetic nanoparticles Fe3O4 magnetic nanoparticles Fe3O4/Ag/Au magnetic nanocomposites

49 50 51 52 53

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Table 11.1

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(Continued)

Transduction principle

Piezoelectric

Type of magnetic nanoparticles

Analyte

Reference

SPR SPR SPR SPR

Goat IgM Rabbit IgG Rabbit IgG Ochratoxin A (wine)

62 63 63 57

Fluorescence

Fe3O4–Au nanorod Core/shell Fe3O4/SiO2 Core/shell Fe3O4/Ag/SiO2 Iron oxide carboxyl-modified magnetic nanoparticles Fe3O4

Escherichia coli

64

QCM

Iron oxide magnetic nanobeads

65

QCM QCM EQCM

Iron oxide magnetic nanoparticles Fe3O4@SiO2 Core–shell Fe3O4@Au-MWCNT composites Iron oxide magnetic nanoparticles

HA unit Avian influenza virus H5N1 (chicken tracheal swab) desulfotomaculum C-reactive protein (human serum) Myoglobin (human serum)

66 67 68

Escherichia coli O157:H7 (Milk)

69

Cubic FeCo nanoparticles

Endoglin (human urine)

70

Cubic FeCo nanoparticles

Interleukin-6 (human serum)

71

Carboxyl functionalized iron oxide nanoparticles

Breast cancer cells (mice cells)

75

Manganese-doped ferrite (MnFe2O4)

Rare cells: MDA-MB-468 cancer cells (whole blood)

76

QCM Magnetic field

a

Giant magnetoresistive immunosensor Giant magnetoresistive immunosensor Superconducting quantuminterference device sensor Hall sensor

MWCNT, Multiwalled carbon nanotube; QCM, Quartz-crystal microbalance; EQCM, Electrochemical quartz-crystal microbalance; SPR, Surface-plasmon resonance.

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Sensor type

Functionalized MNPs in Detection Stage of Analysis/Miniaturization Devices 44–50

285 51,52

different detection modes, such as voltammetry, amperometry, potentiometry,53,54 electrochemiluminescence (ECL)55,56 and EC impedance,57,58 which were used for analyte detection and quantification. Among the sensors, the detection mode most used was voltammetry.47–50 Due to its superparamagnetic property, biocompatibility with antibodies and enzymes and ease of preparation, Fe3O4 is most commonly used in developing biosensors. However, Fe3O4 magnetic dipolar attraction and its large ratio of surface area to volume may lead to aggregation in clusters when exposed to biological solutions. Functionalization can overcome this problem and also enhance biocompatibility. A broad variety of functionalized MNPs have been used, such as core–shell Au–Fe3O4,44 core–shell Au–Fe3O4@SiO2,51 core–shell Fe3O4@SiO2,47 Au–Fe3O4 composite NPs,43 Fe3O4@SiO2/MWCNTs,52 Fe3O4 anchored on reduced graphene oxide48 and Fe3O4@ Au-MWCNTchitosan.49 Carbon materials, such as carbon nanotubes (CNTs) and graphene are also widely used to functionalize MNPs due to their physical properties, such as large surface area, chemical and thermal stability, controlled nanoscale structure, and electronic and optical properties.40,49 Recently, a nanocomposite of graphene oxide decorated with magnetic Fe3O4 was synthetized.40 In most reported works, the MNPs were concentrated on electrode-surface materials and have advantages, such as increased sensitivity and stability, besides ease of renewing the electrode by releasing the MNPs and replacing them with new MNPs. ECL immunosensors currently use MNPs as labeling agent or immobilization support. The ECL signal is based on a sequence of stages, such as EC (single electron redox processes of substance), chemical (biradical combinations) and optical (emission of the ECL quanta).81 The ECL assays can have three main formats (i.e., direct interaction, competition assay and sandwichtype assay).81 Quantum dots, such as CdS, CdSe or core/shell type ZnS/CdSe, have received the most interest in ECL applications due to the quantum confinement effect having optical and electronic properties that make them excellent labels for improving the sensitivity of transducer surfaces coated with MNPs and magnetic capture probes. An ECL immunosensor was developed for detecting a-fetoprotein (AFP) based on a sandwich immunoreaction strategy using magnetic particles as capture probes and quantum dots as signal tags.55 Figure 11.3 shows the process used for preparing magnetic capture probes Fe3O4–Au/primary AFP antibody (Ab1) and signal tag of CdSAu/secondary AFP antibody (Ab2). The Ab1 was first anchored in the surface of Fe3O4–Au nanospheres by the Au–S bond. The products with an Ab1 immobilized on the surface of Fe3O4–Au captured AFP (antigen) from a solution. Finally, the protein-labeled CdSAuNPs were introduced to the immunoreaction with the exposed part of AFP.

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Figure 11.3

11.1.2

Example of the preparation procedure of an electrochemiluminescent (ECL) immunosensor. BSA, Bovine serum albumin; AFP, a-fetoprotein; Ab1, Primary antibody of AFP; Ab2, CdS-Au labeled secondary antibody. Reproduced from ref. 55 with permission from Elsevier, Copyright 2014.

Optical

Optical devices have been applied to the detection of several analytes in clinical samples,42,82 environmental samples83–85 and food samples86 due to their main characteristics, such as low signal-to-noise ratio, reduced interferences, and reduced costs of manufacture. Optical devices can be classified by their principles of detection (i.e., fluorescence spectroscopy, interferometry, reflectance, chemiluminescence (CL), light scattering and refractive index). CL-detection systems have to be enhanced in emission intensity and improved in selectivity for use in quantitative analysis of complex matrices, such as biological and environmental samples. In order to overcome such limitations, MNPs can play a useful part in the CL reactions as catalyst, biomolecule carrier and separation tool.87 Iranifam87 recently reviewed and discussed the analytical applications of CL-detection systems assisted by MNPs, so a detailed presentation and discussion on such methods is beyond the scope of this review. Table 11.1 shows that, among the MNP-based optical devices, the detection modes used were surface plasmon resonance (SPR),57,59–63 and fluorescence spectroscopy.64 Figure 11.4 shows an immunosensor that combines SPR technology with MNP assays for detection and manipulation of b human chorionic gonadotropin (b-hCG).59 The approach is based on a grating-coupled SPR sensor chip that is functionalized by antibodies recognizing the target analyte (b-hCG). The MNPs were conjugated with antibodies and were used both as labels for enhancing refractive-index changes

Functionalized MNPs in Detection Stage of Analysis/Miniaturization Devices

Figure 11.4

287

Example of a surface-plasmon resonance (SPR) immunosensor: (A) Optical sensor set-up and (B) a sensor chip of the magnetic nanoparticle (NP)-enhanced grating coupled SPR sensor. (C) The analytical signal before and after immobilization of the capture antibody. Reproduced from ref. 59 with permission from American Chemical Society, Copyright 2011.

due to the capture of analyte and also as carriers for fast delivery of the analyte at the sensor surface, thus enhancing the SPR-sensor response. A magnetic field was used to capture the MNPs-antibody analyte on the sensor surface. The use of MNPs together with its collection on the sensor surface by applying a magnetic field improved the sensitivity by four orders of magnitude with respect to regular SPR using direct detection. This enhancement was attributed to the larger mass and higher refractive index of MNPs. An LOD of 0.45 pM was achieved for the detection of b-hCG. This working principle should be further investigated for the analysis of analytes, such as viruses or bacterial pathogens, since it can overcome the problems of

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the low sensitivity of SPR-biosensor technology due to mass transfer to the sensor surface being strongly hindered by diffusion for these analytes. The analytical signal associated with fluorescence intensity can also be enhanced using MNPs, such as Fe3O4. A microfluidic immunosensor chip was developed having circular microchannels64 for detection of Escherichia coli. The methodology used involves, in the first step, the conjugation of Fe3O4 MNPs with antibody and, in the second step, the in-flow capture of antigens in the microchannels. The captured MNPs create a heap-like structure at the detection site under the influence of a reversed magnetic flow that increases the retention time of antigens at the site of capture and the capture efficiency of antigens, so enhancing the intensity of the fluorescence signal.

11.1.3

Piezoelectric

Piezoelectric devices can be quartz-crystal microbalance (QCM) and surface acoustic wave (SAW). Table 11.1 shows that the MNP-based piezoelectric sensors and biosensors are based on QCM transduction.65–69 The QCM is a quartz-crystal disk with metal electrodes on each side of the disk88–90 that vibrates under the influence of an electric field. The frequency of this oscillation depends on the cut and the thickness of the disk. This resonant frequency changes as compound(s) adsorb or desorb from the surface of the crystal. A reduction in frequency is proportional to the mass of the adsorbed compound. QCMs are small and robust, inexpensive, and capable of giving a rapid response down to a mass change of 1 ng. The major drawback of these devices is the increase in noise with the decrease in dimensions due to instability as the surface area-to-volume ratio increases. More disadvantages of QCM are the interference from atmospheric humidity and the difficulty in using them for the determination of analytes in solution.91 MNPs with piezoelectric properties can easily eliminate these problems, since they offer an attractive transduction mechanism and recognition event with advantages, such as solid-state construction and cost-effectiveness. The frequency enhancement in the presence of MNPs can be due to:1 the MNPs possessing some inherent piezoelectricity;2 the MNPs binding and helping to concentrate the analyte molecules at the QCM surface; and,3 the MNPs acting as matrix carriers to load labels. A QCM immunosensor for detection of C-reactive protein (CRP) in serum was developed. In a first step, a sandwich-type immunoreaction was made between the capture probe (silicon dioxide-coated magnetic Fe3O4 NPs) labeled with primary CRP antibody (MNs-CRPAb1), CRP and signal tag [horseradish peroxidase (HRP) coupled with HRP-linked secondary CRP antibody co-immobilized on AuNPs (AuNPs-HRP/HRP-CRP Ab2)].67 In a second step, the immunocomplex was exposed to 3-amino-9-ethylcarbazole (AEC) and hydrogen peroxide. Figure 11.5 shows the preparation procedures and the detection principle. The capture probe containing the MNPs (MNsCRPAb1) enhanced the analytical signal due to both magnetic separation and immobilization at the electrode surface.

Example of a quartz-crystal-microbalance (QCM) immunosensor. (Left) Procedures of the preparation of Fe3O4@SiO2-Ab1 and AuNPs-HRP/HRP-Ab2 conjugations. (Right) Detection principle. TEOS, Tetraethyl orthosilicate; EDC, 1-Ethyl-3-(3-dimethylaminopropyl) carbodiimide; NHS, Amine-reactive N-hydroxysuccinimide; CRP, C-reactive protein; Ab1, Primary CRP antibody; Ab2, Secondary CRP antibody; AuNP, Gold nanoparticle; HRP, Horseradish peroxidase; AEC, 3-amino-9-ethylcarbazole; MNP, Fe3O4@SiO2 nanoparticle. Reproduced from ref. 67 with permission from Elsevier, Copyright 2013.

Functionalized MNPs in Detection Stage of Analysis/Miniaturization Devices

Figure 11.5

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Furthermore, the advantages of the magnetic beads (Fe3O4@SiO2) for labeling CRPAb1 include the mono-disperse size distribution and easy preparation of the labeled conjugates. The performance of the QCM methodology was comparable with the ELISA methodology when detecting CRP in human serum. Moreover, the QCM-sensor surface can be regenerated easily and used repeatedly due to the use of the MNPs. More research is needed on the development of magnetic nanostructures, characterization of their piezoelectric behavior and their application in piezoelectric sensors and biosensors, since they promise to overcome the sensitivity and stability issues characteristic of these kinds of devices.

11.1.4

Magnetic Field

Table 11.1 shows that the magnetic field devices using MNPs70–76 include giant magnetoresistive (GMR), Hall Effect, magnetooptical and superconducting quantum interference sensors. Magnetoresistive sensors are based on the intrinsic magnetoresistance of a ferromagnetic material or on ferromagnetic/nonmagnetic heterostructures.92 Depending on the nanostructure of the nanomaterial layer, these devices can show the GMR effect or the tunneling magnetoresistance effect. In these devices, the analytical signal (change in electrical resistance) is measured following the analyte binding in the presence of a magnetic field. The analytical signal can therefore be obtained by small changes in the magnetic field and depends on the magnetic field along the sensor area.93 When using a GMR device and MNPs for interleukin-6 (analyte) detection, two methodologies have been attempted (Figure 11.6).71 In the first possible methodology, the GMR sensor is functionalized with capture antibodies and the analyte binds to the capture antibody. The detection antibodies labeled with MNPs bind to the analyte captured. The second detection methodology involves functionalization of the GMR sensor with capture antibodies, and then the direct capture of the MNP-labeled analyte on the GMR biosensor. In both cases, the GMR biosensor detects the dipole field generated by the MNPs captured on the sensor surface, which is sensitive to distance. The quality of the MNPs is very important for successful magnetoresistive detection, so ideal probes should be superparamagnetic, having high magnetic moment and large susceptibility, in order to enable their magnetization in a small magnetic field. The MNPs also need to have uniform size and shape, since the magnetic signal depends on it, and to be stable in physiological solutions, so that their coupling with biomolecules can be controlled.93 Moreover, the choice of MNPs with high magnetic moment leads to increased signal and therefore high sensitivity. Taking this into consideration, for sensitive magnetoresistive detection, the ideal candidates have been metallic Fe, Co, or their alloy MNPs.93 According to Li et al.,71 considering the same NP volume and an applied field of 10 Oe, the net magnetic moment of one FeCo NP is 7–11 times higher than that of one Fe3O4 NP.

Functionalized MNPs in Detection Stage of Analysis/Miniaturization Devices

Figure 11.6

291

Example of the use of magnetic nanoparticles (MNPs) and giant magneto-resistive (GMR) sensors in two different methodologies. (A) Sandwich-type approach, where the GMR sensor is functionalized with capture antibodies, for subsequent analyte binding. The detection antibodies labeled with MNPs are then applied and bind to the captured analyte. (B) Two-layer approach, where the GMR sensor is functionalized with capture antibodies for the direct application and capture of the MNP-modified analyte. (C) GMR biosensor working principle. Reproduced from ref. 71 with permission from American Chemical Society, Copyright 2010.

MNPs can also be used in microfluidic devices, which, due to their permanent magnetic moment, can be controlled via external inhomogeneous magnetic fields and also detected by magnetoresistive sensors. There are also two types of microfabricated magnetic field devices, which are the magnetoresistive and the Hall Effect devices. A micro-Hall sensor was developed for the enumeration of rare cells ex vivo.76 The microfluidic chipbased micro-Hall sensor measures the magnetic moments of cells in flow that have been labeled with MNPs. The micro-Hall sensor integrates several technological advances for accurate measurements of biomarkers on individual cells such as:1 linear response, which enables operation at such high magnetic fields (40.1 T) that MNPs can be completely magnetized to generate maximal signal strength;2 the Hall element is a similar size to the cells that pass over it, thus increasing the sensitivity of the device;3 an array of eight sensors constituting the micro-Hall sensor allows less-stringent fluidic control than if the cells had to be focused over a single sensor; and4 an array that integrates the overall magnetic flux from each cell enables measurement of the total magnetic moment of a single cell. The micro-Hall sensor is capable of high-throughput screening and has demonstrated clinical utility

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by detecting circulating tumor cells in whole blood of 20 ovarian cancer patients at higher sensitivity than currently possible with clinical standards. A magnetic field sensor was developed combining a magnetic fluid (Fe3O4 NPs) and an optical fiber Loyt–Sagnac interferometer.73 The sensor takes advantage of the magnification of the birefringence effect of the magnetic fluid by the properly designed optical fiber Loyt–Sagnac interferometer structure. The sensor demonstrated a sensitivity enhanced by 1–3 orders of magnitude, compared to existing magnetic fluid sensors. Magnetic field sensors are not easily extended to the detection of multianalytes since the analytical signal arises from the magnetic moment, m, which is a single physical parameter. By using superparamagnetic NPs with different sizes or different materials, the analytical signals can be distinguished by their unique non-magnetization curves, thus enabling multianalyte detection by magnetic field devices.76

11.2 Applications of MNPs in Detection Analysis As solid supports, nano or micro magnetic particles have important applications in biology, biochemistry and analytical chemistry. A magnetic force combined with separation and identification methods is widely employed to separate proteins, nucleic acids, cell organelles, and cells from complex matrices. More recently this technology has been used to concentrate organic and inorganic analytes of economic or environmental interest.94 Magnetic beads functionalized with different reactive groups, such as amines, carboxyls, epoxyls, tosyls, streptavidins, proteins, IgGs, alkyl chains, etc.80 In many cases, the reported supports are used for the preconcentration, isolation, purification, immobilization of analytes, and all these processes are directly performed on complex samples. This represents an important development in separation methods since it avoids the need for sample pretreatment and thus reduces the time of separation.95 Among the large variety of methods used to pre-concentrate analytes, magnetic methods have been widely accepted due to their great versatility and speed.80 Peptide mapping by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-ToF–MS) along with database searching is a major and well-known tool in modern protein analysis for bioanalysis and bioseparation.96 Magnetic solids were first used to isolate biomolecules. However, in recent years the use of magnetic solids bearing different functional groups has been extended to the pre-concentration of organic and inorganic compounds such as: metal ions, heavy metals, antiinflammatory drugs, antibiotics, analgesics, pesticides, insecticides, dyes, surfactants, carcinogens and phenolic compounds.80,97–119

11.2.1

Biomolecules and Cells

The bioanalytical applications of magnetic functionalized particles are limited by their chemical stability, level of dispersion in solution, and

Functionalized MNPs in Detection Stage of Analysis/Miniaturization Devices 120,121

293

biocompatibility. The maghemite Fe2O3 is most widely used in biological applications due to its high stability.122 Magnetic solids have been used for magnetic separation, purification and immobilization of different biomolecules, such as proteins and nucleic acids. The separation of biomolecules and cells is based on complementary components such as antibody plus antigen, virus or cell. The most important characteristics of the magnetic solid are its composition and morphology. Thus, Li et al.123 reported that impregnation of Ni21 on the surface of magnetic silica solids makes the process selective for the adsorption of histidine from a peptide mixture. Likewise, Ruo–Bing et al.80 reported the use of magnetic silica microspheres with Cu21 immobilized on their surface for the purification of proteins/peptides. This method is based on the coordination of transition metal ions such as Cu21, Ni21, Zn21 and Co21 with imidazole, thiol, and indole groups present in the protein chains.80,123–125 Moreover, these methods provide a fast, simple, and sensitive way to detect protein based on competitive immunoassays using magnetic nanoparticles under magnetic fields.126–133 Finally, it should be highlighted that the immobilization of metal ions on the magnetic silica particle surface improves the enrichment or pre-concentration process.134 Other methods such as chemiluminescence enzyme immunoassay (CLEIA) have been successfully used to determine the tumor marker, carbohydrate antigen 50 (CA50), in human serum.135,136 In the fields of microorganisms and gene manipulation, genomic profiling, and clinical diagnostics, magnetic particles are an important tool for the selective separation of nucleic acids for further analysis by techniques such as Polymerase Chain Reaction (PCR) amplification and DNA hybridization. This technology reduces the identification time and increases sensitivity and specificity, while it can also be used for DNA recovery from viruses, bacteria, and plants (for disease or mutation detection).80,137–156 DNA extraction by magnetic assisted separation methods is comparable to the traditional extraction approaches such as non-magnetic silica and solvent procedures but with the added advantages of reduced solvent consumption and processing time.157,158 On the other hand, magnetic cell separation has become a popular tool for the isolation of cells from complex mixtures. This procedure employs specific antibodies, anchored on the surface of magnetic particles. Variables such as antigen expression level, antibody type, type of magnetic particle, and cell size must be controlled and understood to make magnetic separation more efficient. Leucocytes, Bacillus spp. spores, CD341 cells, several cancer cells including Hela cells, Escherichia coli, and human immunodeficiency virus (HIV) have been separated by magnetic cell separation.159–168 Recently Chen et al. used titanium-coated magnetic iron oxide nanoparticles (Fe3O4@TiO2 NPs) as affinity probes to concentrate and characterize pathogenic bacteria. This research group has identified potential biomarker ions for five Gram negative bacteria: Escherichia coli O157 : H7, uropathogenic E. coli, Shigella sonnei, Pseudomonas aeruginosa, and Klebsiella pneumonia.169

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Organic Compounds

Synthetic organic compounds (plastic softeners and detergents) may behave as steroid hormones, adversely affecting humans and wildlife through their interactions with the endocrine system. These noxious compounds are known as environmental endocrine disrupting chemicals (EDCs). Analytical procedures based on magnetic separation have been developed for many organic compounds, and have the benefit that they minimize EDC interference due to their high specificity.116,170,171 Other potentially harmful substances such as melamine, have also become targets of magnetic preconcentration and analysis methods. Thus, Xu et al. prepared a magnetic strong cation exchange resin (MSCX) showing a high magnetic response and extraction efficiency to successfully extract melamine from egg samples, followed by LC–MS/MS analysis. These authors claim their proposed method has many advantages over conventional procedures including easier preparation and regeneration of sorbents, a simpler sample handling procedure, less solvent consumption and improved extraction recovery.172 Magnetic separation and analysis methods have also focused on analyzing drugs, toxins and steroids in different analytical matrices, to explore their adverse effects or biological significance. These methods have served to improve the detection limits of earlier techniques and have even been proposed as rapid screening methods.113,117,173–178 Tumorigenic polynuclear aromatic hydrocarbons such as ergosterol, sulfonamides or salicylic acid have been isolated by magnetic solid-phase extraction. This technique uses magnetic silica functionalized with different organic chains and has demonstrating a reduction in sample pretreatment time and reagents.104,179 Other authors have reported the use of magnetic molecularly imprinted polymer (MMIP) as the sorbent for the determination of fluoroquinolone antibiotics in environmental water samples. The MMIP method minimizes the pre-concentration and elution time compared to traditional SPE and has shown great analytical potential in the separation, purification and concentration of analytes in large volumes of real water samples at the ng L1 level.180

11.2.3

Ions and Inorganic Compounds

Substances hazardous to the environment of an inorganic nature have been pre-concentrated from water samples using magnetic particles. Analytical variables such as the limit of detection (LOD), limit of quantification (LOQ) and percent recovery, are similar to those observed for the more conventional methods indicating the adequate precision and accuracy of analytical methods based on magnetic sample treatment. Selective chemical separation and magnetic extraction are advantages that magnetic nano- or micro particles offer for the recovery of metal ions or inorganic substances. The binding of a specific ligand on the surface of the particle makes the process selective, quick and simple, and reduces the use

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of organic solvents. The variables examined so far for these magnetic separation techniques have been ligand and particle amounts, pH, ionic strength, contact time and eluent solution, along with properties such as selectivity, maximum capacity and the partition coefficient. Magnetic solidphase extraction has been successfully applied to transition metals, heavy metals, radio isotopes and fluoride ions.98–102,181,182 The synthesis of magnetic ferrites has been used to remove metal pollutants from wastewater. The method involves the incorporation of metal ions in the ferrite structure during its synthesis by a co-precipitation method.183,184

References 1. M. R. Goudarzi, M. Bagherzadeh, M. Fazilati, F. Riahi, H. Salavati and S. S. Esfahani, Evaluation of antibacterial property of hydroxyapatite and zirconium oxide-modificated magnetic nanoparticles against Staphylococcus aureus and Escherichia coli, IET Nanobiotechnol., 2019, 13(4), 449–455. 2. M. Bagherzadeh, O. Mousavi and Z. S. Ghahfarokhi, Fabrication and characterization of a Fe 3 O 4/polyvinylpyrrolidone (Fe 3 O 4/PVP) nanocomposite as a coating for carbon steel in saline media, New J. Chem., 2020, 15148–15156. 3. M. Bagherzadeh, H. Haddadi and M. Iranpour, Electrochemical evaluation and surface study of magnetite/PANI nanocomposite for carbon steel protection in 3.5% NaCl, Prog. Org. Coat., 2016, 101, 149–160. 4. K. Heuze, D. Rosario-Amorin, S. Nlate, M. Gaboyard, A. Bouter and ´rac, Efficient strategy to increase the surface functionalization of R. Cle core–shell superparamagnetic nanoparticles using dendron grafting, New J. Chem., 2008, 32(3), 383–387. 5. M. Bagherzadeh, M. Jabouri-Abassi and Z. Akrami, One-step synthesis of reduced graphene oxide and magnetic graphene: characterization and its application in electrochemical detection of lead (II) ions, J. Mater. Sci.: Mater. Electron., 2019, 30(22), 20229–20242. 6. F. Riahi, M. Bagherzadeh and Z. Hadizadeh, Modification of Fe 3 O 4 superparamagnetic nanoparticles with zirconium oxide; preparation, characterization and its application toward fluoride removal, RSC Adv., 2015, 5(88), 72058–72068. 7. M. Bagherzadeh, M. Pirmoradian and F. Riahi, Electrochemical detection of Pb and Cu by using DTPA functionalized magnetic nanoparticles, Electrochim. Acta, 2014, 115, 573–580. 8. M. Bagherzadeh, S. Ansari, F. Riahi and A. Farahbakhsh, A dopamine sensor based on pre-concentration by magnetic nanoparticles, Int. J. Electrochem., 2013, 2013, 1–10. 9. A. Rostami-Vartooni, L. Rostami and M. Bagherzadeh, Green synthesis of Fe 3 O 4/bentonite-supported Ag and Pd nanoparticles and investigation of their catalytic activities for the reduction of azo dyes, J. Mater. Sci.: Mater. Electron., 2019, 30(24), 21377–21387.

296

Chapter 11

10. A. Rostami-Vartooni, A. Moradi-Saadatmand, M. Bagherzadeh and M. Mahdavi, Green synthesis of Ag/Fe3O4/ZrO2 nanocomposite using aqueous Centaurea cyanus flower extract and its catalytic application for reduction of organic pollutants. Iranian, J. Catal., 2019, 9(1), 27–35. 11. M. Nasrollahzadeh, M. Maham, A. Rostami-Vartooni, M. Bagherzadeh and S. M. Sajadi, Barberry fruit extract assisted in situ green synthesis of Cu nanoparticles supported on a reduced graphene oxide–Fe 3 O 4 nanocomposite as a magnetically separable and reusable catalyst for the O-arylation of phenols with aryl halides under ligand-free conditions, RSC Adv., 2015, 5(79), 64769–64780. 12. R. K. Shervedani, F. Yaghoobi and M. Bagherzadeh, Electrocatalytic determination of hydroquinone with Mn þ modified gold-5-amino-2mercaptobenzimidazole self-assembled monolayer electrodes, J. Iran. Chem. Soc., 2009, 6(1), 104–112. 13. R. K. Shervedani, M. Bagherzadeh, H. Sabzyan and R. Safari, Oneimpedance for one-concentration impedimetry as an electrochemical method for determination of the trace zirconium ion, J. Electroanal. Chem., 2009, 633(1), 259–263. 14. R. K. Shervedani and M. Bagherzadeh, Electrochemical impedance spectroscopy as a transduction method for electrochemical recognition of zirconium on gold electrode modified with hydroxamated selfassembled monolayer, Sens. Actuators, B, 2009, 139(2), 657–664. 15. R. K. Shervedani and M. Bagherzadeh, Hydroxamation of gold surface via in-situ layer-by-layer functionalization of cysteamine self-assembled monolayer: Preparation and electrochemical characterization, Electrochim. Acta, 2008, 53(22), 6293–6303. 16. R. K. Shervedani and M. Bagherzadeh, Electrochemical Characterization of In Situ Functionalized Gold Cysteamine Self-Assembled Monolayer with 4-Formylphenylboronic Acid for Detection of Dopamine, Electroanalysis, 2008, 20(5), 550–557. 17. R. K. Shervedani, A. Farahbakhsh and M. Bagherzadeh, Functionalization of gold cysteamine self-assembled monolayer with ethylenediaminetetraacetic acid as a novel nanosensor, Anal. Chim. Acta, 2007, 587(2), 254–262. 18. R. K. Shervedani, M. Bagherzadeh and S. A. Mozaffari, Determination of dopamine in the presence of high concentration of ascorbic acid by using gold cysteamine self-assembled monolayers as a nanosensor, Sens. Actuators, B, 2006, 115(2), 614–621. 19. R. Hong, J. Li, J. Qu, L. Chen and H. Li, Preparation and characterization of magnetite/dextran nanocomposite used as a precursor of magnetic fluid, Chem. Eng. J., 2009, 150(2–3), 572–580. 20. A. K. Gupta and A. S. Curtis, Surface modified superparamagnetic nanoparticles for drug delivery: interaction studies with human fibroblasts in culture, J. Mater. Sci.: Mater. Med., 2004, 15(4), 493–496. 21. C. Yang, H. Liu, Y. Guan, J. Xing, J. Liu and G. Shan, Preparation of magnetic poly (methylmethacrylate–divinylbenzene–glycidylmethacrylate)

Functionalized MNPs in Detection Stage of Analysis/Miniaturization Devices

22.

23.

24.

25.

26.

27.

28.

29.

30.

31.

32.

33.

34.

35.

297

microspheres by spraying suspension polymerization and their use for protein adsorption, J. Magn. Magn. Mater., 2005, 293(1), 187–192. C. Yang, Y. Guan, J. Xing, J. Liu, G. Shan and Z. An, et al., Preparation of magnetic polystyrene microspheres with a narrow size distribution, AIChE J., 2005, 51(7), 2011–2015. S.-J. Lee, J.-R. Jeong, S.-C. Shin, J.-C. Kim and J.-D. Kim, Synthesis and characterization of superparamagnetic maghemite nanoparticles prepared by coprecipitation technique, J. Magn. Magn. Mater., 2004, 282, 147–150. Y. Deng, W. Yang, C. C. Wang and S. K. Fu, A novel approach for preparation of thermoresponsive polymer magnetic microspheres with core–shell structure, Adv. Mater., 2003, 15(20), 1729–1732. B. Polyak and G. Friedman, Magnetic targeting for site-specific drug delivery: applications and clinical potential, Expert Opin. Drug Delivery, 2009, 6(1), 53–70. D. K. Yi, S. T. Selvan, S. S. Lee, G. C. Papaefthymiou, D. Kundaliya and J. Y. Ying, Silica-coated nanocomposites of magnetic nanoparticles and quantum dots, J. Am. Chem. Soc., 2005, 127(14), 4990–4991. C. Zhang, Z. Mo, P. Zhang, C. Feng and R. Guo, Facile synthesis of porous carbon@ Fe3O4 composites and their applications in wastewater treatment, Mater. Lett., 2013, 106, 107–110. H. He and C. Gao, Supraparamagnetic, conductive, and processable multifunctional graphene nanosheets coated with high-density Fe3O4 nanoparticles, ACS Appl. Mater. Interfaces, 2010, 2(11), 3201–3210. J. Shen, Y. Hu, M. Shi, N. Li, H. Ma and M. Ye, One step synthesis of graphene oxide  magnetic nanoparticle composite, J. Phys. Chem. C, 2010, 114(3), 1498–1503. W.-Y. Rho, H.-M. Kim, S. Kyeong, Y.-L. Kang, D.-H. Kim and H. Kang, et al., Facile synthesis of monodispersed silica-coated magnetic nanoparticles, J. Ind. Eng. Chem., 2014, 20(5), 2646–2649. X. Hong, J. Li, M. Wang, J. Xu, W. Guo and J. Li, et al., Fabrication of magnetic luminescent nanocomposites by a layer-by-layer selfassembly approach, Chem. Mater., 2004, 16(21), 4022–4027. A. Gorschinski, G. Khelashvili, D. Schild, W. Habicht, R. Brand and M. Ghafari, et al., A simple aminoalkyl siloxane-mediated route to functional magnetic metal nanoparticles and magnetic nanocomposites, J. Mater. Chem., 2009, 19(46), 8829–8838. K. Somaskandan, T. Veres, M. Niewczas and B. Simard, Surface protected and modified iron based core-shell nanoparticles for biological applications, New J. Chem., 2008, 32(2), 201–209. H. Lu, G. Yi, S. Zhao, D. Chen, L.-H. Guo and J. Cheng, Synthesis and characterization of multi-functional nanoparticles possessing magnetic, up-conversion fluorescence and bio-affinity properties, J. Mater. Chem., 2004, 14(8), 1336–1341. V. Panwar, P. Kumar, A. Bansal, S. S. Ray and S. L. Jain, PEGylated magnetic nanoparticles (PEG@ Fe3O4) as cost effective alternative for

298

36. 37.

38.

39.

40.

41.

42.

43.

44.

45.

46.

47.

48.

Chapter 11

oxidative cyanation of tertiary amines via CH activation, Appl. Catal., A, 2015, 498, 25–31. S. Margel and H. Bamnolker Process for the preparation of microspheres and microspheres made thereby. US Patent 6, 103, 379, 2000. H. Kiwada, J. Sato, S. Yamada and Y. Kato, Feasibility of magnetic liposomes as a targeting device for drugs, Chem. Pharm. Bull., 1986, 34(10), 4253–4258. Y. Almog, S. Reich and M. Levy, Monodisperse polymeric spheres in the micron size range by a single step process, Br. Polym. J., 1982, 14(4), 131–136. A. P. Philipse, M. P. Van Bruggen and C. Pathmamanoharan, Magnetic silica dispersions: preparation and stability of surface-modified silica particles with a magnetic core, Langmuir, 1994, 10(1), 92–99. M. Bagherzadeh, M. Amrollahi and S. Makizadeh, Decoration of Fe 3 O 4 magnetic nanoparticles on graphene oxide nanosheets, RSC Adv., 2015, 5(128), 105499–105506. C. I. Justino, T. A. Rocha-Santos, S. Cardoso and A. C. Duarte, Strategies for enhancing the analytical performance of nanomaterial-based sensors, TrAC, Trends Anal. Chem., 2013, 47, 27–36. C. I. Justino, T. A. Rocha-Santos and A. C. Duarte, Review of analytical figures of merit of sensors and biosensors in clinical applications, TrAC, Trends Anal. Chem., 2010, 29(10), 1172–1183. N. Gan, X. Yang, D. Xie, Y. Wu and W. Wen, A disposable organophosphorus pesticides enzyme biosensor based on magnetic composite nano-particles modified screen printed carbon electrode, Sensors, 2010, 10(1), 625–638. J. Li, H. Gao, Z. Chen, X. Wei and C. F. Yang, An electrochemical immunosensor for carcinoembryonic antigen enhanced by self-assembled nanogold coatings on magnetic particles, Anal. Chim. Acta, 2010, 665(1), 98–104. X. Yang, F. Wu, D.-Z. Chen and H.-W. Lin, An electrochemical immunosensor for rapid determination of clenbuterol by using magnetic nanocomposites to modify screen printed carbon electrode based on competitive immunoassay mode, Sens. Actuators, B, 2014, 192, 529–535. Y. Xin, X. Fu-bing, L. Hong-wei, W. Feng, C. Di-zhao and W. Zhao-yang, A novel H2O2 biosensor based on Fe3O4–Au magnetic nanoparticles coated horseradish peroxidase and graphene sheets–Nafion film modified screen-printed carbon electrode, Electrochim. Acta, 2013, 109, 750–755. D. Chen, J. Deng, J. Liang, J. Xie, C. Hu and K. Huang, A core–shell molecularly imprinted polymer grafted onto a magnetic glassy carbon electrode as a selective sensor for the determination of metronidazole, Sens. Actuators, B, 2013, 183, 594–600. A. Prakash, S. Chandra and D. Bahadur, Structural, magnetic, and textural properties of iron oxide-reduced graphene oxide hybrids and

Functionalized MNPs in Detection Stage of Analysis/Miniaturization Devices

49.

50.

51.

52.

53.

54.

55. 56.

57.

58.

59.

60.

61.

299

their use for the electrochemical detection of chromium, Carbon, 2012, 50(11), 4209–4219. Y. Hu, Z. Zhang, H. Zhang, L. Luo and S. Yao, Selective and sensitive molecularly imprinted sol–gel film-based electrochemical sensor combining mercaptoacetic acid-modified PbS nanoparticles with Fe 3 O 4@ Au–multi-walled carbon nanotubes–chitosan, J. Solid State Electrochem., 2012, 16(3), 857–867. M. Arvand and M. Hassannezhad, Magnetic core–shell Fe3O4@ SiO2/ MWCNT nanocomposite modified carbon paste electrode for amplified electrochemical sensing of uric acid, Mater. Sci. Eng., C, 2014, 36, 160–167. X. Chen, J. Zhu, Z. Chen, C. Xu, Y. Wang and C. Yao, A novel bienzyme glucose biosensor based on three-layer Au–Fe3O4@ SiO2 magnetic nanocomposite, Sens. Actuators, B, 2011, 159(1), 220–228. T. T. Baby and S. Ramaprabhu, SiO2 coated Fe3O4 magnetic nanoparticle dispersed multiwalled carbon nanotubes based amperometric glucose biosensor, Talanta, 2010, 80(5), 2016–2022. ´. Lo ´s, M. A ´pez and A. Escarpa, Simplified calibration and M. Herva analysis on screen-printed disposable platforms for electrochemical magnetic bead-based inmunosensing of zearalenone in baby food samples, Biosens. Bioelectron., 2010, 25(7), 1755–1760. Z. Yang, C. Zhang, J. Zhang and W. Bai, Potentiometric glucose biosensor based on core–shell Fe3O4–enzyme–polypyrrole nanoparticles, Biosens. Bioelectron., 2014, 51, 268–273. T. A. Rocha-Santos, Sensors and biosensors based on magnetic nanoparticles, TrAC, Trends Anal. Chem., 2014, 62, 28–36. J. Li, Q. Xu, X. Wei and Z. Hao, Electrogenerated chemiluminescence immunosensor for Bacillus thuringiensis Cry1Ac based on Fe3O4@ Au nanoparticles, J. Agric. Food Chem., 2013, 61(7), 1435–1440. L.-G. Zamfir, I. Geana, S. Bourigua, L. Rotariu, C. Bala and A. Errachid, et al., Highly sensitive label-free immunosensor for ochratoxin A based on functionalized magnetic nanoparticles and EIS/SPR detection, Sens. Actuators, B, 2011, 159(1), 178–184. M. L. Yola, T. Eren and N. Atar, A novel and sensitive electrochemical DNA biosensor based on Fe@ Au nanoparticles decorated graphene oxide, Electrochim. Acta, 2014, 125, 38–47. Y. Wang, J. Dostalek and W. Knoll, Magnetic nanoparticle-enhanced biosensor based on grating-coupled surface plasmon resonance, Anal. Chem., 2011, 83(16), 6202–6207. R.-P. Liang, G.-H. Yao, L.-X. Fan and J.-D. Qiu, Magnetic Fe3O4@ Au composite-enhanced surface plasmon resonance for ultrasensitive detection of magnetic nanoparticle-enriched a-fetoprotein, Anal. Chim. Acta, 2012, 737, 22–28. J. Wang, D. Song, H. Zhang, J. Zhang, Y. Jin and H. Zhang, et al., Studies of Fe3O4/Ag/Au composites for immunoassay based on surface plasmon resonance biosensor, Colloids Surf., B, 2013, 102, 165–170.

300

Chapter 11

62. H. Zhang, Y. Sun, J. Wang, J. Zhang, H. Zhang and H. Zhou, et al., Preparation and application of novel nanocomposites of magnetic-Au nanorod in SPR biosensor, Biosens. Bioelectron., 2012, 34(1), 137–143. 63. L. Wang, Y. Sun, J. Wang, J. Wang, A. Yu and H. Zhang, et al., Preparation of surface plasmon resonance biosensor based on magnetic core/shell Fe3O4/SiO2 and Fe3O4/Ag/SiO2 nanoparticles, Colloids Surf., B, 2011, 84(2), 484–490. 64. S. Agrawal, K. Paknikar and D. Bodas, Development of immunosensor using magnetic nanoparticles and circular microchannels in PDMS, Microelectron. Eng., 2014, 115, 66–69. 65. D. Li, J. Wang, R. Wang, Y. Li, D. Abi-Ghanem and L. Berghman, et al., A nanobeads amplified QCM immunosensor for the detection of avian influenza virus H5N1, Biosens. Bioelectron., 2011, 26(10), 4146–4154. 66. Y. Wan, D. Zhang and B. Hou, Determination of sulphate-reducing bacteria based on vancomycin-functionalised magnetic nanoparticles using a modification-free quartz crystal microbalance, Biosens. Bioelectron., 2010, 25(7), 1847–1850. 67. J. Zhou, N. Gan, T. Li, H. Zhou, X. Li and Y. Cao, et al., Ultratrace detection of C-reactive protein by a piezoelectric immunosensor based on Fe3O4@ SiO2 magnetic capture nanoprobes and HRP-antibody coimmobilized nano gold as signal tags, Sens. Actuators, B, 2013, 178, 494–500. 68. N. Gan, L. Wang, T. Li, W. Sang, F. Hu and Y. Cao, A novel signalamplified immunoassay for myoglobin using magnetic core-shell Fe3O4@ Au-multi walled carbon nanotubes composites as labels based on one piezoelectric sensor, Integr. Ferroelectr., 2013, 144(1), 29–40. 69. Z.-Q. Shen, J.-F. Wang, Z.-G. Qiu, M. Jin, X.-W. Wang and Z.-L. Chen, et al., QCM immunosensor detection of Escherichia coli O157: H7 based on beacon immunomagnetic nanoparticles and catalytic growth of colloidal gold, Biosens. Bioelectron., 2011, 26(7), 3376–3381. 70. B. Srinivasan, Y. Li, Y. Jing, C. Xing, J. Slaton and J.-P. Wang, A threelayer competition-based giant magnetoresistive assay for direct quantification of endoglin from human urine, Anal. Chem., 2011, 83(8), 2996–3002. 71. Y. Li, B. Srinivasan, Y. Jing, X. Yao, M. A. Hugger and J.-P. Wang, et al., Nanomagnetic competition assay for low-abundance protein biomarker quantification in unprocessed human sera, J. Am. Chem. Soc., 2010, 132(12), 4388–4392. 72. T. Klein, J. Lee, W. Wang, T. Rahman, R. I. Vogel and J.-P. Wang, Interaction of domain walls and magnetic nanoparticles in giant magnetoresistive nanostrips for biological applications, IEEE Trans. Magn., 2013, 49(7), 3414–3417. 73. P. Zu, C. C. Chan, G. W. Koh, W. S. Lew, Y. Jin and H. F. Liew, et al., Enhancement of the sensitivity of magneto-optical fiber sensor by magnifying the birefringence of magnetic fluid film with Loyt-Sagnac interferometer, Sens. Actuators, B, 2014, 191, 19–23.

Functionalized MNPs in Detection Stage of Analysis/Miniaturization Devices

301

74. M. Deng, D. Liu and D. Li, Magnetic field sensor based on asymmetric optical fiber taper and magnetic fluid, Sens. Actuators, A, 2014, 211, 55–59. 75. H. J. Hathaway, K. S. Butler, N. L. Adolphi, D. M. Lovato, R. Belfon and D. Fegan, et al., Detection of breast cancer cells using targeted magnetic nanoparticles and ultra-sensitive magnetic field sensors, Breast Cancer Res., 2011, 13(5), R108. 76. D. Issadore, J. Chung, H. Shao, M. Liong, A. A. Ghazani and C. M. Castro, et al., Ultrasensitive clinical enumeration of rare cells ex vivo using a micro-hall detector, Sci. Transl. Med., 2012, 4(141), 141ra92–1ra92ra92. 77. J. Wang, Z. Zhu, A. Munir and H. S. Zhou, Fe3O4 nanoparticlesenhanced SPR sensing for ultrasensitive sandwich bio-assay, Talanta, 2011, 84(3), 783–788. 78. K. Duarte, C. I. Justino, A. C. Freitas, A. C. Duarte and T. A. Rocha-Santos, Direct-reading methods for analysis of volatile organic compounds and nanoparticles in workplace air, TrAC, Trends Anal. Chem., 2014, 53, 21–32. 79. Y. Xu and E. Wang, Electrochemical biosensors based on magnetic micro/nano particles, Electrochim. Acta, 2012, 84, 62–73. 80. K. Aguilar-Arteaga, J. Rodriguez and E. Barrado, Magnetic solids in analytical chemistry: a review, Anal. Chim. Acta, 2010, 674(2), 157–165. 81. K. Muzyka, Current trends in the development of the electrochemiluminescent immunosensors, Biosens. Bioelectron., 2014, 54, 393–407. 82. L. I. Silva, F. D. Ferreira, A. C. Freitas, T. A. Rocha-Santos and A. Duarte, Optical fiber biosensor coupled to chromatographic separation for screening of dopamine, norepinephrine and epinephrine in human urine and plasma, Talanta, 2009, 80(2), 853–857. ´a, I. Vidondo, F. J. Arregui, C. Bariain, A. Luquin and 83. C. Elosu M. Laguna, et al., Lossy mode resonance optical fiber sensor to detect organic vapors, Sens. Actuators, B, 2013, 187, 65–71. 84. L. I. Silva, T. A. Rocha-Santos and A. Duarte, Development of a fluorosiloxane polymer-coated optical fibre sensor for detection of organic volatile compounds, Sens. Actuators, B, 2008, 132(1), 280–289. 85. L. I. Silva, T. A. Rocha-Santos and A. Duarte, Comparison of a gas chromatography-optical fibre (GC-OF) detector with a gas chromatography-flame ionization detector (GC-FID) for determination of alcoholic compounds in industrial atmospheres, Talanta, 2008, 76(2), 395–399. 86. L. I. Silva, F. D. Ferreira, A. C. Freitas, T. A. Rocha-Santos and A. Duarte, Optical fibre-based micro-analyser for indirect measurements of volatile amines levels in fish, Food Chem., 2010, 123(3), 806–813. 87. M. Iranifam, Analytical applications of chemiluminescence-detection systems assisted by magnetic microparticles and nanoparticles, TrAC, Trends Anal. Chem., 2013, 51, 51–70.

302

Chapter 11

88. M. T. Gomes, T. A. Rocha, A. C. Duarte and J. P. Oliveira, Determination of sulfur dioxide in wine using a quartz crystal microbalance, Anal. Chem., 1996, 68(9), 1561–1564. 89. X. Wang, B. Ding, J. Yu, M. Wang and F. Pan, A highly sensitive humidity sensor based on a nanofibrous membrane coated quartz crystal microbalance, Nanotechnology, 2009, 21(5), 055502. 90. M. T. S. Gomes, T. A. Rocha, A. C. Duarte and J. A. Oliveira, Performance of a tetramethylammonium fluoride tetrahydrate coated piezoelectric crystal for carbon dioxide detection, Anal. Chim. Acta, 1996, 335(3), 235–238. 91. K. Chatterjee, S. Sarkar, K. J. Rao and S. Paria, Core/shell nanoparticles in biomedical applications, Adv. Colloid Interface Sci., 2014, 209, 8–39. 92. P. Freitas, R. Ferreira, S. Cardoso and F. Cardoso, Magnetoresistive sensors, J. Phys.: Condens. Matter, 2007, 19(16), 165221. 93. X. Sun, D. Ho, L.-M. Lacroix, J. Q. Xiao and S. Sun, Magnetic nanoparticles for magnetoresistance-based biodetection, IEEE Trans. Nanobiosci., 2011, 11(1), 46–53. 94. K. M. Danielsen and K. F. Hayes, pH dependence of carbon tetrachloride reductive dechlorination by magnetite, Environ. Sci. Technol., 2004, 38(18), 4745–4752. 95. T. Matsunaga, F. Ueki, K. Obata, H. Tajima, T. Tanaka and H. Takeyama, et al., Fully automated immunoassay system of endocrine disrupting chemicals using monoclonal antibodies chemically conjugated to bacterial magnetic particles, Anal. Chim. Acta, 2003, 475(1–2), 75–83. 96. H. Chen, C. Deng and X. Zhang, Synthesis of Fe3O4@ SiO2@ PMMA core–shell–shell magnetic microspheres for highly efficient enrichment of peptides and proteins for MALDI-ToF MS analysis, Angew. Chem. Int. Ed., 2010, 49(3), 607–611. 97. K. Aguilar-Arteaga, J. Rodriguez, J. Miranda, J. Medina and E. Barrado, Determination of non-steroidal anti-inflammatory drugs in wastewaters by magnetic matrix solid phase dispersion–HPLC, Talanta, 2010, 80(3), 1152–1157. 98. C. Huang and B. Hu, Silica-coated magnetic nanoparticles modified with g-mercaptopropyltrimethoxysilane for fast and selective solid phase extraction of trace amounts of Cd, Cu, Hg, and Pb in environmental and biological samples prior to their determination by inductively coupled plasma mass spectrometry, Spectrochim. Acta, Part B, 2008, 63(3), 437–444. 99. J. Dong, Z. Xu and F. Wang, Engineering and characterization of mesoporous silica-coated magnetic particles for mercury removal from industrial effluents, Appl. Surf. Sci., 2008, 254(11), 3522–3530. 100. P. Ashtari, K. Wang, X. Yang and S. J. Ahmadi, Preconcentration and separation of ultra-trace beryllium using quinalizarine-modified magnetic microparticles, Anal. Chim. Acta, 2009, 646(1–2), 123–127.

Functionalized MNPs in Detection Stage of Analysis/Miniaturization Devices

303

101. M. Khajeh, Synthesis of magnetic nanoparticles for analytical applications, Int. J. Environ. Anal. Chem., 2009, 89(7), 479–487. 102. M. Khajeh, Application of Box–Behnken design in the optimization of a magnetic nanoparticle procedure for zinc determination in analytical samples by inductively coupled plasma optical emission spectrometry, J. Hazard. Mater., 2009, 172(1), 385–389. 103. J. S. Suleiman, B. Hu, H. Peng and C. Huang, Separation/preconcentration of trace amounts of Cr, Cu and Pb in environmental samples by magnetic solid-phase extraction with Bismuthiol-IIimmobilized magnetic nanoparticles and their determination by ICPOES, Talanta, 2009, 77(5), 1579–1583. 104. H. Parham and N. Rahbar, Solid phase extraction–spectrophotometric determination of fluoride in water samples using magnetic iron oxide nanoparticles, Talanta, 2009, 80(2), 664–669. 105. S. Zhang, X.-Y. Li and J. P. Chen, Preparation and evaluation of a magnetite-doped activated carbon fiber for enhanced arsenic removal, Carbon, 2010, 48(1), 60–67. 106. N. Pourreza, H. Parham, A. Kiasat, K. Ghanemi and N. Abdollahi, Solid phase extraction of mercury on sulfur loaded with N-(2-chloro benzoyl)N 0 -phenylthiourea as a new adsorbent and determination by cold vapor atomic absorption spectrometry, Talanta, 2009, 78(4–5), 1293–1297. ´n, R. Galve, M.-P. Marco, S. Alegret and M. I. Pividori, 107. E. Zacco, J. Adria Electrochemical magneto immunosensing of antibiotic residues in milk, Biosens. Bioelectron., 2007, 22(9–10), 2184–2191. 108. L. Chen, J. Liu, Q. Zeng, H. Wang, A. Yu and H. Zhang, et al., Preparation of magnetic molecularly imprinted polymer for the separation of tetracycline antibiotics from egg and tissue samples, J. Chromatogr. A, 2009, 1216(18), 3710–3719. 109. L. Sun, L. Chen, X. Sun, X. Du, Y. Yue and D. He, et al., Analysis of sulfonamides in environmental water samples based on magnetic mixed hemimicelles solid-phase extraction coupled with HPLC–UV detection, Chemosphere, 2009, 77(10), 1306–1312. 110. H.-Y. Shen, Y. Zhu, X.-E. Wen and Y.-M. Zhuang, Preparation of Fe 3 O 4-C18 nano-magnetic composite materials and their cleanup properties for organophosphorous pesticides, Anal. Bioanal. Chem., 2007, 387(6), 2227–2237. 111. K. C. Ahn, P. Lohstroh, S. J. Gee, N. A. Gee, B. Lasley and B. D. Hammock, High-throughput automated luminescent magnetic particle-based immunoassay to monitor human exposure to pyrethroid insecticides, Anal. Chem., 2007, 79(23), 8883–8890. 112. M. Safarikova, P. Lunackova, K. Komarek, T. Hubka and I. Safarik, Preconcentration of middle oxyethylated nonylphenols from water samples on magnetic solid phase, J. Magn. Magn. Mater., 2007, 311(1), 405–408. 113. C.-Y. Hong and Y.-C. Chen, Selective enrichment of ochratoxin A using human serum albumin bound magnetic beads as the concentrating

304

114.

115.

116.

117.

118.

119.

120.

121.

122.

123.

124.

125.

Chapter 11

probes for capillary electrophoresis/electrospray ionization-mass spectrometric analysis, J. Chromatogr. A, 2007, 1159(1–2), 250–255. X. Zhao, Y. Cai, T. Wang, Y. Shi and G. Jiang, Preparation of alkanethiolate-functionalized core/shell Fe3O4@ Au nanoparticles and its interaction with several typical target molecules, Anal. Chem., 2008, 80(23), 9091–9096. X. Zhao, Y. Shi, T. Wang, Y. Cai and G. Jiang, Preparation of silicamagnetite nanoparticle mixed hemimicelle sorbents for extraction of several typical phenolic compounds from environmental water samples, J. Chromatogr. A, 2008, 1188(2), 140–147. Y. Ji, J. Yin, Z. Xu, C. Zhao, H. Huang and H. Zhang, et al., Preparation of magnetic molecularly imprinted polymer for rapid determination of bisphenol A in environmental water and milk samples, Anal. Bioanal. Chem., 2009, 395(4), 1125–1133. N. Jonker, A. Kretschmer, J. Kool, A. Fernandez, D. Kloos and J. Krabbe, et al., Online magnetic bead dynamic protein-affinity selection coupled to LC  MS for the screening of pharmacologically active compounds, Anal. Chem., 2009, 81(11), 4263–4270. H. Wang, J. Cao, Y. Bi, L. Chen and Q.-H. Wan, Magnetically immobilized frits for the preparation of packed columns used in capillary electrochromatography, J. Chromatogr. A, 2009, 1216(31), 5882–5887. Y. Liu, H. Li and J.-M. Lin, Magnetic solid-phase extraction based on octadecyl functionalization of monodisperse magnetic ferrite microspheres for the determination of polycyclic aromatic hydrocarbons in aqueous samples coupled with gas chromatography–mass spectrometry, Talanta, 2009, 77(3), 1037–1042. C. T. Yavuz, A. Prakash, J. Mayo and V. L. Colvin, Magnetic separations: from steel plants to biotechnology, Chem. Eng. Sci., 2009, 64(10), 2510–2521. D. Knopp, D. Tang and R. Niessner, Bioanalytical applications of biomolecule-functionalized nanometer-sized doped silica particles, Anal. Chim. Acta, 2009, 647(1), 14–30. K. Sugawara, A. Yugami and H. Kuramitz, Electrochemical monitoring of binding between wheat germ agglutinin and cellohexose-modified magnetic microbeads, Anal. Bioanal. Chem., 2009, 395(3), 767–772. Y.-C. Li, Y.-S. Lin, P.-J. Tsai, C.-T. Chen, W.-Y. Chen and Y.-C. Chen, Nitrilotriacetic acid-coated magnetic nanoparticles as affinity probes for enrichment of histidine-tagged proteins and phosphorylated peptides, Anal. Chem., 2007, 79(19), 7519–7525. Z.-Y. Ma, X.-Q. Liu, Y.-P. Guan and H.-Z. Liu, Synthesis of magnetic silica nanospheres with metal ligands and application in affinity separation of proteins, Colloids Surf., A, 2006, 275(1–3), 87–91. H. Chen, S. Liu, H. Yang, Y. Mao, C. Deng and X. Zhang, et al., Selective separation and enrichment of peptides for MS analysis using the microspheres composed of Fe3O4@ nSiO2 core and perpendicularly aligned mesoporous SiO2 shell, Proteomics, 2010, 10(5), 930–939.

Functionalized MNPs in Detection Stage of Analysis/Miniaturization Devices

305

126. H. Tsai, C. Hsu, I. Chiu and C. B. Fuh, Detection of C-reactive protein based on immunoassay using antibody-conjugated magnetic nanoparticles, Anal. Chem., 2007, 79(21), 8416–8419. 127. Z.-M. Liu, H.-F. Yang, Y.-F. Li, Y.-L. Liu, G.-L. Shen and R.-Q. Yu, Core– shell magnetic nanoparticles applied for immobilization of antibody on carbon paste electrode and amperometric immunosensing, Sens. Actuators, B, 2006, 113(2), 956–962. 128. Y. Cao, Q. Zhang, C. Wang, Y. Zhu and G. Bai, Preparation of novel immunomagnetic cellulose microspheres via cellulose binding domain-protein A linkage and its use for the isolation of interferon a-2b, J. Chromatogr. A, 2007, 1149(2), 228–235. 129. T. Matsunaga, K. Maruyama, H. Takeyama and T. Katoh, Highthroughput SNP detection using nano-scale engineered biomagnetite, Biosens. Bioelectron., 2007, 22(9–10), 2315–2321. 130. M. Marsza"", R. Moaddel, S. Kole, M. Gandhari, M. Bernier and I. Wainer, Ligand and protein fishing with heat shock protein 90 coated magnetic beads, Anal. Chem., 2008, 80(19), 7571–7575. 131. S. Bronzeau and N. Pamme, Simultaneous bioassays in a microfluidic channel on plugs of different magnetic particles, Anal. Chim. Acta, 2008, 609(1), 105–112. ´, Z. Kucˇerova ´ and M. Ticha ´, Peptide inhibitor modified 132. M. Filuszova magnetic particles for pepsin separation, J. Sep. Sci., 2009, 32(12), 2017–2021. 133. L. Wang and X. Gan, Antibody-functionalized magnetic nanoparticles for electrochemical immunoassay of a-1-fetoprotein in human serum, Microchim. Acta, 2009, 164(1–2), 231. 134. D. Qi, Y. Mao, J. Lu, C. Deng and X. Zhang, Phosphate-functionalized magnetic microspheres for immobilization of Zr4þ ions for selective enrichment of the phosphopeptides, J. Chromatogr. A, 2010, 1217(16), 2606–2617. 135. X. Wang, J.-M. Lin and X. Ying, Evaluation of carbohydrate antigen 50 in human serum using magnetic particle-based chemiluminescence enzyme immunoassay, Anal. Chim. Acta, 2007, 598(2), 261–267. 136. T.-B. Xin, S.-X. Liang, X. Wang, H. Li and J.-M. Lin, Determination of estradiol in human serum using magnetic particles-based chemiluminescence immunoassay, Anal. Chim. Acta, 2008, 627(2), 277–284. 137. Y. Okamoto, F. Kitagawa and K. Otsuka, Online concentration and affinity separation of biomolecules using multifunctional particles in capillary electrophoresis under magnetic field, Anal. Chem., 2007, 79(8), 3041–3047. 138. J. Richardson, P. Hawkins and R. Luxton, The use of coated paramagnetic particles as a physical label in a magneto-immunoassay, Biosens. Bioelectron., 2001, 16(9–12), 989–993. ´, Y. Ohlashennyy, J. Lenfeld, I. Rudolf and 139. B. Rittich, A. ˇ Spanova ´k, et al., Characterization of deoxyribonuclease I immobilized D. Hora

306

140.

141.

142.

143.

144.

145.

146.

147.

148.

149.

150. 151.

152.

Chapter 11

on magnetic hydrophilic polymer particles, J. Chromatogr. B., 2002, 774(1), 25–31. H. Ota, H. Takeyama, H. Nakayama, T. Katoh and T. Matsunaga, SNP detection in transforming growth factor-b1 gene using bacterial magnetic particles, Biosens. Bioelectron., 2003, 18(5–6), 683–687. T. Tanaka, K. Maruyama, K. Yoda, E. Nemoto, Y. Udagawa and H. Nakayama, et al., Development and evaluation of an automated workstation for single nucleotide polymorphism discrimination using bacterial magnetic particles, Biosens. Bioelectron., 2003, 19(4), 325–330. T. Yoshino, T. Tanaka, H. Takeyama and T. Matsunaga, Single nucleotide polymorphism genotyping of aldehyde dehydrogenase 2 gene using a single bacterial magnetic particle, Biosens. Bioelectron., 2003, 18(5–6), 661–666. P. Ashtari, X. He, K. Wang and P. Gong, An efficient method for recovery of target ssDNA based on amino-modified silica-coated magnetic nanoparticles, Talanta, 2005, 67(3), 548–554. S. Dubus, J.-F. Gravel, B. Le Drogoff, P. Nobert, T. Veres and D. Boudreau, PCR-free DNA detection using a magnetic bead-supported polymeric transducer and microelectromagnetic traps, Anal. Chem., 2006, 78(13), 4457–4464. M. J. Archer, B. Lin, Z. Wang and D. A. Stenger, Magnetic bead-based solid phase for selective extraction of genomic DNA, Anal. Biochem., 2006, 355(2), 285–297. Z. Cao, Z. Li, Y. Zhao, Y. Song and J. Lu, Magnetic bead-based chemiluminescence detection of sequence-specific DNA by using catalytic nucleic acid labels, Anal. Chim. Acta, 2006, 557(1–2), 152–158. S. W. Yeung and I.-M. Hsing, Manipulation and extraction of genomic DNA from cell lysate by functionalized magnetic particles for lab on a chip applications, Biosens. Bioelectron., 2006, 21(7), 989–997. M. Fuentes, C. Mateo, A. Rodriguez, M. Casqueiro, J. C. Tercero and H. H. Riese, et al., Detecting minimal traces of DNA using DNA covalently attached to superparamagnetic nanoparticles and direct PCR-ELISA, Biosens. Bioelectron., 2006, 21(8), 1574–1580. X. Xu, D. G. Georganopoulou, H. D. Hill and C. A. Mirkin, Homogeneous detection of nucleic acids based upon the light scattering properties of silver-coated nanoparticle probes, Anal. Chem., 2007, 79(17), 6650–6654. K. D. Barbee and X. Huang, Magnetic assembly of high-density DNA arrays for genomic analyses, Anal. Chem., 2008, 80(6), 2149–2154. T. R. Sarkar and J. Irudayaraj, Carboxyl-coated magnetic nanoparticles for mRNA isolation and extraction of supercoiled plasmid DNA, Anal. Biochem., 2008, 379(1), 130–132. K.-Y. Lien, C.-J. Liu, P.-L. Kuo and G.-B. Lee, Microfluidic system for detection of a-thalassemia-1 deletion using saliva samples, Anal. Chem., 2009, 81(11), 4502–4509.

Functionalized MNPs in Detection Stage of Analysis/Miniaturization Devices

307

153. H.-P. Zhang, S. Bai, L. Xu and Y. Sun, Fabrication of mono-sized magnetic anion exchange beads for plasmid DNA purification, J. Chromatogr. B., 2009, 877(3), 127–133. ´nkova ´, A. ˇ ´, R. Pantu ´k, J. Dosˇkarˇ and ˚ˇ 154. J. Kaha Spanova cek, D. Hora B. Rittich, Extraction of PCR-ready DNA from Staphylococcus aureus bacteriophages using carboxyl functionalized magnetic nonporous microspheres, J. Chromatogr. B., 2009, 877(7), 599–602. 155. R. Shi, Y. Wang, Y. Hu, L. Chen and Q.-H. Wan, Preparation of magnetite-loaded silica microspheres for solid-phase extraction of genomic DNA from soy-based foodstuffs, J. Chromatogr. A, 2009, 1216(36), 6382–6386. 156. S. H. Lim, F. Bestvater, P. Buchy, S. Mardy and A. D. C. Yu, Quantitative analysis of nucleic acid hybridization on magnetic particles and quantum dot-based probes, Sensors, 2009, 9(7), 5590–5599. 157. L. Zhang, Z. Zhang and Q. Wan, Preparation of porous magnetic silica microspheres and their application in genomic deoxyribonucleic acids extraction, Chin. J. Anal. Chem., 2006, 34(7), 923–927. 158. Z. Saiyed, M. Parasramka, S. Telang and C. Ramchand, Extraction of DNA from agarose gel using magnetic nanoparticles (magnetite or Fe3O4), Anal. Biochem., 2007, 2(363), 288–290. 159. K. E. McCloskey, J. J. Chalmers and M. Zborowski, Magnetic cell separation: characterization of magnetophoretic mobility, Anal. Chem., 2003, 75(24), 6868–6874. 160. R. Veyret, A. Elaissari, P. Marianneau, A. A. Sall and T. Delair, Magnetic colloids for the generic capture of viruses, Anal. Biochem., 2005, 346(1), 59–68. 161. W. Chen, H. Shen, X. Li, N. Jia and J. Xu, Synthesis of immunomagnetic nanoparticles and their application in the separation and purification of CD34 þ hematopoietic stem cells, Appl. Surf. Sci., 2006, 253(4), 1762–1769. 162. M. Kuhara, H. Takeyama, T. Tanaka and T. Matsunaga, Magnetic cell separation using antibody binding with protein A expressed on bacterial magnetic particles, Anal. Chem., 2004, 76(21), 6207–6213. 163. S. Yitzhaki, E. Zahavy, C. Oron, M. Fisher and A. Keysary, Concentration of Bacillus spores by using silica magnetic particles, Anal. Chem., 2006, 78(18), 6670–6673. 164. J. E. Smith, C. D. Medley, Z. Tang, D. Shangguan, C. Lofton and W. Tan, Aptamer-conjugated nanoparticles for the collection and detection of multiple cancer cells, Anal. Chem., 2007, 79(8), 3075–3082. 165. K. Maruyama, H. Takeyama, T. Mori, K. Ohshima, S.-I. Ogura and T. Mochizuki, et al., Detection of epidermal growth factor receptor (EGFR) mutations in non-small cell lung cancer (NSCLC) using a fully automated system with a nano-scale engineered biomagnetite, Biosens. Bioelectron., 2007, 22(9–10), 2282–2288. 166. J. Wu, Z. Ye, G. Wang and J. Yuan, Multifunctional nanoparticles possessing magnetic, long-lived fluorescence and bio-affinity

308

167.

168.

169.

170.

171.

172.

173.

174.

175.

176.

177.

178.

Chapter 11

properties for time-resolved fluorescence cell imaging, Talanta, 2007, 72(5), 1693–1697. J.-C. Liu, P.-J. Tsai, Y. C. Lee and Y.-C. Chen, Affinity capture of uropathogenic Escherichia coli using pigeon ovalbumin-bound Fe3O4@ Al2O3 magnetic nanoparticles, Anal. Chem., 2008, 80(14), 5425–5432. B. C. Kim, M. K. Ju, A. Dan-Chin-Yu and P. Sommer, Quantitative detection of HIV-1 particles using HIV-1 neutralizing antibody-conjugated beads, Anal. Chem., 2009, 81(6), 2388–2393. W.-J. Chen, P.-J. Tsai and Y.-C. Chen, Functional nanoparticle-based proteomic strategies for characterization of pathogenic bacteria, Anal. Chem., 2008, 80(24), 9612–9621. T. Yoshino, F. Kato, H. Takeyama, M. Nakai, Y. Yakabe and T. Matsunaga, Development of a novel method for screening of estrogenic compounds using nano-sized bacterial magnetic particles displaying estrogen receptor, Anal. Chim. Acta, 2005, 532(2), 105–111. T. Yoshino, C. Kaji, M. Nakai, F. Saito, H. Takeyama and T. Matsunaga, Novel method for evaluation of chemicals based on ligand-dependent recruitment of GFP labeled coactivator to estrogen receptor displayed on bacterial magnetic particles, Anal. Chim. Acta, 2008, 626(1), 71–77. Y. Xu, L. Chen, H. Wang, X. Zhang, Q. Zeng and H. Xu, et al., Preparation of magnetic strong cation exchange resin for the extraction of melamine from egg samples followed by liquid chromatography– tandem mass spectrometry, Anal. Chim. Acta, 2010, 661(1), 35–41. C.-L. Mao, K. D. Zientek, P. T. Colahan, M.-Y. Kuo, C.-H. Liu and K.-M. Lee, et al., Development of an enzyme-linked immunosorbent assay for fentanyl and applications of fentanyl antibody-coated nanoparticles for sample preparation, J. Pharm. Biomed. Anal., 2006, 41(4), 1332–1341. Y. Okamoto, Y. Ikawa, F. Kitagawa and K. Otsuka, Preparation of fritless capillary using avidin immobilized magnetic particles for electrochromatographic chiral separation, J. Chromatogr. A, 2007, 1143(1–2), 264–269. M. E. Piyasena, L. J. Real, R. A. Diamond, H. H. Xu and F. A. Gomez, Magnetic microsphere-based methods to study the interaction of teicoplanin with peptides and bacteria, Anal. Bioanal. Chem., 2008, 392(5), 877–886. Y. Liu and L. Jia, Analysis of estrogens in water by magnetic octadecylsilane particles extraction and sweeping micellar electrokinetic chromatography, Microchem. J., 2008, 89(1), 72–76. M. Tudorache and C. Bala, Sensitive aflatoxin B1 determination using a magnetic particles-based enzyme-linked immunosorbent assay, Sensors, 2008, 8(12), 7571–7580. ´. Lo ´s, M. A ´pez and A. Escarpa, Electrochemical microfluidic M. Herva chips coupled to magnetic bead-based ELISA to control allowable levels of zearalenone in baby foods using simplified calibration, Analyst, 2009, 134(12), 2405–2411.

Functionalized MNPs in Detection Stage of Analysis/Miniaturization Devices

309

179. Y. Sha, C. Deng and B. Liu, Development of C18-functionalized magnetic silica nanoparticles as sample preparation technique for the determination of ergosterol in cigarettes by microwave-assisted derivatization and gas chromatography/mass spectrometry, J. Chromatogr. A, 2008, 1198, 27–33. 180. L. Chen, X. Zhang, Y. Xu, X. Du, X. Sun and L. Sun, et al., Determination of fluoroquinolone antibiotics in environmental water samples based on magnetic molecularly imprinted polymer extraction followed by liquid chromatography–tandem mass spectrometry, Anal. Chim. Acta, 2010, 662(1), 31–38. 181. B. Buchholz, H. Tuazon, M. Kaminski, S. Aase, L. Nufiez and G. Vandegrift, Optimizing the coating process of organic actinide extractants on magnetically assisted chemical separation particles, Sep. Purif. Technol., 1997, 11(3), 211–219. 182. P. Ashtari, K. Wang, X. Yang, S. Huang and Y. Yamini, Novel separation and preconcentration of trace amounts of copper (II) in water samples based on neocuproine modified magnetic microparticles, Anal. Chim. Acta, 2005, 550(1–2), 18–23. 183. E. Barrado, M. Vega, R. Pardo, P. Grande and J. Del Valle, Optimisation of a purification method for metal-containing wastewater by use of a Taguchi experimental design, Water Res., 1996, 30(10), 2309–2314. 184. E. Barrado, J. Montequi, J. Medina, R. Pardo and F. Prieto, Electrochemical study of iron ferrite sludge obtained under the conditions proposed for the purification of waste water at a carbon paste electrode, J. Electroanal. Chem., 1998, 441(1–2), 227–235.

CHAPTER 12

MNP-based Sensor Development to Evaluate Food Quality and Safety L. MADDALONI,a M. RAPA,a R. RUGGIERI,a M. SANTONICOb AND G. VINCI*a a

Department of Management, Sapienza University of Rome, Rome, Italy; Unit of Electronics for Sensor Systems, Department of Science and Technology for Humans and the Environment, Campus Bio-Medico University of Rome, Rome, Italy *Email: [email protected]

b

12.1 Introduction Consumer expectations for safe and high-quality products have gradually grown over time, due to the direct impact that these two aspects have on health. Food quality is defined as a set of aspects, which all contribute together to the general definition of quality.1 Food quality is characterized by hygienic, sanitary, chemical, nutritional, organoleptic, legal and originrelated factors.2 As the basis of food quality, food safety is an essential prerequisite.3 Food quality can be subjective or objective. The former is requested by consumers and is mainly linked to the consumers expectations and tastes. While the latter is requested by the supermarket chain sector and is mainly based on the chemical-physical characteristics of food, closely related to the food manufacturing process and storage.1,4 Internationally, the need to

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standardize food safety and quality parameters was born. To tackle this problem, the World Health Organization (WHO) and Food and Agriculture Organization (FAO) established a document, called the ‘‘Codex Alimentarius’’, which provides international harmonization of food safety legislation and supports the aim of ensuring ‘‘safe’’ and ‘‘quality’’ food.2 Under the pressure of WHO and FAO, and following serious health accidents, such as Bovine Spongiform Encephalopathy (BSE), greater attention has been paid to these two aspects.5,6 These health crises have also allowed the development of an integrated approach that allows attention to be focused on risk assessment.7 As a result, the idea arose that food safety and quality are shared responsibilities, which must be monitored along the entire supply chain, from agricultural production to consumption.8 To facilitate food industries in exchanges between different countries, certifications and standards have been defined. These standards allow harmonizing the requirements necessary by the various international regulations (Table 12.1). To address the needs of consumers and producers, different types of chemical indicators (product and process markers) have been proposed. These markers can describe, at the molecular level, the changes that occur in food along the entire supply chain.15,16 Food characterization through objective and analytically measurable parameters is very useful to enhance the product and defend it on the market.17 Nowadays, product and/or process marker analyses are carried out by analytical instrumentation. Certified analytical instruments are defined by national and international legislation, which identify, not only the markers to be found in food, but also methods to be followed for sample analysis.18 The most commonly used methods, such as chromatography19 and mass spectrometry,20 require expensive instrumentation and qualified technicians. Therefore, food analysis requires the rise of new methods that not Table 12.1

International food quality and safety certification.

Certification ISO 9001:2015

Features

Iinternationally recognized reference standard for quality management. ISO 22000:2018 The standard specifies the requirements for a Food Safety Management System (FSMS) to enable an organization directly or indirectly involved in the food chain. ISO 22005:2008 iInternational reference document for the certification of agri-food traceability systems. BRC Specific standards for food safety and with the aim to define the food safety and quality requirements necessary to ensure the correct application of mandatory regulations and consumer performance. IFS The IFS (International Food Standard) aims to promote the effective selection of food suppliers branded by the GDO, based on their ability to provide safe products, complying with contract specifications and legal requirements.

Ref. 9 10,11 12 13

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only allow rapid and cheaper identification of molecular markers, but which are also robust, sensitive and selective.21 Thus, in recent years new innovative method development, such as sensors and NIR are introducing major changes in the agri-food field. Among them all, sensor systems are new analysis methods that present environmental and economic sustainability features. These devices contribute significantly to simplifying measurement processes and to the reliability and precision of measurement results.22 In the manufacturing and agro-food sectors, this instrumentation is widely used in monitoring production processes, in food safety and quality control and to simplify the operator’s work.23 However, the use of magnetic nanoparticle-based sensors, in this manufacturing field, are not yet widespread. This chapter highlights the recent applications of these devices in the agri-food field and their applications in food quality and safety along the entire supply chain.

12.2 Sensors Sensors are devices that have the capability to ‘‘receive and respond to a signal or stimulus’’.24 These devices have been studied extensively over the last decade, thanks to their small size, wide versatility and low cost. The Scopus database, using the search word ‘‘sensor’’, shows how publication numbers have grown exponentially in recent years (Figure 12.1A). When searching for the phrase ‘‘magnetic nanoparticles’’ the publication trend is similar to that for ‘‘sensor’’ (Figure 12.1B). In recent years, the trend in number of publications makes it possible to highlight an increase in the interest of the scientific community concerning these two new technologies. However, in the Scopus database when searching using both the words ‘‘sensors’’ and ‘‘magnetic nanoparticles’’, the number of publications is significantly lower, although there is a growing interest in the combined use of these two technologies in scientific research studies (Figure 12.1C). Though in the ‘‘food’’ field the number of publications regarding the application of these two technologies is lower and is equivalent to 0.2% of the total publications on ‘‘magnetic nanoparticles’’ and 0.02% of the total studies on ‘‘sensors’’ (Figure 12.1D).

12.2.1

Sensor Classification and Properties

New technology advances have made it possible to develop low-cost and high-performance electronic measuring devices. These instruments are used in most measurement processes to increase both the reliability and the precision of the results. Sensors are instruments that are part of a complex measurement system.25 Generally, these systems are formed by characterizing elements in a chain, both for their analysis specificity and the field used. Figure 12.2 shows a block diagram of a general sensor system.24,26

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Chapter 12 Physical, chemical and biological property to be measured

IMPUT

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Figure 12.2 Table 12.2

Block diagram of a general sensor system. Classification of the sensor system.

Classification based on: Properties capable Physical (e.g., temperature, acceleration, pressure, etc.); of detecting Chemical (e.g., quantity of chemicals, pH, etc.); Biological (e.g., number or type of cells, cellular respiration, etc.). Application field e.g., environmental, food, industrial, biomedical, etc. Transducer type Primary or ‘‘fundamental’’ (directly convert the input quantity into an electrical output signal); Secondary (depend on the primary ones, transform the output quantity of a primary transducer into an electrical quantity). Transducer output Active (transducers that generate an electrical signal or voltage, e.g., thermocouples); Passive (transducers that modify output as an electrical parameter, e.g., resistance, capacity, etc.) Output signal Analog (the output changes continuously as the input size changes); Digital (variable output to be measured is provided by a binary code e.g., On–Off sensors).

The elements that make up a measuring system are: 1. The sensor, i.e., the system interface that comes into contact with the physical, chemical and biological sample to be measured (input). 2. The transducer, which allows changing one signal into another, generally in an electrical parameter. 3. The signal conditioning, which allows the treatment of the signal, through conversion, amplification and/or filtering operations. An actuator system (not shown in Figure 12.2) can be connected to the latter system, which allows changes to be made to the sensor control process, based on changes in the measured input.27 The sensors can be classified on the basis of different device features. Table 12.2 shows the main classifications of these devices based on their properties.27,28 These devices have representative properties that affect sensor performances. The fundamental parameters that characterize the sensors are:24,25 – Response curve, which provides a graphical representation of the sensor response to the measurand;

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– Sensitivity, which is the ratio between the output signal and the measured property; – Noise, which is the random fluctuation of the input signal leading to a random fluctuation output signal; – Resolution, defined as the minimum quantity of measurand that generates a quantifiable signal; – Resolution, which is the slightest variation in measurand that involves a variation of sensor output; – Selectivity, which is the sensor’s ability to provide an output signal that is influenced as little as possible by changes in environmental conditions or other parameters; – Specificity, which is the ability to react with a specific analyte and not with others that may be present in the measurement environment; – Reproducibility, which is defined as the ability of the sensor to respond in the same way following exposure to the same measurand; – Response time, which is time to reach the steady state following the interaction with the measurand.

12.2.2

NP Properties for NP-based Sensors

MNPs (1–100 nm) have small dimension characteristics and the ability to change their properties (colorimetric, fluorescent and electrochemical) according to the environment in which they are placed.29 Sensors, when interacting with the analytes being searched for, modify their properties, allowing an electrochemical or optical signal to be generated, which can then be detected. This allows the presence and concentration of target analytes to be detected. The advantages in the combined use of MNPs and sensors increase the selectivity and sensitivity of analytical methods, thus improving the system performance.31–33 The main characteristics that NPs, specifically MNPs, must possess are a high surface/volume ratio, high adsorption and monodispersity. Thanks to these properties, the target analyte will move rapidly towards the MNPs, coupled to the sensor surface. After analyte–MNP–sensor interaction, a detectable signal will be generated by the sensor system. Significant for the MNP-based sensors response are the dimensions of the MNPs, which determine their optical and/ or electrochemical characteristics.34,35

12.3 MNP-based Sensor The possibility of applying nanotechnologies in the food quality and food safety field has received noteworthy attention by scientific researchers. The rapid and accurate monitoring of these two aspects allows one to prevent and mitigate the impact that a lack of control of food quality and safety can have on human health.28 However, in the last decade nanotechnology applications have gradually grown, mainly to detect contaminants and antimicrobials or to monitor the presence of antioxidants in food.29 Therefore,

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nanomaterials play an essential role in food protection, monitoring and preservation.30 Among the nanomaterials, magnetic nanoparticles (MNPs) have attracted particular attention for their properties (biocompatibility, environmentally safe, no toxicity, inexpensive to produce, etc.) compared to traditional laboratory analysis methods. For these reasons, the possibility of developing sensors combined with MNPs has been studied, to advance the creation of rapid, sensitive, accurate and low-cost methods.31 The MNPbased sensors allow non-destructive analyses and automated methods, facilitating not only the operator’s work, but also allowing their application in the industrial field.32–34

12.3.1

MNP-based Sensors for Food Safety

In recent years, consumers have been paying close attention to food safety. For this reason, it is necessary to improve robust analysis systems that support control systems in the food safety field.35 As such, new methods have been developed to monitor food safety.36,37 The studies conducted in food products were carried out for the identification and monitoring of compounds that are harmful to human health (Table 12.3). Particular attention has been paid to the presence of antibiotics in foods. Drugs that have been studied are Tetracycline (TC) and Doxycycline (DC). Yakout et al. in 2016, developed an electrochemical MNP-based sensor, in which the MNPs were functionalized with ß-cyclodextrin, to make the interaction between the target antibiotics and MNPs more selective. The device, applied in milk samples, which had undergone different heat treatments, managed to work in a concentration range from 0.5–90.0 ng L1.38 Metronidazole (MNZ) is an antibiotic that is used to treat bacterial or protozoa infections, however, today its use is no longer allowed in many countries, because it can cause genotoxic, carcinogenic and mutagenic effects. An electrochemical sensor for its detection in milk and honey samples was developed. The device consists of a modified magnetic glassy carbon electrode (MGCE) with molecular imprinted polymers (MIP), to which the MNPs have been linked.39 Ractopamine (RAC) is an antibiotic that is often used illegally in addition to animal feed to improve protein acceptance and reduce body fat deposition. A disposable sensor has been developed for its rapid detection in pork meat and liver. This device is made up of a screen-printed magnetic electrode (MSPE) functionalized with Fe3O4-MNPs.40 Another drug that can cause serious effects on human health is Kanamycin. Long et al. in 2015 developed a magnetic imprinted electrochemical sensor, functionalized with MIP modified with MNPs (Fe3O4-NPs). The sensor demonstrated the ability to respond to low analyte concentrations (1.01010–1.0106 M) in different food.41 Particular interest has been placed in developing sensors for dibutyl phthalate (DPB) detection in different types of food. These compounds used in various industrial sectors are

MNP-based sensors for food safety assessment.

Sensor type for food safety Electrochemical sensor

Assay principle Impedentiometric

Sample

Voltametric

Dichlorodiphenyl Radish trichloroethane Ractopamine Pork meat and liver Pathogenic bacteria Apple juice and portable water Sunset Yellow Candy, chocolate, peach juice powder, orangeflavored jelly powder and soft drinks Cu(II) Oil, sugar, tea and water Natural milk, skimmed Tetracycline and milk, semi- skimmed doxycycline milk, full-fat milk antibiotics Chrysoidine Spiked water

Voltametric

Sudan I

Voltametric Voltametric

Metronidazole Dibutylphtalate

Voltametric

Sunset yellow

Voltammetric Impedentiometric Voltammetric

Voltametric Voltametric

Optical sensor

Analyte

MNPs Types

Ref.

110 – M 610 1103 M 0.005–100 mM 13 nM 1–103 CFU mL1 1 CFU mL1



49

MGO/b-CD/ IL/AuNPs

0.0085–30 mM

5.5 nM



CoFe3O4-NPs b-CDMGONPs

1–250 mg Kg1 0.5–90.0 ng L1

0.09 mg Kg1 — 0.18 ng L1 25 min

51 38

1.7108 M

15 min

48

0.001 mM



47

1.6108 M 0.052 ng L1

10 min 25 min

39 42

2109 M



46

20 min

43

2.31011 M 15 min

41

2.3 ng mL1 — 2.09109 M —

50 44

13.8 mg Kg1 —

52

Fe3O4-NPs Fe3O4-NPs

MGO/5.0108– CD@AuNPs 5.0106 M Fe3O4-NPs 0.01–20 mM

Voltametric

Dibutylphtalate

Chilli, ketchup, strawberry sauce, tomato sauce, duck egg yolk Milk and honey Spiked milk and soybean milk Spiked water and fruit drinks Spiked drinks

Voltametric

Kanamycin

Spiked food

Fe3O4-NPs

Colorimetric l-cyhalothrin Chemiluminescent Dibutylphthalate

Honey Drink sample

Fe3O4-NPs Fe3O4-NPs

Refractometric

Meat and fish

Ag-NPs and Au-NPs

Volatile biogenic amine

Fe3O4-NPs Fe3O4-NPs Fe3O4-NPs Fe3O4-NPs

LOD

11

5108–106 M 1108–1103 g L1 5109– 2106 M 2.5109– 106 M 11010– 1106 M 0–50 nM 3.84108– 2.08105 M 0.1–200 mg Kg1

12

810

10

M

o1 min 40 25 min 53 45

317

Time

Fe3O4-NPs

Working range

MNP-based Sensor Development to Evaluate Food Quality and Safety

Table 12.3

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ubiquitous environmental pollutants. DPBs can cause harmful effects to human health by interacting with the endocrine system. Zhang et al. in 2013 and Li et al. in 2015 developed a voltammetric sensor functionalized with Fe3O4-MNPs. These devices have short analysis times, of less than 25 minutes and the ability to determine low analyte concentrations (1.01010 M).42,43 Instead, Qiu et al. in 2013 advanced an optical sensor based on chemiluminescence, in which the device has functionalized MIPMNPs to make it more selective towards DPB. This system showed good response capabilities, resulting from a linear range between 3.84108 to 2.08105 M.44 Additives are added to food that can improve some of the food features, such as color, flavor or shelf life. However, their excessive use can have dangerous effects on human health. For this reason, sensors combined with MNPs have been developed to allow their rapid identification and quantification. Voltammetric sensors for Sunset Yellow (SY) dye determination were developed. These sensors use Fe3O4-MNPs to functionalize glass carbon electrode (GCE).45,46 Furthermore, electrochemical sensors, which apply the use of functionalized GCE electrodes, have been developed for Sudan I additive detection in chili sauce, ketchup sauce, strawberry sauce and tomato sauce.47 Another additive sensor was developed for Chrysoidine detection in water. This sensor is based on the voltammetry principle and uses MGO/-CD@AuNPs linked on the MIP surface. The Chrysoidine sensor has been shown to have a good linear range (5.0108–5.0106 M).48 As well as additives, sensors combined with MNPs have been developed for pesticide control in food. Miao et al. in 2020 developed an impedance sensor for Dichlorobiphenyl trichloroethane (DDT) determination, an insecticide widely used in agriculture. In this study, Fe4O4-MNPs were used to expand the sensor selectivity. The sensor has a working range between 1.01011–1.0103 M.49 Another sensor combined with MNPs was developed by Gao et al. in 2014 for l-cyhalothrin determination in honey samples. This device is an optical sensor, based on the chemiluminescence principle. In this device, the sensor surface has been modified with MIP, to which MNPs have been linked.50 Given the importance of protecting human health, studies have been carried out for sensor system development for heavy metals analysis in different food matrices (drinking water, sugar, oil and tea). An electrochemical sensor functionalized with CoFe2O4-MNPs for the identification of Cu(II) was developed.51 Tseng et al. in 2017 developed a refractometric optical sensor functionalized with gold and silver magnetic nanoparticles, for volatile biogenic amines (VBAs) detection in meat and fish samples. These compounds, if taken in high quantities, can cause allergic reactions. This device showed a good working range (0.1–200 mg Kg1) and LOD equal to 13.8 mg Kg1.52 Of particular importance is electrochemical sensors for pathogenic microorganism (E. coli, S. aureus and S. typhi) detection in drinking water and apple juice samples.

MNP-based sensor for food quality.

Sensor Types Assay for food quality principle Optic sensor

Analyte

Colorimetric Caffeine

Electrochemical Resistivity sensor Resistivity

Could Chain Volatile organic compounds

Sample

MNPs Types

Working range 1

LOD

Bottle of Black Ag–Fe3O4-NPs 0.2–30 mg mL 5.010 and green tea, Coca-Cola Spiked food Co-NPs — — 2.5–250 mg Kg1 — Food degradation Fe3O4-NPs

Time 6

mg mL

1

Ref.

10 min 56 — —

57 58

MNP-based Sensor Development to Evaluate Food Quality and Safety

Table 12.4

319

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Wilson et al. in 2019 modified SPE electrodes with MNPs to which the antimicrobial peptide melittin (MLT) has been linked to make it further selective. The advantage of this sensor is the possibility of not having sample treatments.53

12.3.2

MNP-based Sensors for Food Quality

The food quality assessment process is a difficult aspect to control in food industries. The numerous aspects (appearance, consistency, flavor, nutrient content, etc.) which characterize food quality need to be taken into consideration for its monitoring.35,36 The use of MNP-based sensors as a food quality monitoring device is still weakly applied, even if these new devices have significant advantages in terms of time and analysis costs.54,55 MNP-based sensors applied in food quality evaluation are shown in Table 12.4. As for food quality evaluation the MNP-based sensors developed are colorimetric and electrochemical sensors. In particular, Deng et al. (2019) developed a specific optical sensor for caffeine detection in beverages. These devices are based on the possibility of immobilizing Fe3O4-MNPs on a molecular imprinted polymer (MIP) substrate. Following Ag-NPs interaction with caffeine, sensors modify the absorption at a specific wavelength.56 Moreover, MNP-based sensors based on electrochemical principles have been developed. Kenning et al. in 2014 applied Co-MNPs to monitor the cold chain in milk samples using the radio frequency principle.57 A RFID sensor was a thermally activated Time-Temperature Indicator (TTI). In addition, Tung et al., 2014, developed a chemo-resistive quantum vapor sensor for volatile organic compounds (VOCs), since these analytes are specific markers for food degradation. The device consists of the union of MNPs, graphene oxide and poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT), whose properties allow the sensor to be applied on the packaging, permitting food degradation to be applied during storage.58

12.4 Conclusion Food quality and safety are two important aspects that the food industry must be able to guarantee and respect for its products. To assist the food sector in ensuring and monitoring these two aspects, laboratory analytical methods have been developed to monitor food. However, in recent years, new technologies have shown great potential in supporting traditional laboratory methods. Among these new technologies, the combined use of magnetic nanoparticles (MNPs) and sensors stand out increasingly more, as these devices allow rapid, non-destructive analyses to be carried out in real time and at low cost. MNP-based sensor use allows devices with excellent advantages compared to conventional laboratory analyses, in terms of assay time, sensitivity, selectivity and cost. The MNPs used are small and have a high surface-to-volume ratio, features that allow them to be applied in

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sensors, thus expanding the device’s ability to interact with the target analyte. The possibility of applying MNPs to sensors is possible through an accurate study of molecule targets, and thanks to their chemical–physical characteristics, the possibility to integrate MNPs into optical, colorimetric and electrochemical sensors is evaluated. Sensors functionalized with MNPs have been applied for antibiotics, pesticides, illegal food additives, heavy metals and caffeine detection in food. However, the application of MNPbased sensors for monitoring and evaluating food quality and safety requires further exploration in the future.

References 1. K. G. Grunert, in European Review of Agricultural Economics, 2005. 2. European Food Safety Authority (EFSA) Panel on Biological Hazards (BIOHAZ), Scientific Opinion on risk based control of biogenic amine formation in fermented foods, EFSA J., 2011, 9(10), 2393–2486. 3. G. Molnar and S. B. Godefroy, Food Control, 2020, 115, 107206. 4. C. Peri, The universe of food quality, Food Qual. Prefer., 2005, 17, 3–8. 5. L. Goodridge, J. Chen and M. Griffiths, The use of a fluorescent bacteriophage assay for detection of Escherichia coli O157:H7 in inoculated ground beef and raw milk, Int. J. Food Microbiol., 1999, 47(1–2), 43–50. 6. J. Novakofski, M. S. Brewer, N. Mateus-Pinilla, J. Killefer and R. H. McCusker, Prion biology relevant to bovine spongiform encephalopathy, J. Anim. Sci., 2005, 83(6), 1455–1476. ¨ferstein, Food safety, HACCP and the increase in 7. Y. Motarjemi and F. Ka foodborne diseases: A paradox? Food Control J., 1999, 10, 325–333. 8. Y. Shoenfeld, The Future of Autoimmunity, Clin. Rev. Allergy Immunol., 2012, 42, 113–120. 9. J. P. Wilson and L. Campbell, ISO 9001:2015: the evolution and convergence of quality management and knowledge management for competitive advantage, Total. Qual. Manage. Bus. Excell., 2018, 31(2), 1–16. 10. ISO 22000:2018, Food Safety Management System. 11. ISO 22000 (ISO 22000: 2005), Food Safety Management Systems. ´-Turza, Encyclopedia of Food Safety, 2014. 12. M. Petro 13. BRC, BRC Global Standard for Food Safety – Issue 8, 2018. 14. P. W. White, IFS Documentation International Food Standard, 2002. 15. G. A. Kleter, A. Prandini, L. Filippi and H. J. Marvin, Identification of potentially emerging food safety issues by analysis of reports published by the European Community’s Rapid Alert System for Food and Feed (RASFF) during a four-year period, Food Chem. Toxicol., 2009, 47(5), 932– 950. ¨gel, N. Busscher, M. Huber, D. Kusche, 16. J. Kahl, T. Baars, S. Bu E. Rembia"kowska, O. Schmid, K. Seidel, B. Taupier-Letage, A. Velimirov and A. Za"e-cka, J. Sci. Food Agric., 2012, DOI: 10.1002/jsfa.5640. 17. L. Pereira, Molecular Markers for food traceability, Food Technology and Biotechnology, 2013.

322

Chapter 12

18. FAO, Food and Nutrition Paper., Manual of Food Quality Control. Food Analysis: General Techniques, Additives, Contaminants and Composition, 1986. ´, Liquid chromatography-mass spec19. A. K. Malik, C. Blasco and Y. Pico trometry in food safety, J. Chromatogr. A, 2010, 1217(25), 4018–4040. 20. P. Zhu, P. Bowden, D. Zhang and J. G. Marshall, Mass spectrometry of peptides and proteins from human blood, Mass Spectrom. Rev., 2011, 30(5), 685–732. 21. S. S. Nielsen, Food Analysis, 4th edn, 2014. 22. J. P. Hart, A. Crew, E. Crouch, K. C. Honeychurch and R. M. Pemberton, Electrochemical Sensor Analysis, 2007. 23. D. Li and X. Wang, Dynamic supply chain decisions based on networked sensor data: An application in the chilled food retail chain, Int. J. Prod. Res., 2017, 55(17), 5127–5141. 24. A. D’Amico, C. Di Natale and P. M. Sarro, Ingredients for sensors science, Sens. Actuators, B, 2015, 207, 1060–1068. 25. J. Christenson, in Handbook of Biomechatronics, 2018. 26. M. Pleil, Plug and Play Microelectromechanical System (MEMS) Technology into your Engineering and Technology Programs, Southwest Center for Microsystems Education, 2014. 27. J. F. Vetelino and A. Reghu, in Introduction to Sensors, 2017. 28. B. Kuswandi, Y. Wicaksono and J. Jayus, et al., Smart packaging: sensors for monitoring of food quality and safety, Sens. Instrum. Food Qual. Saf., 2011, 5, 137–146. 29. K. M. A. El-Nour, E. T. A. Salam and H. M. Soliman, et al., Gold Nanoparticles as a Direct and Rapid Sensor for Sensitive Analytical Detection of Biogenic Amines, Nanoscale Res. Lett., 2017, 12, 231. 30. Y. Li, Z. Wang, L. Sun, L. Liu, C. Xu and H. Kuang, TrAC, Trends Anal. Chem., 2019, 113, 74–83. 31. C. A. dos Santos, A. P. Ingle and M. Rai, Appl. Microbiol. Biotechnol., 2020, 104, 2373–2383. 32. X. Luo, A. Morrin, A. J. Killard and M. R. Smyth, Electroanalysis: Int. J. Dev. Fundam. Pract. Aspects Electroanalysis, 2006, 18(4), 319–326. 33. A. Jain, M. Gupta and K. K. Verma, Salting-out assisted liquid–liquid extraction for the determination of biogenic amines in fruit juices and alcoholic beverages after derivatization with 1-naphthylisothiocyanate and high performance liquid chromatography, J. Chromatogr. A, 2015, 1422, 60–72. 34. S. Mørup, M. F. Hansen and C. Frandsen, in Comprehensive Nanoscience and Nanotechnology, 2019. 35. M. Jamieson and N. Pire-Smerkanich, in An Overview of FDA Regulated Products: From Drugs and Cosmetics to Food and Tobacco, 2018. 36. X. Zhao, H. Zhao, L. Yan, N. Li, J. Shi and C. Jiang, Crit. Rev. Anal. Chem., 2020, 50, 97–110. 37. F. Rollin, J. Kennedy and J. Wills, Consumers and new food technologies, Trends Food Sci. Technol., 2011, 22(2), 99–111. 38. A. A. Yakout and D. A. El-Hady, RSC Adv., 2016, 6, 41675–41686.

MNP-based Sensor Development to Evaluate Food Quality and Safety

323

39. D. Chen, J. Deng, J. Liang, J. Xie, C. Hu and K. Huang, Sens. Actuators, B, 2013, 183, 594–600. 40. Y. Poo-arporn, S. Pakapongpan, N. Chanlek and R. P. Poo-arporn, Sens. Actuators, B, 2019, 284, 164–171. 41. F. Long, Z. Zhang, Z. Yang, J. Zeng and Y. Jiang, J. Electroanal. Chem., 2015, 755, 7–14. 42. Z. Zhang, L. Luo, R. Cai and H. Chen, Biosens. Bioelectron., 2013, 49, 367– 373. 43. X. Li, X. Wang, L. Li, H. Duan and C. Luo, Talanta, 2015, 131, 354–360. 44. H. Qiu, L. Fan, X. Li, L. Li, M. Sun and C. Luo, J. Pharm. Biomed. Anal., 2013, 75, 123–129. 45. M. Arvand, Z. Erfanifar and M. S. Ardaki, Food Anal. Methods, 2017, 10, 2593–2606. 46. J. Li, X. Wang, H. Duan, Y. Wang, Y. Bu and C. Luo, Talanta, 2016, 147, 169–176. 47. H. Yin, Y. Zhou, X. Meng, T. Tang, S. Ai and L. Zhu, Food Chem., 2011, 127, 1348–1353. 48. C. Wang and C. Yu, Rev. Anal. Chem., 2013, 32, 1–14. 49. J. Miao, A. Liu, L. Wu, M. Yu, W. Wei and S. Liu, Anal. Chim. Acta, 2020, 1095, 82–92. 50. L. Gao, J. Wang, X. Li, Y. Yan, C. Li and J. Pan, Anal. Bioanal. Chem., 2014, 406, 7213–7220. 51. G. I. Mohammed, A. S. Bashammakh, A. A. Alsibaai, H. Alwael and M. S. El-Shahawi, A critical overview on the chemistry, clean-up and recent advances in analysis of biogenic amines in foodstuffs, TrAC, Trends Anal. Chem., 2016, 78, 84–94. 52. S. Y. Tseng, S. Y. Li, S. Y. Yi, A. Y. Sun, D. Y. Gao and D. Wan, ACS Appl. Mater. Interfaces, 2017, 9, 17306–17316. ´n, G. Iba ´n ˜ ez-Redı´n, R. C. Faria, D. S. Correa and 53. D. Wilson, E. M. Matero O. N. Oliveira, Talanta, 2019, 194, 611–618. 54. L. Rashidi and K. Khosravi-Darani, The applications of nanotechnology in food industry, Crit. Rev. Food Sci. Nutr., 2011, 51(8), 723–730. 55. A. Scroccarello, F. Della Pelle, L. Neri, P. Pittia and D. Compagnone, Silver and gold nanoparticles based colorimetric assays for the determination of sugars and polyphenols in apples, Food Res. Int., 2019, 119, 359–368. 56. M. Wu, Y. Fan and J. Li, et al., Vinyl Phosphate-Functionalized, Magnetic, Molecularly-Imprinted Polymeric Microspheres’ Enrichment and Carbon Dots’ Fluorescence-Detection of Organophosphorus Pesticide Residues, Polymers, 2019, 11(11), 1770. 57. G. G. Kenning, 2014 IEEE Int. Conf. RFID, IEEE RFID 2014, 2014, pp. 134–140. 58. T. T. Tung, M. Castro, I. Pillin, T. Y. Kim, K. S. Suh and J. F. Feller, Carbon, 2014, 74, 104–112.

CHAPTER 13

Functionalized Magnetic Nanoparticle (MNPs)-based Biosensors ´ a AND M. LEITGEB*a,b K. VASIC a

University of Maribor, Faculty of Chemistry and Chemical Engineering, Smetanova 17, SI-2000 Maribor, Slovenia; b University of Maribor, Faculty of Medicine, Taborska ulica 8, SI-2000 Maribor, Slovenia *Email: [email protected]

13.1 Introduction Nanotechnology in material sciences is one of the most trending research fields, where nanomaterials, such as magnetic nanoparticles (MNPs) show remarkable physical and chemical properties. The advantages and applicability of MNPs have opened up a large scope of studies. The main advantages of nanoparticles, compared to larger-sized particles, are their high surfaceto-volume ratio and hence higher surface energy with excellent magnetic properties. MNPs are crystals of inorganic elements for which the largest characteristic dimension is approx. 1–100 nm. Their inorganic magnetic core is surrounded by layers of functional coatings. Their large surface and smaller size volume ratio, which is dependent on their strong magnetic dipole, gives key features which make them useful in many biomedical applications. MNPs are therefore used as carriers to which different bioactive substances can bind. The development and synthesis of such materials have contributed immensely to several research disciplines, such as pharmaceutical, biomedical, and biotechnological fields, physics, electronics, advanced materials Analytical Applications of Functionalized Magnetic Nanoparticles Edited by Chaudhery Mustansar Hussain r The Royal Society of Chemistry 2021 Published by the Royal Society of Chemistry, www.rsc.org

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and to chemical science in general in the form of imaging agents, sensors and biosensors, drug delivery targets vehicles and other detection or diagnostic tools.1–3 Functionalized MNPs have also been used to develop biosensors with enhanced sensitivity and stability for the detection of different analytes in environmental, food and clinical applications.4–15 Figure 13.1 presents different properties and functions of functionalized MNPs used in biosensing applications. Iron oxides are the most widely used ferromagnetic materials in bioanalytical applications, because of their advantages in using MNPs magnetic properties, such as the ability to concentrate the analyte before its detection. Sensing properties based on functionalized MNPs display enhanced sensitivity, high signal to noise ratio and shorter time of analysis, where they are used for direct application such as being integrated into different transducer materials in the sample followed by an external magnetic field for the detection surface of the biosensor. An additional advantage of MNP-based biosensors is their ability to carry different analytes in microfluidic systems to access the transduction platform. MNPs can be coated with fluorescent materials or silica,10 metal or a polymer.9,16 MNPs coated with such materials are used as bioanalytical sensors. In developing new biosensors, gold nanoparticles show good mechanical resistance and electrical properties, as well as good biocompatibility.17,18 All MNPs have a large surface

Figure 13.1

Properties and functions of functionalized MNPs used in biosensing applications.

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area for enzyme or protein immobilization. Biosensors contain layers that are bio-selective, which can react with a target biomolecule that transforms the biologic interaction into a physical signal (optical, chemical, electrical, thermal etc.).19 Such nanomaterials are important components in bioanalytical technologies, since they are able to enhance the performance in the form of sensitivity and detection limits for even a single molecule detection.20 MNPs show their best properties for performance at sizes less than 20 nm due to supermagnetic properties, which make them suitable for a fast response due to applied magnetic fields. MNPs also have high mass transference. Properties of MNPs strongly depend on their synthesis protocols, obtained dimensions and preparation, which has to be designed to obtain particles with appropriate physicochemical properties. MNPs, which possess tailored surface properties have been synthesized under precise conditions for many applications, such as disease diagnosis (magnetic resonance imaging),21,22 disease therapy,23,24 cell labeling and imaging,25,26 tissue engineering,27–29 purification,30,31 and sensors, biosensors and other detection systems.7,32–36 In addition, MNPs are used to enhance the sensitivity and stability of biosensors for the detection of several analytes, such as environmental and other applications.37–39 Biosensor consists of three main parts as shown in Figure 13.2. Its fundamental parts are a sensitive recognition element, signal transducer and data evaluation component. The recognition component can be in the form of biomolecules, such as enzymes, nucleic acids, receptors or antibodies. In a biosensor, the transducer signal is converted into a readable and detectable signal. The electronic system mainly serves as the data evaluation component. The measuring of electronic response is performed when the biomolecular component is combined with the transducer, such as an electrochemical optical, piezoelectric and magnetic field.7

Figure 13.2

Simplified schematic of a biosensor.

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327

Considering the immense possibilities of applications of MNPs in biosensing systems, this chapter discusses the current state of recent applications of MNPs in biosensors.

13.2 Synthesis, Properties and Characterization of MNPs Recently, many different kinds of MNPs have been synthesized and prepared, such as iron oxides (magnetite – Fe2O3 and hematite – Fe3O4); ferrites of manganese, cobalt, nickel, magnesium, iron, FeCo particles; and, multifunctional composite MNPs, such as Fe3O4–Ag and Fe3O4–Au. MNPs can be synthesized by different synthesis methods: physical methods (gas-phase deposition and electron-beam lithography),17,40 wet chemical methods (coprecipitation, high temperature thermal decomposition or reduction, sol–gel synthesis, flow-injection synthesis, oxidation method, electrochemical method, aerosol/vapor-phase method, supercritical fluid method, and synthesis using nanoreactors)41–47 and microbial methods.48–51 MNP stabilization is required to enable dissociation and to prevent the irreversible agglomeration. To reach such stabilization, surface coatings must be developed, which can be achieved with surface polymer or surfactants coatings, such as dextran and polyethylene glycol (PEG).9,52,53 Such polymeric coatings prevent clusters and form lipid-like coatings around a magnetic core. Materials are classified into five basic types of magnetism (paramagnetism, diamagnetism, ferromagnetism, anti-ferromagnetism and ferrimagnetism), according to their response to a magnetic field, which is applied externally. Due to their smaller volume, MNPs are usually superparamagnetic, meaning they have zero net magnetic dipole. The shape and size of MNPs will also contribute to determine their magnetic behavior. Superparamagnetism in MNPs is determined by their structure crystallinity, material type and number of spins. Magnetism is usually evaluated using a magnetometer that controls magnetization as a function of an applied magnetic field.54,55 Several characterization techniques were utilized to analyze the composition and concentration of MNPs. The most used and applied techniques are: – scanning electron microscope (SEM), transmission electron microscope (TEM), near-field scanning optical microscope, atomic force microscope, and environmental SEM to determine and asses the shapes and sizes of MNPs; – energy-dispersive X-ray spectrometer, X-ray fluorescence, and X-ray diffraction to determine the elemental compositions of MNPs.

13.3 Biosensors Based on MNPs Biosensors and their different strategies have been developing immensely over recent years (Figure 13.3). Biosensing strategies that are based on MNPs offer advantages in terms of analytical standards, such as low detection

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Figure 13.3

Biosensor development over the last five years.

limit, high signal-to-noise ratio, shorter time of analysis and most importantly enhanced sensitivity. In biosensing applications, MNPs are integrated into transducer materials, which are used for direct application of the biosensor. In addition, MNPs can also be dispersed in a specific sample, which is attracted by an external magnetic field on the biosensor surface’s active detection. Considering the analytical data of biosensing approaches based on different MNPs, especially linear range and detection limit, there are many different examples of biosensors based on MNPs, which are used to detect all kinds of analytes in various materials.18,35–39 These MNP-based biosensors are based on different transduction principles, such as electrochemical, optical, piezoelectric and magnetic field.

13.3.1

Electrochemical Biosensors

Electrochemical (EC) devices (Figure 13.4) measure EC signals (voltage, current and impedance) that are generated and induced by the interaction of analytes and electrodes. Such electrodes are coated with biochemical, biological and chemical materials, which are used to improve and enhance their surface activity.56–58 EC devices possess benefits of high sensitivity and low cost with rapid and easy operational properties, and are therefore attractive in various applications, such as pharmaceutical, clinical and environmental.59–61 EC devices can be classified as potentiometric, amperometric, voltammetric, chemiresistive, and capacitive, according to their working principles.57

Functionalized Magnetic Nanoparticle (MNPs)-based Biosensors

Figure 13.4

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Schematic of an electrochemical biosensor.

EC enzyme, immuno, tissue and DNA biosensors are designed through immobilizing biological-recognition elements on the working electrode surface of enzymes, antibodies, tissue and DNA, respectively. To improve the sensitivity of such EC devices, functionalized MNPs are used to amplify EC signals. In order to achieve this kind of improvement, MNPs are integrated in EC devices with the electrode surface, where transport of a redox-active species to the electrode surface and the formation of a thin film on the electrode surface are achieved. For MNP-based EC biosensors, there are different detection modes used to detect and quantify various analytes, such as voltammetry,36,62 potentiometry, amperometry, electrochemiluminescence and electrochemical impedance. Among these biosensors, the most used detection mode is voltammetry, because of its biocompatibility with different enzymes or antibodies and its superparamagnetic properties, easy preparation, where synthesized Fe3O4 is the most commonly used MNPs in biosensing developments. However, as already established, Fe3O4 magnetic attraction and large volume-to-surface ratio can cause aggregation in the form of clusters. With a suitable functionalization process of MNPs, such limitations can be overcome and the biocompatibility of such biosensors can be achieved. Various MNPs have been synthesized and used for biosensor development, such as MnFe2O4 and CoFe2O4 MNPs,36 where such MNPs were synthesized using a simple polyol and diethylene glycol. Such MNPs were used in hemoglobin-based biosensors for the detection of H2O2 as a mediator, where the surface area of CoFe2O4 MNPs was found to be higher than the MnFe2O4 MNPs and the CoFe2O4 MNPs show a wider linearity range because of its higher conductivity, which increases the catalytic activity of the biosensor. Another biomimetic electrochemical biosensor was developed for H2O2 detection, based on an electrogenerated reduced form of Mn(II) meso-tetra(N-methyl-4-pyridyl)

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porphyrin as a catalyst with high sensitivity and with a low detection limit (5107 M). The proposed Mn-based electrode was investigated as an electrochemical transducer in glucose-oxidase-based biosensors.62 In another study, ZnO-capped mesoporous silica nanoparticles were used to develop an acid-responsive microfluidic biosensor using curcumin for the sensitive and rapid detection of Salmonella. This proposed biosensor was able to quantitatively detect S. typhimurium ranging from 102 to 107 CFU mL1 in 1.5 h, where the lower detection limits were calculated to be 63 CFU mL1 for colorimetric measurement and 40 CFU mL1 for fluorescent measurement, respectively.63 An electrochemical immunosensor for the detection of the cancer antigen 125 oncomarker was developed based on polyamidoamine/ gold nanoparticles, which were used to increase the conductivity and enhance the number of antibodies immobilized on the electrode surface. The biosensor showed excellent stability, high sensitivity and selectivity with good reproducibility.64 A non-enzymatic electrochemical biosensor based on Prussian blue nanoparticles, which were intercalated with Ti3C2 nanosheets (PB/Ti3C2) was fabricated as a platform for detecting H2O2, as well. The obtained physico–chemical characterizations revealed optimized morphology and enlarged surface area with low detection limit (0.20 mM) and a wide linear response in the range of 0.6 mM to 63.6 mM and from 63.6 mM to 254 mM. The proposed biosensor also exhibited good stability with low cytotoxicity by prepared PB/Ti3C2, which was validated as a potential application in living cell concerned fields.65 A nanocomposite was prepared from graphene oxide and functionalized with (3-aminopropyl) triethoxysilane/silver nanoparticles (AgNPs/[NH2–Si]-f-GO), which were used to modify the glassy carbon electrode to prepare a nanoaptasensor for electrochemical measurement of chloramphenicol.66 Superparamagnetic core– shell Fe3O4@Au nanoparticles were synthesized and used as a platform for maize taxon detection in biosensing for the construction of a magnetogenoassay with electrochemical transduction.67 Ye et al. reported an attomolar sensitive electrochemical genosensor for the detection of the cauliflower mosaic virus 35S gene, using a gold–silver core–shell (Au@Ag)-loaded iron oxide (Fe3O4) nanocomposite (Fe3O4–Au@Ag) for labeling signal DNA probes. The improvement of detection sensitivity was achieved by the amplified reduction signal of H2O2), which takes advantage of the enhanced electrocatalytic activity of Fe3O4–Au@Ag. The genosensor exhibited excellent selectivity, stability and reproducibility.68 Another study reported a graphite electrode modified with a polypyrrole-coated Fe3O4 nanohybrid by a core–shell structure (Fe3O4@PPy NPs) and multiwall carbon nanotubes (MWCNTs) for voltammetric oxidation of atorvastatin. The proposed electrochemical biosensor exhibited two linear segments in the concentration ranges of 0.0314 to 21.3 mM, and 21.3 to 201 mM with the detection limit of 0.0230 mM and was successfully utilized for measurements of atorvastatin in human blood serum samples.69 An electrochemical biosensor was designed based on Fe3O4@Au@polyethylene glycol (PEG)@chondroitin sulfate (CS) nanoparticles for mycoplasma ovipneumonia. This biosensor exhibited good selectivity

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for DNA samples, good reproducibility and storage stability with high analytical performance and a low detection limit of 3.3 aM.70 In another study, graphene oxide (GO) with Ag and hybrid Ag–Fe3O4 metallic nanoparticles were developed for a retrievable biosensor for the detection of ascorbic acid in order to determine various kinds of disease through measuring the level of oxidative stress. The glassy carbon electrode was modified to improve selectivity and sensitivity of this biosensor, which showed a detection limit and sensitivity of 74 nM and 1146.8 mA mM1 cm2, respectively.71 In addition, a highly sensitive acetylcholinesterase electrochemical biosensor was developed for the determination of acetylcholine (Ach), where the enzyme acetylcholinesterase was immobilized onto poly(neutral red) film on Fe2O3 magnetic nanoparticle modified electrodes. This biosensor exhibited a detection limit of 1.04 mM for Ach and had excellent stability and reproducibility.72 Silver nanoparticles (AgNPs) coated with a graphene film using a hybrid graphene nanoplasmonic structure for the development of plasmonic biosensors were reported. It was shown that the increase in graphene thickness significantly affected the sensitivity of the biosensor.73

13.3.2

Optical Biosensors

Optical biosensors have been applied to detect several analytes in environmental,74 clinical75,76 and food industries,77 because of their specific characteristics, such as low signal-to-noise ratio, low cost of production and reduced interferences. Optical biosensors can be classified according to their detection principles, such as interferometry, reflectance, fluorescence spectroscopy, chemiluminescence (CL), light scattering and refractive index. CL-detection systems display enhanced emission intensity and are improved in selective and quantitative usage, such as in environmental or different biological samples. In this case, MNPs play an important role as a separation tool, catalyst and a bio-molecule carrier.78 A biosensor based on chemiluminescence was established for detecting thrombin using a thrombin aptamer1-functionalized magnetic sodium alginate hydrogel. For this purpose, a metalloporphyrin metal–organic framework nanosheet was prepared for signal amplification. This biosensor displayed a detection limit of 2.1781013 mol L1 and exhibited excellent selectively.79 In another study, cerium-doped magnetite nanoparticles were synthesized and used as the coreactant of the luminol-K3Fe(CN)6 chemiluminescent system to determine concentrations of metronidazole (MNZ). The quenching efficacy of MNZ in the studied chemiluminescence system was in linear range of 3.47106– 9.37105 mol L1 and obtained a detection limit of 3.91107 mol L1. This developed biosensor was used for MNZ detection in human serum biological samples.80 Surface plasmon resonance (SPR) biosensors (Figure 13.5) have many important applications in immuno-sensing analysis, in medical diagnostics, as well as in food safety detection and others. The surface plasmon waves are excited by evanescent waves that are used to detect the external biomolecule interactions. The binding between antigen and antibody on the

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Simplified schematic of an SPR biosensor.

surface of a biosensor is specific and results in the variation of external refractive index, which leads to the shift of resonance wavelength. Such SPR biosensors are cost-effective and undergo a simple fabrication with beneficial characteristics.81,82 Optical SPR biosensors were fabricated with many structures, such as D-shaped fiber,83 tilted fiber Bragg grating84 and reflection-type structures.85 However, its sensing performance needs further improvements for the successful detection of low concentration analytes and small biomolecules. Techniques to improve these characteristics were proposed using MNPs, such as gold MNPs and others in order to improve its sensitivity characteristics. However, the incorporation of MNPs in SPR biosensors is affected by the size and shape of MNPs, which affects its sensing performance, making the synthesis process time consuming and complex. Graphene oxide (GO) is a promising nanomaterial that is based on carbon and is used to enhance the effective process of antibody immobilization.86 GO displays improved sensing properties, and improved biocompatibility with a large surface area, since it contains many functional groups, which improve immobilization efficiency for different biomolecules.87–89 A biosensor based on cobalt-doped hydroxyapatite nanoparticles was developed for chemiluminescence reaction of luminol oxidation by H2O2. The sensing system was based on sulfonamide-dependent quenching of the chemiluminescence intensity.90 A simple method for ultrasensitive detection of circulating tumor cells (CTCs) was developed based on an enzyme-free chemiluminescence reaction. For this purpose, Au@luminol-HCR assembly (ALHA) and MNPs-AS1411 were synthesized to isolate and detect the CTCs.91 Also, gold nanoparticles (AuNPs) were synthesized and used as doseenhancing agents in a chemiluminescence technique.92 Chen et al. reported a SPR biosensor for detecting cardiac troponin-I, where the magnetic

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immuno-probe was Fe3O4-based for enhanced selectivity and sensitivity. The method showed good accuracy with high selectivity for complex biosamples.93 A study by Karami et al. reported a colorimetric SPR-based biosensor based on gold nanoparticles for the detection of prostate-specific antigen, where its linear detection ranged from 0.01 to 20 ng mL1 with a detection limit of 0.009 ng mL1. This biosensor displayed excellent selectivity and is simple and effective in real-time analysis when analyzing clinical samples.94 Another study reported citrate-stabilized Fe3O4@Au core/shell nanoparticles for plasmon signal amplification labels for combined detection of serum proteins and nucleotide markers. This kind of MNP-based biosensor enables multiplex detection of different biomolecules and offers enhanced dynamic range detection and sensitivity.95

13.3.3

Piezoelectric Biosensors

Piezoelectric devices can be in the form of a quartz-crystal microbalance (QCM) or in the form of bulk surface acoustic wave (SAW). Most MNP-based piezoelectric biosensors are based on QCM transduction, which consists of a quartz-crystal disk with metal electrodes, where the oscillation frequency depends on the thickness of the disk (Figure 13.6). For such biosensing applications the electrodes are typically gold. QCMs are inexpensive, small and robust and are capable of providing a response rapidly down to a mass change of 1 ng. The main drawback presents the increase of noise with the decrease of dimensions, which occurs because of the instability as the surface area-to-volume ratio increases. Another disadvantage presents the interference caused by atmospheric humidity, which makes it difficult for use in solutions. However, with the incorporation of functionalized MNPs with piezoelectric properties, these limitations can easily be avoided, since

Figure 13.6

Components for QCM biosensor operations.

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an efficient transduction mechanism can be applied. The enhancement can occur due to piezoelectricity by functionalized MNPs caused by binding and concentrating analyte molecules on the surface of QCM, and due to functionalized MNPs performing as carriers for different labels.96,97 Pohanka reported a biosensor,98 which contained antibodies against the interferon gamma cytokine (IFNy) immobilized on QCM and gold nanoparticles. A sandwich containing QCM, gold nanoparticles and IFNg was formed, which caused a decrease of oscillation frequency. The assay showed a detection limit of 5.7 pg mL1. Another study by Pohanka99 describes a QCM biosensor to which an antibody against tumor necrosis factor alpha was immobilized. This assay used functionalized MNPs to achieve picograms of analyte and the detection limit was 1.62 pg mL1.

13.3.4

Magnetic Field Biosensors

With the ever-increasing need for higher specificities and sensitivities in biosensors, MNPs have been used in the development for biosensors with the use of magnetoresistive (MR) effect. The advantages of such biosensors are in their chemistry, manipulation ability and the ability to detect low concentrations in different bio-samples. Target biomolecules are attached to functionalized MNPs to generate detected electronic signals by magneticallylabeled biomolecules that are bound to counter biomolecules on the biosensor’s surface (Figure 13.7). Magnetic field biosensors, which use MNPs,

Figure 13.7

Schematic presentation of magnetically-labeled biomolecule on the surface of functionalized MNPs in a biosensor detection system.

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are superconducting quantum interference sensors, magneto-optical sensors, Hall effect and giant magneto-resistive (GMR) sensors. Biosensors based on the planar Hall effect are highly sensitive to spin configuration changes and are easily achieved with transverse voltage, which is used in biosensor technologies, such as spin formation. These Hall effect-based magnetic biosensors have a high signal-to-noise ratio and possess a small voltage with linear response, which allows the development of biosensors with high resolutions.100,101 GMR sensors have been applied in detection systems as an excellent tool for multiplex and ultra-sensitive sensing. GMR sensors are developed on the magnetoresistance of ferromagnetic materials or on non-magnetic/ferromagnetic hetero structures. GMR or the tunneling magneto-resistance effects are dependent on the type of nanomaterial layers in the nanostructure. Those techniques include analytical signals with a variation in electrical variation and are based on binding of analytes under an external magnetic field. Analytical signals can be acquired by weak variations in the magnetic field and are dependent on an applied magnetic field together with the biosensor area. There are two different processes, when applying functionalized MNPs and GMR biosensors. In one process the GMR biosensor is functionalized with biomolecules to which the analytes are immobilized. In the second process, GMR biosensors are functionalized with a trapped antibody with MNP-bound analytes on the GMR biosensor. This biosensor can detect the dipole field, which is produced by MNPs on the surface of a biosensor. Functionalized MNPs in such cases must be uniform in size and shape, since the magnetic signals are dependent on them. The sensitivity of a biosensor can be improved with the MNPs high magnetic moments, which promotes the magnetic signal. MNPs-based GMR biosensors have the advantage of high sensitivity and low-cost and offer direct detection of clinical samples, since they are not affected by matrix interference, which has a insignificant magnetic signal.7,100 Mujika et al. reported a developed microfabricated biosensor, which was designed for immunomagnetic quantification and detection of the Escherichia coli pathogen. This device is capable of detecting variations of a small magnetic field, which are caused by superparamagnetic beads that are immobilized with different antigens.102

13.4 Enzyme-based Biosensors Enzymes as biological molecules have a key role in biosensing technologies, since they provide crucial selective features. As well as enzymes, antibodies, nucleic acids and receptors also have the ability to attach themselves to specific substrates. Enzymes that are used in different biosensors are detected electrochemically through the process of oxidation or reduction. Figure 13.8 presents schematic enzymatic biosensors based on mediated electron transfer (a) and direct electron transfer (b).103 Such enzyme-based biosensors have many applications in the drug industry, as well as in the food industry. For example, a glucose electrode can

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Figure 13.8

Schematic of enzymatic biosensor based on (A) mediated electron transfer and (B) direct electron transfer.

be used in detecting contaminated meat caused by microbes, due to the consumption of glucose on the meat surface. A commonly used enzyme, glucose oxidase, is used for glucose determination in different fruit juices or in the fermentation process of liquors.104 In addition, lactose as the main disaccharide present in milk and other dairy products and can be hydrolyzed by galactosidase.105 Detection of lactate is required in the dairy and wine industries, as well as the detection of different phenolic compounds in wine and plant flavonoids.106,107 Also, alcohol content can be detected using the alcohol oxidase enzyme in the brewing, wine-making and distilling industries.108 In addition, hypoxanthine biosensors can detect the freshness109 of fish and meat. Biosensors based on xanthine oxidase are used for the detection of hypoxanthine and xanthine levels, which demonstrate meat spoilage.110 More importantly, enzyme-based biosensors are used in the detection of glucose content in beverages, analysis of cholesterol, detection of food freshness and for food components of sugars. In the worldwide market, there are many enzyme-based biosensors that are commonly used, such as for the detection of glucose, sucrose, lactose, ethanol and methanol.104,108,111–113

13.4.1

Glucose-based Biosensors

Over the last decades, biosensing technologies for glucose detection improved significantly with a goal to support diabetics in diagnosis and longterm control management of diabetes disease. The evolution of glucose biosensor protocols was made more reliable and easy to use, overcoming many glucose level testing limitations, which lead to developments of many different glucose biosensors. There are various detection protocols for glucose detection, such as electrochemical or optical. As receptor elements for

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glucose, different biomolecules are used. Thus, classification of glucose biosensors is based on the type of transducer or biomolecule. However, despite all the advantages and improvements in glucose biosensing systems, glucose detection still faces limitations such as the lack of precision and a time delay, which present challenges in glucose biosensor applications.114,115 Because of their excellent electronic and optical properties, gold nanoparticles (AuNPs) are used as contrast agents in many applications, such as biology and nanotechnology. The most extensive use of AuNPs is in glucose biosensor applications, where they are used as immobilization agents or electrode modifiers, due to their electrocatalytic activity. Among all MNPs, AuNPs are the most stable for biosensing applications and can bind to all kinds of biomolecules, such as nucleic acid or antibodies. Since AuNPs have a large surface-to-volume area, they are able to increase the loading capacity of enzymes, such as glucose oxidase (GOx). When fabricating the surface of an electrode with AuNPs, they present an excellent surface functionalization, which has great affinity towards GO. Therefore, AuNPs are applied in many biosensor applications nowadays. In many ways, AuNPs and other MNPs are used to avoid enzyme degradation and prevent enzyme leakage. However, to improve those characteristics in terms of avoiding enzyme degradation and leakage, different polymers are incorporated in the surface modification of a biosensor, such as chitosan or silica. With such surface compositions the stability of the biosensor surface is improved and resistant to extreme conditions.104,116–119 In recent studies, the effect of glucose and GOx on the UV–vis spectrum of AuNPs was investigated by Koushki et al. for the improvement of glucose monitoring optical methods. This study opened new insights in using AuNPs in glucose biosensors for optical monitoring of saliva glucose.120 A study by Kausaite– Minkstimiene et al. reported a novel amperometric glucose biosensor based on AuNPs and a nano-biocomposite consisting of poly(1,10-phenanthroline5,6-dione), poly(pyrrole-2-carboxylic acid) (PPCA) and GOx. This biosensor displayed a wide linear range from 0.2 to 50 mM, with a low detection limit of 0.08 mM and good reproducibility, repeatability and excellent stability.121 An optical fiber-based glucose biosensor was developed by Yang et al., using AuNPs and graphene oxide to increase the biocompatibility of the biosensor. This biosensor showed high sensitivity for glucose detection, which was 0.06 nm mM1 in the linear range of 0 mM to 11 mM.122 Another study by Baek et al. reports an electrochemical biosensor for glucose detection based on AuNPs and graphene oxide nanofibers decorated with copper nanoflowers. The designed biosensor exhibited excellent electrochemical properties and high selectivity for glucose conversion, with a linear range from 0.001 to 0.1 mM and a detection limit of 0.018 mM.123 Also, a highly sensitive glucose biosensor was developed by Liu et al. using AuNPs to which GOx was immobilized. This developed biosensor showed a wide detection range from 0.001 to 9 mM with a sensitivity of 1106 mA mM1 cm2 and is efficient in biosensing applications of different biomolecules.124 Among different MNPs, zinc oxide nanostructures (ZnO) have been widely used in biosensing

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applications, due to their excellent piezoelectric, pyroelectric and semiconducting properties. ZnO nanoparticles exhibit good biocompatibility, non-toxicity with good electrochemical activity and chemical stability. Therefore, a ZnO nanostructure offers an appropriate surface for GOx immobilization, since it has a large surface-to-volume ratio, which can increase the loading capacity for GOx.125–127 For example, a glucose biosensor was developed by Bagyalakshimi et al. based on ZnO nanorods combined with chitosan using an electrochemical method, to which GOx was immobilized. The linear range of glucose for this biosensor ranged from 10 mM to 40 mM and exhibited great electrocatalytic activity.128 Another study by Rafiee et al. describes the development of a glucose biosensor based on ZnO nanowires, which are sensitive to glucose because of their adsorption and strong electron transfer. The developed biosensor displayed a detection range of 0.003 to 30 000 mg dL1 and long-term electrical stability.129 Also, using a ZnO nanostructure composed of micro rods was reported by Khalifa et al. for the development of a glucose and pH biosensor.130 Platinum nanoparticles (PtNPs) have various applications in nanobiotechnology and medicine because of their excellent antioxidant properties. Their incorporation into glucose biosensors significantly improves the detection with improving catalytic activities using H2O2 to detect glucose. Different MNPs were combined with PtNPs mixed with GOx to increase the sensitivity of glucose biosensors, such as iron oxide MNPs, chitosan MNPs and other composites.131,132 Using PtNPs for immobilization of GOx for the development of glucose biosensors was reported by Hossain et al. This biosensor showed good electrocatalytic activity with a linear range from 0.5 mM to 13.5 mM and a low detection limit of 1.3 mM. This PtNP-based biosensor was considered to be a good candidate for glucose biosensor applications.133 Also, novel PtNP nanocomposites incorporated with EMT zeolite were prepared for glucose and H2O2 detection. The prepared nanocomposite showed great catalytic performance with a wide temperature and pH range and long stability. The detection limit of this biosensor was 13.2 mM for glucose and 1.1 mM for H2O2.134 However, significant improvement in glucose biosensing systems is still required, such as improved quality control, good performance and its commercialization, which can assure precise monitoring of diabetes disease.

13.4.2

Cholesterol-based Biosensors

Enzymatic cholesterol determination is based on spectro-photometrical use of the enzymes cholesterol oxidase (ChOx), cholesterol esterase (ChEt) and horseradish peroxidase (HRP). The use of free and expensive free enzymes increases the cost of analysis. Therefore, the use of immobilized enzymes in biosensor applications is gaining great interest, which reduces the overall cost for biosensor applications, promotes selectivity of biomolecules and enzyme reuse in modern nanotechnology. Nanoparticles offer great advantages for biosensing developments, due to their optical and catalytical features, as well as large surface-to-volume ratio, which make them promising

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immobilization supports for the development of biosensor applications. For example, AuNPs are great for designing analytical systems. Alagappan et al. reported the design of an electrochemical cholesterol biosensor based on ChOx, which is immobilized onto functionalized AuNPs. The designed cholesterol biosensor has a detection limit of 0.1103 M and shows great reproducibility and stability.135 Functionalized AuNPs with an immobilized ChOx-based biosensor was developed for the determination of free cholesterol in human serum.136 The designed biosensor displayed a low detection limit of 0.2 mg dL1, which was also effective in higher cholesterol ranges, with detection limit of 19 mg dL1. Another study by Rahim et al. reports a cholesterol biosensor based on AuNPs with immobilized ChOx, ChEt and polypyrrole. This biosensor has a cholesterol concentration detection level of 25 mM, with low sensitivity of 0.1 mA mM1 cm2 and shows high selectivity.137 A cholesterol biosensor was also developed based on AuNPs immobilized with ChOx, ChEt and GO, which has a detection limit of 0.001 mg mL1 and exhibited great reproducibility, high specificity and excellent recovery for the detection of cholesterol.138 Among AuNPs, PtNPs and silver nanoparticles (AgNPs) are also considered for the development of different biosensors. Biosensors based on Au-PtNPs were developed for the estimation of vitamin D, with a detection limit of 0.49 pg mL1 and stability of 10 days.139 Also, a biosensor based on AgNPs was developed for H2O2 and cholesterol detection, which was highly selective and sensitive towards H2O2, exhibiting a detection limit of 3.5 mM and for cholesterol of 40 mM. This biosensor was applied in serum samples detection.140 There are also many metal oxide-based biosensors for the detection of cholesterol, based on zinc oxide (ZnO), iron oxide (Fe3O4), titanium oxide (TiO2) and cerium oxide (CeO2). Metal oxide NPs have a great adsorption capability, which leads to higher biosensor stability. Such metal oxide NPs improve the performance of a biosensor.141 For distinctive features in biosensor applications, ZnO offers great potential properties, such as optical transparency, catalytic efficiency, high surface area, photochemical and chemical stability and biocompatibility together with easy fabrication.142,143 A cholesterol biosensor was developed,144 where ZnO NPs and chitosan were fabricated onto an indium– tin–oxide (ITO) glass plate to immobilize ChOx. The biosensor exhibited a detection limit of 5 mg dl1 and sensitivity of 1.41104 A mg dl1. There are many drawbacks for cholesterol biosensors, since they are not portable and do not offer real-time cholesterol monitoring, therefore there still needs to be improvement for the effective and precise development of cholesterol biosensors. In that manner, incorporation of different functionalized MNPs could offer simplified and more effective fabrication of such biosensors.

13.5 Conclusions and Future Trends In recent years, MNPs have gained great interest worldwide and have been incorporated in various applications for analytes, such as for sensing and biosensing devices. MNPs were applied onto the surface of sensors or

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biosensors and used as labels, such as in magnetic labeling of different molecules and biomolecules. However, in order to gain such biocompatibility, non-toxicity and monodispersion that assures possibility of biosensor application, MNPs need to be suitably functionalized in order to assure specific bindings. In that manner, MNPs functionalization with suitable functional groups and appropriate immobilization procedures can improve biosensor sensitivity, selectivity and specificity. For such purposes, intensive research in the field of development of suitable synthesis and preparation processes of MNPs for biosensor applications are required. Most of the biosensors using MNPs are incorporated in transducers, which are used effectively in clinical, environmental and food industries. Most optical biosensors are based on CL detection, which is the most advanced form of optical biosensors. Piezoelectric biosensors need more research incorporating functionalized MNPs to further improve their stability and sensitivity. Therefore, incorporation of MNPs in biosensing devices needs additional research and investigation to incorporate different functionalized MNPs in order to improve analytical signals in labeling of biomolecules and for the detection of different analytes.

Acknowledgements The authors acknowledge the financial support of the Slovenian Research Agency, research core funding Nr. P2-0046 – ‘‘Separation Processes and Product Design’’ and research core funding Nr. J2-1725 – ‘‘Smart Materials for Bioapplications’’. The authors also acknowledge the World Federation of Scientists for ´. granting a one-year WFS National Scholarship for candidate Katja Vasic

References 1. D. Sharma and C. M. Hussain, Arabian J. Chem., 2020, 13, 3319–3343. 2. R. Keçili and C. M. Hussain, Recent Progress of Imprinted Nanomaterials in Analytical Chemistry, https://www.hindawi.com/journals/ijac/2018/ 8503853/, (accessed 26 September 2020). ¨yu ¨ktiryaki and C. M. Hussain, TrAC, Trends Anal. Chem., 3. R. Keçili, S. Bu 2019, 110, 259–276. 4. J. B. Haun, T.-J. Yoon, H. Lee and R. Weissleder, WIREs Nanomed. Nanobiotechnol., 2010, 2, 291–304. 5. M. Holzinger, A. Le Goff and S. Cosnier, Nanomaterials for biosensing applications: a review, Front. Chem., 2014, 2, 63. 6. V. Nabaei, R. Chandrawati and H. Heidari, Biosens. Bioelectron., 2018, 103, 69–86. 7. T. A. P. Rocha-Santos, TrAC, Trends Anal. Chem., 2014, 62, 28–36. ˇ. Knez and K. Vasic´, in Micro and Nanotechnologies for 8. M. Leitgeb, Z Biotechnology, ed. S. G. Stanciu, InTech, 2016. ˇ. Knez, E. A. Konstantinova, A. I. Kokorin, S. Gyergyek and 9. K. Vasic´, Z M. Leitgeb, React. Funct. Polym., 2020, 148, 1–13.

Functionalized Magnetic Nanoparticle (MNPs)-based Biosensors

341

ˇ. Knez, J. Magn. Magn. Mater., 10. F. ˇ Sulek, M. Drofenik, M. Habulin and Z 2010, 322, 179–185. 11. M. Leitgeb, K. Herzˇicˇ, G. H. Podrepsˇek, A. Hojski, A. Crnjac and Z. Knez, Acta Chim. Slov., 2014, 61, 145–152. 12. C. M. Hussain, Adv. Environ. Anal., 2016, 1–13. ¨yu ¨ktiryaki, Y. Su ¨mbelli, R. Keçili and C. M. Hussain, Advancement 13. S. Bu in bioanalytical science through nanotechnology: Past, present and future, TrAC, Trends Anal. Chem., 2019, 110, 259–276. 14. C. M. Hussain and R. Kecili, Modern Environmental Analysis Techniques for Pollutants, Elsevier, 1st edn, 2020, vol. 2020. 15. C. Hussain, Handbook on Miniaturization in Analytical Chemistry: Application of Nanotechnology, Elsevier, 1st edn. 2020, vol. 16. G. Hojnik Podrepsˇek, Mater. Technol., 2014, 48, 689–692. 17. E. Danielson, V. A. Sontakke, A. J. Porkovich, Z. Wang, P. Kumar, Z. Ziadi, Y. Yokobayashi and M. Sowwan, Sens. Actuators, B, 2020, 320, 128432. 18. J. S. Boruah, P. Kalita, D. Chowdhury and M. Barthakur, Mater. Today: Proc., 2020, DOI: 10.1016/j.matpr.2020.06.422. ˇ. Knez, J. Kumar Pandey and M. Leitgeb, SCIREA J. Clin. 19. M. Primozˇicˇ, Z Med., 2018, 4, 23–29. ˇ. Knez and M. Leitgeb, Molecules, 2019, 24, 20. G. Kravanja, M. Primozˇicˇ, Z 1–23. 21. K. Hola, Z. Markova, G. Zoppellaro, J. Tucek and R. Zboril, Biotechnol. Adv., 2015, 33, 1162–1176. 22. F. Yazdani, B. Fattahi and N. Azizi, J. Magn. Magn. Mater., 2016, 406, 207–211. ´pez-Abarrategui, I. de la Serna Go ´mez, S. C. Dias, 23. G. R. Rodrigues, C. Lo ´lez and O. L. Franco, Int. J. Pharm., 2019, 555, 356–367. A. J. Otero-Gonza 24. S. Urandur, V. T. Banala, R. P. Shukla, S. Gautam, D. Marwaha, N. Rai, M. Sharma, S. Sharma, P. Ramarao and P. R. Mishra, Acta Biomater., 2020, DOI: 10.1016/j.actbio.2020.06.023. 25. L. L. Matta and E. C. Alocilja, Biosens. Bioelectron., 2018, 117, 781–793. 26. A. M. Demin, A. V. Mekhaev, O. F. Kandarakov, V. I. Popenko, O. G. Leonova, A. M. Murzakaev, D. K. Kuznetsov, M. A. Uimin, A. S. Minin, V. Y. Shur, A. V. Belyavsky and V. P. Krasnov, Colloids Surf., B, 2020, 190, 110879. 27. M. Rotherham, J. R. Henstock, O. Qutachi and A. J. El Haj, Nanomed.: Nanotechnol., Biol. Med., 2018, 14, 173–184. 28. J. Ding, R. Venkatesan, Z. Zhai, W. Muhammad, J. R. Nakkala and C. Gao, Colloids Surf., B, 2020, 192, 111075. 29. S. Aliramaji, A. Zamanian and M. Mozafari, Mater. Sci. Eng., C, 2017, 70, 736–744. ˇ. Knez and M. Leitgeb, J. Cleaner Prod., 2018, 179, 30. L. Krizˇnik, K. Vasic´, Z 225–234. ´ndez de Luis, M. I. Arriortua, F. J. Wolman and 31. G. I. Tovar, R. Ferna G. J. Copello, J. Ind. Eng. Chem., 2020, 88, 90–98.

342

Chapter 13

32. C.-Y. Lee, L.-P. Wu, T.-T. Chou and Y.-Z. Hsieh, Sens. Actuators, B, 2018, 257, 672–677. ´valo-Villena, 33. M. L. Villalonga, B. Borisova, C. B. Arenas, A. Villalonga, M. Are ´ ´ ´ A. Sanchez, J. M. Pingarron, A. Briones-Perez and R. Villalonga, Sens. Actuators, B, 2019, 279, 15–21. 34. Y. Yuan, J. Wang, X. Ni and Y. Cao, J. Electroanal. Chem., 2019, 834, 233–240. 35. N. Elahi, M. Kamali, M. H. Baghersad and B. Amini, Mater. Sci. Eng., C, 2019, 105, 110113. 36. S. R. Sabale, Mater. Today: Proc., 2020, 23, 139–146. 37. M. M. Rahman, M. M. Rana, M. S. Rahman, M. S. Anower, M. A. Mollah and A. K. Paul, Opt. Mat., 2020, 107, 110123. 38. R. Cheng, L. Xu, X. Yu, L. Zou, Y. Shen and X. Deng, Opt. Commun., 2020, 473, 125850. 39. K. Woo, W. Kang, K. Lee, P. Lee, Y. Kim, T.-S. Yoon, C.-Y. Cho, K.-H. Park, M.-W. Ha and H. H. Lee, Biosens. Bioelectron., 2020, 159, 112186. ´bel, Opto40. E. Bobko, D. P"och, M. Wiater, T. Wojtowicz and J. Wro Electron. Rev., 2017, 25, 65–68. 41. I. Nkurikiyimfura, Y. Wang, B. Safari and E. Nshingabigwi, J. Alloys Compd., 2020, 156344. 42. N. Hosni, K. Zehani, R. P. Brazuna, J. Moscovici, L. Bessais and H. Maghraoui-Meherzi, Mater. Sci. Eng., B, 2018, 232–235, 48–54. 43. M. A. Ait Kerroum, A. Essyed, C. Iacovita, W. Baaziz, D. Ihiawakrim, O. Mounkachi, M. Hamedoun, A. Benyoussef, M. Benaissa and O. Ersen, J. Magn. Magn. Mater., 2019, 478, 239–246. 44. V. Arakcheev, V. Bagratashvili, A. Bekin, D. Khmelenin, N. Minaev, V. Morozov and A. Rybaltovsky, J. Supercrit. Fluids, 2018, 140, 159–164. 45. V. Arakcheev, V. Bagratashvili, A. Bekin, D. Khmelenin, N. Minaev, V. Morozov and A. Rybaltovsky, J. Supercrit. Fluids, 2017, 127, 176–181. 46. S. Z. Mirahmadi-Zare, A. Allafchian, F. Aboutalebi, P. Shojaei, Y. Khazaie, K. Dormiani, L. Lachinani and M.-H. Nasr-Esfahan, Protein Expression Purif., 2016, 121, 52–60. 47. E. I. Anastasova, D. Puzyrev, V. Ivanovski and A. S. Drozdov, J. Magn. Magn. Mater., 2020, 503, 166619. ´ez, 48. M. A. Quinteros, J. O. Bonilla, S. V. Albore´s, L. B. Villegas and P. L. Pa Colloids Surf., B, 2019, 184, 110517. 49. K. B. Narayanan and N. Sakthivel, Adv. Colloid Interface Sci., 2010, 156, 1–13. 50. S. Mahanty, M. Bakshi, S. Ghosh, T. Gaine, S. Chatterjee, S. Bhattacharyya, S. Das, P. Das and P. Chaudhuri, Environ. Nanotechnol., Monit. Manage., 2019, 12, 100276. 51. A. F. V. da Silva, A. P. Fagundes, D. L. P. Macuvele, E. F. U. de Carvalho, M. Durazzo, N. Padoin, C. Soares and H. G. Riella, Colloids Surf., A, 2019, 583, 123915. 52. M. Yu, S. Huang, K. J. Yu and A. M. Clyne, Int. J. Mol. Sci., 2012, 13, 5554–5570.

Functionalized Magnetic Nanoparticle (MNPs)-based Biosensors

343

53. M. Jouyandeh, S. M. Hamad, I. Karimzadeh, M. Aghazadeh, Z. Karami, V. Akbari, F. Shammiry, K. Formela, M. R. Saeb, Z. Ranjbar and M. R. Ganjali, Prog. Org. Coat., 2019, 137, 105285. 54. M. Musielak, I. Piotrowski and W. M. Suchorska, Rep. Pract. Oncol. Radiother., 2019, 24, 307–314. 55. L. Khanna, N. K. Verma and S. K. Tripathi, J. Alloys Compd., 2018, 752, 332–353. 56. Y. Ye, J. Ji, Z. Sun, P. Shen and X. Sun, TrAC, Trends Anal. Chem., 2020, 122, 115718. 57. E. Cesewski and B. N. Johnson, Biosens. Bioelectron., 2020, 159, 112214. 58. J. Riu and B. Giussani, TrAC, Trends Anal. Chem., 2020, 126, 115863. 59. G. Maduraiveeran and W. Jin, Trends Environ. Anal. Chem., 2017, 13, 10–23. 60. S. Kurbanoglu, B. Dogan-Topal, E. P. Rodriguez, B. Bozal-Palabiyik, S. A. Ozkan and B. Uslu, J. Electroanal. Chem., 2016, 775, 8–26. 61. F. Arduini, L. Micheli, D. Moscone, G. Palleschi, S. Piermarini, F. Ricci and G. Volpe, TrAC, Trends Anal. Chem., 2016, 79, 114–126. ¨usser, Y. Ermolenko and Y. Mourzina, Sens. 62. R. Peng, A. Offenha Actuators, B, 2020, 321, 128437. 63. F. Huang, R. Guo, L. Xue, G. Cai, S. Wang, Y. Li, M. Liao, M. Wang and J. Lin, Sens. Actuators, B, 2020, 312, 127958. 64. P. Samadi Pakchin, M. Fathi, H. Ghanbari, R. Saber and Y. Omidi, Biosens. Bioelectron., 2020, 153, 112029. 65. Y. Dang, X. Guan, Y. Zhou, C. Hao, Y. Zhang, S. Chen, Y. Ma, Y. Bai, Y. Gong and Y. Gao, Sens. Actuators, B, 2020, 319, 128259. 66. M. Roushani, Z. Rahmati, S. Farokhi, S. J. Hoseini and R. H. Fath, Mater. Sci. Eng., C, 2020, 108, 110388. ´lvarez, 67. J. B. Sousa, J. Ramos-Jesus, L. C. Silva, C. Pereira, N. de-los-Santos-A ´nior R. A. S. Fonseca, R. Miranda-Castro, C. Delerue-Matos, J. R. Santos Ju and M. F. Barroso, Talanta, 2020, 206, 120220. 68. Y. Ye, S. Mao, S. He, X. Xu, X. Cao, Z. Wei and S. Gunasekaran, Talanta, 2020, 206, 120205. 69. A. Tavousi, E. Ahmadi, L. Mohammadi-Behzad, V. Riahifar and F. Maghemi, Microchem. J., 2020, 158, 105159. 70. S. Zhao, Y. Zhou, L. Wei and L. Chen, Anal. Chim. Acta, 2020, 1126, 91–99. 71. S. A. Hashemi, S. M. Mousavi, S. Bahrani, S. Ramakrishna, A. Babapoor and W.-H. Chiang, Anal. Chim. Acta, 2020, 1107, 183–192. 72. W. da Silva and C. M. A. Brett, J. Electroanal. Chem., 2020, 114050. 73. M. El barghouti, A. Akjouj and A. Mir, Vacuum, 2020, 180, 109497. 74. Y. Chen, J. Liu, Z. Yang, J. S. Wilkinson and X. Zhou, Biosens. Bioelectron., 2019, 144, 111693. 75. A. T. Kal-Koshvandi, TrAC, Trends Anal. Chem., 2020, 128, 115920. 76. H. Sohrabi, H. kholafazad Kordasht, P. Pashazadeh-Panahi, P. Nezhad-Mokhtari, M. Hashemzaei, M. R. Majidi, J. Mosafer, F. Oroojalian, A. Mokhtarzadeh and M. de la Guardia, Microchem. J., 2020, 158, 105287.

344

Chapter 13

77. N. Khansili, G. Rattu and P. M. Krishna, Sens. Actuators, B, 2018, 265, 35–49. 78. M. Iranifam, TrAC, Trends Anal. Chem., 2013, 51, 51–70. 79. Y. Lin, Y. Sun, Y. Dai, W. Sun, X. Zhu, H. Liu, R. Han, D. Gao, C. Luo and X. Wang, Talanta, 2020, 207, 120300. 80. Y. Orooji, M. Haddad Irani-nezhad, R. Hassandoost, A. Khataee, S. Rahim Pouran and S. W. Joo, Spectrochim. Acta, Part A, 2020, 234, 118272. 81. F. Fathi, M.-R. Rashidi and Y. Omidi, Talanta, 2019, 192, 118–127. 82. J. Zhou, Q. Qi, C. Wang, Y. Qian, G. Liu, Y. Wang and L. Fu, Biosens. Bioelectron., 2019, 142, 111449. 83. A. A. Melo, M. F. S. Santiago, T. B. Silva, C. S. Moreira and R. M. S. Cruz, IFAC-PapersOnLine, 2018, 51, 309–314. 84. T. Liu, L.-L. Liang, P. Xiao, L.-P. Sun, Y.-Y. Huang, Y. Ran, L. Jin and B.-O. Guan, Biosens. Bioelectron., 2018, 100, 155–160. 85. D. Wang, J. Tong, B. Jin, Y. Wang and M. Zhang, Sens. Actuators, A, 2018, 279, 140–144. 86. J. Sengupta and C. M. Hussain, TrAC, Trends Anal. Chem., 2019, 114, 326–337. 87. Z. Dehghani, J. Mohammadnejad, M. Hosseini, B. bakhshi and A. H. Rezayan, Food Chem., 2020, 309, 125690. ´ndez and F. J. Are ´valo, Microchem. J., 88. W. I. Riberi, M. A. Zon, H. Ferna 2020, 158, 105192. 89. Q. Ren, X. Shen, Y. Sun, R. Fan and J. Zhang, Food Chem., 2020, 304, 125397. 90. C. Vakh, A. Kuzmin, A. Sadetskaya, P. Bogdanova, M. Voznesenskiy, O. Osmolovskaya and A. Bulatov, Spectrochim. Acta, Part A, 2020, 237, 118382. 91. H.-X. Cao, P.-F. Liu, L. Wang, Z.-J. Liu, S.-Y. Ye and G.-X. Liang, Sens. Actuators, B, 2020, 318, 128287. 92. M. Nakayama, H. Akasaka, M. Geso, K. Morita, R. Yada, K. Uehara and R. Sasaki, Radiat. Meas., 2020, 134, 106317. 93. F. Chen, Q. Wu, D. Song, X. Wang, P. Ma and Y. Sun, Colloids Surf., B, 2019, 177, 105–111. 94. P. Karami, H. Khoshsafar, M. Johari-Ahar, F. Arduini, A. Afkhami and H. Bagheri, Spectrochim. Acta, Part A, 2019, 222, 117218. 95. G. Premaratne, A. C. Dharmaratne, Z. H. Al Mubarak, F. Mohammadparast, M. Andiappan and S. Krishnan, Sens. Actuators, B, 2019, 299, 126956. 96. S. Arif, S. Qudsia, S. Urooj, N. Chaudry, A. Arshad and S. Andleeb, Biosens. Bioelectron., 2015, 65, 62–70. ´dal, TrAC, Trends Anal. Chem., 2016, 79, 127–133. 97. P. Skla 98. M. Pohanka, Talanta, 2020, 218, 121167. 99. M. Pohanka, Talanta, 2018, 178, 970–973. 100. Y. Xianyu, Q. Wang and Y. Chen, TrAC, Trends Anal. Chem., 2018, 106, 213–224.

Functionalized Magnetic Nanoparticle (MNPs)-based Biosensors

345

101. B. Cao, K. Wang, H. Xu, Q. Qin, J. Yang, W. Zheng, Q. Jin and D. Cui, Sens. Actuators, A, 2020, 312, 112130. ˜ o, M. Tijero, R. Vilares, 102. M. Mujika, S. Arana, E. Castan ´ J. M. Ruano-Lopez, A. Cruz, L. Sainz and J. Berganza, Biosens. Bioelectron., 2009, 24, 1253–1258. ´rez, J. E. Sosa-Herna ´ndez, S. M. Hussain, M. Bilal, 103. J. A. C. Pe R. Parra-Saldivar and H. M. N. Iqbal, Biocatal. Agric. Biotechnol., 2019, 17, 168–176. 104. V. Scognamiglio and F. Arduini, TrAC, Trends Anal. Chem., 2019, 120, 115642. 105. S. K. Sharma and R. M. Leblanc, Anal. Biochem., 2017, 535, 1–11. 106. I. S. Kucherenko, Y. V. Topolnikova and O. O. Soldatkin, TrAC, Trends Anal. Chem., 2019, 110, 160–172. 107. K. Rathee, V. Dhull, R. Dhull and S. Singh, Biochem. Biophys. Rep., 2016, 5, 35–54. 108. A. M. Azevedo, D. M. F. Prazeres, J. M. S. Cabral and L. P. Fonseca, Biosens. Bioelectron., 2005, 21, 235–247. 109. A. T. Lawal and S. B. Adeloju, Talanta, 2012, 100, 217–228. 110. C. S. Pundir and R. Devi, Enzyme Microb. Technol., 2014, 57, 55–62. 111. M. Stredansky, L. Redivo, P. Magdolen, A. Stredansky and L. Navarini, Food Chem., 2018, 254, 8–12. 112. C. Wagner, J. K. Amamcharla, A. Rao and L. E. Metzger, J. Dairy Sci., 2020, 103, 7585–7597. 113. M. Bilgi and E. Ayranci, J. Electroanal. Chem., 2018, 823, 588–592. 114. P. Mehrotra, J. Oral Biol. Craniofacial Res., 2016, 6, 153–159. 115. M. Taguchi, A. Ptitsyn, E. S. McLamore and J. C. Claussen, J. Diabetes Sci. Technol., 2014, DOI: 10.1177/1932296814522799. 116. A. A. Saei, J. E. N. Dolatabadi, P. Najafi-Marandi, A. Abhari and M. de la Guardia, TrAC, Trends Anal. Chem., 2013, 42, 216–227. 117. B.-Y. Wu, S.-H. Hou, F. Yin, J. Li, Z.-X. Zhao, J.-D. Huang and Q. Chen, Biosens. Bioelectron., 2007, 22, 838–844. 118. Y. Bai, H. Yang, W. Yang, Y. Li and C. Sun, Sens. Actuators, B, 2007, 124, 179–186. 119. C. Sabu, T. K. Henna, V. R. Raphey, K. P. Nivitha and K. Pramod, Biosens. Bioelectron., 2019, 141, 111201. 120. E. Koushki, F. Mirzaei Mohammadabadi, J. Baedi and A. Ghasedi, Photodiagn. Photodyn. Ther., 2020, 30, 101771. 121. A. Kausaite-Minkstimiene, L. Glumbokaite, A. Ramanaviciene and A. Ramanavicius, Microchem. J., 2020, 154, 104665. 122. Q. Yang, G. Zhu, L. Singh, Y. Wang, R. Singh, B. Zhang, X. Zhang and S. Kumar, Optik, 2020, 208, 164536. 123. S. H. Baek, J. Roh, C. Y. Park, M. W. Kim, R. Shi, S. K. Kailasa and T. J. Park, Mater. Sci. Eng., C, 2020, 107, 110273. 124. J. Liu, H. Zhang, X. Xiaochuan, U. A. Aqrab, D. Xue, H. Huang, N. Xu, Q. Xi, W. Guo and H. Liang, Sens. Actuators, A, 2020, 312, 112128.

346

Chapter 13

125. N. P. Shetti, S. D. Bukkitgar, K. R. Reddy, C. V. Reddy and T. M. Aminabhavi, Biosens. Bioelectron., 2019, 141, 111417. 126. S. Kumar, W. Ahlawat, R. Kumar and N. Dilbaghi, Biosens. Bioelectron., 2015, 70, 498–503. 127. M. M. Rahman, A. J. S. Ahammad, J.-H. Jin, S. J. Ahn and J.-J. Lee, Sensors, 2010, 10, 4855–4886. 128. S. Bagyalakshmi, A. Sivakami and K. S. Balamurugan, Obes. Med., 2020, 18, 100229. 129. Z. Rafiee, A. Mosahebfard and M. H. Sheikhi, Mater. Sci. Semicond. Process., 2020, 115, 105116. 130. A. M. Khalifa, S. A. Abdulateef, E. A. Kabaa, N. M. Ahmed and F. A. Sabah, Mater. Sci. Semicond. Process., 2020, 108, 104911. 131. J. Li, R. Yuan, Y. Chai and X. Che, J. Mol. Catal. B: Enzym., 2010, 66, 8–14. 132. X. Xu, X. Niu, X. Li, Z. Li, D. Du and Y. Lin, Sens. Actuators, B, 2020, 315, 128100. 133. M. F. Hossain and G. Slaughter, J. Electroanal. Chem., 2020, 861, 113990. 134. X. Li, X. Yang, X. Cheng, Y. Zhao, W. Luo, A. A. Elzatahry, A. Alghamdi, X. He, J. Su and Y. Deng, J. Colloid Interface Sci., 2020, 570, 300–311. 135. M. Alagappan, S. Immanuel, R. Sivasubramanian and A. Kandaswamy, Arabian J. Chem., 2020, 13, 2001–2010. 136. N. R. Nirala, P. S. Saxena and A. Srivastava, Spectrochim. Acta, Part A, 2018, 190, 506–512. 137. M. Z. A. Rahim, G. Govender-Hondros and S. B. Adeloju, Talanta, 2018, 189, 418–428. 138. Y. Huang, J. Tan, L. Cui, Z. Zhou, S. Zhou, Z. Zhang, R. Zheng, Y. Xue, M. Zhang, S. Li, N. Zhu, J. Liang, G. Li, L. Zhong and Y. Zhao, Biosens. Bioelectron., 2018, 102, 560–567. 139. A. Kaur, S. Kapoor, A. Bharti, S. Rana, G. R. Chaudhary and N. Prabhakar, J. Electroanal. Chem., 2020, 873, 114400. 140. H. V. Tran, T. V. Nguyen, L. T. N. Nguyen, H. S. Hoang and C. D. Huynh, J. Sci.: Adv. Mater. Devices, 2020, DOI: 10.1016/j.jsamd.2020.06.001. 141. E. Sharifi, A. Salimi, E. Shams, A. Noorbakhsh and M. K. Amini, Biosens. Bioelectron., 2014, 56, 313–319. 142. V. Narwal, R. Deswal, B. Batra, V. Kalra, R. Hooda, M. Sharma and J. S. Rana, Steroids, 2019, 143, 6–17. 143. U. Saxena and A. B. Das, Biosens. Bioelectron., 2016, 75, 196–205. 144. R. Khan, A. Kaushik, P. R. Solanki, A. A. Ansari, M. K. Pandey and B. D. Malhotra, Anal. Chim. Acta, 2008, 616, 207–213.

CHAPTER 14

Sensing Applications by Functionalized Magnetic Nanoparticles NATALIA L. PACIONIa,b a

´rdoba, Facultad de Ciencias Quı´micas, Universidad Nacional de Co ´nica, Haya de la Torre y Medina Allende s/n, Departamento de Quı´mica Orga ´rdoba, Argentina; b Consejo Nacional de X5000HUA, Ciudad Universitaria, Co ´cnicas (CONICET), INFIQC, Co ´rdoba, Argentina Investigaciones Cientı´ficas y Te Email: [email protected]

14.1 Introduction Chemical sensors are defined conventionally as ‘‘devices’’ able to release analytical information about a sample in real-time through performing analyte recognition and signaling (transduction).1 In the broader sense, any (supra)molecule or nanomaterial that upon interacting with the analyte (recognition) provokes a detectable new or changed analytical response (signaling) can be treated within the chemical sensor classification. Thus, analytical strategies based on chemical sensing involve mainly the design of supra- or nanomolecular systems that can perform two functions: (1) molecular recognition and (2) concentration-dependent signaling.2 When nanomaterials accomplish any of those functions, the sensing system is named a nanosensor. In this sense, the application of functionalized magnetic nanoparticles (FMNPs) as part of nanosensors has notoriously increased in the last years, maintaining a constant pace (see Figure 14.1a).3–6 One main reason is their ability to show a response when a magnetic field is applied, thus permitting Analytical Applications of Functionalized Magnetic Nanoparticles Edited by Chaudhery Mustansar Hussain r The Royal Society of Chemistry 2021 Published by the Royal Society of Chemistry, www.rsc.org

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Figure 14.1

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(a) Representation of the scientific publications in the period 2015–2020 according to Scopuss using ‘‘magnetic nanoparticles’’ AND ‘‘sensor’’ OR ‘‘sensing’’ as the searching input. The asterisk indicates that this result is partial (January–May 2020). (b) Sketch summarizing the main techniques where FMNPs are applied as part of the sensing platforms.

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an easy separation of the analyte from complex samples. This type of nanoparticle can be composed of ferromagnetic (e.g., iron, nickel, cobalt), antiferromagnetic (e.g., MnO, CoO, NiO), and ferrimagnetic (e.g., magnetite Fe3O4 and maghemite g-Fe2O3) materials, of which Fe3O4 is the most commonly used. As a consequence of their size, the FMNPs usually consist of a single magnetic domain, becoming superparamagnetic. This property means that after the magnetic field is off, no residual magnetization is observed, and then aggregation and flocculation of FMNPs are avoided, contributing to their colloidal stability.1,7 In this chapter, advances in the use of FMNPs as part of different sensing systems are reviewed with the focus on the last five years. The content is organized in sections, each one devoted to detection techniques classified as optical sensing or electrochemical analysis (see Figure 14.1b). Different examples were selected to show and discuss the function of the FMNPs in the analytical strategies. As details on the synthesis and characterization protocols of the used FMNPs are out of the scope of this chapter, it is recommended that the interested reader consult the specific references and other literature reviews.8–10 Given the variety of analytes the FMNPs have been applied for, it is expected that this chapter will be helpful for researchers and professionals working in the fields of chemistry, biochemistry, environmental science, and agronomy.

14.2 Analytical Strategies Based on Optical Sensing Optical sensing is based on the interaction of light with matter, provoking different photophysical phenomena such as absorption, emission, or scattering. All these phenomena are, among other factors, concentrationdependent, which makes them relevant in analytical chemistry. As advantages, optical detection usually presents high sensitivity, simplicity, and ease of instrument operation. The first pre-requisite for proposing optical sensing as part of the analytical strategy is the presence of a chromophore that absorbs the electromagnetic radiation (and emits light). For its part, light scattering techniques mainly require the existence of polarizable bonds. In this sense, it is possible to have direct sensing when the optical species is the analyte itself, the nanosensor, or a product of the interaction analyte– nanosensor (see Figure 14.2a–b). In contrast, indirect sensing implies a competitive process or adding an external signal reporter (see Figure 14.2c–d). In this kind of sensing application, the FMNPs commonly act as the recognition unit and, in a few cases, for signal amplification. In the following sub-sections, examples showing these facts are briefly described.

14.2.1

UV–Visible Absorbance

As mentioned above, when the detection is based on light absorption, the first rule is that a chromophore must be present in the system. Upon molecular recognition, the sample absorbance is monitored using a spectrophotometer,

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Figure 14.2

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Illustration of direct (a–b) and indirect (c–d) optical sensing concepts. Direct detection is based on (a) the change in the sensing probe signals or (b) the analyte itself upon recognition. Indirect sensing is based on external reporter signals provoked by (a) a chemical reaction due to the presence of the sensor–analyte system or (b) a displacement reaction.

or in some cases, is perceived by the naked-eye. Both are usually denoted as colorimetric methods. The main difference is that in the first case, the method is quantitative whilst it is qualitative to semi-quantitative in the last one. In the last years, analytical strategies involving FMNPs and colorimetric detection have been proposed for a wide variety of analytes such as bacteria,11–16 proteins,17 amino acids,18 cancer biomarkers,19,20 and inorganic ions21 among others. The central role of the FMNPs in these methods is recognition (and capture) of the analytes, which can be followed by a peroxidase-like activity (PLA) and signal amplification. PLA refers to the capability of FMNPs to mimic the peroxidase enzyme role as catalysts in the oxidation of substrates, also known as reporters, to produce a color change. The most common PLA reporters are presented in Scheme 14.1.

14.2.1.1

Colorimetric Detection Using Peroxidase-like Activity Reporters

The fundamental of this chemical sensor strategy is indirect sensing. First, the magnetic nanoparticles are functionalized to recognize an analyte (the more specific, the better). Once the interaction takes place, they are separated from unbound FMNPs usually, using an external magnetic field. Then, a PLA reporter is added to the vessel where the analyte-bound FMNPs are. Owing to the FMNPs catalytic activity over the oxidation of the reporter (see Scheme 14.1), a remarkable color change is observed. The proposed role

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Scheme 14.1

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Chemical reactions associated with colorimetric reporters commonly used in peroxidase-like applications of FMNPs in optical sensing. For full IUPAC names, the reader should refer to the main text.

of FMNPs in the mechanism is the catalytic generation of reactive oxygen species (ROS) in a Fenton-like reaction with hydrogen peroxide (H2O2).22 The following paragraphs describe a few examples using this phenomenon as an analytical strategy with its variations. Wu et al.15 designed an aptasensor to detect the bacteria Vibrio parahaemolyticus using iron FMNPs and gold nanoparticles (AuNPs). The FMNPs were modified to act as a recognition element with a short single-stranded DNA, known as an aptamer, and the AuNPs were functionalized with horseradish peroxidase (HRP) and a different aptamer to function as the signal amplifier. In combination with the analyte, a sandwich-type complex is obtained, which can be separated from unbound AuNPs using a magnet. Thus, the addition of H2O2 and 3,3 0 ,5,5 0 -tetramethylbenzidine (TMB) as the reporter generates a detectable optical signal at 450 nm (see Figure 14.3). Using this methodology, the detection limit (LOD) for V. parahaemolyticus is 10 colony-forming units per mL (cfu mL1).

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Figure 14.3

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Illustration of the colorimetric sensor procedure for Vibrio parahaemolyticus using bio-aptamer functionalized MNPs as the recognition and magnetic separation probe, and SH-aptamer and HRP-modified AuNP as signal amplification of the TMB oxidation reaction. Reproduced from ref. 15 with permission from American Chemical Society, Copyright 2015.

Zhang et al.16 also modified Fe3O4 nanoparticles using an aptamer to obtain a nanoprobe for the gram-positive bacteria Listeria monocytogenes. First, the FMNPs were cross-linked with poly-L-lysine to form clusters with high PLA useful for visualization and signal amplification. Then, these clusters were bound to an aptamer to get the recognition unit. The biosensor structure was completed with an additional L. monocytogenes capture probe composed of a vancomycin (VAN)–bovine serum albumin (BSA) conjugate, which was fixed to a well plate by physisorption. In the presence of the bacteria, a sandwich-type complex was formed through affinity interaction with VAN and the aptamer. Then, the addition of TMB/H2O2 provoked a blue color due to its oxidation catalyzed by the FMNPs. Using this nanosensor, the LOD for L. monocytogenes was 5.4103 cfu mL1. Liang et al.20 developed a microfluidic paper-based analytical device (mPAD) to detect tumor biomarkers like the carcinoembryonic antigen (CEA) and a-fetoprotein (a-AFP) (see Figure 14.4). The 3D mPAD was constructed by immobilizing AuNPs modified with CEA and a-AFP antibodies to capture the analytes. In the presence of CEA or a-AFP, the addition of Pd/Fe3O4 FMNPs bioconjugated to CEA and a-AFP secondary antibodies allowed the formation of the sandwich-type immunosensor on the a-sheet. Then, the a-sheet (recognition unit) was clamped to a b-sheet (signaling unit) containing TMB or o-phenylenediamine (OPD) and H2O2. The Pd/Fe3O4 FMNPs present peroxidase-like activity, thus they catalyzed the oxidation of TMB or OPD, provoking a naked-eye observable color change on the b-sheet with a LOD of 1.7 pg mL1.

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Figure 14.4

Schematic representation of the microfluidic paper-based colorimetric device construction and the principle of detection for two tumor markers using Pd/Fe3O4 magnetic nanoparticles. Reproduced from ref. 20 with permission from Elsevier, Copyright 2015.

Figure 14.5

Schematic representation of (i) the MNPs functionalization reaction with monomers and an antibody and (ii) the colorimetric assay for S. typhymurium detection using the FMNPs and an HRP-labeled antibody. Reproduced from ref. 11 with permission from Elsevier, Copyright 2016.

Chattopadhyay et al.11 accomplished the detection of Salmonella typhimurium using the combination of functionalized Fe3O4 nanoparticles with a covalently immobilized antibody on the polymeric shell to capture the analyte and an HRP-labeled secondary antibody for signal amplification (see Figure 14.5). Again, the colorimetric reporter was TMB, reaching a LOD for this bacterium of 10 cells mL1.

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Li et al. biofunctionalized Fe3O4 MNPs with human anti-melanoma associated chondroitin sulfate proteoglycan (FMNP-Ab1) to capture and detect melanoma circulating tumor cells (CTC). Once the FMNP-Ab1 recognized by affinity the CTC present in a sample, magnetic separation permitted isolation from unbound normal cells. The FMNP-Ab1-CTC complexes were separated from free FMNP-Ab1 using centrifugation. Finally, the colorimetric detection with a LOD of 13 cells mL1 was done using TMB as the reporter, as previously commented. In a different approach, Can et al.23 developed an analytical method for the determination of explosive triacetone triperoxide (TATP). The TATP detection is based on its degradation by acidic hydrolysis to H2O2. The in situ produced H2O2 can oxidize N,N-dimethyl-p-phenylenediamine (DMPD, see Scheme 14.1) catalyzed by Fe3O4 MNP. The assays can be performed in solution or on a reusable Nafion membrane with high selectivity. The obtained radical cation DMPD1 absorbs strongly at 550 nm, then a remarkable color change is observed (see Figure 14.6). The LOD for TATP is 0.1 mg L1 in the Nafion membrane. Similarly, Kim et al.24 detected glucose and cholesterol with a LOD of 7.5 mg dL1 using as a sensor mesoporous silica entrapping Fe3O4 MNPs, glucose-oxidase (GOx) and cholesterol-oxidase (ChOx) and 2,2 0 azino-bis(3-ethylbenzo-thiazoline-6-sulfonic acid) diammonium salt (ABTS, Scheme 14.1). First, GOx and ChOx selectively oxidize glucose and cholesterol, respectively, producing H2O2. Owing to the presence of FMNPs in the system, the oxidation of ABTS by H2O2 to a colored radical cation is possible, enabling the colorimetric detection. Recently, Mazhani et al.18 found that core–shell Fe3O4 and silver nanoparticles (AgNP@MNP) present an enhanced PLA compared to bare MNPs. They used as substrate OPD (see Scheme 14.1) to prove this fact, whose

Figure 14.6

Original (a) and reference Nafion membrane before (b) and after addition of hydrolyzed TATP (c) at 20 mg L1 concentration, (d) at 60 mg L1 concentration and (e) at 100 mg L1 concentration. Reproduced from ref. 23, https://pubs.acs.org/doi/10.1021/acs.analchem. 5b01775, with permission from American Chemical Society, Copyright 2015.

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oxidation product absorbs strongly around 415 nm. Taking advantage of the anti-oxidant capacity of cysteine to trap the ROS and hence, plotting the absorbance difference provoked by the OPD oxidation inhibition, they detected L-cysteine with a LOD of 87 nM. The selectivity was attributed to the affinity of the thiol functional group in the cysteine towards the metal surface.

14.2.1.2

Colorimetric Detection Using Gold Nanoparticles and Surfaces

In the following examples, the principle of colorimetric detection is the perceptible naked-eye color of gold surfaces (yellow) or nanoparticles (reddish to blueish). The FMNPs role in these sensors is as capture probes, whereas the signal probe contains the gold (nano)material. Ma et al.14 detected S. typhimurium using this analytical strategy. They functionalized Fe3O4 MNPs with streptavidin and a biotin-labeled DNA sequence (FMNP-DNA-1) to capture the target, a single-stranded DNA obtained previously from the bacterium (DNA-3). To act as a signal probe, they customized AuNPs using a thiol-DNA sequence (AuNP-DNA-2). Sodium dodecyl sulfate (SDS) and sodium chloride were added to enhance the signal. The colorimetric detection was based on the AuNP interparticle distancedependent color. When the nanoparticles are close, the absorbance spectra redshifted, observing a color change from red to purple-blue. Due to the base complementation pairing rule, DNA-3 (analyte) was ‘‘captured’’ by the FMNPDNA-1 (37 1C for 12 h) and magnetically purified. Then, the signal probe was added (37 1C for 12 h), obtaining a sandwich-type structure whose absorbance spectrum depends on the AuNP interparticle distance (see Figure 14.7). The 700 nm to 520 nm absorption intensity ratio depended linearly with the DNA-3 concentration, with a LOD for the bacterium of 23 cfu mL1. Recently, Man et al.25 proposed a microfluidic immunoassay for the detection of mycotoxin alternariol monomethyl ether (AME) based on the red color displayed due to the generation of AuNP. The assay was designed to be performed either using a spectrophotometer or a smartphone. A micro fluid chip containing two reaction chambers was constructed. When the analyte was present in a sample (positive test), it conjugated to an antibody (mAb)-functionalized AuNP (capture probe) in chamber A. The unbound AuNPs, were captured by AME-antigen FMNPs in chamber B and separated using a magnet. Then, the AME-mAb-AuNPs in the supernatant was transferred to an immunogold amplification solution as seeds for the growth of AuNP, observing a color change. If no AME was present (negative test), all the mAb-AuNPs are retained by the AME-antigen FMNPs. Hence, no AuNP seeds are found in the supernatant, and the color did not change. The LODs were 12.5 pg mL1 and 200 pg mL1 using a spectrophotometer and a smartphone, respectively. Another analytical strategy was implemented by Zourob et al. to detect Pseudomona aeruginosa12 and L. monocytogenes13 bacteria, and plasmin,17 a serine-protease whose role in mastitis development is relevant. A biosensor was constructed using a self-adhesive sheet placed on the front-side of

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Figure 14.7

Absorbance spectra and colorimetric detection using AuNPs/FMNPs in the presence of S. typhimurium target DNA (1, 50, 250, 500, 750, 1000, 1250, 1500 pM (1–8)). The maximum absorbance wavelength redshifts with the bacterium concentration increase. Reproduced from ref. 14 with permission from Springer Nature, Copyright 2017.

a plastic strip, while in the back-side, a permanent magnet was held (see Figure 14.8A). Thus, a yellow gold surface was sputtered on the frontside, followed by peptide-FMNPs deposition. The immobilized peptideFMNPs presented a black color covering the gold sensing platform. The peptide sequence was selectively cleaved by the desired protease (analyte). Thus, upon the addition of the test sample, the peptide sequence was cleaved, releasing the FMNPs that are attracted to the magnetic extreme, showing the appearance of the golden color (see Figure 14.8A–B). Using this kind of biosensor, the LODs obtained for P. aeruginosa, L. monocytogenes, and plasmin were 102 cfu mL1, 2.17102 cfu mL1 and 1 ng mL1, respectively.

14.2.2

Luminescence

Optical sensing can also be performed through measuring the light emission produced during different luminescence phenomena like fluorescence, phosphorescence, and chemiluminescence, among others. Fluorescence and phosphorescence are photophysical processes related to the molecular singlet and triplet excited states, respectively, whereas chemiluminescence implies light emission as a chemical reaction product.26

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Figure 14.8

357

(A) Illustration of the colorimetric magnetic sensing device to detect proteases. Adapted from ref. 17 with permission from Elsevier, Copyright 2017. (B) Colorimetric P. aeruginosa proteases sensor probe tested with different concentrations (4.5107 to 4.510 cfu mL1 of proteases. Reproduced from ref. 12, https://pubs.acs.org/doi/10.1021/acsomega. 9b02080, with permission from American Chemical Society, Copyright 2019.

Among other luminescence techniques, fluorescence sensing with FMNPs has been mostly explored with examples covering different types of analytes: proteins,27 DNA,28–31 inorganic ions,32,33 and indeed for temperature sensing.34 Recently, a chemiluminescence based sensor for cancer cell detection using aptamer FMNPs was reported;35 however no explicit description of the chemiluminescence reaction was described to understand entirely the sensing mechanism.

14.2.2.1

Fluorescence Sensing 32

Tong et al. developed an analytical procedure to detect the pyrophosphate anion (PPi) in synovial fluid as an index for arthritis diagnosis using Fe3O4 FMNPs. The strategy consisted of the fluorescence emission recovery of fluorescent-labeled single-stranded DNA (signal probe) after its release from the FMNPs surface (recognition unit) due to the presence of the stronger ligand PPi in the sample. The fluorescence of the DNA-label 6-carboxyfluorescein (6-FAM, see Scheme 14.2) was strongly quenched by interacting with the FMNPs surface through a phenomenon known as photo-induced electron transfer (PET). As PPi can efficiently coordinate with the nanoparticle surfaces, the signal probe is liberated to the medium, and the fluorescence recovered. The achieved LOD for PPi was 76 nM. Likewise, Tan et al.28 designed an assay for detecting DNA using as the model a DNA sequence associated with the human immunodeficiency virus (HIV). The molecular recognition and signaling were performed by a sensing

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Scheme 14.2

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Chemical structures for standard fluorescent probes used in optical sensing applications of FMNPs. 6-FAM: 6-carboxyfluorescein or (3 0 ,6 0 dihydroxy-1-oxospiro[2-benzofuran-3,9 0 -xanthene]-5-carboxylic acid); Hoescht 33342: 2-(4-ethoxyphenyl)-6-[6-(4-methylpiperazin-1-yl)-1Hbenzimidazol-2-yl]-1H-benzimidazole; RhB-ITC: Rhodamine B isothiocyanate or ([9-(2-carboxy-6-isothiocyanatophenyl)-6-(diethylamino)xanthen-3-ylidene]-diethylazanium); Rh-Si: alkoxysilane-modified Rhodamine B; Cy-5: (2E)-2-[(2E,4E)-5-[3,3-dimethyl-5-sulfo-1-(3-sulfopropyl)indol-1-ium-2-yl]penta-2,4-dienylidene]-3,3-dimethyl-1-[6-(amide)hexyl]indole-5-sulfonic acid; PMDP: poly-methyldopa.

platform composed of magnetic porous carbon (MPC) labeled with FAMsingle-stranded (ss)-DNA (signal probe). The MPC was obtained by thermolysis of an iron-containing metal organic framework named MIL-88A. The MPC effectively quenched the FAM-DNA fluorescence. In the presence of the target DNA (T-DNA), the signal probe was released from the MPC surface and its fluorescence recovered (see Figure 14.9), presenting a LOD of 1 nM. Sun et al.33 used Fe3O4@SiO2 superparamagnetic core-shell nanoparticles labeled with a rhodamine fluorescent probe (Rh-Si, see Scheme 14.2) to remove and detect Hg21 ion with a LOD of 2.13 mM. The rhodamine moiety did

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Figure 14.9

359

(a) Fluorescent spectra of FAM-DNA (100 nM) at different conditions: FAM-DNA alone, FAM-DNA@MPC (50 mg mL1), FAM-DNA@MPC@TDNA (600 nM), and MPC@hybridized dsDNA of FAM-DNA/T-DNA. (b) Gel electrophoresis images of FAM-DNA alone (lane 2), FAMDNA@MPC (lane 3), and FAM-DNA@ MPC@ T-DNA (lane 4). DNA marker is on lane 1. Reproduced from ref. 28 with permission from Elsevier, Copyright 2016.

the ion recognition that upon Hg21 binding underwent a spirolactam ringopening and recovered its fluorescence. Then, the Hg21 loaded FMNPs were removed from the aqueous solution using an external magnetic field. Bhaisare et al.36 obtained fluorescent magnetic carbon dots to use as sensors for Staphylococcus aureus and Escherichia coli bacteria. These FMNPs combine magnetic and luminescence properties, useful for separation and analyte detection, respectively. After interacting with the bacteria, a fluorescence enhancement was observed, allowing S. aureus and E. coli quantification with LODs of 300 cfu mL1 and 350 cfu mL1, respectively. Once the bacteria was separated from the solution using an external magnetic field, their identity was verified using matrix-assisted laser desorption inducedmass spectrometry (MALDI-MS). Liu et al.30 synthesized FMNPs labeled with Hoechst dyes (see Scheme 14.2) as a potential sensor for DNA separation and detection and cell imaging. The fluorescent Hoechst dyes are usually employed for nuclear staining, and their attachment to FMNPs can improve their photostability and adsorption permanence. The potential applications in cell imaging were assessed using human embryonic kidney cells (HEK293T) and rabbit corneal epithelial cells (SIRC) where the FMNPs were clearly observed in the nucleus (see Figure 14.10). Xu et al.27 designed a biosensor for p53 protein (a carcinogenic biomarker) separation and detection using FMNPs. The nanoparticles have an attached DNA duplex to capture the p53 protein; hence it can be separated from the solution using a magnet. The DNA duplex is composed of a DNA sequence covalently attached to the nanoparticle surface (DNA-1) and a DNA sequence

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Figure 14.10

Fluorescence and phase-contrast images of HEK 293T (a) and SIRC (b) after Hoechst MNPs treatment for 1 minute. Acridine orange is stained by green (ex: 502 nm, em: 526 nm) and HC by blue (ex: 352 nm, em: 455 nm). The scale bar in the photos represents 40 mm. Reproduced from ref. 30 with permission from the Royal Society of Chemistry.

(DNA-2), partially complementary with DNA-1. Before the separation procedure, Cy-5 (see Scheme 14.2) labeled DNA with a complementary sequence to DNA-1 was added. In the absence of p53, the Cy-5-DNA would replace DNA-2; hence fluorescence emission was observed in the FMNPs colloidal dispersion. In contrast, when p53 is attached to the DNA duplex, a lower exchange took place, and therefore, the observed fluorescence is decreased. A LOD for p53 of 8 pM was reported. As can be deduced from the examples above, most optical sensing applications of FMNPs use magnetite, with only a few sensors employing others like maghemite. For instance, Shahabadi et al.29 used polymer modified g-Fe2O3 MNPs to detect calf thymus DNA (ct-DNA). The polymer of methyldopa (PMDP, see Scheme 14.2) confers fluorescence to the maghemite nanocrystals.37 The ct-DNA quenched the PMDP fluorescence upon interaction with the PMDP-g-Fe2O3 MNPs, which is fundamental to the sensor performance.

14.2.3

Surface Enhanced Raman Spectroscopy

Besides radiative absorption and emission, light scattering due to molecular vibrations has also been exploited for optical sensing applications. When the light is inelastically scattered by colliding with a molecule, this phenomenon is known as Raman in honor of its discoverer Sir C.V. Raman. Raman spectroscopy is classified in Stokes (lower energy) and anti-Stokes (higher energy) depending on the observed spectral region. Also, it can be performed on-resonance (when the irradiation wavelength matches an absorption peak) or in contrast off-resonance. Due to the fundamental of the

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38

technique itself, sensitivity is relatively low. This disadvantage for sensing applications has mainly been overcome thanks to the local electromagnetic near-field enhancement produced around metal Au, Ag and Cu nanoparticles, given rise to surface-enhanced Raman spectroscopy (SERS) as a powerful analytical technique.39 In the last years, the power of SERS detection combined with the magnetic properties of FMNPs has also been exploited in optical sensing applications of biological40–43 and environmental interest.44 Rong et al.40 developed a SERS-based biosensor for carcinoembryonic antigen (CEA) as a cancer biomarker using silver-coated gold nanorods (Au@Ag NRs) and Fe3O4@Ag core–shell MNPs (see Figure 14.11). The FMNPs were coated with a CEA antibody (capture probe and isolation via magnetic separation). The Au@Ag NRs were functionalized with diethylthiatricarbocyanine (DTTC) Raman tag for detection and another CEA antibody. Once the CEA-FMNPs were separated from the solution, the addition of the DTTC-Au@Ag NRs induced the formation of a sandwich-type complex, hence acting as a hot spot that shows enhancement of DTTC resonance Raman signals (lex: 715 nm, 25 mW, 10 s). Using this strategy for CEA, a LOD of 4.75 fg mL1 was determined. A different approach was proposed by Yang et al.42 to detect the prostatespecific antigen (PSAg). In this case, 4,4-dipyridyl (DP) was adsorbed on AuNPs to act as the Raman tag, and the nanoprobe was completed by modifying the surface with the PSA-complementary DNA sequence.

Figure 14.11

Illustration of (a) the functionalization of Fe3O4 MNPs, (b) the conjugation of Au@AgNRs to the detection antibody and DTTC SERS tag, and (c) the principle of the SERS assay for CEA detection. Reproduced from ref. 40 with permission from Elsevier, Copyright 2016.

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The capture probes were FMNPs labeled with a PSA-aptamer. The aptamerFMNPs were assembled with the DP-AuNPs due to DNA hybridization. In the presence of PSAg, the hybridization was broken, releasing free DP-AuNPs. After magnetic separation, the supernatant was rich in DP-AuNP, showing a high SERS signal. In contrast, when no PSAg exists or is lower than the 5.0 pg mL1 LOD, the supernatant SERS signal is neglected. Another competitive assay was developed for detecting clenbuterol (CL), a b-adrenergic agonist, using 4-mercapto benzoic acid (MBA) as the Raman reporter. In this case, Wei et al.41 used CL-antibody-AuNPs also containing MBA to react with CL-antigen-Fe3O4@Au NPs followed by magnetic separation and the resulting sediment presented the SERS signals. When CL was in the sample, it complexed with the CL-antibody-AuNP remaining in solution; hence the external magnetic field retained only free CL-antigenFe3O4@Au NPs with no SERS signal. Thus, based on the decreasing SERS signal upon CL addition, a LOD of 0.22 fg mL1 was obtained. Recently, Chattopadhyay et al.43 modified the previously reported nanosensor (see Figure 14.4)11 to become a SERS-based optical sensor. Now, the Salmonella typhimurium bacteria were captured using the FMNPs and detected using antibody-functionalized AuNP with MBA or 5,5 0 -dithio-bis-(succinimidyl2-nitrobenzoate) (DSNB) as Raman tags. Upon the formation of a sandwichtype structure, the 1588 cm1 MBA or 1336 cm1 DSNB SERS signals were enhanced because of the hot-spot effect. Using MBA and DSNB nanosensors, the determined LODs were 100 cells mL1 and 10 cells mL1, respectively.

14.3 Analytical Strategies Based on Electrochemical Sensing An important sub-class of chemical sensors uses an electrode as the transducer, and so they are defined as electrochemical sensors. In this class of sensors, once the analyte recognition event occurs, a concentrationdependent electrical signal is produced that can be amperometric (current) or potentiometric (potential).45 Generally, electrochemical sensors present high sensitivity and fast response as advantages. A few cases are reviewed below to present the detection principles, and further examples are compiled at the end of this section (see Table 14.1). Guivar et al.46 employed chronoamperometry (applied potential: 0.2 V) to detect citric acid with a LOD of 40 mM using cetyltrimethylammonium bromide (CTAB) functionalized Fe3O4 MNPs. A layer-by-layer (LbL) electrostatic self-assembly strategy was used to deposit the FMNPs on a fluorinated tin oxide (FTO) working electrode. Ag/AgCl/KCl and Pt plate were the reference and counter electrodes, respectively. The sensor works by (i) adsorption of citric acid on the positive surface of the modified FTO and (ii) the nanoparticle surface catalyzes the one-electron reduction of citric acid. This electrochemical sensor also presented peroxidase-like activity, showing promise as a non-enzymatic sensor.47

Selected examples of electrochemical sensing applications of FMNPs.a

Type of FMNPs

Electrode

Technique

Analyte

Limit of detectionb

Reference

Fe3O4@Ag core–shell Fe3O4–COCl

CPE SPE

DPV DPASV

CPE Ag SPIDE

DPV EIS

MMIP@SiO2 MMIP Fe3O4@TAPB@DMTF-COF IL-Fe3O4@aptamer MMIP Ab-Fe3O4 CoFe2O4@CdSe/PVP Fe3O4/carbon dots rGO-Fe3O4 AChE-CS-Fe3O4

Gr/GCE SPE GCE SPE CPE SPE GCE SPE SPE SPE

DPV EIS DPASV CV Potentiometry DPV SWASV DPV DPASV Chronoamperometry

0.018 mM 0.07 ng mL1 0.19 ng mL1 0.02 mM 10 cfu mL1 10 cfu mL1 1 cfu mL1 5.5 nM 5.37 pM 7.2 nM 1 nM 6.4 pM 22 ng mL1 0.0455 fM 20 nM 0.1 mg L1 0.3 nM

Arvand et al.52 Prasad et al.53

MWNT@ZnCrFeO4 Fe3O4@melittin

Olanzapine Ce(IV) Gd(III) Phenazopyridine S.aureous S. typhi. E. coli Sunset yellow Tributyltin Luteolin Tetracycline Gemifloxacin mesylate Synthetic cannabinoid Rifampicin NADH As(III) Malathion

Taei et al.54 Wilson et al.55 Arvand et al.56 Zamora et al.57 Xie et al.58 Shi et al.59 Abdallah et al.60 Sanli et al.61 Asadpour et al.62 Canevari et al.63 Chimezie et al.64 Marinho et al.65

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Table 14.1

a

CPE: carbon paste electrode; DPV: differential pulse voltammetry; SPE: screen-printed electrode; DPASV: differential pulse anodic stripping voltammetry; MWNT: multi-walled carbon nanotubes; SPIDE: screen-printed interdigitated electrode; EIS: electrochemical impedance spectroscopy; MMIP: magnetic molecular imprinted polymer; Gr: graphite; GCE: glassy carbon electrode; TAPB: 1,3,5-tris(4-aminophenyl)benzene; DMTF: 2,5-dimethoxyterephaldehyde; COF: covalent organic framework; IL: ionic liquid; CV: cyclic voltammetry; Ab: antibody; PVP: poly vinylpyrrolidone; SWASV: square wave anodic stripping voltammetry; rGO: reduced graphene oxide; AChE: acetyl cholinesterase; CS: chitosan. b Concentration units are those reported in the original publication.

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Figure 14.12

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Comparison of square-wave voltammograms for a mixture of 4.0 mM melatonin and dopamine in Britton–Robinson buffer solution (pH 5.0) on the surface of different electrodes: Pt, glassy carbon and Gr–Fe3O4/CPE. Reproduced from ref. 48 with permission from the Royal Society of Chemistry.

The simultaneous determination of melatonin and dopamine, two important neuromodulators, has been reported by Bagheri et al.48 using Fe3O4@reduced graphene oxide (rGO–Fe3O4) modified carbon paste electrodes (CPE) as the working electrode in square-wave voltammetry (SWV) measurements. The nanoparticle-modified CPE increased the oxidation peak current significantly compared to other electrodes (see Figure 14.12), property ascribed to the role of rGO–Fe3O4 as a promoter to assist the electrochemical oxidation of both analytes. The two well-separated peaks at þ 0.40 V and þ 0.68 V permitted the quantification of dopamine (LOD ¼ 6.5 nM) and melatonin (LOD ¼ 8.4 nM), respectively. Likewise, Shi et al.49 designed a chiral sensor capable of detecting simultaneously L- and D-Tyrosine (Tyr). Magnetic glassy carbon electrodes (MGCE) were modified with L-cysteine–Au/Fe3O4 NPs to differentiate the tyrosine enantiomers. Using SWV measurements, both L- and D-Tyr amino acids were detected with LODs of 0.017 mM and 0084 mM, respectively. Mahmoud et al.50 developed an analytical strategy for trinitrotoluene (TNT) in water samples using modified GCE. First, TNT was captured and separated from the aqueous sample using functionalized magnetic microspheres (L-MMS). The composition of the L-MMS consisted of poly(styrene-co-acrylic acid)–SiO2–Fe3O4 NP-AuNP-lignin (see Figure 14.13). After magnetic separation, the TNT/L-MMS system was dropped off on GCE and analyzed using differential pulse voltammetry

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Figure 14.13

365

Schematic illustration of the analytical strategy for TNT described in ref. 50.

(DPV) to decrease the background current, obtaining a LOD of 1.8 nM and high efficiency. Recently, a dual-mode biosensor was reported by Ganganboina et al.51 to detect norovirus using colorimetric and electrochemical sensing with LODs of 0.34 pg mL1 and 4.1 fg mL1, respectively. The strategy consists of forming a sandwich-like structure in the presence of norovirus between V2O5 NPs encapsulated liposomes and antibody-Fe3O4 MNPs. After magnetic separation, the immunocomplex is treated with Triton X, a surfactant, to break the liposome and release the catalytic V2O5 NPs. Hence, addition of TMB/H2O2 permits the colorimetric indirect detection of the norovirus. Furthermore, the V2O5 NPs/virus/Fe3O4 system can be deposited on graphene GCE for its electrochemical detection using DPV signals.

14.4 Concluding Remarks The application of magnetic nanoparticles in chemical sensing strategies is still a growing field. Their capability to be functionalized with a wide variety of molecular recognition elements combined with properties like superparamagnetism and catalytic activity makes them a versatile chemical tool in developing analytical methods, based on optical and electrochemical sensing, of interest in chemical, biological, environmental, pharmaceutical, and agricultural fields.

Acknowledgements I would like to thank all the scientific community whose relevant work is referenced in this chapter. Also, I am deeply grateful to the CONICET and SECyT-UNC for financial support. N.L.P. is a research member of the CONICET, Argentina.

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References 1. F.-G. Banica, Chemical Sensors and Biosensors: Fundamentals and Applications, Wiley, Chichester, 2012. 2. L. You, D. Zha and E. Anslyn, Chem. Rev., 2015, 115, 7840–7892. 3. R. Keçili and C. M. Hussain, Int. J. Anal. Chem., 2018, 2018, 1–18. ¨yu ¨ktiryaki and C. M. Hussain, TrAC, Trends Anal. Chem., 4. R. Keçili, S. Bu 2019, 110, 259–276. 5. D. Sharma and C. M. Hussain, Arabian. J. Chem., 2020, 13, 3319–3343. ¨yu ¨ktiryaki, R. Keçili and C. M. Hussain, TrAC, Trends Anal. Chem., 6. S. Bu 2020, 127, 115893. 7. B. Issa, I. Obaidat, B. Albiss and Y. Haik, Int. J. Mol. Sci., 2013, 14, 21266– 21305. 8. L. Reddy, J. Arias, J. Nicolas and P. Couvreur, Chem. Rev., 2012, 112, 5818–5878. 9. Z. P. Aguilar, Nanomaterials for Medical Applications, Elsevier Ltd., Waltham, USA, 2013. ˜ ez, in Nanoengineering ´n 10. N. L. Pacioni, M. Torres, A. Marı´a and R. N. Nu ´ Materials for Biomedical Uses, ed. E. I. Alarcon and M. Ahumada, Springer Nature, Switzerlarnd AG, Suiza, 2019, pp. 13–34. 11. S. Chattopadhyay, A. Kaur, S. Jain, P. K. Sabharwal and H. Singh, Anal. Chim. Acta, 2016, 937, 127–135. 12. S. Alhogail, G. A. R. Y. Suaifan, F. J. Bikker, W. E. Kaman, K. Weber, D. Cialla-May, J. Popp and M. M. Zourob, ACS Omega, 2019, 4, 21684– 21688. 13. S. Alhogail, G. A. R. Y. Suaifan and M. Zourob, Biosens. Bioelectron., 2016, 86, 1061–1066. 14. X. Ma, L. Song, Y. Xia, C. Jiang and Z. Wang, Food Anal. Methods, 2017, 10, 2735–2742. 15. S. Wu, Y. Wang, N. Duan, H. Ma and Z. Wang, J. Agric. Food Chem., 2015, 63, 7849–7854. 16. L. Zhang, R. Huang, W. Liu, H. Liu, X. Zhou and D. Xing, Biosens. Bioelectron., 2016, 86, 1–7. 17. R. Chinnappan, S. Al Attas, W. E. Kaman, F. J. Bikker and M. Zourob, Anal. Biochem., 2017, 523, 58–64. 18. M. Mazhani, M. T. Alula and D. Murape, Anal. Chim. Acta, 2020, 1107, 193–202. 19. J. Li, J. Wang, Y. Wang and M. Trau, Analyst, 2017, 142, 4788–4793. 20. L. Liang, S. Ge, L. Li, F. Liu and J. Yu, Anal. Chim. Acta, 2015, 862, 70–76. 21. C. Li, P. Dai, X. Rao, L. Shao, G. Cheng, P. He and Y. Fang, Talanta, 2015, 132, 463–468. 22. L. Gao, J. Zhuang, L. Nie, J. Zhang, Y. Zhang, N. Gu, T. Wang, J. Feng, D. Yang, S. Perrett and X. Yan, Nat. Nanotechnol., 2007, 2, 577–583. ¨ zer, K. Tu ˘ and R. Apak, Anal. Chem., 2015, 87, ¨rkekul, E. Erçag 23. Z. Can, A. U 9589–9594.

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24. M. ll Kim, D. Cho and H. G. Park, J. Nanosci. Nanotechnol., 2015, 15, 7955–7961. 25. Y. Man, A. Li, B. Li, J. Liu and L. Pan, Anal. Chim. Acta, 2019, 1092, 75–84. 26. B. Valeur and M. N. Berberan-Santos, Molecular Fluorescence: Principles and Applications, Wiley-VCH; Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim, Germany: [Chichester, England], 2nd edn, 2012. 27. Q. Xu, K. Liang, R.-Y. Liu, L. Deng, M. Zhang, L. Shen and Y.-N. Liu, Talanta, 2018, 187, 142–147. 28. H. Tan, G. Tang, Z. Wang, Q. Li, J. Gao and S. Wu, Anal. Chim. Acta, 2016, 940, 136–142. 29. N. Shahabadi, M. Maghsudi and S. Kashanian, Spectrochim. Acta, Part A, 2016, 157, 104–109. 30. C.-H. Liu, M.-H. Tsao, S. L. Sahoo and W.-C. Wu, RSC Adv., 2017, 7, 5937– 5947. 31. Q. Xue, Y. Zhang, S. Xu, H. Li, L. Wang, R. Li, Y. Zhang, Q. Yue, X. Gu, S. Zhang, J. Liu and H. Wang, Analyst, 2015, 140, 7637–7644. 32. L. Tong, Z. Chen, Z. Jiang, M. Sun, L. Li, J. Liu and B. Tang, Biosens. Bioelectron., 2015, 72, 51–55. 33. Z. Sun, D. Guo, H. Li, L. Zhang, B. Yang and S. Yan, RSC Adv., 2015, 5, 11000–11008. 34. Z. Wang, X. Ma, S. Zong, Y. Wang, H. Chen and Y. Cui, Talanta, 2015, 131, 259–265. 35. L. Ding, Y. Wu, W. Liu, L. Liu, F. Yu, S. Yu, Y. Tian, J. Feng and L. He, Talanta, 2019, 205, 120129. 36. M. L. Bhaisare, G. Gedda, M. S. Khan and H.-F. Wu, Anal. Chim. Acta, 2016, 920, 63–71. 37. N. Shahabadi, M. Maghsudi and L. Nemati, J. Photochem. Photobiol., B, 2015, 149, 215–223. 38. P. Larkin, Infrared and Raman Spectroscopy, Elsevier Ltd., The Netherlands, 2nd edn, 2018. 39. P. Stiles, J. Dieringer, N. Shah and R. Van Duyne, Annu. Rev. Anal. Chem., 2008, 1, 601–626. 40. Z. Rong, C. Wang, J. Wang, D. Wang, R. Xiao and S. Wang, Biosens. Bioelectron., 2016, 84, 15–21. 41. C. Wei, C. Zhang, M. Xu, Y. Yuan and J. Yao, J. Raman Spectrosc., 2017, 48, 1307–1317. 42. K. Yang, Y. Hu, N. Dong, G. Zhu, T. Zhu and N. Jiang, Biosens. Bioelectron., 2017, 94, 286–291. 43. S. Chattopadhyay, P. K. Sabharwal, S. Jain, A. Kaur and H. Singh, Anal. Chim. Acta, 2019, 1067, 98–106. 44. D. Song, R. Yang, F. Long and A. Zhu, J. Environ. Sci., 2019, 80, 14–34. 45. J. Wang, Electroanalytical Chemistry, John Wiley & Sons, Inc., Hoboken, NJ, USA, 3rd edn, 2006. 46. J. A. Ramos Guivar, E. A. Sanches, C. J. Magon and E. G. Ramos Fernandes, J. Electroanal. Chem., 2015, 755, 158–166.

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47. J. A. R. Guivar, E. G. R. Fernandes and V. Zucolotto, Talanta, 2015, 141, 307–314. 48. H. Bagheri, A. Afkhami, P. Hashemi and M. Ghanei, RSC Adv., 2015, 5, 21659–21669. 49. X. Shi, Y. Wang, C. Peng, Z. Zhang, J. Chen, X. Zhou and H. Jiang, Electrochim. Acta, 2017, 241, 386–394. 50. K. A. Mahmoud, A. Abdel-Wahab and M. Zourob, Water Sci. Technol., 2015, 72, 1780–1788. 51. A. B. Ganganboina, A. D. Chowdhury, I. M. Khoris, F. Nasrin, K. Takemura, T. Hara, F. Abe, T. Suzuki and E. Y. Park, Biosens. Bioelectron., 2020, 157, 112169. 52. M. Arvand, S. Orangpour and N. Ghodsi, RSC Adv., 2015, 5, 46095–46103. 53. B. B. Prasad and D. Jauhari, Anal. Chim. Acta, 2015, 875, 83–91. 54. M. Taei, F. Hasanpour, M. Movahedi and S. Mohammadian, RSC Adv., 2015, 5, 37431–37439. ´n, G. Iba ´n ˜ ez-Redı´n, R. C. Faria, D. S. Correa and 55. D. Wilson, E. M. Matero O. N. Oliveira, Talanta, 2019, 194, 611–618. 56. M. Arvand, Z. Erfanifar and M. S. Ardaki, Food Anal. Methods, 2017, 10, 2593–2606. ´lvez, C. C. Mayorga-Matinez, C. Parolo, J. Pons and 57. A. Zamora-Ga A. Merkoçi, Electrochem. Commun., 2017, 82, 6–11. 58. Y. Xie, T. Zhang, Y. Chen, Y. Wang and L. Wang, Talanta, 2020, 213, 120843. 59. Z. Shi, W. Hou, Y. Jiao, Y. Guo, X. Sun, J. Zhao and X. Wang, Int. J. Electrochem. Sci., 2017, 7426–7434. 60. N. A. Abdallah, H. F. Ibhrahim and N. H. Hegabe, Int. J. Electrochem. Sci., 2017, 10894–10910. 61. S. Sanli, F. Ghorbani-Zamani, H. Moulahoum, Z. P. Gumus, H. Coskunol, D. Odaci Demirkol and S. Timur, Anal. Chem., 2020, 92, 1033–1040. 62. K. Asadpour-Zeynali and F. Mollarasouli, Biosens. Bioelectron., 2017, 92, 509–516. 63. T. C. Canevari, F. H. Cincotto, D. Gomes, R. Landers and H. E. Toma, Electroanalysis, 2017, 29, 1968–1975. 64. A. B. Chimezie, R. Hajian, N. A. Yusof, P. M. Woi and N. Shams, J. Electroanal. Chem., 2017, 796, 33–42. 65. N. Marinho Rodrigues, S. Neto, R. Luz, F. Damos and H. Yamanaka, Biosensors, 2018, 8, 16.

CHAPTER 15

Magnetoresistance-based Biosensors APOORVA SHARMA,a ASHOK D. CHOUGALE,b GEORGETA SALVANa AND PRASHANT B. PATIL*c,y a

Institute of Physics, Chemnitz University of Technology, Chemnitz-09126, Germany; b Department of Chemistry, The New College, Shivaji University, Kolhapur, Maharashtra-416012, India; c Department of Physics, The New College, Shivaji University, Kolhapur, Maharashtra-416012, India *Email: [email protected]

15.1 Introduction Biosensors utilizing biological reactions for detecting target analytes are highly sought after in the field of clinical diagnostics, pharmaceutics, and environmentally hazardous material detection. In a biosensor, the analyte to be detected interacts with the bioreceptor (biological recognition element) to produce an effect which is converted into a measurable signal by a transducer.1 The formation of the analyte/bioreceptor complexes is commonly triggered by antigen/antibody interactions, nucleic acid interactions, enzymatic interactions, cellular interactions or by the usage of biomimetic materials.2 The immobilization of the analyte on the bioreceptor needs to be detected and converted into an electronic signal by a transducer. Several types of signal transducers such as electrochemical, optical, piezoelectrical, and magnetic sensors are commonly used in biosensors.3 y

Section 15.3 Tunnel Magnetoresistance Sensors and parts of 15.3 Spin-Valves and Pseudo SpinValves have been adapted from ref. 100.

Analytical Applications of Functionalized Magnetic Nanoparticles Edited by Chaudhery Mustansar Hussain r The Royal Society of Chemistry 2021 Published by the Royal Society of Chemistry, www.rsc.org

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Currently, a few analytical techniques employing biosensors, such as enzyme-linked immunosorbent assays (ELISA), western blot, and polymerase chain reaction (PCR) are widely used for the detection of antigen/antibody, DNA, etc. in the biomedical field. However, the analysis of the results of these techniques requires state-of-the-art laboratory and special skills. Smaller, faster, and cheaper Point-of-Care (PoC) devices are highly desired for replacing time-consuming laboratory-analyses. Making analytical results available at the patient’s bedside within a few minutes can significantly improve disease management. However, the instrumentation required for the conventional techniques mentioned above is difficult to translate to the PoC devices. During the last two decades, magnetoresistance (MR)-based biosensors have received significant attention as they not only fulfill the prerequisite of high sensitivity, quick response, and excellent selectivity but also present the possibility of miniaturization as required for PoC and Lab-on-Chip (LoC) devices. The emergence of MR-based sensors, which has significantly improved the capability to precisely measure ultralow magnetic fields, has opened several possibilities to develop magnetic field sensors that can be used in such applications. A general scheme of an MR biosensor is sketched in Figure 15.1. The analytes to be detected are initially attached to magnetic nanoparticles (MNPs) through linker molecules. Analyte-tagged MNPs are then passed over an array of on-chip magnetic field sensors pre-coated with the receptor specific to the analyte to be detected. The labeled MNPs become immobilized on the sensors due to the interaction between the analyte and the receptor. The applied magnetic field induces a magnetization in the immobilized MNPs, which changes the resistance in the underlying MR sensor. The superparamagnetic nanoparticles (SP-MNP) commonly used for biosensing usually exhibit a blocking temperature lower than the room temperature. At room temperature they thus typically remain in the superparamagnetic

Figure 15.1

Schematic illustration of the general scheme of an MR-based biosensor. The target analyte bound to the functionalized MNP interacts with the receptor on the surface of a magnetic field sensor. To detect a superparamagnetic MNP over the MR sensor, an external magnetic field (B) is applied to magnetize the MNP.

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state, i.e., they behave as an ensemble of macrospin magnetic moments (similar to a Langevin paramagnet,4 but having much larger magnetic susceptibility). The stray or demagnetizing field of each SP-MNP averages zero during the measurement time in the absence of an external magnetic field. It is, therefore, necessary to apply an external magnetic field that will induce the alignment of the magnetization of each SP-MNP parallel to the field direction to create a measurable signal at the MR sensor. After washing away the unbound analyte, the signal from the magnetic field sensor will be proportional to the number of SP-MNPs and hence to the analyte concentration,5 as long as the concentration is lower than the value required to saturate the receptors. If the functionalized MNPs are used in combination with microfluidic systems with integrated MR sensors, diagnostics and analytics at a microscale level are possible. We preface our discussion by noting that the intention behind this chapter is to provide a short overview of the principles and technological realizations in the field of MR-based biosensors and to promote enthusiasm in the field without highlighting a specific technological achievement and its implementation. We will first introduce the basics of several types of MR effects, namely anisotropic magnetoresistance (AMR), giant magnetoresistance (GMR), and tunneling magnetoresistance (TMR). The properties of MNPs that are essential for MR based biosensors, their functionalization, as well as different bioassays used in MR-based biosensors, will then be discussed. Finally, device concepts and future perspectives of MR-based biosensors will be addressed.

15.2 Magnetoresistive Sensors In the past few decades, we have witnessed tremendous development in extremely sensitive and novel methods that allow us to measure the feeble magnetic field (in range of a few pT) generated by neurons, muscles and other bio-entities. Each technique devoted to the measurement of such a weak magnetic field comes, however, with its own sets of challenges, such as working temperature, environment, etc., which in turn restricts its usage to a limited number of applications. The most commonly used magnetic field sensors in the field of biomedical diagnosis are categorized according to their application in Figure 15.2. The inner-circle with puzzle pieces is divided into two halves, with the lower half representing methods for sensing biomagnetic signals such as magnetocardiography (MCG), magnetoencephalography (MEG), magnetoneurography (MNG), and magnetomyography (MMG). The upper half of the inner circle shows direct and MNP-based detection methods for biological entities (such as antigen, antibody, DNA, etc.). Each concentric circle or arc shows the potential of a particular magnetic field sensor to be used in the specific biosensing or detection application. Although there is a variety of magnetic field sensors available on the market, it was the emergence of spintronics that has revolutionized magnetic field sensors. The term spintronics is a combination of the terms spin and electronics, indicating that both the spin and the charge of the

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Figure 15.2

Chapter 15

Diagram showing the most common magnetic field sensors used in the biomedical field such as magnetocardiography (MCG),76–79 magnetoencephalography (MEG),76,79–83 magnetoneurography (MNG),79,84–86 and magnetomyography (MMG).79,84,87–89 The upper half of the diagram presents the magnetic field sensors compatible with LoC applicationbased magnetic nanoparticles (MNP)57,90–92 and direct detection.93–95

electron(/s) are exploited in spintronic devices. An often-proposed scheme of a spintronic device is based on magnetoresistive effects. The MR effect is the manifestation of change in the resistance of a material when subjected to an external magnetic field. The magnetoresistance is usually expressed by: MR ¼

RðBÞRð0Þ R ð0 Þ

(15:1)

here, R(B) and R(0) are the resistance levels in the presence and absence of a magnetic field (B), respectively. In the following part of this section, an overview of the different types of magnetoresistance effects is given. In non-magnetic conductors, a change in electrical resistance can be caused by the Lorentz force that a magnetic field exerts on moving electrons or in general on charge carriers. This resistance change is exploited especially for magnetic field sensing applications in the sensors nowadays known as Hall sensors, making use of the Hall effect.6

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In the following, the Hall effect will not be further highlighted because it is a purely electrically driven effect. We will focus instead on the discussion of magnetoresistive devices based on the anisotropy magnetoresistance (AMR), as well as giant magnetoresistance (GMR), and tunneling magnetoresistance (TMR)-based devices. In general, MR sensors either comprise of a ferromagnetic thin film (in case of AMR) or a non-magnetic (NM) layer (conducting in the case of GMR and insulating for TMR) sandwiched between two ferromagnetic (FM) layers. The eminent advantage of spintronic MR sensors is that they are compatible with current complementary metal oxide semiconductor (CMOS) microfabrication technology. This allows for the miniaturization of the sensors and the integration of sensor arrays on a testing platform and hence for the analysis of minute quantities of biological samples and at the same time for low amounts of reagents needed for testing. This, in turn, reduces the overall costs and waste produced while testing.

15.2.1

Anisotropy Magnetoresistance Sensors

Anisotropy magnetoresistance (AMR) was discovered by William Thomson (Lord Kelvin) in 1857. In ferromagnetic conductors, the electrical resistance depends on the angle between magnetization and electric current (Figure 15.3). In the presence of an external magnetic field, this angle may change and thereby the electrical resistance. This change in resistance is known as anisotropic magnetoresistance.7 The typical AMR ratio of ferromagnetic materials at room temperature does not exceed a few percent,8 resulting in a sensitivity of approximately 1 mV/Oe for an AMR effect-based sensors. AMR sensors are usually used as angular sensors because the magnetization of soft ferromagnets can easily be rotated by very small fields.

15.2.2

Giant Magnetoresistance Sensors

The giant magnetoresistance (GMR) is a magnetoresistance effect observed in thin film structures composed of alternating ferromagnetic and nonmagnetic conductive layers. It was discovered in 1988 in [Fe/Cr] multilayers by Baibich et al.9 and Binasch et al.10 The variation of the electrical resistance as a function of the applied magnetic field for various [Fe(30 Å)/Cr(t)]n

Figure 15.3

A typical geometry used to observe the anisotropy magnetoresistance effect (left) and the schematic illustration of the change in resistance of a ferromagnetic film as a function of the angle between the magnetization and the direction of the electrical current (right).

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Figure 15.4

Chapter 15

Magnetoresistance of [Fe/Cr]n multilayers for n ¼ 30, 35, and 60 at 4.2 K with the in-plane applied current and magnetic field. Reproduced from ref. 9, https://doi.org/10.1103/PhysRevLett.61.2472, with permission from American Physical Society, Copyright 1988.

structures at a measurement temperature of 4.2 K reported by Baibich et al.9 is shown in Figure 15.4. This figure shows how the electrical resistance of these FM/NM heterostructures drops with an increasing magnetic field, as the magnetization of the Fe layers aligns from antiparallel to parallel to each other. HS represents the saturation field required to overcome the interlayer antiferromagnetic coupling through the Cr layers. The MR response of such a magnetic multilayer device is several orders of magnitude higher than that of the typical AMR sensors and hence the effect was named giant magnetoresistance. The fields of applications of GMR sensors range from the medical and health care sector to the technology of everyday life, such as smartphones,11 automobile,12 Internet-of-Things,13 etc. In Figure 15.5, a simplified scheme of the GMR effect in a trilayer structure (FM/NM/FM) is illustrated, which is based on Mott’s two-current model with separate spin channels for spin-up and spin-down electrons.14 The two channels experience different electrical resistance in ferromagnetic materials due to the different density of spin-up and spin-down states at the Fermi level. In a trilayer structure, as shown in Figure 15.5, the overall electrical resistance depends additionally on the mutual magnetization directions of the two FM layers. The total device resistance for different magnetization configurations can be visualized in an equivalent resistor representation. For the case when

Magnetoresistance-based Biosensors

Figure 15.5

375

An equivalent resistor representation of the giant magnetoresistance in parallel (a) and antiparallel (b) orientation of the two FM layer magnetizations. In the parallel magnetic configuration, spin-up electrons flow easily through the device, resulting in a low resistance state. In the antiparallel magnetic configuration, electrons of both spin orientations experience scattering, resulting in a high resistance state.

the magnetizations in the two FM layers are aligned parallel to each other, the net resistance in this configuration is given by15,16 RP ¼ 2

RHigh :RLow RHigh þRLow

(15:2)

Similarly, in the case of the antiparallel orientation of the magnetization in the FM layers, both spin-up and spin-down electrons encounter alternating magnetization, thus resulting in a final high resistance state RAP ¼

RHigh þRLow c RP 2

(15:3)

In the case of the GMR, the electrical resistance for the antiparallel magnetization state (RAP) will always be greater as compared to the parallel state (RP). This gives rise to the GMR ratio given by GMR ¼

RAP RP RP

(15:4)

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Tunnel Magnetoresistance Sensors

In the year 1971, P.M. Tedrow and R. Meservey et al. laid the foundation of the tunnel magnetoresistance (TMR) devices by discovering the spinpolarized tunneling in the Al/Al2O3/Ni junction.17 M. Julliere, in 1975, proposed the spin conservation theory and presented a quantitative explanation for the response of the magnetic tunnel junction (MTJ)18 composed of a thin non-magnetic insulating tunnel barrier sandwiched between two ferromagnetic electrodes. M. Bowen et al. emphasized the importance of the electronic and crystal structure of the entire electrode/barrier/electrode system in the year 2001. They measured a TMR ratio of 60% at 30 K for a Fe(001)/MgO(001)/FeCo(001) MTJ.19 This MR response was four times higher than the best performance of Al2O3-based MTJs studied until that date. However, the very low operational temperature limited its device application. Later on, Ikeda et al. presented in 2008 a breakthrough result for the CoFeB/ MgO/CoFeB system with an extraordinary TMR ratio of 603% at room temperature.20 Since the layer structure of a TMR sensor is fundamentally similar to that of a GMR sensor, often both types of sensors are found sharing the same field-of-applications. The TMR sensors offer several advantages over the existing GMR sensors, such as high accuracy, high resolution, low power consumption, high thermal stability, and less ageing deterioration. Despite the advantages mentioned above, the TMR sensors suffer a drawback due to the shot noise arising from the tunnel barriers.21 The charge transfer through the tunnel barrier occurs due to quantum tunneling. As in the case of the giant magnetoresistance, one can treat the current through the junction as consisting of two separate spin current channels for spin-up and spin-down electrons (Mott’s two-current model14). The two channels encounter different electrical resistance in ferromagnetic materials depending on the magnetization and hence on the spin polarization of the FM. The electrode spin polarization arises from the imbalance of the density of states of the spin-up and spin-down electrons near the Fermi level in the ferromagnetic layers and thus from their magnetic anisotropy in the magnetized state (Figure 15.6). In FM/NM/FM structures, the overall electrical resistance depends then on the mutual magnetization directions of both FM layers: TMR ¼

2P1 P2 1P1 P2

(15:5)

where P1 and P2 represent the spin polarizations of two ferromagnetic layers. Experimentally, the TMR ratio is calculated as: TMR ¼

R"# R"" R""

where Rmk and Rmm are the resistances of MTJ in antiparallel and parallel magnetization configuration, respectively.

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Figure 15.6

377

Schematic representation of the tunnel magnetoresistance in the case of two identical ferromagnetic layers separated by a non-magnetic insulating barrier such as MgO. The tunneling process conserves the spin. When the electronic states of the FM on each side of the barrier are spin polarized, the electrons will more easily find free states to tunnel through the barrier if the FM magnetizations are parallel (a) than if they are antiparallel (b) to each other. The arrows in green and red indicate the higher and lower tunneling probability of a spinpolarized electron through a tunnel barrier, respectively. The yellow balls represent the electrons with their intrinsic spin orientation. Adapted from ref. 96 with permission from Elsevier, Copyright 2016.

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Spin-Valves and Pseudo Spin-Valves

Layer stacks consisting of at least two ferromagnetic conducting materials being exchange decoupled by a non-magnetic spacer layer are called spinvalves (SV).22 The non-magnetic spacer layer is usually electrically conducting and the resistance of the spin-valve can be controlled by the relative orientation of the FM layer magnetization orientation, based on the GMR effect discussed above. When one of the two ferromagnetic layers is exchange coupled to an antiferromagnetic material due to the exchange bias effect,23 this layer will be called pinned or fixed, or the reference layer (RL). The corresponding layer stack is named ‘‘spin-valve’’ (see the sketch in Figure 15.7a). The exchange bias effect induces a shift of the hysteresis loop along the applied magnetic field axis by the amount of the exchange field. This corresponds to a preferred (therefore pinned) magnetization state at fields smaller than the exchange field. The other ferromagnetic layer of the spin-valve system, which is exchange decoupled from the pinned reference layer, is called the free layer (FL) since its magnetization is free to rotate in accordance to the external applied magnetic field. The spin-valve structures leveraged spintronics due to the well-defined magnetization reversal of the free layer with small hysteresis and very high field sensitivity. Such magnetic field sensors were able to compete with Hall sensors and additionally enabled new applications, such as smartphone navigation based on the earth’s magnetic field.11 A pseudo-spin-valve (PSV) is very similar to the SV system except for the missing antiferromagnetic layer (see Figure 15.7b for a sketch). The different magnetization of the two ferromagnetic layers in an applied magnetic field is enabled either by the antiferromagnetic coupling of the two FM layers (which is achieved by the careful choice of the thickness of the NM layer9) or by the use of different materials with different coercive fields for the two FM layers (with the larger coercive field corresponding to the RL layer). In magnetic saturation, in both directions, the parallel state (corresponding to low resistance) occurs, whereas for applied magnetic fields in between both magnetization reversal of the antiparallel state (corresponding to high resistance) is present.24

15.3 MNPs in MR-based Biosensors Recently, various types of (non-) magnetic nanomaterials have been used in pharmaceutical, bioanalytical, and environmental analysis.25–30 MNPs are an essential component of MR-based biosensors since, as discussed in the introduction (Section 15.1), the conversion from biological information to the magnetic signal is realized by tagging target analytes with MNPs. MNPs can be synthesized with different sizes ranging from a few nanometers to several micrometers which makes them compatible for tagging various bioentities ranging from proteins (a few nm) to cells and bacteria (several mm)2. An essential aspect for the MNP–biomolecule conjugation is the surface modification of MNPs by coating or functionalization with suitable moieties. We refer to functionalization when an active chemical group

Magnetoresistance-based Biosensors

Figure 15.7

379

Schematic diagram of a spin-valve (SV) (a) and pseudo-spin-valve (PSV) (b). The free layer (FL) is the layer above the non-magnetic spacer. In the case of SV, the pinned layer (PL) is the FM layer in direct contact with an antiferromagnetic layer (AFM) which is responsible for the pinning via the exchange bias effect. In PSV, the FM layer below the spacer is the reference layer (RL).

(e.g., amine in APTES) is used to treat the MNP, whereas a nonfunctional surface modification (e.g., SiO2 passivation) will be referred to as a surface coating. The specificity of the MNP–biomolecule conjugation leads to the high reliability of the sensor response. In addition to the appropriate MNP– biomolecule conjugation, which can be achieved by the suitable functionalization (see Section 15.4) for MR-based biosensor applications, MNPs must possess the following combined properties: a high magnetic moment, biocompatibility, and colloidal stability. These properties will be discussed in more detail in the following sub-sections.

15.3.1

High Magnetic Moment

Magnetic labels should have a large magnetic moment and corresponding large magnetic susceptibility so that their magnetic response can easily be detected by MR sensors.31 Superparamagnetic particles with different sizes have been used in MR biosensing.32,33 Micrometer-sized spheres (usually referred to as beads) are widely studied.5 Such microspheres generally have a high magnetic moment per label, which permits the detection of a very small

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number of particles. Furthermore, due to the uniform size and shape of the microspheres, quantitative analysis is possible as the signal will be proportional to the number of the monodispersed magnetic labels34 (as long as the receptors on the sensor surface are not saturated). However, the ‘‘large’’ diameter of the microsphere labels limits the density of the labels over the sensor area. Presently, MNPs have replaced the microspheres because they can be stable in suspension and do not agglomerate in an applied magnetic field.32 Additionally, with the small-sized MNPs, a high-density binding on the sensor area becomes possible. Similar to the microspheres, the MNPs should be monodispersed in both their size and magnetic moment in order to allow for the quantification of the analyte.

15.3.2

Biocompatibility

In the MR-based biosensor applications, one of the essential properties that the MNPs should possess is high biocompatibility towards bioentities. For this, iron-oxide particles are mostly used as they are highly biocompatible and cheap.35 To date, magnetite (Fe3O4) or maghemite (g-Fe2O3) magnetic particles with a biocompatible coating are used in biosensing applications. Metallic nanoparticles such as cobalt or nickel particles are toxic and susceptible to oxidation and hence are often avoided.36

15.3.3

Colloidal Stability

The MNPs should be chemically and colloidally stable and should not aggregate in the media required for MR-based sensor applications. For quantitative analysis, MNPs should be chemically stable and uniformly dispersed in an aqueous solvent at physiological pH.37 The MNPs must be in a superparamagnetic state to avoid agglomerations caused by magnetic dipolar interactions. For small enough sizes, in the absence of an applied magnetic field, the colloidal stability of the particles depends on the balance between attractive forces (van der Waals interactions) and repulsive forces (steric and electrostatic interactions) acting between the particles in the superparamagnetic state.38 In order to create repulsive (mainly steric repulsion) forces, surfactants or polymers can be chemically anchored or physically adsorbed on MNPs.39 By electrostatic charging of the particles, additional repulsive Coulomb forces can be induced. Thus, the colloidal stability depends on the particle size as well as on the charge and surface chemistry.36

15.4 Functionalization The functionalization of the MNPs resides in adding chemical functional groups on the surface (e.g., –OH, –NH2, –COOH, –SH), which can be used to conjugate specific biomolecules with the MNPs depending on the intended application.40 The specific binding of biomolecules on the MNPs surface is crucial for MR-based biosensors.41 The biofunctionalization of MNPs with biomolecules responsible for the recognition (e.g., proteins, DNA and other

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ligands) is essential for the MNP–analyte conjugation. The biofunctionalization plays, therefore, an important role in methodological and device development. The surface functionalization of MNPs can be done by two general approaches: ligand addition and ligand exchange.34 In ligand addition, a ligand is added to the surface of the MNPs without removing preexisting ligands. Amino silanes are commonly used to prepare amine-functionalized MNPs employing the ligand addition process.42 The ligand exchange method comprises of replacement of the original ligand with a bifunctional ligand; one functional group binds to the particle surface and a second functional group can be used for further functionalization, i.e., for binding to the analyte.34 Biocompatible polyethylene glycol (PEG) is a commonly used polymer for ligand exchange which avoids any nonspecific reactions between MNPs and proteins.34 Besides PEG, natural polymers such as dextran, chitosan, and dendrimers have also been used in the ligand exchange.43 Among various small molecules, 2,3-mesodimercaptosuccinic acid (DMSA), with two carboxylic and two thiol groups, has been extensively used for functionalizing MNPs.44 MNP-biomolecule conjugates offer the unique combination of the properties and functionality of both materials, i.e., the magnetic moment of the MNPs and the specificity of the biomolecules for recognition.45 For MR-based biosensor applications, the conjugation of biomolecules to the functionalized MNPs can be done in different ways and is discussed in the next section.

15.5 Assays for MR-based Biosensors The MNP conjugated with a biomolecule (antigen, antibody, or DNA probe) interacts with the complementary biomolecule pre-coated on the MR sensor surface. The presence of the MNPs on the sensor surface leads to changes in the sensor resistance, which is used to evaluate the presence and/or estimate the amount of the analyte. Interaction between antigen/antibody or similarly interacting biomolecules (e.g., biotin–streptavidin) and the receptors on the sensor surface mostly takes place via noncovalent interactions like hydrogen bonds, van der Waals, ionic, or hydrophobic interactions. Each of these noncovalent interactions operates over a very short distance of about a few Å. Therefore, these biomolecules have to come in close contact with each other in order to interact. The interaction between them is responsible for their trapping on the sensor surface and hence for their detection in the MR-based biosensors. Different bio-assays can be used for qualitative and quantitative measurements of the analyte, as discussed in detail in the following subsections.

15.5.1

Direct Assay

The MR-based direct assay method can be used for the detection and/or quantification of several types of biomolecules. We will first discuss the basics of the direct assay method as it has been applied to the detection of antigens (Ag) as well as antibodies (Ab) from biological samples.46

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The procedure for the direct assay is schematically shown in Figure 15.8 and explained in the following. The antigen detection scheme is explained in Figure 15.8a and the antibody detection scheme is explained in Figure 15.8b. 1. The biological sample containing the analyte (antigen or antibody) is initially coated on the MR sensor surface. The blood sample contains a vast number of different antigens, antibodies and other proteins, that also get coated on the surface. 2. The unbound biomolecules are washed away using a washing buffer solution. 3. The remaining free surface of the MR sensor is then blocked with a blocking agent (BSA or casein) to avoid unspecific binding of the biomolecules in the later steps. The excess blocking agent is washed off. 4. A solution containing MNP-conjugated antibodies for the detection of respective antigens is added on the sensor (Figure 15.8a). For the detection of antibodies, MNP-conjugated antigens specific against the respective antibody are added on the sensor (Figure 15.8b). Incubation is allowed in order to induce the reaction of the analyte on the MR sensor surface with the respective complementary moiety. The unbound material from the sample is subsequently washed away. 5. The MR sensor measures the change in the magnetic induction due to the presence of the MNPs. This change depends upon the magnetic moment of the individual MNP and on the amount of MNPs present on the sensor surface, assuming monodispersed MNPs. The measured magnetic field will thus be proportional to the concentration of the analyte present in the sample (assuming that each tagged MNP binds to an analyte molecule). Similarly, target DNA from the sample can also be detected using a direct method. This type of sensor is also known as a DNA biosensor (Figure 15.8c). The direct assay detection method employed for DNA detection involves a similar scheme as discussed for the antigen or antibody detection: 1. The sensor surface is coated with suitable probe DNA molecules. 2. The DNA from the sample is initially isolated and biotinylated. The biotinylated DNA analyte is then allowed to react with the probe DNA molecules pre-coated on the MR sensor to form DNA–DNA hybridization. 3. Streptavidin-coated MNPs are added to the hybridized DNA. The streptavidin molecules specifically bind to the biotinylated DNA in the hybridized strand.47 4. Consequently, the amount of MNPs on the sensor surface directly relates to the concentration of the target DNA in the sample. DNA biosensors using a direct assay method have been utilized, for example, for DNA microarrays and for the detection of viral DNA.47–49 There are also several reports on the direct assay-based detection of the proteins from the biosamples. Adem et al. developed an activity-based protease

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Figure 15.8

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Schematic representation of the direct assay detection of antigens (a) and antibodies (b) from a sample. The antigens/antibodies from the sample are coated on the MR sensor and incubated with the MNP-conjugated antibodies/antigens. The MNP-conjugated antibodies/ antigens selectively bind to a respective moiety (antigens/antibodies) present on the MR sensor. The sensor signal will be proportional to the amount of MNPs present on the sensor and hence to the analyte concentration. (c) Detection of target DNA molecules from the sample. The DNA probe corresponding to the target DNA is coated on the MR sensor. Biotinylated DNA is added, which hybridizes with a respective pre-coated DNA probe. The streptavidin-coated MNPs are then added to specifically bind to biotinylated DNA.

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sensor to quantify the active enzyme level, which is crucial for a number of human disease diagnosis, using the direct assay method.50

15.5.2

Sandwich Assay

Despite the suitability of the direct assay for antigen detection, the most common assay preferred for antigen detection remains the sandwich assay.51 The name of the method stems from the final structure acquired in this method. Here, the analyte antigens get sandwiched between the capture antibodies and MNP-conjugated antibodies. The process flow of the MRbased sandwich assay is shown in Figure 15.9 and the corresponding working procedure is as follows: 1. The antibodies (capture antibodies) specific to the antigen to be analyzed are initially coated on the MR sensor surface. 2. The unbound antibodies are washed away with the buffer solution. 3. The free surface of the MR sensor is blocked with a blocking agent (BSA or casein) to avoid the unspecific binding of the antigens during the later steps. The excess blocking agent is washed away using the buffer solution. 4. The sample containing antigens (to be detected) is then added and allowed to react with the pre-coated antibodies. 5. The unbound sample is washed away with buffer. 6. MNP-conjugated antibodies specific for a different epitope on the analyte antigens are added and allowed to react with the antigens. Free MNP-conjugated antibodies are removed by washing.

Figure 15.9

Schematic representation of the sandwich assay method for the detection of the antigen from the sample. Coating of the MR sensor surface with capture antibody is followed by blocking and addition of the sample. The target antigen from the sample, specifically binds to the capture antibody coated on the MR surface. In the last step secondary antibody conjugated with MNP binds with an antigen to form a sandwich structure.

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7. The signal from the MR sensor will thus be proportional to the amount of MNPs present, which in turn corresponds to the antigen’s concentration. The sandwich assay has been usually employed for the detection of protein biomarkers for various human diseases such as tuberculosis, lung cancer, prostate cancer, heart disease, and environmental pollutants such as mercury.52–61

15.5.3

Competitive Assay

This method is used to detect either antigens or antibodies and is based on the competition between labeled and unlabeled antigens (or antibodies) for a limited number of binding sites on the sensor surface. The procedure for the MR based competitive assay is schematically shown in Figure 15.10 and explained in the following. 1. For the detection of antibodies, the respective antigens are coated on the MR sensor surface (Figure 15.10a). On the other hand, to detect antigens, respective antibodies are coated on the MR sensor surface (Figure 15.10b). 2. The unbounded antigens/antibodies are washed away with a washing buffer. 3. The remaining surface of the MR sensor is blocked with a blocking agent. The excess blocking agent is washed away using the buffer. 4. The sample containing the antibodies (to be detected) and identical antibodies labeled with MNPs are then added to the antigens already coated on the MR sensor (Figure 15.10a). Here the MNP-conjugated antibodies and antibodies from the sample compete to bind with an antigen on the MR surface. Similarly, for antigen detection (Figure 15.10b), the sample containing the antigens to be detected and identical MNP-conjugated antigens is added to the antibodies previously coated on the MR sensor. In this case, the MNP-conjugated antigens and antigens from the sample will compete to bind with the antibodies on the MR surface. The unbound material is washed away. 5. While detecting antibodies, if a large number of antibodies is present in the sample, then fewer MNP-conjugated antibodies will be bound to pre-coated antigens (Figure 15.10a). Similarly, in the case of antigen detection, if the sample contains a large number of antigens, then fewer MNP-conjugated antigens will be bound to pre-coated antibodies (Figure 15.10b). The MR sensor signal will be proportional to the MNP number and hence inversely proportional to the analyte concentration. The competitive assay method for MR-based biosensors is the least studied technique compared to other assay methods. In a recent study, Srinivasan et al. successfully quantified endoglin from unprocessed human urine

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Figure 15.10

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Schematic representation of antibody (a) and antigen (b) detection from a sample by competitive assay. The antigens (or antibodies) of the respective antibodies (or antigens) in the sample are coated on the MR sensor. The free sensor surface is blocked. The sample containing analyte antibodies (or analyte antigens) and identical MNP-conjugated antibodies (or MNP-conjugated antigens) is added on the MR sensor. MNP-conjugated moieties (antibodies/antigens) and analytes from the sample compete to bind the pre-coated moieties (antigens/antibodies). The more MNPs are present on the MR surface, the lower the concentration of the target moiety in the sample.

samples.62 The endoglin levels in urine are used to predict the presence of prostate cancer and to distinguish between prostate cancers of different grades.

15.6 Device Concept Building a MNP-based PoC platform is like building a Lego model, where every PoC device consists of some fundamental components (basic building blocks) that must be combined following a specific set of rules dictated by the choice of assay method, type of sensor, detection method, device geometry, etc. A typical MNP-based PoC device requires the following basic building blocks:

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15.6.1

387

Magnetic Tags

These are magnetic nanoparticles that fulfill a two-fold purpose: the first purpose is to serve as a carrier that assists in the near-frictionless transportation of fluid in the microchannel (in microchannel-based LoC/PoC). Secondly, the magnetic markers are responsible for the distortion of the applied magnetic field and thereby for the signal generation in the MR sensors. To ensure their immobilization on the sensor surface, the MNPs can be labeled with any relevant bio-entity required for the biorecognition process via functionalization.

15.6.2

Magnetic Field Sensor

The magnetic field sensors are transducers that detect and measure the change in an applied magnetic field caused by the magnetic susceptibility of the magnetic nanoparticles and output an electrical response accordingly (see Figure 15.11). Although the MR-based magnetic field sensors are very sensitive to minute changes in the magnetic field, the overall device response can be improved by several orders of magnitude when several MR sensors are used in the Wheatstone bridge configuration. A generic Wheatstone bridge is comprised of two or four identical MR sensors resulting in a half or full bridge configuration, respectively. In a balanced bridge condition (equal MR of all the sensors) the output of the bridge is null, however, when the magnetic beads pass over on one of the MR sensors, the bridge becomes unbalanced and outputs an electrical response proportional to the difference in the magnetic field experienced by that MR sensor and the rest of the sensors. Since all MR sensors are placed on the same die, any drift in response due to temperature, environment or stray magnetic field is self-compensated. This device configuration ensures, therefore, high accuracy and excellent sensitivity with built-in drift compensation. An even further improvement in sensitivity can be archived by using sensor design strategies like rolled-up MR sensors as a part of a microchannel, as shown in Figure 15.11b or by using magnetic flux guides.63

15.6.3

Sensor Surface Passivation and Functionalization

To avoid the direct contact of the aqueous solution with the electric circuit and to isolate the toxic biomolecules from the magnetic layers of the MR sensor, the sensor surface is usually passivated with a thin layer of SiO2 or Al2O3.64 After passivation, the sensor surface is functionalized for the attachment of biomolecules depending on the assay to be used. This step is important in PoC devices for the specific detection of the analyte of interest from the sample. Mostly the surface coating agents are the antigens, antibodies, other proteins, or DNA which have specificity for binding the target analyte in the sample, as discussed in Section 15.5. The specificity of these coating agents is important for the correct identification and quantifications of the target analyte. Therefore, the choice of the surface coating agent is a crucial step in the biosensors.

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Left: An exemplary TMR-based biosensor and its application in MNP-based E. coli detection. Reproduced from ref. 91 with permission from Elsevier, Copyright 2014. Right: A rolled-up GMR biosensor for the detection of magnetic tags with a Wheatstone bridge sensor array built around the microchannel. Reproduced from ref. 97 with permission from American Chemical Society, Copyright 2011.

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Magnetic Field Source

An external magnetic field can be applied using either microinductor coils or permanent magnets that are integrated into the measurement platform. The magnetic field from the magnetic field source can drag the magnetic nanoparticles inside microfluidic channels by high gradient magnetic fields (in the case of PoC/LoC based on microfluidic channels), and/or can simply serve as the external field required for the functioning of the magnetic sensors (see Figure 15.12a). In the latter case, it provides the biasing magnetic field which drives the MR sensors to their peak sensitivity, for offset correction, and for inducing magnetization in SP-MNPs.

15.6.5

Microfluidic Channel

The microfluidics channel enables the transport of the controlled minimal amount of biofluid down to the femtoliter level over the magnetic field sensor from or to the reservoirs. Typical dimensions of the microfluidic channel are in the range of a few tens to hundreds of micrometers,65–67 which makes it compatible with the standard dimensions of MR sensors. A prerequisite for a microfluidic platform with built-in MR sensors is the fabrication of the microchannel and of the sensors on the same platform. Providing further details regarding the microfabrication of the microfluidic device is beyond the scope of this chapter. We suggest reading more comprehensive reviews on this topic in the literature.68–70

15.6.6

Readout Electronic

The typical layout for a magnetic field sensor arranges MR sensors to form a Wheatstone bridge. While this arrangement increases the sensitivity of the MR sensors significantly, another critical part of the LoC device is the readout electronic circuit. Such electronic circuits enable the conversion of the variation in resistance of the MR sensors to a digital signal with a high signal-to-noise ratio as well as the recording and decoding of the digital signal to the relevant information such as the strength of the effective magnetic field to which the sensor is exposed. A basic electronic readout unit comprises of two main components succeeding the MR sensor, i.e., an amplifier circuit followed by an analog-to-digital converter (ADC), as shown in Figure 15.13. The choice of a particular amplifier and ADC integrated circuit (IC) depends solely on the application; one must choose a low noise hermetically-sealed IC with a broad dynamic range and zero offsets if it is to be used in corrosive and electromagnetic noisy environments. While such ICs improve the performance significantly, they will, unfortunately, also increase the cost-per-unit. Nevertheless, with the increased computing capabilities of mobile phones and the advent of small single-board computers (e.g., Raspberry Pi, Intel Edison, Asus Tinker Board, etc.) the overall cost for the readout electronic can be reduced significantly.59,71

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Top: An example setup for a microfluidic chip platform with integrated magnetic nanochain for stirring and separation of biofluids.98 Reproduced from ref. 98, https://doi.org/10.1038/s41467-018-04172-1, under the terms of the CC BY 4.0 license, http://creativecommons.org/ licenses/by/4.0/. Bottom: An experimental measurement setup with an electromagnet and a GMR sensor array chip.99 Reproduced from ref. 99, https://doi.org/10.1038/srep45493, under the terms of the CC BY 4.0 license, http://creativecommons.org/licenses/by/4.0/.

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The block diagram of a typical electronic readout for an MR sensorbased LoC device. At first, the change in the magnetic signal due to the MNPs is detected with an array of sensors in the Wheatstone bridge (full bridge) configuration. The electrical response is then amplified and converted into a machine-readable digital format. Afterwards, the signal is recorded and processed with an external computing unit.

15.7 Future Perspectives Due to their suitability for PoC devices, MR-based biosensors are among the most promising candidates for the development of next-generation analytical techniques to detect and quantify a variety of biological and chemical analytes. Presently, efforts are being made to integrate MR sensors within microfluidic devices to develop low-cost, portable, and disposable devices. However, to realize the transformation from conventional centralized laboratory techniques to a decentralized PoC sensing device, several issues need to be addressed. Functionalized MNPs are the most critical building block of the MR biosensors as they provide a means to label bio-entities. For quantitative analysis, the MR sensor signal should be proportional to the number of labels to be detected, which is only possible when the MNPs are of uniform size and shape. Even though considerable progress has been made in the synthesis of MNPs, there is scope to improve available methods to prepare monodispersed and high magnetic moment MNPs on a large scale and with low cost. The MR sensor response depends not only on the number of immobilized MNPs but also on the magnetic moment of the individual MNPs and the distance from the MNPs to the sensor surface. Therefore, a small hydrodynamic radius of functionalized MNPs is advantageous for the sensitivity of the biosensor. This aspect should be considered while functionalizing the MNPs. Another aspect which has been rarely considered is that the surface functionalization of MNPs can reduce the magnetic susceptibility of the MNPs.72 Therefore, new strategies need to be developed for the surface modification of MNPs, which keeps the hydrodynamic radius low and magnetic properties unchanged.42 So far, only iron oxide MNPs have been used for MR-based biosensors. Cobalt and manganese ferrites that have a larger magnetization than iron oxide could be considered after surface modification with a biocompatible coating. The sandwich assay has been the most preferred assay for MR-based biosensing due to its simplicity. Other assays are seldom reported in the

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literature. The bioassay structure is very crucial in MR biosensors since the distance of the MNP from the sensor surface will depend on the assay structure. Therefore, competitive and direct assays should also be explored more intensively in the future. GMR sensors are preferred over other types of MR sensors due to the simplicity of the nanofabrication process and their high linearity.64 TMR sensors can currently achieve the highest sensitivity among the MR sensors, but their large intrinsic noise still limits their use in biosensors. Nevertheless, TMR sensors can be useful in the detection of ultra-low field (e.g., in single-particle detection) and low power applications, if their noise level is well controlled. Furthermore, a linear hysteresis-free sensor response is essential for quantitative analysis. Depending on the specific application, different magnetic anisotropic configurations can be used to prefer either the dynamic range of MR sensing or the field sensitivity.73 While some MR-based biosensors have already been commercialized,74,75 extensive research is still needed to make them competitive with the conventional analytical techniques and to allow their further real-world use. For this, multidisciplinary collaboration in the field of physics, biochemistry, materials science and engineering is required.

Websites of Interest ¨nberg i. Lectures from the noble laureates Albert Fert and Peter Gru (2007), https://www.nobelprize.org/prizes/physics/2007/summary/ ii. Webpage of NVE corporation ‘‘Medical Device Sensors’’, https://www. nve.com/medical.php iii. Nanomagnetism and quantum spintronic lab at the University of Minnesota ‘‘Magnetic Biosensing’’, http://nanospin.umn.edu/research/ magnetic-biosensing iv. The Wang group at Stanford University, ‘‘Smartphone-based Mobile Health Sensors and Apps’’, https://wanggroup.stanford.edu/smartphonebased-mobile-health-sensors-and-apps-xprize

Acknowledgements P. B. Patil and A. D. Chougale would like to acknowledge the Science and Engineering Research Board, Department of Science and Technology (DST-SERB), Government of India, for financial support through a grant (No. EMR/2017/001810). A. Sharma and G. Salvan acknowledge the financial support provided by the Deutsche Forschungsgemeinschaft (DFG) under project number 282193534.

References 1. A. P. F. Turner, Science, 2000, 290, 1315–1317. 2. V. K. Varadan, L. Chen and J. Xie, Nanomedicine, ch. 8, John Wiley & Sons, Ltd, Chichester, UK, 2008.

Magnetoresistance-based Biosensors

393

3. T. A. P. Rocha-Santos, TrAC, Trends Anal. Chem., 2014, 62, 28–36. 4. J. M. D. Coey, Magnetism and Magnetic Materials, Cambridge University Press, Cambridge, 2010, vol. 3. 5. D. L. Graham, H. A. Ferreira and P. P. Freitas, Trends Biotechnol., 2004, 22, 455–462. 6. E. H. Hall, Am. J. Math., 1879, 2, 287. 7. W. Thomson, Proc. R. Soc., 1857, 8, 546–550. 8. T. McGuire and R. Potter, IEEE Trans. Magn., 1975, 11, 1018–1038. 9. M. N. Baibich, J. M. Broto, A. Fert, F. N. Van Dau, F. Petroff, P. Etienne, G. Creuzet, A. Friederich and J. Chazelas, Phys. Rev. Lett., 1988, 61, 2472–2475. ¨nberg, F. Saurenbach and W. Zinn, Phys. Rev. B, 1989, 10. G. Binasch, P. Gru 39, 4828–4830. 11. M. J. Caruso, in SAE Technical Paper Series, 1997, vol. 1, pp. 1–8. 12. C. P. O. Treutler, Sens. Actuators, A Phys., 2001, 91, 2–6. 13. G. Hancke, B. Silva and G. Hancke, Jr, Sensors, 2012, 13, 393–425. 14. N. F. Mott, Proc. R. Soc. London. Ser. A – Math. Phys. Sci., 1936, 153, 699–717. 15. C. Reig, S. Cardoso and S. C. Mukhopadhyay, Giant Magnetoresistance (GMR) Sensors, Springer, Berlin, Heidelberg, 2013, vol. 6. 16. D. A. Hall, R. S. Gaster, T. Lin, S. J. Osterfeld, S. Han, B. Murmann and S. X. Wang, Biosens. Bioelectron., 2010, 25, 2051–2057. 17. P. M. Tedrow and R. Meservey, Phys. Rev. B, 1973, 7, 318–326. 18. M. Julliere, Phys. Lett. A, 1975, 54, 225–226. 19. M. Bowen, V. Cros, F. Petroff, A. Fert, C. Martı´nez Boubeta, ¨mer, J. V. Anguita, A. Cebollada, F. Briones, J. L. Costa-Kra ´n, M. R. Ibarra, F. Gu ´ and ¨ell, F. Peiro J. M. De Teresa, L. Morello A. Cornet, Appl. Phys. Lett., 2001, 79, 1655–1657. 20. S. Ikeda, K. Miura, H. Yamamoto, K. Mizunuma, H. D. Gan, M. Endo, S. Kanai, J. Hayakawa, F. Matsukura and H. Ohno, Nat. Mater., 2010, 9, 721–724. 21. J. Scola, H. Polovy, C. Fermon, M. Pannetier-Lecœur, G. Feng, K. Fahy and J. M. D. Coey, Appl. Phys. Lett., 2007, 90, 252501. 22. B. Dieny, V. S. Speriosu, S. Metin, S. S. P. Parkin, B. A. Gurney, P. Baumgart and D. R. Wilhoit, J. Appl. Phys., 1991, 69, 4774–4779. 23. F. Radu and H. Zabel, Magnetic Heterostructures, Springer, Berlin, Heidelberg, 2008, vol. 227. 24. R. R. Katti, D. Zou, D. Reed and H. Kaakani, IEEE Trans. Magn., 2003, 39, 2848–2850. 25. C. M. Hussain, Advanced Environmental Analysis: Applications of Nanomaterials, 2016, vol. 2. 26. D. Sharma and C. M. Hussain, Arab. J. Chem., 2020, 13, 3319–3343. 27. R. Keçili and C. M. Hussain, Int. J. Anal. Chem., 2018, 2018, 1–18. ¨yu ¨ktiryaki and C. M. Hussain, TrAC, Trends Anal. Chem., 28. R. Keçili, S. Bu 2019, 110, 259–276. 29. J. Sengupta and C. M. Hussain, TrAC, Trends Anal. Chem., 2019, 114, 326–337.

394

Chapter 15

¨yu ¨ktiryaki, R. Keçili and C. M. Hussain, TrAC, Trends Anal. Chem., 30. S. Bu 2020, 127, 115893. 31. X. Sun, D. Ho, L.-M. Lacroix, J. Q. Xiao and S. Sun, IEEE Trans Nanobioscience, 2012, 11, 46–53. 32. I. Koh and L. Josephson, Sensors, 2009, 9, 8130–8145. 33. H. Sharma, K. John, A. Gaddam, A. Navalkar, S. K. Maji and A. Agrawal, Sci. Rep., 2018, 8, 1–14. 34. M. Faraji, Y. Yamini and M. Rezaee, J. Iran. Chem. Soc., 2010, 7, 1–37. 35. D. L. Leslie-Pelecky, V. Labhasetwar and R. H. Kraus, in Advanced Magnetic Nanostructures, Springer US, Boston, MA, 2006, pp. 461–490. 36. C. C. Berry, J. Mater. Chem., 2005, 15, 543–547. 37. V. K. Varadan, L. Chen and J. Xie, Nanomedicine: Design and Applications of Magnetic Nanomaterials, Nanosensors and Nanosystems, John Wiley & Sons, Ltd, Chichester, UK, 2008, p. 130. 38. L. H. Reddy, J. L. Arias, J. Nicolas and P. Couvreur, Chem. Rev., 2012, 112, 5818–5878. ¨th, Angew. Chem., Int. Ed., 2007, 46, 39. A. Lu, E. L. Salabas and F. Schu 1222–1244. 40. W. Wu, Z. Wu, T. Yu, C. Jiang and W.-S. Kim, Sci. Technol. Adv. Mater., 2015, 16, 023501. 41. V. K. Varadan, L. Chen and J. Xie, Nanomedicine, ch. 3, John Wiley & Sons, Ltd, Chichester, UK, 2008. 42. R. P. Dhavale, P. P. Waifalkar, A. Sharma, R. P. Dhavale, S. C. Sahoo, P. Kollu, A. D. Chougale, D. R. T. Zahn, G. Salvan, P. S. Patil and P. B. Patil, J. Colloid Interface Sci., 2018, 529, 415–425. 43. K. Wu, D. Su, J. Liu, R. Saha and J.-P. Wang, Nanotechnology, 2019, 30, 502003. 44. V. D. Chavan, V. P. Kothavale, S. C. Sahoo, P. Kollu, T. D. Dongale, P. S. Patil and P. B. Patil, Phys. B, 2019, 571, 273–279. 45. R. A. Sperling and W. J. Parak, Philos. Trans. R. Soc., A, 2010, 368, 1333– 1383. 46. D. R. Baselt, G. U. Lee, M. Natesan, S. W. Metzger, P. E. Sheehan and R. J. Colton, Biosens. Bioelectron., 1998, 13, 731–739. 47. L. Xu, H. Yu, M. S. Akhras, S.-J. Han, S. Osterfeld, R. L. White, N. Pourmand and S. X. Wang, Biosens. Bioelectron., 2008, 24, 99–103. 48. L. Xu, H. Yu, S.-J. Han, S. Osterfeld, R. L. White, N. Pourmand and S. X. Wang, IEEE Trans. Magn., 2008, 44, 3989–3991. 49. W. Wang, Y. Wang, L. Tu, Y. Feng, T. Klein and J. P. Wang, Sci. Rep., 2014, 4, 1–5. 50. S. Adem, S. Jain, M. Sveiven, X. Zhou, A. J. O’Donoghue and D. A. Hall, Sci. Rep., 2020, 10, 7941. 51. J. Shen, Y. Li, H. Gu, F. Xia and X. Zuo, Chem. Rev., 2014, 114, 7631–7677. 52. S. Gupta and V. Kakkar, Tuberculosis, 2019, 118, 101852. 53. Y. Gao, W. Huo, L. Zhang, J. Lian, W. Tao, C. Song, J. Tang, S. Shi and Y. Gao, Biosens. Bioelectron., 2019, 123, 204–210.

Magnetoresistance-based Biosensors

395

54. W. Wang, Y. Wang, L. Tu, T. Klein, Y. Feng, Q. Li and J.-P. Wang, Anal. Chem., 2014, 86, 3712–3716. 55. Y. Wang, W. Wang, L. Yu, L. Tu, Y. Feng, T. Klein and J.-P. Wang, Biosens. Bioelectron., 2015, 70, 61–68. 56. J. Choi, A. W. Gani, D. J. B. Bechstein, J. R. Lee, P. J. Utz and S. X. Wang, Biosens. Bioelectron., 2016, 85, 1–7. 57. V. D. Krishna, K. Wu, A. M. Perez and J. P. Wang, Front. Microbiol., 2016, 7, 1–8. 58. K. Kim, D. A. Hall, C. Yao, J. R. Lee, C. C. Ooi, D. J. B. Bechstein, Y. Guo and S. X. Wang, Sci. Rep., 2018, 8, 1–10. 59. K. Wu, T. Klein, V. D. Krishna, D. Su, A. M. Perez and J.-P. Wang, ACS Sens., 2017, 2, 1594–1601. 60. H. Yang, B. Qu, B. Lei and L. Xie, in 2011 IEEE SENSORS Proceedings, IEEE, 2011, pp. 805–808. 61. D. Su, K. Wu, V. D. Krishna, T. Klein, J. Liu, Y. Feng, A. M. Perez, M. C. J. Cheeran and J.-P. Wang, Front. Microbiol., 2019, 10, 1–10. 62. B. Srinivasan, Y. Li, Y. Jing, C. Xing, J. Slaton and J.-P. Wang, Anal. Chem., 2011, 83, 2996–3002. 63. A. Guedes, J. M. Almeida, S. Cardoso, R. Ferreira and P. P. Freitas, IEEE Trans. Magn., 2007, 43, 2376–2378. 64. D. Su, K. Wu, R. Saha, C. Peng and J. P. Wang, Micromachines, 2020, 11, 34. + G. A. J. Besselink and R. B. M. Schasfoort, Lab Chip, 2001, 1, ¨dos, 65. A. J. Tu 83–95. 66. A. M. Streets and Y. Huang, Biomicrofluidics, 2013, 7, 011302. 67. X. Z. Niu, S. L. Peng, L. Y. Liu, W. J. Wen and P. Sheng, Adv. Mater., 2007, 19, 2682–2686. 68. N. Convery and N. Gadegaard, Micro Nano Eng., 2019, 2, 76–91. 69. Y.-H. V. Ma, K. Middleton, L. You and Y. Sun, Microsyst. Nanoeng., 2018, 4, 17104. 70. M. Yew, Y. Ren, K. S. Koh, C. Sun and C. Snape, Glob. Challenges, 2019, 3, 1800060. 71. J. Choi, A. W. Gani, D. J. B. Bechstein, J.-R. Lee, P. J. Utz and S. X. Wang, Biosens. Bioelectron., 2016, 85, 1–7. 72. P. P. Waifalkar, S. B. Parit, A. D. Chougale, S. C. Sahoo, P. S. Patil and P. B. Patil, J. Colloid Interface Sci., 2016, 482, 159–164. 73. S. Oh, P. B. Patil, T. Q. Hung, B. Lim, M. Takahashi, D. Y. Kim and C. Kim, Solid State Commun., 2011, 151, 1248–1251. 74. E. Ng, K. C. Nadeau and S. X. Wang, Biosens. Bioelectron., 2016, 80, 359–365. 75. G. Kokkinis, B. Plochberger, S. Cardoso, F. Keplinger and I. Giouroudi, Lab Chip, 2016, 16, 1261–1271. 76. K. Fujiwara, M. Oogane, A. Kanno, M. Imada, J. Jono, T. Terauchi, T. Okuno, Y. Aritomi, M. Morikawa, M. Tsuchida, N. Nakasato and Y. Ando, Appl. Phys. Express, 2018, 11, 023001. 77. M. Pannetier-Lecoeur, H. Polovy, N. Sergeeva-Chollet, G. Cannies, C. Fermon and L. Parkkonen, J. Phys. Conf. Ser., 2011, 303, 012054.

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78. M. Wang, Y. Wang, L. Peng and C. Ye, IEEE Sens. J., 2019, 19, 9610–9615. 79. M. Balynsky, D. Gutierrez, H. Chiang, A. Kozhevnikov, G. Dudko, Y. Filimonov, A. A. Balandin and A. Khitun, Sci. Rep., 2017, 7, 11539. 80. S. Singh, Ann. Indian Acad. Neurol., 2014, 17, 107. 81. L. Ren, K. Yu and Y. Tan, Materials, 2019, 12, 1135. 82. L. Caruso, T. Wunderle, C. M. Lewis, J. Valadeiro, V. Trauchessec, J. Trejo Rosillo, J. P. Amaral, J. Ni, P. Jendritza, C. Fermon, S. Cardoso, P. P. Freitas, P. Fries and M. Pannetier-Lecoeur, Neuron, 2017, 95, 1283– 1291, e4. 83. R. Zetter, J. Iivanainen and L. Parkkonen, Sci. Rep., 2019, 9, 5490. 84. J. F. Barry, M. J. Turner, J. M. Schloss, D. R. Glenn, Y. Song, M. D. Lukin, H. Park and R. L. Walsworth, Proc. Natl. Acad. Sci. U. S. A., 2016, 113, 14133–14138. 85. B.-M. Mackert, Clin. Neurophysiol., 2004, 115, 2667–2676. 86. K. Jensen, R. Budvytyte, R. A. Thomas, T. Wang, A. M. Fuchs, M. V. Balabas, G. Vasilakis, L. D. Mosgaard, H. C. Stærkind, ¨ller, T. Heimburg, S.-P. Olesen and E. S. Polzik, Sci. Rep., 2016, J. H. Mu 6, 29638. 87. S. Zuo, H. Heidari, D. Farina and K. Nazarpour, Adv. Mater. Technol., 2020, 5, 2000185. 88. D. Cohen and E. Givler, Appl. Phys. Lett., 1972, 21, 114–116. 89. T. Masuda, H. Endo and T. Takeda, Clin. Neurophysiol., 1999, 110, 384–389. 90. P. Zhang, N. Thiyagarajah and S. Bae, IEEE Sens. J., 2011, 11, 1927–1934. 91. F. Li and J. Kosel, Biosens. Bioelectron., 2014, 59, 145–150. 92. S. Krishnapriya, R. Komaragiri and K. J. Suja, Sens. Actuators, A, 2019, 290, 190–197. 93. F. Gorrini, R. Giri, C. E. Avalos, S. Tambalo, S. Mannucci, L. Basso, N. Bazzanella, C. Dorigoni, M. Cazzanelli, P. Marzola, A. Miotello and A. Bifone, ACS Appl. Mater. Interfaces, 2019, 11, 24412–24422. 94. W. Xue, L. R. Moore, N. Nakano, J. J. Chalmers and M. Zborowski, J. Magn. Magn. Mater., 2019, 474, 152–160. 95. J. R. Bai, S. Mohanasankar and V. J. Kumar, in 2016 IEEE International Symposium on Medical Measurements and Applications (MeMeA), IEEE, 2016, pp. 1–6. 96. D. A. Petukhov, Physica E Low Dimens. Syst. Nanostruct., 2016, 80, 31–35. ¨nch, D. Makarov, R. Koseva, L. Baraban, D. Karnaushenko, 97. I. Mo C. Kaiser, K.-F. Arndt and O. G. Schmidt, ACS Nano, 2011, 5, 7436–7442. 98. Q. Xiong, C. Y. Lim, J. Ren, J. Zhou, K. Pu, M. B. Chan-Park, H. Mao, Y. C. Lam and H. Duan, Nat. Commun., 2018, 9, 1743. 99. C. Huang, X. Zhou and D. A. Hall, Sci. Rep., 2017, 7, 45493. 100. A. Sharma, PhD thesis, Chemnitz University of Technology, 2021.

Section 5: Other Analytical Applications Functionalized Magnetic Nanoparticles

CHAPTER 16

Analytical Applications of Molecularly Imprinted Polymer-decorated Magnetic Nanoparticles ABDERRAHMAN LAMAOUI,a,b LAURA CUBILLANA-AGUILERA,b MARI´A LUISA ALMORAIMA GIL,c AZIZ AMINE*a AND ´ MARI´A PALACIOS-SANTANDER*b JOSE a

´nie des Proce ´de ´s & Environnement, Faculte ´ des Sciences et Laboratoire Ge Techniques, Hassan II University of Casablanca, B.P. 146. Mohammedia, Morocco; b Department of Analytical Chemistry, Institute of Research on Electron Microscopy and Materials (IMEYMAT), Faculty of Sciences, Campus de Excelencia Internacional del Mar (CEIMAR), University of Cadiz, Campus Universitario de Puerto Real, Polı´gono del Rı´o San Pedro S/N, ´diz, Spain; c Department of Physical Chemistry, 11510, Puerto Real, Ca Institute of Research on Electron Microscopy and Materials (IMEYMAT), Faculty of Sciences, Campus de Excelencia Internacional del Mar (CEIMAR), University of Cadiz, Campus Universitario de Puerto Real, Polı´gono del Rı´o ´diz, Spain San Pedro S/N, 11510, Puerto Real, Ca *Emails: [email protected]; [email protected]

16.1 Introduction Because of the high demand for modern analytical methods to reach an advanced level in analytical chemistry, nanotechnology has become a powerful tool to achieve the required needs for that application.1–5 Nanotechnology Analytical Applications of Functionalized Magnetic Nanoparticles Edited by Chaudhery Mustansar Hussain r The Royal Society of Chemistry 2021 Published by the Royal Society of Chemistry, www.rsc.org

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represents the knowledge and control of nanoscale materials (nanomaterials) using whole techniques that enable their fabrication, manipulation, and characterization. Magnetic nanoparticles (MNPs) are one of the most attractive nanomaterials in the analysis field. MNPs are characterized with outstanding magnetic properties, allowing facile isolation of analytes by using externally a normal magnet or an alternating current magnetic field. The use of MNPs can make the purification and separation processes faster and easier because centrifugation or filtration are not required. The application of MNPs in analytical chemistry can be divided into two main groups:6 (i) the purification and separation of analytes through, mainly, magnetic solid-phase extraction (SPE); and (ii) the usage of MNPs in sensors and biosensors that has recently increased considerably.7,8 However, the main drawback related to MNPs is their low selectivity which makes a lot of optimization essential for the typical steps in the adsorption and extraction processes. Even with these optimizations, some compounds could be co-adsorbed/co-eluted with the analyte and the selectivity still cannot achieve satisfactory results according to the current accurate regulations.9 Thus, the decoration of MNPs with molecularly imprinted polymers (MIPs) is of paramount importance to overcome the limitations of MNPs in the analysis field (see Scheme 16.1). It is well known that each person has unique fingerprints, and each finger has a unique fingerprint. This example of fingerprints can find parallelism with chemical species since each molecule has its own imprint with specific size, functional group, and shape. To create this imprint, a polymerization process in the presence of the target molecule is required to form a polymer around that molecule. The removal of the target molecule leads to a polymer with specific imprints for the target analyte. The obtained polymer is called MIP. It has the potential to recognize specifically the analyte, that was templated during synthesis, through a rebinding process, mimicking the antibody–antigen recognition.10 Due to their characteristics, such as easiness of preparation, good stability compared to natural antibodies, and high selectivity, MIPs are widely used in many analytical fields. Therefore,

Scheme 16.1

Comparison between MNPs and MIP-decorated MNPs.

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Figure 16.1

Analysis of search results related to magnetic MIPs from 2000 to 2020 (source: Scopus).

Figure 16.2

Subject areas of magnetic MIPs from 2000 to 2020 (source: Scopus).

the combination of MNPs and MIPs has opened tremendously new roads for separation and sensing and biosensing. An analysis of the search results obtained from Scopus about magnetic MIPs from 2000 to 2019 is presented in Figure 16.1. It can be observed clearly that the number of publications increased strongly in the last ten years, which indicates the high importance of these materials and their outstanding characteristics. Figure 16.2 presents the subject areas of the

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research articles published on magnetic MIPs from 2000 to 2020 according to Scopus. The main objective of this chapter is to increase the understanding of magnetic MIPs and their analytical applications. Thus, this chapter presents concisely some generalities about MNPs and MIPs. The preparation and characterization of MIP-decorated MNPs are highlighted. Then, the applications of these materials for the extraction/clean-up of real samples are described focusing on solid-phase extraction. Furthermore, this chapter discusses the integration of MIP-decorated MNPs in sensing, including electrochemical and optical sensors.

16.2 Generalities 16.2.1

Magnetic Nanoparticles

MNP material is composed of ‘‘nanoparticles’’ possessing magnetic properties. The term nanoparticle is included in the nanotechnology domain, which is based on the knowledge and control of nanoscale materials (nanomaterials) using whole techniques that enable their fabrication, manipulation, and characterization. According to ISO TS 80004-1, a nanomaterial is a material with at least one external dimension at the nanoscale, i.e., between approximately 1 and 100 nm, or with an internal or surface structure at the nanoscale. Nanomaterials are classified into two groups: nanostructured materials (or compact materials) that have an internal or surface structure at the nanoscale, such as nanocomposites, nanoporous materials, and aggregates, and agglomerates of nano-objects. Unlike nanostructured materials, nano-objects are materials with one (2D), two (1D), or three (3D) external dimensions at the nanoscale, i.e., approximately less than 100 nm. MNPs are inorganic, zero-dimensional materials characterized by outstanding magnetic properties, allowing easy manipulation using a magnet or an alternating current magnetic field. Moreover, they exhibit unique and intrinsic properties, such as biocompatibility, high saturation magnetization, and less toxicity. Therefore, they have been employed widely in various applications such as environmental,11,12 medical treatment,13 analytical,7 petroleum industry,14 and catalysis,15,16 among others. There are different MNP families: (i) iron oxides, such as maghemite ¨stite (FeO), and magnetite (Fe3O4); (ii) pure metals (g-Fe2O3); hematite; wu such as Fe and Co; (iii) alloys, such as FePt and MgFe2O4. Among these types, iron oxide nanoparticles have received much attention due to their easiness of preparation, high magnetic properties, and low toxicity.7,17

16.2.2 Molecularly Imprinted Polymers 16.2.2.1 Definition Molecularly imprinted polymers are synthetic materials containing specific recognition sites, called imprints that are capable of selectively binding the

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desired molecules with which they were templated during preparation, mimicking the immune system through antigen–antibody affinity. From a very simple point of view, the functioning mechanism of these MIPs is like a ‘‘lock and key’’ process to selectively insert the molecule in its cavity. Unlike biological systems, MIPs are intrinsically stable in different media, low cost, and have a longer storage life.10,18

16.2.2.2

MIP History

In 1931, M. V. Polyakov discovered the imprinting effect, i.e., the formation of an imprint left by a template molecule in porous silica particles for chromatographic applications.19 In 1949, F. H. Dickey polymerized silica gels in the presence of helianthin; and subsequently removed the helianthin from the silica gel to liberate the imprints created and then, re-exposed the gels to the different species.20 He observed an increase in selectivity for the species in which they were present during the polymerization compared to a silica gel polymerized without the presence of helianthin. In 1972, the groups of G. Wulff21 and I. M. Klotz22 demonstrated independently that it is possible to carry out molecular imprints in organic polymers. A significant revolution in the evolution of molecularly imprinted polymers was the introduction of the so-called ‘‘non-covalent’’ approach by K. Mosbach’s team, at the beginning of the 1980s.23,24 This method consists of the copolymerization of monomers, whose functional groups are capable of interacting with the target molecule via non-covalent interactions, and a cross-linking agent in a solvent. Polymerization allows three-dimensional interaction sites complementary to the printed molecule to be fixed within the polymer. After the extraction of the template molecule with appropriate solvents, these sites ensure the specific recognition of the target molecule, unlike a polymer.

16.2.2.3

MIP Approaches

The key step in the molecular imprinting process is the formation of a complex before the polymerization step between the template molecule and the functional monomers. There are three distinct strategies, differing in the nature of the interactions, that lead to the formation of this complex including non-covalent, covalent, and semi-covalent approaches.25 16.2.2.3.1 Covalent Approach. The covalent approach is based on the formation of a pre-polymerization complex between the template molecule and the functional monomers by reversible covalent bonds. The method, therefore, requires performing before any polymerization, a fairly advanced chemical synthesis whose goal is to covalently graft the template molecule on a polymerizable monomer. Following the copolymerization (activated by an initiator) of the complex thus formed in the presence of a crosslinking agent in a pore-forming solvent, the template molecule is

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extracted by chemical cleavage, revealing cavities exposing functional groups which allow the recognition of the target molecule via covalent interactions. However, this approach is less simple to carry out and requires chemical skills for the formation of the pre-polymerization complex. On the other hand, the number of molecules that can be imprinted by this technique is smaller, since it is not always possible to chemically modify all the molecules. Finally, since the covalent bonds require a longer time to establish themselves, the interaction kinetics of the covalent is lower, overall, than for the non-covalent method. 16.2.2.3.2 Non-covalent Approach. In the non-covalent approach, the functional monomers self-assemble around the template molecule via weak electrostatic, hydrogen, van der Waals, ionic or hydrophobic interactions. After the preparation of the MIP, the same type of weak interactions allows the recognition of the target molecule in the imprints created. This method is the most widespread (more than 90% of MIPs described in the literature), in particular, because of its simplicity of implementation (no functionalization steps of the target molecule) and also because of the wide choice of commercially available functional monomers, which increases the number of printable target molecules and, thus, the range of application areas. Moreover, the extraction of the template could be done easily in comparison with the covalent approach using a polar organic solvent in acidic medium to break the weak interactions. 16.2.2.3.3 Semi-covalent Approach. The semi-covalent approach benefits from the advantages of the two previous techniques. As in the covalent method, the complex formation is accomplished through covalent interactions and the molecular recognition with the target molecule is accomplished through non-covalent interactions. Nevertheless, this technique remains little used in the MIP community.

16.2.2.4

The Components

The preparation of MIPs, through a non-covalent approach, requires the use of different constituents depending on the method of preparation. Generally, there are five important constituents including a template, a functional monomer, a porogen solvent, a cross-linker, and an initiator. 16.2.2.4.1 Template. The template is the imprinted molecule used during the synthesis of MIPs, called also the target molecule. The impression of this molecule requires taking into account its structure and its functional groups. It must be chemically inert under polymerization conditions (UV-irradiation, ultrasound waves, temperature, pH, etc.). However, the template can be replaced by an analog molecule at the chemical and structural (dummy template) levels during the preparation due to several reasons, such as high price, handling difficulties, stability, toxicity,

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unavailability, etc.). For analytical purposes, the use of MIP molded by employing a structural analog of the target analyte avoids problems related to incomplete removal (referred to as residual template bleeding), which sometimes prevents the use of MIPs in quantitative trace analysis. 16.2.2.4.2 Functional Monomer. Monomers are small molecules that have the potential to interact with each other to form a large polymer chain through the polymerization process. In the MIPs, this monomer must contain some functional groups, which is why they are called ‘‘functional monomers’’, and constitute the essential compounds for the elaboration of MIPs, since they are responsible for forming a complex with the template, through a self-assembly step, by weak interactions (electrostatic, hydrogen, van der Waals, hydrophobic, etc.), that allow the recognition of the target molecule. More than one functional monomer can be used to prepare MIPs, but they should be selected precisely. Normally, different monomers should be evaluated experimentally, however, it is time-consuming. Therefore, the appearance of the computational approach has reduced drastically the experimental time as detailed later (Subsection 16.3.2.1). 16.2.2.4.3 Solvent. The solvent also plays a very important role in the preparation of MIPs. On the one hand, it solubilizes the polymerization reagents, including the monomer, the target, the cross-linking agent and the initiator. On the other hand, it is also responsible for the formation of porosity in the polymer (usually called the porogen solvent) which is necessary for the extraction of the template molecule and the access of the target molecule to the imprints. The type, nature, and quantity of the solvent have an important effect on the strength of non-covalent interactions between the monomer and the template, which can affect directly the recognition performance of the resultant MIPs. The solvent selected should not participate with the template molecule for its binding to the monomer, i.e., the binding energy of the solvent–monomer must be lower than that of the template–monomer. There are three kinds of solvents according to their properties including non-polar, polar aprotic, and polar protic solvents. 16.2.2.4.3.1 Non-polar Solvent. Non-polar solvents have a null dipole moment, such as toluene, dichloromethane and chloroform, and they are highly recommended in MIPs, since they do not form hydrogen bonds with the functional monomers and stabilize hydrogen interactions of the template–monomer. However, most templates are not soluble in this kind of solvent. 16.2.2.4.3.2 Polar Aprotic Solvent. This is a polar solvent that has a dipole moment but without an acidic hydrogen atom. Acetonitrile, acetone, DMSO, and DMF are the best examples. This type of solvent is generally used to improve the solubility of the reagents. A combination of this type of solvent

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with the non-polar one is possible to achieve the benefits of both advantages. Moreover, DMSO, DMF and ethanol could be a good choice in the case of using an ultrasound probe as a synthesis technique to prepare MIPs because they exhibit high ultrasound properties. It has been reported that there is a correlation between solvent properties (viscosity, vapor pressure, and surface tension) and dissipated ultrasonic power, which is related to the cavitation process and, thus, the efficiency of bubble collapses.26,27 Solvents with high ultrasonic dissipated power (high surface tension and low vapor pressure) lead to important energy very quickly with low applied amplitudes. On the other hand, solvents that have low dissipated ultrasonic power (low surface tension and high vapor pressure), such as acetone and acetonitrile, lead to a low sonochemical polymerization rate. 16.2.2.4.3.3 Polar Protic Solvent. This is a polar solvent with at least one hydrogen that can be involved in hydrogen bonds, such as methanol, water and acetic acid. This type of solvent is theoretically not recommended except in some specific cases, such as for biological templates when water is required, or when the interactions are hydrophobic. However, the computational approach can facilitate the choice of solvent. This will be detailed later (Subsection 16.3.2.1). 16.2.2.4.4 Cross-linker. In the polymerization process, the cross-linking agent is used to freeze the template molecule/functional monomer complex in a rigid polymer matrix with a high degree of cross-linking. This ensures the mechanical stability of the imprints obtained after extraction of the template molecule and, thus, the preservation of the molecular recognition property. The nature of the cross-linking agent can potentially decrease or increase the hydrophilic or hydrophobic character of a polymer. This means that it can be strategically chosen depending on the environment in which the resulting MIPs will be used. The ratio between the amount of cross-linking agent to the amount of functional monomer and the amount of template molecule must be precisely controlled since it has a significant effect on the mechanical properties of the final polymer. Thus, a small amount of cross-linking agent will lead to a mechanically unstable polymer (too soft) and the imprints will not be maintained. On the contrary, too much cross-linking agent will lead to an overly rigid polymer and lower imprinting efficiency (fewer sites per unit mass). A polymer that is too rigid will have a detrimental effect on the diffusion of the target molecule in the matrix, which will lead to poor accessibility of the target molecule to the cavities. 16.2.2.4.5 Initiator. Since free-radical polymerization is the most employed method to synthesize MIPs, we introduce the radical initiator term, which is considered as a substance that is capable of forming radicals. It generally exhibits weak chemical bonds, i.e., bonds that have low homolytic dissociation energy. The choice of this type of initiator is made

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according to the polymerization conditions. For example, azobisisobutyronitrile (AIBN) is commonly used and requires a fairly high temperature between 60 and 80 1C. Azobisvaleronitrile (ABDV) can be used to synthesize MIPs at lower temperatures (between 50 and 75 1C). Ammonium persulfate is used when aqueous medium is utilized to prepare MIPs, since this initiator is soluble in water compared to other initiators that are not soluble in water, and requires temperatures higher than 60 1C. When photopolymerization is used as a technique to prepare MIPs, the photoinitiator must exhibit several properties such as (i) strong absorptivity at the exposure wavelength of the UV-lamp and high molar extinction factor, (ii) high quantum efficiency of the generation of initiator species, and (iii) good reactivity of the radical with the monomer.

16.3 Preparation of MIP-decorated MNPs 16.3.1

Preparation and Modification of MNPs

The preparation of MIP-decorated MNPs is a multistep procedure. First of all, the MNPs should be prepared or purchased. There are three different preparation routes including biomineralization, physical and chemical methods. The latter is the most used in analytical applications and implies different synthesis routes, such as co-precipitation, solvothermal, hydrothermal, thermal decomposition, and micro-emulsion. Generally, coating procedures for MNPs can be divided into adsorptive and covalent techniques. For the covalent coating of a MIPs shell, prior functionalization of the MNP surface is required. For example, the functio¨eber method; then with nalization of a thin SiO2 layer through the Sto functional silane precursors having functional groups, such as amine28 or vinyl29 ones. The second coating method is to prepare MIPs directly onto the surface of MNPs. In this case, some dispersive agents could be added to disperse MNPs well and, thus, get an appropriate core–shell.

16.3.2 Decoration of MNPs by MIPs 16.3.2.1 Pre-synthesis of MIPs The development of an optimum MIP requires several syntheses that are carried out in different configurations, taking into account the types and quantities of monomers which may generate important quantities of waste products. Thus, it is time and energy consuming and very expensive. Computational methods are the best way to make the determination of the best monomer and solvent easy and to understand the nature of the interaction between the template and the functional monomer, thus reducing the quantity and number of solvents and reagents and increasing the likelihood of producing powerful MIPs characterized by good properties. Recently, an important review was published about this context.30 The authors presented literature

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information regarding the basic software used in the field of development of MIPs and pointed out the main advantages resulting from the employment of computer-assisted techniques. Briefly, this technique requires the availability of suitable software, such as HyperChem,31 Gaussian,32 Spartan,33 2016), etc., and a list of monomers from large libraries and solvents in which the template is soluble. After building the molecule structure and selecting the calculation methods, generally Density Functional Theory (DFT) or Hartree–Fock (HF)34,35 with a suitable basis set, the optimization/calculation starts. Generally, three calculations are necessary to obtain the binding energy between the template and one monomer, including the energy of the optimized template–monomer complex Etemplate–monomer, the energy of the optimized molecule template Etemplate and the energy of the optimized functional monomer Emonomer. Thus, the binding energy is calculated according to the following equation: DEin gas ¼ Etemplate–monomer  (Etemplate þ Emonomer)

(16.1)

Similarly, the calculations are done for other monomers and the one that gives the minimum binding energy would be selected to pass to the second stage, involving the study and selection of the best porogen solvent. The Polarizable Continuum Model (PCM) method is one of the most widely used methods, taking into account the solute size and dielectric constant of the solvent, since it has a good compromise between accuracy and computation time.36 The solvent energy is calculated according to the following equation: DEsolvent energy ¼ DEin solvent  DEin gas

(16.2)

where DEin gas and DEin solvent correspond to the interaction energies in the gas and solvent, respectively. The DEin solvent is calculated in the same manner as DEin gas, but taking into consideration the solvent.

16.3.2.2

The Preparation of MIP-decorated MNPs

The preparation of this composite material is a multistep procedure (Scheme 16.2). The first step consists of preparing the template–monomer complex by dissolving a specific amount of template in the selected solvent and adding the monomer that provides the best results according to the computational approach. The mixture could be kept for a few hours under/ without stirring at a temperature higher than 60 1C. Lamaoui et al.27 studied the effect of the time to obtain the maximum adsorption capacity of the magnetic MIPs towards the target analyte. Their results showed that the adsorption capacities increased over time and tended to stabilize at around 1 hour and thus they selected 1 h as the optimal time. This step allows the formation of interactions between the template and the functional monomer. Secondly, a specific amount of MNPs, cross-linking agent, and initiator are added and the mixture is heated through the reflux system at 60 1C for 24 h in the presence of nitrogen to avoid the oxidation of radical initiators.

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Scheme 16.2

409

Schematic illustration of the preparation process of MIP-decorated MNPs.

Other synthesis techniques rather than thermal heating can also ensure the polymerization process such as microwave,37 UV waves,38 ultrasound bath,39 and ultrasound probe.40 Afterwards, the template is removed using the appropriate solution depending on the template.

16.4 Characterization of MIP-decorated MNPs After the preparation of MIP-decorated MNPs there is a need for characterizing them using different techniques. The characterization techniques can be classified into three types.

16.4.1

Morphological Characterization

The morphological characterization of MIP-decorated MNPs is a primordial part before going to the application of this material. Several types of information can be obtained, such as shape, size, porosity, etc. Different techniques allow analyzing and visualizing the elaborated materials, such as atomic force microscopy (AFM), scanning electron microscopy (SEM), transmission electron microscopy (TEM), etc. Normally the MNPs present a spherical shape with small size, depending on the synthesis conditions. After their modifications with MIPs, the diameter size of the particles increases, which confirms the good decoration of MNPs with the polymer layer of MIPs. Moreover, the layer size could be measured with SEM by subtracting the diameter size of MNPs after and before decoration or with TEM which shows the polymer layer with a light color in comparison with MNPs, which usually appear in dark color. The morphological characterization provides further information regarding the difference between the MIPs and NIPs layer. The NIPs could

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have a smoother and more uniform shape than the MIPs, which is attributed to the extraction of template molecules presented during polymerization leaving imprinted cavities. The choice of the monomer, porogen solvent, and the volume of solvent affects the morphology of the resultant polymers influencing their surface morphology and porosity.41 For example, in the SEM images, MIPs obtained with methacrylic acid showed a more porous surface compared to 4-vinylpyridine. On the other hand, MIPs synthesized with acetonitrile demonstrated more microporous shapes than MIPs synthesized with dichloromethane or chloroform. Moreover, a larger volume could lead to better-defined spherical particles.

16.4.2

Structural Characterization

The structure of MIP-decorated MNPs could be characterized by different techniques such as X-ray diffraction (XRD), nuclear magnetic resonance (NMR), and Fourier transform infrared (FTIR).42,43 The XRD technique provides information about the magnetic core (crystalline system parameters and diameter size using the Scherrer equation). The FTIR technique plays an important role in the characterization of the magnetic core and even after decoration with the MIPs by confirming the presence of the main functional groups. The NMR technique allows us to analyze the general chemical structure of the resultant materials and to confirm the effective removal of the template during the washing process.44

16.4.3

Magnetic Characterization

To characterize the magnetic properties of MNPs before and after their decoration with MIPs, the vibrating sample magnetometry (VSM) technique is frequently used.45,46 Generally, the MNPs present high magnetization saturation, about 70 emu g1, depending on the type and size of the MNPs, but after modification with MIPs, the magnetization saturation decreases considerably depending also on the layer size and density of the polymer. Therefore, VSM is a good way to confirm the appropriate modification of MNPs with MIPs.

16.4.4

Adsorption Characterization

One of the most important parts in the development of MIP-decorated MNPs is the adsorption characterization. Indeed, this characterization is based on the rebinding experiments, by means of which the presence of specific cavities and the potential of MIPs to rebind the target analyte (in which it was templated during polymerization) are demonstrated. The adsorption performance of MIPs and NIPs includes several studies such as isotherm adsorption, adsorption kinetic, adsorption thermodynamic, and selectivity study. These studies are carried out using a specific amount of adsorbent in a specific volume and varying the concentration of the target analyte, the

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adsorption time, temperature and adsorbate for isotherm, kinetic, thermodynamic and selectivity studies, respectively. The principle is to make an adsorbent mass, m, in contact with a volume, V, of the adsorbate solution at the initial concentration Ci; the adsorption will cause a decrease in this concentration. After a specific time, it is, therefore, necessary to separate the solid from the free solution (called supernatant), and measure the equilibrium concentration, Ce. Then, the equilibrium binding/adsorption capacity, Q, is calculated according to the following equation: Q ¼ (Ci  Ce)V/m

(16.3)

The experimental results could be modeled using the models that fit well with the results obtained. For the isotherm adsorption, it is possible to cite, for example, Freundlich,27 Langmuir47 and Scatrchard48 models, and adsorption kinetic pseudo-first-order and pseudo-second-order equations.47 The adsorption performance of the MIPs to rebind selectively and efficiently the target analyte compared to other analog molecules could be performed with the selectivity study. Indeed, the optimal adsorption conditions are chosen and applied for other similar molecules to determine the capacity of MIPs to rebind the target analyte better than others.

16.5 Application of MIP-decorated MNPs for Solid-phase Extraction Nowadays, the analysis of interesting compounds at trace levels is highly required. The sample preparation method undoubtedly plays an important role in the analytical procedure, which allows the pre-concentration of the analyte, the elimination of interferences, the transformation of the analyte to an appropriate form for separation, and the proper detection process. This method relies on the use of an extraction material that has the potential to uptake selectively the analyte. Recently, MIP-decorated MNPs have attracted a lot of attention due to not only the fact they exhibit fast magnetic separation but also demonstrate specific binding towards the target analyte.

16.5.1

Introduction to Solid-phase Extraction (SPE) and Dispersive SPE

Solid-phase extraction (SPE) was introduced in the 1970s and has been a frequently exploited sorbent-based technique in sample preparation for enrichment/pre-concentration and the clean-up process of analytes. Generally, SPE relies on a solid chromatographic filler material usually consisting of small porous particles contained in a column device or cartridge. Fundamentally, SPE operates in two different modes. The first mode consists of retaining the target analyte on the solid support and not the interference species; then, eluting with an appropriate solvent. In the second mode, the

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interferences present in the samples at high concentrations are retained, not the target analyte, providing a significant clean-up. The cartridge is conditioned, in both modes, with an appropriate solvent and then, the sample is passed through the column by gravitational flow or vacuum/pressure assisted flow. Although SPE has several advantages, it faces some problems such as cartridge blocking, time-consuming, and difficulty in performing simultaneous extractions. Dispersive SPE (DSPE) techniques can clearly overcome the drawbacks of conventional SPE, especially when magnetic molecularly imprinted polymers are used as sorbents. In this technique, the sorbent material (MIP-decorated MNPs) is directly put in contact with the sample (liquid) which contains the analytes. With this technique, the conditioning step is avoided.

16.5.2 16.5.2.1

Application of Magnetic MIPs in Dispersive Solid-phase Extraction Principle

The principle of using magnetic MIPs in DSPE is that it can be operated in two different modes (extraction mode and clean-up mode), both similar to conventional SPE. Basically, an amount of sample is added into a specific amount or concentration (solid/liquid) of magnetic MIPs in an appropriate solvent, in case they are dried or stored in liquid, respectively. Then, the mixture is stirred for a time (adsorption time) that should be optimized to achieve the maximum adsorption of the analyte in the imprinted cavities. Later, the mixture is magnetically separated using a strong external magnet. The supernatant is removed and the magnetic solid phase, in which the target analyte is retained, is maintained for subsequent operations. The magnetic solid material is washed with a suitable solvent to remove the interferences remaining on the surface of magnetic MIPs. Finally, the elution of the target analyte using an elution solvent is accomplished. For the other mode (clean-up), the interferent molecule is adsorbed by the MIP through a similar procedure, leading to a pure solution containing the target analyte.

16.5.2.2

Significant Factors for the Use of Magnetic MIPs in SPE

Several parameters are crucial in the use of MIP-decorated MNPs in DSPE including adsorption medium, adsorption time, the concentration of sorbent, washing solvent, elution solution, and elution time. One of the most important parameters in the application of MIPdecorated MNPs in DSPE is the adsorption medium.49 Different solution properties should be taken into consideration to select the best solvent/ solution for analyte adsorption, such as polarity, pH, solubility, and its effect on the polymer. Adsorption time or rebinding time is an important parameter that allows high recognition of the target analyte. It depends on different parameters,

Applications of Molecularly Imprinted Polymer-decorated Magnetic Nanoparticles

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such as the particle size, but it is preferred to make a kinetic study to determine the minimum time required to achieve good recognition. In order to rebind the maximum amount of target analyte, the concentration of magnetic MIPs should be optimized. Another important step in DSPE is the choice of the washing solution, which should be carefully selected to eliminate the co-adsorbed interferents from the sample matrix without losing the target analyte. Obviously, the target analyte should not be highly soluble in the selected washing solution. The elution stage is the main step to extract the maximum possible amount of target analyte from the magnetic MIPs. The elution solution plays an important role at this point. It should have the potential to extract quantitatively the target analyte without affecting the polymer/imprinted cavities and should be suitable for analytical detection. The elution time or extraction time is an important parameter that needs to be considered to apply the magnetic MIPs in DSPE as well. For example, Ben Messaoud et al. optimized two parameters, such as the amount of magnetic MIP and the rebinding time.39 For the first parameter, they tested different amounts, from 1 to 5 mg, in 0.5 mL of phosphate buffer containing bisphenol A (1 mM), and found that 3.5 mg exhibited the maximum recovery. The rebinding time was also studied from 5 to 20 min and found that after 15 min, a high recovery of bisphenol A was achieved. In another example, Liu et al. studied the effect of several parameters.48 They investigated the effect of the eluent including methanol : acetic acid (9 : 1, v/v), dimethyl sulfoxide, acetonitrile : ethanol (1 : 2, v/v) and ethanol, and found that the highest recovery value was obtained with acetonitrile : ethanol (1 : 2, v/v). They also tested several washing solutions and found that water was the best solution to remove interferents without losing the target analyte, which was curcumin. Regarding the adsorption time, 10 min exhibited the highest recovery value.

16.5.2.3

Sorption Thermodynamic

The sorption thermodynamic study is important to investigate the adsorption of the analyte by the magnetic MIP at different temperatures. The variation of temperature allows to determine thermodynamic parameters, such as DG1, DH1, and DS1, using the following equations: Kd ¼ Qe/Ce

(16.4)

DG1 ¼ R  T  ln Kd

(16.5)

Ln Kd ¼ DS1/R  DS1/R  T

(16.6)

where Kd represents the distribution coefficient; Ce and Qe are the equilibrium concentration of the analyte and the adsorption capacity, respectively; and DG1, DH1 and DS1 are the standard free energy, the standard enthalpy and the standard entropy, respectively.

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For example, Toudeshki et al., performed the thermodynamic study for the sorption of metformin by magnetic MIPs.50 They showed that the adsorption process was good at higher temperatures. The positive value of DH1 indicated that the adsorption process was endothermic. Meanwhile, the negative value of DG1 indicated spontaneous adsorption. The fact that the disorder of metformin increased upon retention by the magnetic MIP was confirmed by the positive value of DS1.

16.5.2.4

Reusability

The reusability of magnetic MIPs plays an important role in developing reliable, economic, and sustainable applications. After the elution of the target analyte, the magnetic MIPs could be washed to remove the remaining analyte from the material. Then, the adsorption–desorption cycle is repeated several times until the magnetic MIPs lose their performance.

16.6 MIP-decorated MNPs for Sensing 16.6.1

MIP-decorated MNPs for Electrochemical Sensors

The unique advantages of magnetic MIPs have facilitated immensely the integration of this composite on electrode surfaces permitting the development of new electrochemical sensors with outstanding analytical performances in terms of reproducibility, high sensitivity and selectivity, simplicity, low fabrication cost, rapid assay time and easiness of miniaturization.51–53 Hence, electrochemical sensors based on MIP-decorated MNPs have gained great attention and have become an international research hotspot.29,39,54,55 There are two main strategies in which magnetic MIPs are integrated into electrochemical sensors. The first one is the drop-casting of magnetic MIPs on electrochemical sensors and their collection with an external magnet under the electrode surface. The second strategy is the collection of magnetic MIPs by magneto-actuated electrodes.

16.6.1.1

Modification with Magnetic MIPs by Drop-casting/coating

The principle of this approach consists of immobilizing the synthesized magnetic MIPs on the surface of a working electrode by dropping a small ´lvez et al.56 developed a volume of the dispersion. In this context, Zamora-Ga highly selective and sensitive impedimetric sensor for sulfamethoxazole (SMX) detection. After the incubation of the synthesized magnetic MIPs with sulfamethoxazole for rebinding, they were re-dispersed in a new buffer solution and a small volume of the suspension (magnetic MIPs–SMX in buffer) were dropped onto the surface of a homemade screen-printed carbon electrode (SPCE), used as the working electrode. The use of a disk magnet under the working electrode (the magnet and the working electrode had the same diameter size) allowed the collection/de-collection of the magnetic MIPs

Applications of Molecularly Imprinted Polymer-decorated Magnetic Nanoparticles

415

particles, leading to the possibility of reusing the SPCE. The measurements were performed via electrochemical impedance spectroscopy using the ferri/ ferrocyanide system as a redox probe. This strategy achieved a very low limit of detection (1012 mol L1). A similar strategy has been exploited for 17-bestradiol determination but using direct detection with square-wave voltammetry.57 Rather than SPCE, other electrodes were used to be modified with magnetic MIPs, such as glassy carbon,58 gold,59 and carbon paste60 electrodes. The main advantage of the impedimetric method is the possibility to detect non-electroactive analytes through indirect determination.

16.6.1.2

Magnetic Capture onto Magneto-actuated Electrodes

The integration of magnetic MIPs in the electrochemical sensor could be done by the magnetic capture of magnetic MIPs onto magneto-actuated electrodes. Basically, the magnetic MIPs are incubated with the target analyte in a selected solution for a time that should be optimized. Then, the magnetic MIPs with the preconcentrated analyte are magneto-actuated on the surface of the electrode by dipping it in the incubation solution until all the magnetic MIPs are captured by the electrode. Finally, the electrochemical measurement is carried out by a suitable electroanalytical technique. In this context, Bilici et al.61 reported the integration of magnetic MIPs onto a magneto-actuated electrode based on a graphite–epoxy composite for the electrochemical determination of histamine preconcentrated from fish samples. The developed biomimetic sensor exhibited a low limit of detection of 1.6106 mg L1. Hassan et al.54 developed an electrochemical sensor for the detection of methyl parathion using magnetic MIPs as artificial receptors. The pesticide was pre-concentrated on the magnetic MIPs and the measurements were carried out using a magneto-actuated electrode based on a graphite–epoxy composite. The developed sensor exhibited outstanding analytical performance with a low limit of detection 1.22106 mg L1 and recovery values in the range of 90–95%. In another example, H. Jiang et al.55 reported an economical sensor for Gram-negative bacterial quorum signaling molecule measurements using magnetic MIPs. They used 2,5-dimethyl-4-hydroxy-3(2H)-furanone as the analog template and a magnetic carbon paste electrode as the working electrode. Differential pulse voltammetry (DPV) was used to record the oxidative current signal of the target analyte. The developed sensor showed high sensitivity, with 81010 mol L1 as the limit of detection. The integration of the magnetic MIPs in electrochemical sensors leads to other types of characterization based on electrochemistry using, for example, cyclic voltammetry.57

16.6.2

MIP-decorated MNPs for Optical Sensors

Traditional magnetic MIPs have good recognition performance, but they do not possess the capability to generate signals during analysis and detection. Therefore, they require a combination of instrumental methods. Indeed,

416

Chapter 16

optical sensors have attracted attention as an analytical application of MIPs and magnetic MIPs.

16.6.2.1

UV–Vis Spectrophotometry

UV–Vis spectrophotometry is the most commonly used determination technique because of its high efficiency, good reliability, simplicity, and low cost. However, it has some drawbacks related mainly to sensitivity, and selectivity, when detecting some compounds at the trace level. Sample preparation and enrichment steps using SPE before the detection are necessary to overcome the challenges of this technique. One of the excellent materials that plays an important role in the SPE is the MIP or magnetic MIP. Recently, Liu et al. reported the use of magnetic MIP coupled with UV–Vis spectrophotometry to detect curcumin in food.48 Bilici et al. developed a sensitive spectrophotometric detection of metoclopramide in urine samples.62 The magnetic molecularly imprinted solid-phase extraction coupled with a colorimetric method before the detection of sulfonamide has been also reported.27

16.6.2.2

Fluorescence

The word ‘‘fluorescence’’ was invented in 1852 by the English physicist George Gabriel Stokes, who noticed that fluorite crystals (calcium fluoride) emitted blue light when illuminated with ultraviolet light. The phenomena of fluorescence, therefore, appear when a substance absorbs visible and often ultraviolet light and, then, re-emits it at a longer wavelength. The operating principle of a fluorescence sensor is based on the conversion of the recognition between the molecular recognition unit and a target into a fluorescence response signal, which depends on the concentration of the analyte. Fluorescent magnetic MIPs are fabricated by introducing fluorescent materials during the synthesis process. There are two main strategies: direct and indirect fabrication.63 Direct fabrication is easier than the indirect one, since it is similar to the preparation of traditional MIP composites. It requires an intrinsically fluorescent molecule that acts as a template.64 This condition could limit the applicability of this strategy. Indirect fabrication: generally, for non-fluorescent target analytes, no fluorescence signal can be emitted after recognition, if no external fluorescence source is doped into the MIP composite. Therefore, a fluorescent substance must be introduced. There are three common methods used to introduce extrinsic fluorescence, such as competitive binding against prebound fluorescent indicators,65 employment of fluorescent functional monomers,66 and embedding of fluorescent substances.67

16.6.2.3

Chemiluminescence

Chemiluminescence is the production of light as a result of chemical reactions that produce energy in the form of light. Reagents in this type of reaction

Applications of Molecularly Imprinted Polymer-decorated Magnetic Nanoparticles

417

exchange electrons with each other: it is during this exchange that the electrons, once excited, will return to their normal state by producing light. The chemiluminescence phenomenon has been exploited in the application of sensors. Therefore, chemiluminescence-based sensors have been developed to combine the sensitivity of the reactions emitting light with the practicality of the sensors. Since the intensity of the light emitted is directly proportional to the concentration of the analyte, chemiluminescence is a promising analytical technique that offers rapid determination, convenient operation, and accuracy to the analysis. The introduction of magnetic MIPs in the chemiluminescence sensors could overcome the limitation of those sensors by improving the selectivity. After the preparation of magnetic MIPs, they are introduced into a colorless glass tube producing a magnetic MIPs column. This column is connected to the chemiluminescence flow system as the recognition element for the sensor.

16.7 Recent Advances in the Analytical Applications of Magnetic MIPs 16.7.1 16.7.1.1

Food Safety Biomarkers

Monitoring of N-acyl homoserine (AHLs) signaling molecules as a biomarker of Gram-negative bacteria in food samples is necessary to identify trends in contaminated and unsafe foods, in order to prevent large-scale food epidemics. Thus, Cui et al. developed a magnetic fluorescence probe based on magnetic carbon quantum dot-doped MIPs for the detection of AHLs in milk and fish juice samples. Good selectivity and fast response were exhibited for AHLs monitoring in agri-food products for early detection and prevention of disease caused by food spoilage.68 Against Gram-negative and positive bacteria, ceftazidime is usually used as an antibiotic for the treatment of bacterial infections in food. However, sideeffects may include bloody diarrhea, seizures, and hyperactivity. Therefore, it is necessary to develop a new detection method of ceftazidime in food and that is what Bunkoed et al. performed.69 They synthesized a fluorescent probe nanocomposite based on MNPs, graphene quantum dots, and MIP. The MIP was prepared by a sol–gel polymerization reaction. The concentration range was 0.10–10 mg L1 and the limit of detection was 0.05 mg L1. The developed optosensor was utilized for ceftazidime detection in milk samples. Rapidity, easy operation, selectivity, and sensitivity were the main advantages of this sensor.

16.7.1.2

Pesticides

Organophosphorus pesticides are the most widely used pesticides because of their low price and high efficiency. They account for about 70% of all

418

Chapter 16

pesticides. Overuse of these pesticides causes food pollution, which can cause some diseases due to their excessive accumulation in the body leading to a lot of disease and deaths each year. Therefore, it is important to develop a sensitive, selective and rapid analytical method to detect organophosphorus pesticides to ensure food safety and human health. Wu et al. developed a fluorescent sensor based on vinyl phosphate-modified carbon dots and magnetic MIPs to enrich and detect organic phosphorus. The linear range was from 0.0035 to 0.20 mmol L1 and the limit of detection was 0.0015 mmol L1. The developed sensor was applied to the detection of triazophos in cucumber samples.70

16.7.1.3

Toxins

Wang et al. produced a thermo-responsive MIP on the surface of magnetic halloysite nanotubes using N-isopropylacylamide as other types of monomers (thermo-sensitive functional monomer). Adsorption properties, magnetic properties, and temperature-responsive behaviors were studied. The developed material was coupled with HPLC for the selective recognition, enrichment, and detection of sterigmatocystin in wheat samples. The recoveries obtained were in the range of 88.62–102.9% with a limit of detection of 1.1 mg Kg1.71 Acrylamide has received a lot of attention since it was discovered in fried cereal-based foods in 2002. It is formed during the heating of starchy foods at temperatures exceeding 120 1C as a result of the Maillard reaction between reducing sugars and amino acids, particularly asparagine. Therefore, it is important to develop new, rapid, and selective methods for the enrichment and highly sensitive detection of acrylamide in fried foods. MIP is one of the best candidates for use as a sorbent for SPE. However, the development of MIPs for this compound is difficult, since it is considered to be a monomer that polymerizes during the preparation of MIP and no imprints can be created. The use of dummy templates can overcome this problem in addition to other advantages of this strategy related to reducing the leakage of template molecules. Propionamide was used as a dummy template for that purpose. The prepared magnetic MIPs coupled to HPLC showed good recoveries (83.9–96.8%) and low limit of detection for the quantitation of acrylamide in potato chips.72 In previous research, biocompatible magnetic MIPs were prepared successfully using Zein protein as a cross-linking agent. The proposed material was combined with electrochemistry to enrich and detect selectively tetracycline compounds in milk. The linearity range was 0.025–500 mg mL1, and very low limits of detection 50.025 mg mL1) and quantitation (0.083 mg mL1) were obtained.73 The combination of magnetic MIP and a surface plasmon resonance technique has also been reported for the detection of tetracycline in milk by Gao et al. The proposed method showed a linear range between 5.0 and 100 pg mL1 and a detection limit of 1.0 pg mL1. The recovery was in the range of 95.7–104.6%.74

Applications of Molecularly Imprinted Polymer-decorated Magnetic Nanoparticles

16.7.2

419

Emerging Pollutants

Magnetic MIPs were used successfully by Zhang et al. to prepare an electrochemiluminescence sensor for bisphenol A determination. After the synthesis of the magnetic MIPs by reverse micro-emulsion polymerization, they were immobilized onto the surface of a glassy carbon electrode. A linear concentration range of 0.002 mg L1 to 5.0103 mg L1 with a limit of detection of 2.0104 mg L1 was obtained. This sensor showed high sensitivity and good selectivity and demonstrated great potential to detect bisphenol A in aquaculture samples.75 In another important work, Fan et al. investigated the pre-polymerization effects on the property of multi-templates surface magnetic MIPs to simultaneously and quickly separate and detect six sulfonamides (sulfathiazole, sulfadiazine, sulfamethazine, sulfamerazine, sulfadoxine, and sulfamethoxazole) in real water samples. The adsorption capacities of the magnetic MIPs prepared with the pre-polymerization stage towards the six sulfonamides were higher than those of the magnetic MIP prepared without pre-polymerization. Then, the magnetic MIPs were used as adsorbents for SPE and coupled with HPLC to detect the six sulfonamides in real water samples.76 The magnetic MIPs in combination with flowing atmospheric-pressure afterglow mass spectrometry has also been applied for the analysis of estrogen hormones (estrone (E1) and b-estradiol) in water. The developed magnetic MIP was used for SPE and pre-concentration of estrogens before analysis. A very low limit of detection was achieved at 0.135 mg L1.77 Acetaminophen is used to treat migraine headaches, neuralgia, and fever and for pain relief after surgery. Excessive use of acetaminophen can cause symptoms of anorexia, kidney failure, liver necrosis, and nausea, which can be lifethreatening. The detection of this compound is important in physiological functions and clinical applications. Su et al. developed an efficient electrochemical sensor based on magnetic MIPs for the determination of acetaminophen in tablets, granules, Altapharmas, oral solution, human serum, and urine samples. Before the synthesis of the magnetic MIPs, the suitable functional monomer and solvent were chosen through molecular simulation calculations. After the synthesis of the magnetic MIP, a carbon paste electrode was filled with a strong magnet to make a magnetic electrode, and the magnetic MIP was attracted onto the surface of the electrode thanks to this property. Two ranges of linearity were obtained depending on the concentration (6108–5105 mol L1 and 5105–2104 mol L1), and a low detection limit was achieved based on the lower linear range (1.73108 mol L1). The recovery of the sensor was 95.80–103.76% when used for the determination in real samples.78 The MIP was also developed for multi-templates molecules on the surface of mesoporous silica-coated magnetic graphene oxide by Xie et al.79. The proposed material was used for SPE coupled to HPLC to detect selectively and rapidly alkylphenol compounds, including 4-nonylphenol, 4-tert-octylphenol, and bisphenol A in water. The limits of detection for 4-nonylphenol, 4-tertoctylphenol, and bisphenol A were 0.010, 0.010, and 0.013 mg L1, respectively.

420

16.7.3

Chapter 16

Disease Biomarkers

Glucosylsphingosine is a reliable biomarker of Gaucher disease and has an isomer named galactosylsphingosine, which is also a biomarker but of Krabbe disease. Thus, the selective detection of each biomarker in plasma is difficult, since the simultaneous separation and quantification of both isomers is not easy. Chen et al. reported a strategy for the absolute quantification of multiplexed stable isotope labeling coupled with magnetic dispersive SPE using a novel dummy magnetic MIP by ultra HPLC tandem mass spectrometry. Good linearity was obtained in the range of 0.02–800 nmol L1 and a very low limit of detection 0.005 nmol L1 was achieved for both biomarkers. This method was applied for the multiplex quantitative analysis of these biomarkers in human plasma samples. The proposed method showed the great potential value in the study diagnosis, therapy, monitoring, and drug screening for Krabbe and Gaucher diseases.80

16.7.4

Medical Treatment and Drugs

Globotriaosylsphingosine (lyso-Gb3) is usually used as a diagnostic biomarker by quantification of clinical examination. Very low concentrations of lyso-Gb3 in plasma in a large proportion of heterozygous women with Fabry’s disease make the development of a sensitive, selective, rapid, and accurate detection method for the quantification of this biomarker and the treatment and diagnosis of Fabry’s disease essential. Dummy magnetic MIPs were prepared and used as sorbent materials for magnetic dispersive SPE of 9-plexed derivatives of lyso-Gb3 by Hu et al. Ultra HPLC tandem mass spectrometry was used to quantify the enriched lyso-Gb3 derivatives from real samples. This method was applied to the detection of lyso-GB3 in plasma samples with satisfactory recoveries indicating that the proposed method is promising for the medical testing and bioanalysis of this biomarker in the future.81 Alzheimer’s disease is one of the most common forms of neurodegenerative disorders affecting the memory and behavior of older people around the world. Triptolide, an active component extracted from traditional herbal medicines, has received great attention because of its pharmacological properties, including neuroprotective, anti-inflammatory, antitumor and immunosuppressive activities. It is therefore essential to investigate and compare the pharmacokinetics of triptolide in the blood and brain of normal rats and rats with Alzheimer’s disease, to provide efficient data for the explanation and prediction events related to triptolide efficiency after oral administration. An accurate, specific, and sensitive method based on stable isotope labeling derivatization and magnetic SPE (using magnetic MIP as the sorbent material) combined with ultra HPLC–mass spectrometry was developed by Zhu et al. for the simultaneous determination of triptolide in rat blood and brains by in vivo microdialysis. Good linearity (3–5000) and low limits of detection (0.45 in the brain and 0.50 pg mL1 in blood) and quantitation (3.0 pg mL1) were achieved.82

Applications of Molecularly Imprinted Polymer-decorated Magnetic Nanoparticles

421

Lysozyme is one of the potential biomarkers for the diagnosis of leukemia and other diseases that can mark lesions or changes in human tissues, organs and cells, etc. Lian et al. developed a novel magnetic MIP-modified electrochemical sensor for the determination of lysozyme. Under the optimized conditions, the constructed sensor displayed good linearity 0.05–0.8 mg mL1 with the limit of detection of 1.58103 mg mL1. The developed sensor showed good selectivity and sensitivity for lysozyme determination and was applied successfully to detect it in complex biological samples.83 A novel green magnetic MIP based on the cross-linking of chitosan was prepared for the selective separation of memantine from human serum before its determination by fluorimetry. The linearity range was obtained in the range of 1.84–95.0 ng mL1 with 0.6 ng mL1 as a limit of detection. The proposed method was applied for the determination of memantine in human serum and pharmaceutical tablets with recoveries of 97.6  2.9 and 100.8  3.0, respectively.84 The magnetic MIP was also combined with spectrophotometric detection for the analysis of metoclopramide in urine samples. The proposed method was applied successfully for the enrichment and determination of metoclopramide through the formation of a charge–transfer complex between the eluted metoclopramide and picric acid. Under optimal conditions, the calibration curve was obtained in the linear range of 5.0–150.0 ng mL1 and the limit of detection and quantitation was calculated to be 1.5 ng mL1 and 4.95 ng mL1, respectively.62 Metformin is one of the most common drugs prescribed for type-2 diabetes. Toudeshki et al. developed a new MIP on the surface of magnetic MWCNTs for the selective recognition and pre-concentration of metformin in biological fluids before its chemiluminescence determination. The proposed method exhibited a linear range between 0.5 and 50.0 mg L1 with a limit of detection of 0.13 mg L1 and an enhancement factor of 195.3 for the pre-concentration of 500 mL of the eluent and 100 mL of the sample.50 The development of new stereoisomeric drugs requires that for each new racemic drug, both enantiomers need to be treated as separate substances in the establishment of toxicological and pharmacokinetic profiles. (S)-Naproxen and (R)-naproxen are two enantiomeric, non-steroidal anti-inflammatory drugs, where the first one is responsible for many pharmaceutical applications, such as the treatment of inflammatory and rheumatism diseases and pain. It possesses 28-fold higher activity than the second one that has some unwanted side effects. A biomimetic material based on magnetic MIP was developed by Goyal et al. The highly selective magnetic MIP was used to separate (S)-naproxen from (R)-naproxen, with about 4 times more the affinity for (S)-naproxen.85 We reported this study in this chapter to show that magnetic MIPs could also successfully separate the enantiomers. Table 16.1 presents an overview of the recent advances in the analytical applications of MIP-decorated MNPs.

422

Table 16.1

Selected analytical applications of MIP-decorated MNPs.a

Analyte

Analytical technique

N-acyl homoserine lactones Ceftazidime BPA

0.62–29.90 mg L (6510 – B10.010 0.96101 mmol L1) mg L1 (105 mmol L1) Fluorimetry 0.10–10.0 mg L1 0.05 mg L1 2.0104 Electrochemiluminescence 0.002–5.0103 mg L1 mg L1

Lyso-Gb3 Sulfonamides Triptolide

UHPLC–MS HPLC UHPLC–MS

STG E1 and E2

Linear range

Fluorimetry

HPLC Flowing atmosphericpressure afterglow mass spectrometry Tetracycline Electrochemical detection Acrylamide HPLC Acetaminophen Electrochemical detection

LOD 1

3

3

— — 3103 – 5 mg L1

— — 0.50103 mg L1

— —

1.1 mg kg1 0.135 mg L1 for both

2.5101 mg L1 2.5101–5105 mg L1 — 20 mg L1 9.07–7.56103 and 2.61 mg L1 7.56103–30.23103 mg L1

Real sample

Recovery %

Reference

Fish juice and milk

83.10–90.74

68

Milk Fish and seawater samples Plasma samples Water samples Brain and blood of normal and Alzheimer’s disease rats Wheat —

90.7–99.2 93.5–98.3

69 75

95.0–102.4 73.34–102.34 —

81 76 82

88.62–102.9 —

71 77

— 83.9–96.8 95.80–103.76

73 72 78 Chapter 16

Milk Potato chips Tablets, granules, Altapharmas, oral liquid, serum, and urine

5.0–150.0 mg L1 0.5–50.0 mg L1

Lysozyme Memantine

Electrochemical detection Fluorimetry

0.05103–0.8103 mg L1 1.84–5.0 mg L1

Triazophos (organophosphorus pesticide) (S)-naproxen Tetracycline BPA, 4-tert-OP and 4-NP

Fluorescence detection

1.1103–6.3104 mg L1 (0.0035–0.20 mmol L1)

HPLC-UV SPR HPLC

— — —

HPLC–MS

0.02–800 nmol L1

GlcS and GalS a

1.5 mg L1 0.13 mg L1

Urine Biological fluids and water 1.58 mg L1 Urine sample 0.6 mg L1 Pharmaceutical tablets and human serum 4.7104 mg L1 Cucumber (1.5 mmol L1) samples — 1.0103 mg L1 0.013, 0.010 and 0.010 mg L1, respectively 0.005 nmol L1 for both

92.8 and 99.2 —

62 50

— 83 100.8  3.0–97.6  2.9 84 —

70

— 95.7–104.6 81.5–104.1

85 74 79

Human plasma 96.1–107.2 samples

80

— — Real water

BPA: bisphenol A; GlcS: glucosylsphingosine; GalS: galactosylsphingosine; lyso-Gb3: globotriaosylsphingosine; E1: estrone; E2: b-estradiol; STG: Sterigmatocystin; 4-tert-OP: 4-tert-octylphenol; 4-NP: 4-nonylphenol; UHPLC: ultra-high-performance liquid chromatography; MS: mass spectrometry; SPR: surface plasmon resonance.

Applications of Molecularly Imprinted Polymer-decorated Magnetic Nanoparticles

Metoclopramide Spectrophotometry Metformin Chemiluminescence

423

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16.8 Conclusions The combination of MNPs and MIPs leads to a composite that has the advantages of both materials, providing an exceptional adsorbent for use in analytical chemistry. Indeed, the MIPs exhibit good selectivity, and the MNPs simplify the separation process and reduce the procedure time. Moreover, the decoration of MNPs with MIPs allows the formation of the imprinted polymer layer with a small thickness compared to traditional MIPs, and the imprinted cavities are situated on the polymer surface making the access/removal of the template easier. There are different approaches for MIPs preparation, but the non-covalent approach is considered as the most widespread. Before the preparation of MIPs on the surface of MNPs, a computational study to choose the best monomer and solvent is encouraged, since it helps to save experimental time and costs. After the synthesis of MIPdecorated MNPs, several characterizations are required to test whether the main or desired properties of the final products are achieved. The application of these MIP-decorated MNPs in analytical chemistry can be divided into two main applications: (i) the purification and separation of analytes through magnetic imprinted solid-phase extraction (SPE); and (ii) the usage of MIP-decorated MNPs for sensing (electrochemical and optical sensors). An overview of the recent advances in the analytical applications of MIP-decorated MNPs was presented demonstrating that MIP-decorated MNPs have the potential to be applied for different target analytes achieving good selectivity in real samples. Despite the increase in the number of publications about magnetic MIPs, these materials still face some challenges that should be overcome to produce efficient materials applicable in analysis, following their commercialization. Among those problems, the heterogeneity of adsorption sites, low accessibility to the cavity, the problem of an efficient removal step without affecting the polymer layer, imprinting large molecules, imprinting of ions, etc. must be further improved.

References ´. Rı´os, Talanta, 2018, ´rcel and A 1. M. Laura Soriano, M. Zougagh, M. Valca 177, 104–121. 2. D. Sharma and C. M. Hussain, Arabian J. Chem., 2020, 13, 3319–3343. ¨yu ¨ktiryaki, R. Keçili and C. M. Hussain, TrAC, Trends Anal. Chem., 3. S. Bu 2020, 127, 115893. ¨yu ¨ktiryaki and C. M. Hussain, TrAC, Trends Anal. Chem., 4. R. Keçili, S. Bu 2019, 110, 259–276. 5. C. M. Hussain, Handbook of Nanomaterials in Analytical Chemistry: Modern Trends in Analysis, Elsevier, 2019. 6. K. Aguilar-Arteaga, J. A. Rodriguez and E. Barrado, Anal. Chim. Acta, 2010, 674, 157–165. 7. L. Gloag, M. Mehdipour, D. Chen, R. D. Tilley and J. J. Gooding, Adv. Mater., 2019, 31, 1904385.

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8. 9. 10. 11. 12. 13. 14. 15. 16.

17. 18. 19. 20. 21. 22. 23. 24. 25. 26.

27.

28. 29. 30. 31. 32. 33.

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T. A. P. Rocha-Santos, TrAC, Trends Anal. Chem., 2014, 62, 28–36. S. Ansari and M. Karimi, Talanta, 2017, 167, 470–485. J. J. BelBruno, Chem. Rev., 2019, 119, 94–119. I. Ali, C. Peng, D. Lin, D. P. Saroj, I. Naz, Z. M. Khan, M. Sultan and M. Ali, J. Environ. Manage., 2019, 234, 273–289. C. M. Hussain, Adv. Environ. Anal., 2016, 1–13. A. Alirezaie Alavijeh, M. Barati, M. Barati and H. Abbasi Dehkordi, Adv. Pharm. Bull., 2019, 9, 360–373. G. Simonsen, M. Strand and G. Øye, J. Pet. Sci. Eng., 2018, 165, 488–495. L. M. Rossi, N. J. S. Costa, F. P. Silva and R. Wojcieszak, Green Chem., 2014, 16, 2906–2933. C. Sappino, L. Primitivo, M. De Angelis, M. O. Domenici, A. Mastrodonato, I. B. Romdan, C. Tatangelo, L. Suber, L. Pilloni, A. Ricelli and G. Righi, ACS Omega, 2019, 4, 21809–21817. N. Zhu, H. Ji, P. Yu, J. Niu, M. U. Farooq, M. W. Akram, I. O. Udego, H. Li and X. Niu, Nanomaterials, 2018, 8, 810. A. Karrat, A. Lamaoui, A. Amine, J. M. Palacios-Santander and L. Cubillana-Aguilera, Chem. Africa, 2020, 3, 513–533. M. V. Polyakov, Zhurnal Fizieskoj Khimii/Akademiya SSSR, 1931, 2, 799–805. F. H. Dickey, Proc. Natl. Acad. Sci., 1949, 35, 227–229. G. Wulff and A. Sarhan, Angew. Chem., Int. Ed., 1972, 11, 334–342. T. Tagagishi and I. M. Klotz, Biopolymers, 1972, 11, 483–491. L. Andersson, B. Sellergren and K. Mosbach, Tetrahedron Lett., 1984, 25, 5211–5214. R. Arshady and K. Mosbach, Macromol. Chem. Phys., 1981, 182, 687–692. E. Turiel and A. M. Esteban, Solid-Phase Extraction, Elsevier, 2020, pp. 215–233. C. P. Frizzo, C. Bacim, D. N. Moreira, L. V. Rodrigues, G. C. Zimmer, H. G. Bonacorso, N. Zanatta and M. A. P. Martins, Ultrason. Sonochem., 2016, 32, 432–439. ´n, J. M. Palacios-Santander, A. Lamaoui, A. A. Lahcen, J. J. Garcı´a-Guzma L. Cubillana-Aguilera and A. Amine, Ultrason. Sonochem., 2019, 58, 104670. D. Gao, D.-D. Wang, Q.-F. Fu, L.-J. Wang, K.-L. Zhang, F.-Q. Yang and Z.-N. Xia, Talanta, 2018, 178, 299–307. S. Khan, A. Wong, M. V. B. Zanoni and M. D. P. T. Sotomayor, Mater. Sci. Eng.,C, 2019, 103, 109825. M. Marc´, T. Kupka, P. P. Wieczorek and J. Namies´nik, TrAC, Trends Anal. Chem., 2018, 98, 64–78. M. S. Khan, P. S. Wate and R. J. Krupadam, J. Mol. Model., 2012, 18, 1969–1981. H. Li, H. He, J. Huang, C.-Z. Wang, X. Gu, Y. Gao, H. Zhang, S. Du, L. Chen and C.-S. Yuan, Biomed. Chromatogr., 2016, 30, 117–125. ˘er, C. Selçuki and B. Okutucu, J. Mol. Model., 2016, 22, 148. ¨ndeg E. Gu

426

Chapter 16

34. N. T. Abdel Ghani, R. Mohamed El Nashar, F. M. Abdel-Haleem and A. Madbouly, Electroanalysis, 2016, 28, 1530–1538. 35. T. Alizadeh and S. Amjadi, New J. Chem., 2017, 41, 4493–4502. 36. B. Zhang, X. Fan and D. Zhao, Polymers, 2018, 11, 17. 37. J. Hou, H. Li, L. Wang, P. Zhang, T. Zhou, H. Ding and L. Ding, Talanta, 2016, 146, 34–40. ´nager and N. Griffete, ACS Appl. Polym. 38. C. Boitard, A. Lamouri, C. Me Mater, 2019, 1, 928–932. 39. N. Ben Messaoud, A. Ait Lahcen, C. Dridi and A. Amine, Sens. Actuators, B, 2018, 276, 304–312. ´n, J. M. Palacios-Santander, L. Cubillana40. A. A. Lahcen, J. J. Garcı´a-Guzma Aguilera and A. Amine, Ultrason. Sonochem., 2019, 53, 226–236. ´lez, P. F. Hernando and J. S. D. Alegrı´a, Anal. Chim. Acta, 41. G. P. Gonza 2006, 557, 179–183. 42. J. Courtois, G. Fischer, S. Schauff, K. Albert and K. Irgum, Anal. Chem., 2006, 78, 580–584. ´. Pen ´nchez-Gonza ´lez, A ˜ a-Gallego, J. Sanmartı´n, A. M. Bermejo, 43. J. Sa ˜ eiro, Microchem. J., 2019, 147, P. Bermejo-Barrera and A. Moreda-Pin 813–817. 44. M. Cantarella, S. C. Carroccio, S. Dattilo, R. Avolio, R. Castaldo, C. Puglisi and V. Privitera, Chem. Eng. J., 2019, 367, 180–188. 45. H. Fu, W. Xu, H. Wang, S. Liao and G. Chen, J. Chromatogr. B: Anal. Technol. Biomed. Life Sci., 2020, 1145, 122101. 46. S. Wang, B. Wang, H. Si, J. Shan and X. Yang, RSC Adv., 2015, 5, 8028– 8036. 47. S. Khan, T. Bhatia, P. Trivedi, G. N. V. Satyanarayana, K. Mandrah, P. N. Saxena, M. K. R. Mudiam and S. K. Roy, Food Chem., 2016, 199, 870–875. 48. X. Liu, L. Zhu, X. Gao, Y. Wang, H. Lu, Y. Tang and J. Li, Food Chem., 2016, 202, 309–315. 49. N. W. Turner, E. V. Piletska, K. Karim, M. Whitcombe, M. Malecha, N. Magan, C. Baggiani and S. A. Piletsky, Biosens. Bioelectron., 2004, 20, 1060–1067. 50. R. M. Toudeshki, S. Dadfarnia and A. M. Haji Shabani, Anal. Chim. Acta, 2019, 1089, 78–89. 51. A. A. Lahcen and A. Amine, Electroanalysis, 2019, 31, 188–201. ´n ˜ ez-Seden ˜ o, S. Campuzano and J. M. Pingarro ´n, Anal. Chim. Acta, 52. P. Ya 2017, 960, 1–17. 53. Y. Yang, W. Yan, C. Guo, J. Zhang, L. Yu, G. Zhang, X. Wang, G. Fang and D. Sun, Anal. Chim. Acta, 2020, 1106, 1–21. 54. A. H. A. Hassan, S. L. Moura, F. H. M. Ali, W. A. Moselhy, M. del, P. Taboada Sotomayor and M. I. Pividori, Biosens. Bioelectron., 2018, 118, 181–187. 55. H. Jiang, D. Jiang, J. Shao and X. Sun, Biosens. Bioelectron., 2016, 75, 411–419.

Applications of Molecularly Imprinted Polymer-decorated Magnetic Nanoparticles

427

´lvez, A. Ait-Lahcen, L. A. Mercante, E. Morales-Narva ´ez, 56. A. Zamora-Ga A. Amine and A. Merkoçi, Anal. Chem., 2016, 88, 3578–3584. 57. A. A. Lahcen, A. A. Baleg, P. Baker, E. Iwuoha and A. Amine, Sens. Actuators, B, 2017, 241, 698–705. 58. Y. Li, X. Zhao, P. Li, Y. Huang, J. Wang and J. Zhang, Anal. Chim. Acta, 2015, 884, 106–113. 59. X. Li, X. Wang, L. Li, H. Duan and C. Luo, Talanta, 2015, 131, 354–360. 60. L. Zhu, Y. Cao and G. Cao, Biosens. Bioelectron., 2014, 54, 258–261. 61. A. H. A. Hassan, L. Sappia, S. L. Moura, F. H. M. Ali, W. A. Moselhy, M. del, P. T. Sotomayor and M. I. Pividori, Talanta, 2019, 194, 997–1004. 62. M. Bilici, M. U. Badak, A. Zengin, Z. Suludere and N. Aktas, Mater. Sci. Eng., C, 2020, 106, 110223. 63. Q. Yang, J. Li, X. Wang, H. Peng, H. Xiong and L. Chen, Biosens. Bioelectron., 2018, 112, 54–71. 64. X.-A. Ton, V. Acha, K. Haupt and B. Tse Sum Bui, Biosens. Bioelectron., 2012, 36, 22–28. 65. W. Ming, X. Wang, W. Lu, Z. Zhang, X. Song, J. Li and L. Chen, Sens. Actuators, B, 2017, 238, 1309–1315. 66. X. Lu, Y. Yang, Y. Zeng, L. Li and X. Wu, Biosens. Bioelectron., 2018, 99, 47–55. 67. X. Zhang, S. Yang, R. Jiang, L. Sun, S. Pang and A. Luo, Sens. Actuators, B, 2018, 254, 1078–1086. 68. Z. Cui, Z. Li, Y. Jin, T. Ren, J. Chen, X. Wang, K. Zhong, L. Tang, Y. Tang and M. Cao, Food Chem., 2020, 328, 127063. 69. O. Bunkoed, P. Raksawong, R. Chaowana and P. Nurerk, Talanta, 2020, 218, 121168. 70. M. Wu, Y. Fan, J. Li, D. Lu, Y. Guo, L. Xie and Y. Wu, Polymers, 2019, 11, 1170. 71. R. Wang, P. Wu, Y. Cui, M. Fizir, J. Shi and H. He, J. Chromatogr. A, 2020, 1619, 460952. 72. C. Zhang, X. Shi, F. Yu and Y. Quan, Food Chem., 2020, 317, 126431. 73. S.-X. Wang, R.-R. Ma, Y. Z. Mazzu, J.-W. Zhang, W. Li, L. Tan, L.-D. Zhou, Z.-N. Xia, Q.-H. Zhang and C.-S. Yuan, Food Chem., 2020, 326, 126969. 74. W. Gao, P. Li, S. Qin, Z. Huang, Y. Cao and X. Liu, Microchim. Acta, 2019, 186, 637. 75. R.-R. Zhang, J. Zhan, J.-J. Xu, J.-Y. Chai, Z.-M. Zhang, A.-L. Sun, J. Chen and X.-Z. Shi, Sens. Actuators, B, 2020, 317, 128237. 76. Y. Fan, G. Zeng and X. Ma, J. Colloid Interface Sci., 2020, 571, 21–29. 77. M. Guc´ and G. Schroeder, Biomolecules, 2020, 10, 672. 78. C. Su, Z. Li, D. Zhang, Z. Wang, X. Zhou, L. Liao and X. Xiao, Biosens. Bioelectron., 2020, 148, 111819. 79. X. Xie, X. Ma, L. Guo, Y. Fan, G. Zeng, M. Zhang and J. Li, Chem. Eng. J., 2019, 357, 56–65.

428

Chapter 16

80. S.-E. Chen, S. Zhu, J. Hu, J. Sun, Z. Zheng, X.-E. Zhao and H. Liu, Anal. Chim. Acta, 2020, 1124, 40–51. 81. J. Hu, S. Zhu, S.-E. Chen, R. Liu, J. Sun, X.-E. Zhao and H. Liu, Microchim. Acta, 2020, 187, 373. 82. S. Zhu, X. Wang, Z. Zheng, X.-E. Zhao, Y. Bai and H. Liu, J. Pharm. Biomed. Anal., 2020, 185, 113263. 83. A. Liang, B. Tang, H. Hou, L. Sun and A. Luo, J. Electroanal. Chem., 2019, 853, 113465. 84. F. A. Mohamed, P. Y. Khashaba, M. M. El-Wekil and R. Y. Shahin, Int. J. Biol. Macromol., 2019, 140, 140–148. 85. G. Goyal, S. Bhakta and P. Mishra, ACS Appl. Nano Mater, 2019, 2, 6747–6756.

CHAPTER 17

Characterization of Functional Magnetic Nanoparticle-modified Polymeric Composites by Computer Modeling Z. HU* AND J. KANAGARAJ South Dakota State University, Department of Mechanical Engineering, Brookings, South Dakota 57007, USA *Email: [email protected]

17.1 Introduction Materials at the nanoscale, called ‘‘nanomaterials’’, have attracted the attention of researchers for hundreds of years. Among different types of nanomaterials, in recent years, functionalized magnetic nanoparticles and their nanomaterials have received extensive attention due to their unique properties, and have shown promising applications in analytical chemistry, environmental and bioanalytical science, pharmaceutical analysis and theranostics, nanomedicines and biosensors, imaging and chromatography, separation and catalysis, electronic devices, high-density magnetic recording, wireless communication, etc.1–15 There are fast growing demands for materials with desirable magnetic and dielectric properties, such as high permeability and permittivity, for the miniaturization of antennas for handheld and/or mobile wireless devices that use wireless access points to exchange and transmit data. The three desired characteristics of the antennas are smaller size, wider bandwidth Analytical Applications of Functionalized Magnetic Nanoparticles Edited by Chaudhery Mustansar Hussain r The Royal Society of Chemistry 2021 Published by the Royal Society of Chemistry, www.rsc.org

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and higher efficiency. By printing a patch antenna on a substrate with a high permittivity, the antenna can be easily miniaturized, as shown in Figure 17.1.16 However, due to the strong capacitive coupling between the antenna and the antenna ground layer, its performance is considerably degraded. To overcome this problem, instead of using a high-dielectric material (only with high e), a magneto-dielectric (both with e and m) substrate can be used. Therefore, by choosing a material with moderate values of er (relative permittivity) and mr (relative permeability), the same pffiffiffiffiffiffiffiffi miniaturization factor (n ¼ mr er ) can be achieved while the coupling between the antenna and the ground layer is greatly reduced. This will increase the efficiency and bandwidth of the antenna.17 Common ferromagnetic metals are transition metals such as iron, cobalt, nickel and some rare earth metals. These materials have high electrical conductivity and therefore cannot be used as dielectrics. Ferrites are usually nonconductive ferromagnetic or ferrimagnetic ceramic compounds derived from iron oxides such as hematite (Fe2O3) or magnetite (Fe3O4) and oxides of other metals. Ferrimagnetic materials exhibit permanent magnetization and good dielectric properties. Some ferrites exhibit useful magneto-dielectric properties at low frequencies, while others exhibit these properties at high frequencies. Ferrites having low coercivity are called soft ferrites. Examples include manganese–zinc ferrites (molecular formula MnaZn(1a)Fe2O4) and nickel–zinc ferrites (molecular formula NiaZn(1a)Fe2O4). MnZn ferrites have higher permeability and saturation induction than NiZn ferrites, and for applications below 5 MHz, MnZn ferrites are used. NiZn ferrites exhibit higher resistivity than MnZn ferrites, so they are more suitable for frequencies above 1 MHz.18–22 Figure 17.2 shows the magnetization curves of a series of synthesized spinel nickel–zinc ferrite nanopowders measured at room temperature, in which Ni0.5Zn0.5Fe2O4 shows a higher magnetization property.23 Engineering a composite material with effective and moderate properties by properly configuring the constituents of the magneto-dielectric materials provides greater freedom in achieving the desired functionalities. Studies have shown that artificial materials, often referred to as metamaterials, can significantly extend the range of material properties and provide potential

Figure 17.1

Schematic diagram of a microstrip rectangular patch antenna.

Polymeric Composites by Computer Modeling

Figure 17.2

431

Hysteresis curves of [NixZn1x]Fe2O4 with different compositions and proportions.

for new magneto-dielectric behavior. By incorporating magnetic fillers, such as typical spinel NiZn ferrites or MnZn ferrites, the dielectric permittivity of the composites can be changed to maximize the absorption of electromagnetic energy. It was found that incorporating ferrites into the polymer matrix can reduce the dielectric loss. The superior performance of metamaterials not only stems from the characteristic length scales and volume fraction but also more importantly from the periodic arrangement of the constituents of the magneto-dielectric composition in the composite material.17,24–44 Therefore, the main challenge for developing metamaterials is to control the concentration, shape, orientation, and distribution of the magneto-dielectric components in engineering composites in addition to improving the cost-effectiveness and good processability of the materials. Recent studies have shown that the characteristic length (surface-tovolume ratio) of particles and their distribution, orientation and effective volume in composite materials play an important role in determining the dielectric and magnetic properties of composite materials.45–56 The most promising way to clarify the impact of all these factors on the dielectric and magnetic properties of the composite materials is to make a nanocomposite material, especially using copolymers, which can template nanoparticles with a narrow size distribution and uniform confinement throughout the periodic micro-domains to control the spatial distribution and orientation of the nanocomposites.34,57–59 This allows much more complex adjustments to the overall performance of the composite materials.

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The physical properties of functionalized magnetic nanoparticles and their nanocomposites depend on the fabrication procedures and process parameters. The effective design and use of nanoparticles and nanoparticlemodified composites rely on the accurate characterization of the nano/ microstructure of the nanoparticles and the nanocomposites. Traditionally, characterization through experimental techniques has been widely used, such as X-ray diffraction and spectrometry, light and electron microscopy, thermogravimetric analysis, nuclear magnetic resonance and mass spectroscopy. The characterization methods and technologies associated with magnetic nanoparticles can be divided into size, crystal structure, element composition and physical properties. Each type of characterization can be evaluated using multiple techniques. The advantages and limitations of each technique complicate the selection of the most suitable method, and a combined characterization approach is usually required. Current knowledge about the use, progress, advantages and disadvantages of many experimental techniques are available for the characterization of nanoparticles.60–64 For a summary of the experimental techniques that are used for nanoparticle characterization refer to Table 1 in ref. 61 and for the parameters needed to be determined and the corresponding characterization techniques refer to Table 2 in ref. 61. i) Dimensionality determination: Nanoparticle size, shape, size distribution, degree of aggregation, surface charge and surface area, and to some extent surface chemistry, which are key parameters of nanoparticles, can be measured or evaluated. Different measurement techniques measure the size of nanoparticles in different ways. Some techniques measure the physical size of the nanoparticles, i.e., the hard material interface, while others measure the hydrodynamics size, i.e., the water layer attached to the nanoparticles as it moves in solution. Therefore, the measurement result, i.e., the resulting size, depends on the type of interface being probed. The shape of the nanoparticle also plays a role in size measurement. For example, some characterization tools approximate all objects as spherical and therefore assign effective diameters to non-spherical nanoparticles. In addition to nanoparticle size, size distribution is also important. The size distribution can reveal, for example, the presence of aggregates in the solution, which in turn can indicate poor dispersion of the nanoparticles. However, there are unmet challenges in measurement of the concentration of nanoparticles in situ and on-line, especially in a scaled-up production, as well as their analysis in complex matrices. There are six main methods to provide information either on the ensemble level or at the single nanoparticle level: dynamic light scattering (DLS), differential centrifugal sedimentation (DCS), nanoparticle tracking analysis (NTA), tunable resistive pulse sensing (TRPS), atomic force microscopy (AFM), and electron microscopy (EM). ii) Structure and composition determination: The crystal structure of the nanoparticles and their chemical composition need to be thoroughly

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433

investigated as a first step after nanoparticle synthesis. Until now, there have been no standardized protocols for this aim. Credible and robust measurement methods greatly affect the uptake of the nanomaterials in commercial applications and allow the industry to comply with regulations. Nevertheless, there are important challenges in the analysis of nanomaterials because of the interdisciplinary nature of the field, the absence of suitable reference materials for the calibration of analytical tools, the difficulties linked to the sample preparation for analysis and the interpretation of the data. X-ray-based techniques, such as X-ray diffraction (XRD), and X-ray absorption spectroscopy (XAS) are the most extensively used techniques for the characterization of nanoparticles. Typically, X-ray-based techniques provide information regarding the crystalline structure, nature of the phase, lattice parameters and crystalline grain size. However, it is not suitable for amorphous materials and the XRD peaks are too broad for particles with a size below 3 nm. X-ray photoelectron spectroscopy (XPS) is the most widely used analytical technique for surface chemical analysis, also employed for the characterization of nanoscale materials. Its underlying physical principle is the photoelectric effect. XPS is a powerful quantitative technique, useful to elucidate the electronic structure, elemental composition and oxidation states of elements in a material. It can also analyze the ligand exchange interactions and surface functionalization of nanoparticles as well as core/shell structures, and it operates under ultra-high vacuum conditions. There are also several other techniques that help in the determination of the structure, composition, size, and other basic features of the nanoparticles, such as Fourier transform infrared spectroscopy (FTIR), nuclear magnetic resonance (NMR), thermal gravimetric analysis (TGA), low-energy ion scattering (LEIS), UV–Vis spectroscopy (UV–Vis), Photoluminescence (PL) spectroscopy, mass spectrometry (MS), secondary ion mass spectrometry (SIMS), and time of flight secondary ion mass spectrometry (ToF-SIMS), iii) Physical property determination: The magnetic properties of nanoparticles are what makes these materials unique. The first attribute of interest is usually the magnetization (M) as a function of the applied magnetic field (H). In order to describe this relationship experimentally, there are several different methods that can be used. One of the most common ways to describe the magnetic behavior of a material is using direct current (dc) magnetometry techniques. Superconducting quantum interference device magnetometry (SQUID) is a tool for measuring the magnetic properties of nanoscale materials. Nanomaterials in particular exhibit different properties to those in the bulk state due to their small size and sensitivity to local conditions. As a material decreases in size, it progresses from multi-domain, to single domain and finally to superparamagnetic status. Typical SQUID measurements yield properties such as the magnetization saturation (MS), magnetization

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remanence (MR), blocking temperature (TB) and magnetic response of individual molecules. A scanning magnetic microscope including a nanoSQUID has also been developed recently, fabricated on an apex of a sharp quartz. NanoSQUID is considered as a highly promising probe for nanoscale magnetic imaging and spectroscopy. Vibrating sample magnetometry (VSM) is another method that can be used to record the M–H loops for magnetic nanomaterials and obtain parameters such as ¨ssbauer spectroscopy is a valuable analytical tool that is MS and MR. Mo based on the recoil-free resonance fluorescence of g-photons in matter ¨ssbauer—active elements, such as Fe. Mo ¨ssbauer can be used to with Mo evaluate the oxidation state, the symmetry and spin state as well as the magnetic ordering of the Fe atoms in a nanoparticle sample and thus identify the magnetic phases in a sample. It can also be used to measure other magnetic properties. In addition, ferromagnetic resonance (FMR) is a spectroscopic technique that probes the magnetization of ferromagnetic materials, including nanoscale ones. X-ray magnetic circular dichroism (XMCD) is a technique that is used as a local probe for the study of the site symmetry and the magnetic moments of transition metal ions in ferro- and ferrimagnetic materials. However, characterization of material properties by experimental methods is expensive and time consuming, especially for the design and development of a new metamaterial. Characterization based on computer modeling provides a powerful alternative for evaluating the magnetic properties of the functionalized magnetic nanoparticles and the magnetic nanoparticle modified nanocomposites.65–70 In recent years, considerable effort has been devoted in using magnetoelectric nanocomposites to miniaturize wireless communication devices. However, due to the inherent incompatibility between inorganic particles and organic matrices, to date, there is no systematic study of the effect of effective volume fraction, characteristic length, geometrical topology, and arrangement of magneto-dielectric components on the magneto-dielectric properties of the composite materials. Most published studies have adopted the conventional method of mixing magneto-dielectric particles into polymers, which cannot really control the size, shape, and dispersion of particles in the polymer matrices.24–27,30–33,35–38,52,53,71–74 In this chapter, polymeric nanocomposite materials with an epoxy matrix modified by spinel structured nickel zinc ferrite (Ni0.5Zn0.5Fe2O4) nanoparticles were selected for numerical analysis. The effects of the shape, concentration, orientation, and distribution of the nanoparticles on the magnetic and dielectric properties of the resulting polymer nanocomposites were systematically studied using computer modeling based on finite element analysis (FEA). The numerical results were compared with the analytical results. Material design by modeling will help to develop new nanocomposites with the required dielectric and magnetic properties and manufacturing-friendly fabrication methods.

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17.2 Computer Modeling Understanding the properties of metamaterial is the key to designing materials. The material properties can be evaluated through experiments (an expensive and time-consuming method) or through predictive modeling (an inexpensive alternative and a more effective method). The following section of this chapter uses computer modeling based on FEA and the Monte-Carlo method to evaluate the magneto-dielectric properties of materials, which is a key step in the design of materials with desired magnetic and dielectric properties.

17.2.1

Fundamental of Electro-magnetic Wave

Whenever an electromagnetic wave hits a conductive object, electrons are excited and produce a surface current. Surface current transmits electromagnetic energy, which is temporarily captured on the surface of the object. The energy will be absorbed or re-radiated by the object. Electromagnetic waves can be analyzed by solving Maxwell’s equations, which are governed by Ampere’s law, Faraday’s law, Poisson’s law, and the conditions of solenoid magnetic flux density as follows75,76 @D @t

(17:1)

@B @t

(17:2)

r  H¼J þ r E¼ 

r  B¼0

(17.3)

r  D¼r

(17.4)

where r is a curl operator, r  is a divergence operator, H is a magnetic field intensity vector (A m1 or Oe), J is a current density vector (A m2), D is an electric displacement vector (C m2), E is an electric field intensity vector (V m1), B is a magnetic flux density vector (T or Wb m2), and r is an electric charge density (C m3). In electromagnetism, the permittivity is a measure of the resistance encountered when an electric field is formed in a medium. In other words, the permittivity is a measure of how an electric field affects, and is affected by, a dielectric medium. For the simulation calculation of permittivity, the voltage difference between the two opposite end faces of the model is applied, which will induce the electrical displacement D and form the following constitutive equations: D ¼ e0 er  E

(17.5)

J ¼ sE

(17.6)

where e0 ¼ 8.8541012 F m1 is the permittivity of vacuum, er is the complex relative permittivity, and s is the conductivity of material (S m1).

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In electromagnetism, magnetic permeability is a measure of a material’s ability to support the formation of a magnetic field within itself, which can be expressed as the degree of magnetization that a material obtains in response to an applied magnetic field. For the simulation calculation of permeability, a similar way of calculating permittivity will be used, i.e., a surface force of magnetic potential is applied, which will induce the magnetic flux B and form the following constitutive equation: B ¼ m0 mr  H

(17.7)

where m0 ¼ 4p107 H m1 is the permeability of vacuum, and mr is the complex relative permeability. The solutions to all electromagnetic problems incorporate the above equations related to material properties, called constitutive equations, and these material properties govern the propagation of electromagnetic waves in the material. Furthermore, the relative complex permittivity and permeability can be written as: er ¼

e ¼ e0r  ie00r e0

(17:8)

mr ¼

m ¼ m0r  im00r m0

(17:9)

where the relative permittivity, or dielectric constant, of a material is the ratio of its absolute permittivity of a specific medium to the vacuum (free space) permittivity, and the relative permeability is the ratio of the absolute permeability of a specific medium to the vacuum (free space) permeability. The ratio of the transverse components of the electric and magnetic fields E to H is the wave impedance Z of an electromagnetic wave propagating in a specific medium. In the case of an ideal dielectric (where the conductivity is zero, approximate in the case of nanocomposite materials of this application), the wave impedance reduces to the real number. rffiffiffi m Z¼ (17:10) e This shows that the wave impedance is a function of the permeability and the permittivity of the medium that wave propagates in. In the case of a normalized wave impedance where the wave impedance is divided by the wave impedance of air, Z0, eqn (17.10) becomes: Z ¼ Z0

rffiffiffirffiffiffiffiffi rffiffiffiffiffi m m0 mr ¼ e e0 er

(17:11)

Polymeric Composites by Computer Modeling

17.2.2

437

Effective Permittivity and Permeability of Nanocomposites

Before computer modeling nanocomposites, the essential steps are to build solid models and assume initial conditions and boundary constraints. In this chapter, a three-dimensional model of the magnetic and dielectric properties of a two-phase mixture (epoxy polymer matrix and Ni0.5Zn0.5Fe2O4 ferrite magnetic nanoparticles) is established. The model is composed of threedimensional unit cells that repeat periodically, and periodic boundary conditions are applied on the side surfaces. In the unit cell, one of the modeling cases is that the nanoparticles are randomly distributed based on the Monte Carol method, as shown in Figure 17.3. Different volume fractions, shapes, distributions, and orientations of the nanoparticles in the nanocomposites were considered in the modeling. An electric or magnetic field is applied on both end faces in the X-, Y-, and Z-directions, respectively, to obtain the effective permittivity and effective permeability of the designed composites. As long as the wavelength of the applied electric field E and the length of the magnetic field H are greater than the length scale of the material structural inhomogeneities, that is, greater than the particle diameters and interparticle distances, the composite material can be considered as a socalled effective medium with homogeneous material properties (effective permittivity eeff and effective permeability meff).77–80 This calculation illustrates two main features: (i) The effective material parameters are not only

Figure 17.3

Schematic of a nanocomposite FEA model with periodical boundary conditions and randomly distributed nanoparticles for magnetic and dielectric property modeling.

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dependent on the nature of the components and their mixing ratio. In this case, the microstructure, particle shape and size distribution, and their spatial arrangement directly affect the field distribution, which in turn affect eeff and meff. Therefore, analytical mixing rules are only applicable to simple geometries (for monodisperse arrays of spheres and spheroids).81–83 (ii) For a given microstructure, the permittivity and permeability have the same formal relationship. Therefore, after obtaining the E and D of each element through modeling, the following equations can be used to derive the permittivity in the corresponding direction (x-, y- or z-direction): ! m X Di1 V1 þ Di2 V2 þ    þ Dim Vm ¼ Dij Vj =V Di ¼ (17:12) V1 þ V2 þ V3 þ    þ V m j¼1 Ei1 V1 þ Ei2 V2 þ    þ Eim Vm ¼ Ei ¼ V1 þ V2 þ V 3 þ    þ Vm

m X

! Eij Vj =V

(17:13)

j¼1

Pm 1 Di 1 j ¼ 1 Dij Vj ¼ Pm eri ¼ e 0 Ei e0 j ¼ 1 Eij Vj

(17:14)

where the index i ¼ x, y, or z for the three perpendicular directions. Similarly, after obtaining the B and H of each element through modeling, the permeability of the corresponding direction (x-, y-, or z-direction) can be derived using the following equations: ! m X Bi1 V1 þ Bi2 V2 þ    þ Bim Vm Bi ¼ ¼ Bij Vj =V (17:15) V1 þ V2 þ V 3 þ    þ Vm j¼1 Hi1 V1 þ Hi2 V2 þ    þ Him Vm ¼ Hi ¼ V1 þ V2 þ V3 þ    þ V m

m X

! Hij Vj =V

(17:16)

j¼1

Pm 1 Bi 1 j ¼ 1 Bij Vj ¼ P mri ¼ m0 Hi m0 m j ¼ 1 Hij Vj

(17:17)

Finally, averaging three permittivities or permeabilities in the x-, y-, and z-directions can obtain the effective permittivity or effective permeability of the nanocomposite: eeff ¼

erx þ ery þ erz 3

(17:18)

meff ¼

mrx þ mry þ mrz 3

(17:19)

and

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17.2.3

439

Analytical Calculation of Effective Permittivity and Effective Permeability

The Maxwell–Garnett rule for effective permittivity can be represented by84   2f ep  em þ ep þ 2em   eeff ¼ em (17:20) 2em þ ep  f ep  em and the Bruggeman rule for effective permittivity can be represented by85 ð1  f Þ

ep  eeff em  eeff þf ¼0 em þ 2eeff ep þ 2eeff

(17:21)

where f is the volume fraction of the particles in the nanocomposite, and ep and em are the effective permittivity of the particles and the matrix, respectively. For the Maxwell–Garnett rule, the formula is explicit, and the effective permittivity can be directly obtained. For the Bruggeman rule, the formula is implicit, and the effective permittivity can be solved by solving the root of the formula under the given parameters. Similarly, the Maxwell–Garnett rule for effective permeability can be represented by   2f mp  mm þ mp þ 2mm   meff ¼ mm 2mm þ mp  f mp  mm

(17:22)

and the Bruggeman rule for effective permeability can be represented by ð1  f Þ

mp  meff mm  meff þf ¼0 mm þ 2meff mp þ 2meff

(17:23)

where mp and mm are the effective permeability of the particles and the matrix, respectively.

17.2.4

Modeling of Nanocomposites

Computer modeling of 2D and 3D systems allows the calculation of the effective material parameters for various particle arrangements and shapes.67,68,86–95 The schematic models of the unit cell with different nanoparticle distributions, shapes, and orientations are shown in Figure 17.4. In the modeling, the different nanoparticle distributions include random, simple cubic, body-centered cubic, and face-centered cubic distributions, and the different nanoparticle shapes include cubic, spherical, and bar shapes parallel or perpendicular to the field direction. The commercial FEA software ANSYSs was used for modeling.96 As a powerful metamaterial design tool, computer modeling can be used to predict the material properties and design magnetodielectric nanocomposites with the desired properties. Design factors include

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Figure 17.4

Chapter 17

Schematic of nanoparticle shapes and distributions: (a) random distribution of balls, (b) simple cubic distribution of cubes, and (c) body-centered cubic distribution of bars parallel to the field direction.

volume fraction (concentration), shape, orientation, and distribution of nanoparticles. After the solid model is build, the model needs to be discretized into elements and nodes (meshes). Considering the modeling accuracy, on the one hand, if the mesh size was too small, the computation time would be very long. On the other hand, if the element size was too coarse, the modeling results would not be accurate enough. In this application, due to the irregular topology of the solid model, a 3D tetrahedron element type was adopted for meshing the model. By studying the convergence of the physical properties of the models of various unit cells for various element numbers, the appropriate element size or total number of elements in a unit cell was determined, so that the models are mesh independent. Figure 17.5 shows the graphs of changes in effective permeability and modeling solution time with changes in number of elements in one-unit cell for different numbers of unit cell models with 8% (by volume) of nanoparticles in the nanocomposite. The convergence function of the effective permeability verses the number of elements in a unit cell can be well fitted as: y ¼ 1.05666 þ 0.50012x0.656426

(17.24)

For the case of 8 vol% of nanoparticles in a nanocomposite, when the number of elements is close to infinity, the convergence value is close to 1.05666. When the number of elements in a unit cell reaches 100 000, modeling can provide highly accurate results. Furthermore, the solution time increases parabolically with the increase in the number of elements in one-unit cell of the models and increases with the increase in the number of unit cells of the model. In a similar manner, modeling convergence can be further confirmed by checking the convergence of the effective permittivity of the model or by checking the different volume fraction of nanoparticles in the nanocomposites. In the modeling, the material properties of each component in the nanocomposite were inputted. Some measured electro-magnetic properties

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Figure 17.5

441

Diagrams of changes in effective permeability and modeling solution time with changes in the number of elements in one-unit cell for different number unit cell models.

of Ni0.5Zn0.5Fe2O4 ferrite nanopowder are coericity (Hc) of 0.042 kOe,23,67,68 saturated magnetization (Ms) of 62.5 emu g1, and the ratio of remanence to saturated magnetization (Mc/Ms) of 0.133,23,67,68 effective permittivity of 6.5 at high frequency,97,98 and maximum permeability of 1.889 derived from the M–H curve23,67 and justified in another article.99 Some electro-magnetic properties of the epoxy matrix are effective permittivity of 3.6 at 60 Hz frequency,100,101 and effective permeability of 1.

17.3 Results and Discussion After the element size was determined, several parameters were considered to study the effects on the magnetic and dielectric properties of nanocomposites. Parameters include the distribution of cubic nanoparticles, the shapes of nanoparticles, orientations of bar-shaped nanoparticles, and the volume fraction of nanoparticles. The modeling results were compared with the analytical results.

17.3.1

Effect of Distribution of Cubic Nanoparticles

The electric and magnetic fields in the periodic unit cell for various cubic nanoparticle distributions of 8 vol% of nanoparticles are shown in Figures 17.6 and 17.7. It is hard to differentiate the overall performance of the different nanoparticle distribution models by visual inspection of the electric and magnetic contour plots. Quantitative and accurate estimations of the effective permittivity and effective permeability of the models can be extracted step by step from the modeling data by using eqn (17.12)–(17.19).

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Figure 17.6

Electric field (V m1) distributions of various cubic nanoparticle distributions with 8 vol% nanoparticles. Reproduced from ref. 49 with permission from Elsevier, Copyright 2020.

Figure 17.7

Magnetic field (Oe) distributions of various cubic nanoparticle distribution models with 8 vol% nanoparticles. Reproduced from ref. 49 with permission from Elsevier, Copyright 2020.

Permittivity of the model is calculated by eqn (17.12)–(17.14) and (17.18), where the electric field intensity (E), the electric displacement (D) and the volume of each element can be extracted from the modeling results. Similarly, permeability of the model is calculated by eqn (17.15)–(17.17) and (17.19), where the magnetic field intensity (H) and the magnetic flux density (B) can be extracted from the modeling results. Figure 17.8 shows (a) the relationships of the effective permittivity and effective permeability of the nanocomposites extracted from the modeling data changing with the volume fraction of cubic nanoparticles, and (b) the nanoparticle distributions including simple cubic (SC), body-centered cubic (BCC), face-centered cubic (FCC), and random distributions. As shown in the figures, the modeling results are also compared with the results from the analytical methods (the Maxwell–Garnett rule and the Bruggeman rule). The figures show that as the volume fraction of nanoparticles increases, the effective permittivity and effective permeability increase nearly linearly. The modeling data is very close to the predictions by the analytical methods.

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Figure 17.8

443

Simulation results: (a) Effective permittivity vs. volume fraction of cubic nanoparticles for various distributions and comparison with analytical calculations, and (b) effective permeability vs. volume fraction of cubic nanoparticles for various distributions and comparison with analytical calculations. Reproduced from ref. 49 with permission from Elsevier, Copyright 2020.

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The proposed nanoparticle distributions (simple cubic, body-centered cubic, face-centered cubic, and random distributions) have no significant effect on the properties of the designed nanocomposites.

17.3.2

Effect of Shape and Orientation of Nanoparticles

The effects of the shape and orientation of Ni0.5Zn0.5Fe2O4 ferrite nanoparticles on nanocomposite properties were studied. Figure 17.9 shows the relationship between the effective permeability extracted from the modeling results and the nanoparticle volume fraction for various shapes and orientations of the nanoparticles. As shown in the figure, the modeling results are also compared with the predictions by the analytical methods (the Maxwell– Garnett rule and the Bruggeman rule). The effective permeability calculations by the Maxwell–Garnett rule and the Bruggeman rule refer to eqn (17.22) and (17.23). It can be clearly seen from the figure that for spherical and cubic shapes of nanoparticles, the effective permeability of the nanocomposites from the modeling matches well with the analytical calculations, and as the volume fraction of nanoparticles increases, the effective permeability increases nearly linearly. However, for the bar-shaped nanoparticles, when the bar is parallel to the axial direction, as the volume fraction of the nanoparticles increases, the effective permeability of the nanocomposites from the modeling increases much faster than that when the bar is perpendicular to the axial direction. On the one hand, because Maxwell and Bruggeman

Figure 17.9

Effective permeability vs. volume fraction of nanoparticles for various nanoparticle shapes and comparison with analytical calculations. Adapted from ref. 49 with permission from Elsevier, Copyright 2020.

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formulas consider spherical inclusions as the nanoparticle shape, and in the modeling, since the cubic shape is close to the spherical shape, therefore, the results of the cubic shape give almost the same results as for the spherical shape. On the other hand, for the nanocomposites with bar-shaped nanoparticles aligned in the axial direction, it gives higher permeability and permittivity than other shapes, especially much higher than that of the barshaped nanoparticles in the perpendicular direction. This phenomenon is supported by the literature.102–105 An axial directional bar means its direction perpendicular to the electromagnetic wave propagation direction. When nanoparticles or flaky thin amorphous particles are aligned in a polymer in the direction perpendicular to the electromagnetic wave propagation direction, it enhances the dielectric and magnetic properties of the composites. Meanwhile, when bar-shaped nanoparticles are aligned in the polymer in the direction parallel to the electromagnetic wave propagation direction, the dielectric and magnetic properties of the composites are enhanced least.

17.3.3

More Result Displays of the Randomly Distributed Nanoparticle Model

The randomly distributed particle models were built based on the Monte Carlo method. In order to better understand the detailed electric and magnetic fields and the interactions between the particles in the matrix, more result display options can be adopted. Figures 17.10 and 17.11 show the magnetic field and magnetic flux and the interaction between Ni0.5Zn0.5 Fe2O4 ferrite magnetic nanoparticles in an epoxy matrix. The display options include: (1) Cut-out 3D view (Figure 17.10(b) and (c) – portioned 3D unit cell), in which field distributions on surface and partial cross-sectional areas in three perpendicular planes can be displayed in a single plot; (2) particle only 3D view (Figure 17.11(a)), in which how the particles interact with each other

Figure 17.10

Magnetic field (Oe) and magnetic flux (T) distributions of a randomly distributed spherical nanoparticle model.

446

Figure 17.11

Chapter 17

Magnetic flux (T) distributions of randomly distributed spherical and cubic nanoparticle models.

can be clearly displayed in a 3D view. We can see that one particle produces a magnetic field that affects the other particle only on the surface of the particle, it does not significantly affect the inside of the particle; and (3) cross-sectional multiple 2D view (Figure 17.11(b) and (c)), in which the field distributions in three perpendicular cross-sectional planes can be displayed in a single plot. Both contours of magnetic field and magnetic flux look similar outside the nanoparticles but different inside the nanoparticles.

17.4 Conclusion Computer modeling based on finite element analysis was used to characterize the magnetic and dielectric properties of the epoxy matrix nanocomposites dispersed by spinel structured nickel zinc ferrite (Ni0.5Zn0.5Fe2O4) nanoparticles. The effective permittivity and permeability of the nanocomposites were extracted from the modeling data. The effects of the concentration, shape, orientation, and distribution of the nanoparticles on the effective permittivity and permeability of the nanocomposites were systematically investigated by computer modeling. No significant effect of the shapes (cube, sphere) and distributions (simple cubic, body-centered cubic, face-centered cubic, and random distributions) of the nanoparticles was found on the permittivity and permeability of the nanocomposites, and the permittivity and the permeability of the nanocomposites increase as the concentration (volume fraction) of the nanoparticles increases. However, computer modeling has revealed that the bar-shaped particles aligned with the applied field can significantly enhance the permittivity and permeability of the nanocomposites. The effective relative permittivity and permeability of the nanocomposites predicted by the numerical method are in good agreement with the predictions from the analytical methods (Maxwell–Garnett rule and Bruggeman rule),

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except the bar-shaped particle cases. Computer modeling can be applied to quantitatively predict the electromagnetic properties of nanocomposites to help design nanocomposites with the desired properties.

Acknowledgements The authors gratefully acknowledge generous support from the Composite and Nanocomposite Advanced Manufacturing Center (CNAM) (Grant number SA1800366), a South Dakota governor’s center. Also acknowledged is the Department of Mechanical Engineering at South Dakota State University and the computational facility support from University High Performance Computing at South Dakota State University.

References 1. C. M. Hussain, Magnetic Nanomaterials for Environmental Analysis, ed. C. M. Hussain and B. Kharisov, Advanced Environmental Analysisapplication of Nanomaterials, The Royal Society of Chemistry, 2017. 2. D. Sharma and C. M. Hussain, Smart nanomaterials in pharmaceutical analysis, Arabian J. Chem., 2020, 13(1), 3319–3343. 3. R. Keçili and C. M. Hussain, Recent progress of imprinted nanomaterials in analytical chemistry, Int. J. Anal. Chem., 2018, 2018, 8503853. ¨yu ¨ktiryaki and C. M. Hussain, Advancement in bioanaly4. R. Keçili, S. Bu tical science through nanotechnology: Past, present and future, TrAC, Trends Anal. Chem., 2019, 110, 259–276. ¨yu ¨ktiryaki, Y. Su ¨mbelli, S. Bu ¨yu ¨ktiryaki, R. Keçili and C. M. 5. S. Bu Hussain, Lab-On-Chip Platforms for Environmental Analysis, ´, Encyclopedia of ed. P. Worsfold, C. Poole, A. Townshend and M. Miro Analytical Science, 3rd edn, 2019, Academic Press, pp. 267–273. 6. J. Sengupta and C. M. Hussain, Graphene and its derivatives for Analytical Lab on Chip platforms, TrAC, Trends Anal. Chem., 2019, 114, 326–337. 7. C. M. Hussain, Nanomaterials in Chromatography: Current Trends in Chromatographic Research Technology and Techniques, Elsevier, 2018. 8. C. M. Hussain and R. Keçili, Modern Environmental Analysis Techniques for Pollutants, 1st edn, 2019, Elsevier. 9. C. M. Hussain, Handbook of Nanomaterials in Analytical Chemistry: Modern Trends in Analysis, Elsevier, 2019. ¨yu ¨ktiryaki, R. Keçili and C. M. Hussain, Functionalized nanoma10. S. Bu terials in dispersive solid phase extraction: Advances & prospects, TrAC, Trends Anal. Chem., 2020, 127, 115893. 11. C. M. Hussain, Handbook on Miniaturization in Analytical Chemistry: Application of Nanotechnology, Elsevier, 2020. 12. S. Gul, S. B. Khan, I. U. Rehman, M. A. Khan and M. I. Khan, A comprehensive review of magnetic nanomaterials modern day theranostics, Front. Mater., 2019, 6, 1–15.

448

Chapter 17

13. H. Lai, F. Xu and L. Wang, A review of the preparation and application of magnetic nanoparticles for surface-enhanced Raman scattering, J. Mater. Sci., 2018, 53, 8677–8698. 14. L. Mohammed, H. G. Gomaa, D. Ragab and J. Zhu, Magnetic nanoparticles for environmental and biomedical applications: A review, Particuology, 2017, 30, 1–14. 15. H. Shokrollahi, A review of the magnetic properties, synthesis methods and applications of maghemite, J. Mag. Magn. Mater., 2017, 426, 74–81. 16. J. S. Colburn and Y. Rahmat-Samii, Patch antennas on externally perforated high dielectric constant substrates, IEEE Trans. Antennas Propag., 1999, 47, 1785–1794. 17. H. Mosallaei and K. Sarabandi, Magneto-dielectrics in electromagnetics: concept and applications, IEEE Trans. Antennas Propag., 2004, 52(6), 1558–1567. 18. W. H. von Aulock, Handbook of Microwave Ferrite Materials, Academic Press, New York, NY, USA, 1965. 19. Y. Naito and K. Suetake, Application of ferrite to electromagnetic wave absorber and its characteristics, IEEE Trans. Microwave Theory Tech., 1971, 19(1), 65–72. 20. A. Okamoto, The invention of ferrites and their contribution to the miniaturization of radios, in 2009 IEEE Globecom Workshops, Honolulu, Hawaii, USA, 2009, pp. 1–42. 21. S. E. Shirsath, B. G. Toksha, R. H. Kadam, S. M. Patange, D. R. Mane, G. S. Jangam and A. Ghasemi, Doping effect of Mn21 on the magnetic behavior in Ni-Zn ferrite nanoparticles prepared by sol-gel autocombustion, J. Phys. Chem. Solids, 2010, 71, 1669–1675. 22. C. B. Carter and M. G. Norton, Ceramic Materials: Science and Engineering, 2nd edn, 2013, Springer, New York, NY, pp. 617–640. 23. Y. Jiang, M. Opoku, Z. Hu, M. Liu, H. Hong, J. A. Puszynski and X. Yan, Synthesis and characterization of spinel ferrite based nanofluids, J. Nanofluids, 2015, 4(2), 133–139. 24. S. S. Kim, S. B. Jo, K. I. Gueon, K. K. Choi, J. M. Kim and K. S. Chum, Complex permeability and permittivity and microwave absorption of ferrite-rubber composition in X-band frequencies, IEEE Trans. Magn., 1991, 27(6), 5462–5464. 25. D. Y. Kim, Y. C. Chung, T. W. Kang and H. C. Kim, Dependence of microwave absorbing property on ferrite volume fraction in MnZn ferrite-rubber composites, IEEE Trans. Magn., 1996, 32(2), 555–558. 26. P. Singh, V. K. Babbar, A. Razdan, R. K. Puri and T. C. Goel, Complex permittivity, permeability, and X-band microwave absorption of CaCoTi ferrite composites, J. Appl. Phys., 2000, 87(9), 4362–4366. 27. M. R. Anantharaman, K. A. Malini, S. Sindhu, E. M. Mohammed, S. K. Date, S. D. Kulkarni, P. A. Joy and P. Kurian, Tailoring magnetic and dielectric properties of rubber ferrite composites containing mixed ferrites, Bull. Mater. Sci., 2001, 24(6), 623–631.

Polymeric Composites by Computer Modeling

449

28. S. T. Chui and L. Hu, Theoretical investigation on the possibility of preparing left-handed materials in metallic magnetic granular composites, Phys. Rev. B, 2002, 65(14), 144407. 29. E. Ozbay, K. Aydin, E. Cubukcu and M. Bayindir, Transmission and reflection properties of composite double negative metamaterials in free space, IEEE Trans. Antennas Propag., 2003, 51(10), 2592–2595. 30. N. E. Kazantseva, N. G. Ryvkina and I. A. Chmutin, Promising materials for microwave absorbers, J. Commun. Technol. Electron., 2003, 48(2), 173–184. 31. C. H. Peng, H. W. Wang, S. W. Kan, M. Z. Shen, Y. M. Wei and S. Y. Chen, Microwave absorbing materials using Ag-NiZn ferrite coreshell nanopowders as fillers, J. Magn. Magn. Mater., 2004, 284, 113–119. 32. Y. J. Chen, M. S. Cao, T. H. Wang and Q. Wan, Microwave absorption properties of the ZnO nanowire-polyester composites, Appl. Phys. Lett., 2004, 84(17), 3367–3369. 33. J. L. Wilson, Synthesis and Magnetic Properties of Polymer Nanocomposites, Ph.D. Thesis, University of South Florida, Tampa, FL, USA, 2004. 34. M. R. Bockstaller, R. A. Mickiewicz and E. L. Thomas, Block copolymer nanocomposites: perspectives for tailored functional materials, Adv. Mater., 2005, 17(11), 1331–1349. 35. A. Buerkle and K. Sarabandi, A wide-Band, circularly polarized, magnetodielectric resonator antenna, IEEE Trans. Antennas Propag., 2005, 53(11), 3436–3442. 36. K. M. Lim, K. A. Lee, M. C. Kim and C. G. Park, Complex permeability and electromagnetic wave absorption properties of amorphous alloyepoxy composites, J. Non-crystal. Solids, 2005, 351(1), 75–83. ¨ . Yavuz, M. K. Ram, M. Aldissi, P. Poddar and S. Hariharan, Synthesis 37. O and the physical properties of MnZn ferrite and NiMnZn ferritepolyaniline nanocomposite particles, J. Mater. Chem., 2005, 15, 810–817. 38. S. Sindhu, S. Jegadesan, A. Parthiban and S. Valiyaveettil, Synthesis and characterization of ferrite nanocomposite spheres from hydroxylated polymers, J. Magn. Magn. Mater., 2006, 296, 104–113. 39. T. I. Yang, Low Loss Polymer Nanoparticle Composites for Radio Frequency Applications, Ph.D. Thesis, University of Maryland, College Park, MD, USA, 2008. 40. T. Sebastian, Magneto-Dielectric Wire Antennas: Theory and Design, Ph.D. Thesis, Arizona State University, Tempe, AZ, USA, 2013. 41. K. Han, M. Swaninathan, P. M. Raj, H. Sharma, R. Tummala, B. Rawlings, S. Yang, and V. Nair, Synthesis of magneto-dielectrics from first principles and antenna design, in Electronic Components and Technology Conference (ECTC), 2015 IEEE 65th, May 26–29, 2015. 42. K. Han, Magneto-Dielectric Material Characterization and RF Antenna Design, Ph.D. Thesis, Georgia Institute of Technology, Atlanta, GA, USA, 2015. 43. K. Han, M. Swaninathan, R. Pulugurtha, H. Sharma, R. Tummala, S. Yang and V. Nair, Magneto-dielectric nanocomposite for antenna

450

44. 45.

46. 47.

48. 49.

50.

51.

52. 53.

54.

55.

56.

57. 58. 59.

60.

Chapter 17

miniaturization and SAR reduction, IEEE Antenna Wireless Propag. Lett., 2016, 15, 72–75. A. C. Razzitte, W. G. Fano and S. E. Jacobo, Electrical permittivity of Ni and NiZn ferrite-polymer composites, Phys. B, 2004, 354, 228–231. P. S. Neelakanta, Handbook of Electromagnetic Materials: Monolithic and Composite Versions and Their Applications, CRC Press, Boca Raton, 1995, p. 133. R. H. Kodama, Magnetic nanoparticles, J. Magn. Magn. Mater., 1999, 200, 359–372. E. Tuncer, Y. V. Serdyuk and S. M. Gubanski, Dielectric mixtures: electrical properties and modelling, IEEE Trans. Dielectr. Electr. Insulat., 2002, 9(5), 809–828. X. Batlle and A. Labarta, Finite-size effects in fine particles: magnetic and transport properties, J. Phys. D: Appl. Phys., 2002, 35(6), R15–R42. M. A. Willard, L. K. Kurihara, E. E. Carpenter, S. Calvin and V. G. Harris, Chemically prepared magnetic nanoparticles, Int. Mater. Rev., 2004, 49(3–4), 125–170. T. I. Yang, R. N. G. Brown, L. C. Kempel and P. Kofinas, Magnetodielectric properties of polymer-Fe3O4 nanocomposites, J. Magn. Magn. Mater., 2008, 320, 2714–2720. M. G. H. Zaidi, P. L. Sah, S. Alam and A. K. Rai, Synthesis of epoxy ferrite nanocomposites in supercritical carbon dioxide, J. Exp. Nanosci., 2009, 4(1), 55–66. ´, Polymer-nanoparticle composites: from T. Hanenann and D. V. Szabo synthesis to modern applications, Materials, 2010, 3, 3468–3517. S. H. Hosseini, R. Rahimi and H. Kerdari, Preparation of a nanocomposite of magnetic, conducting nanoporous polyaniline and hollow manganese ferrite, Polym. J., 2011, 43, 745–750. R. Skomski, B. Balamurugan, E. Schubert, A. Enders and D. J. Sellmyer, Length scales of interactions in magnetic, dielectric, and mechanical nanocomposites, Mater. Res. Soc. Symp. Proc., 2011, 1312, 171–182. C. Sirisathitkul, P. Jantaratana and N. Muensit, Dielectric and magnetic properties of polyvinylidene fluoride polymer composites high loaded with nickel, Sci. Eng. Compos. Mater., 2012, 19(3), 255–258. ´n, A. Tamion, F. Tournus, V. Dupuis and M. Hillenkamp, Size S. Oyarzu effects in the magnetic anisotropy of embedded cobalt nanoparticles: from shape to surface, Sci. Rep., 2015, 5, 14749. S. Forster and M. Antonietti, Amphiphilic block copolymers in structurecontrolled nanomaterial hybrids, Adv. Mater., 1998, 10(3), 195–217. C. Park, J. Yoon and E. L. Thomas, Enabling nanotechnology with self assembled block copolymer patterns, Polymer, 2003, 44, 6725–6760. J. B. Chang, H. K. Choi, A. F. Hannon, A. Alexander-Katz, C. A. Ross and K. K. Berggren, Design rules for self-assembled block copolymer patterns using tiled templates, Nat. Commun., 2014, 5, 3305. V. Mittal, Characterization Techniques for Polymer Nanocomposites, Wiley, 2012.

Polymeric Composites by Computer Modeling

451

61. S. Mourdikoudis, R. M. Pallares and N. T. K. Thanh, Characterization techniques for nanoparticles: comparison and complementarity upon studying nanoparticle properties, Nanoscale, 2018, 10, 12871–12934. 62. S. E. Sandler, B. Fellows and O. T. Mefford, Best practices for characterization of magnetic nanoparticles for biomedical applications, Anal. Chem., 2019, 91, 14159–14169. ¨sslein and A. Prina-Mello, 63. F. Caputo, J. Clogston, L. Calzolai, M. Ro Measuring particle size distrution of nanoparticle enabled medicinal products, the joint view of EUNCL and NCI-NCL. A step by step approach combining orthogonal measurements with increasing complexity, J. Controlled Release, 2019, 299, 31–43. 64. A. Kim, W. B. Ng, W. Bernt and N. J. Cho, Validation of size estimation of nanoparticle tracking analysis on polydisperse macromolecule assembly, Sci. Rep., 2019, 9, 2639. 65. D. A. Winkler, Computational modelling of magnetic nanoparticle properties and in vivo responses, Curr. Med. Chem., 2017, 24(5), 483–496. 66. I. Raouf, S. Khalid, A. Khan, J. Lee, H. S. Kim and M.-H. Kim, A review on numerical modeling for magnetic nanoparticle hyperthermia: progress and challenges, J. Therm. Biol., 2020, 91, 102644. 67. Z. Hu, J. Kanagaraj, H. Hong, K. Yang, X. Ji, Q. H. Fan and P. Kharel, Characterization of ferrite magnetic nanoparticle modified polymeric composites by modeling, J. Magn. Magn. Mater., 2020, 493, 165735. 68. J. Kanagaraj, Electro-magnetic Responsive Ni0.5Zn0.5Fe2O4 Nano-particle Composite, Master’s thesis, South Dakota State University, USA, 2018. 69. C.-W. Liu, M.-H. Liu, C.-C. Tai, B.-C. Kuo, C.-L. Chen and H.-Z. Shen, Computer simulation to investigate magnetic and wave absorbing characteristics of iron nanoparticles, J. Chin. Chem. Soc., 2020, 67(1), 25–32. 70. T. Bora, A. Dousse, K. Sharma, K. Sarma, A. Baev, G. L. Hornyak and G. Dasgupta, Modeling nanomaterial physical properties: theory and simulation, Int. J. Smart Nano Mat., 2019, 10(2), 116–143. 71. P. H. C. Camargo, K. G. Satyanarayana and F. Wypych, Nanocomposites: synthesis, structure, properties and new application opportunities, Mater. Res., 2009, 12(1), 1–39. 72. Hybrid and Hierarchical Composite Materials, ed. C. S. Kim, C. Randow and T. Sano, Springer, 2015, pp. 11–20. 73. W. Song, Z. Sun, D. Zhang, B. Han, L. He, X. Wang and Q. Lei, Synthesis and characterization of low density polyethylene with multiferroic bismuth ferrite nanocomposite, J. Mater. Sci: Mater. Electron., 2016, 27, 2328–2334. 74. A. Teber, K. Cil, T. Yilmaz, B. Eraslan, D. Uysal, G. Surucu, A. H. Baykal and R. Bansal, Manganese and zinc spinel ferrites blended with multiwalled carbon nanotubes as microwave absorbing materials, Aerospace, 2017, 4(1), 2. 75. W. R. Smythe, Static and Dynamic Electricity, McGraw-Hill Book Co., New York, NY, 1950.

452

Chapter 17

76. K. Rohlfs and T. L. Wilson, Tools of Radio Astronomy, 4th rev. and enl. edn, 2004, Springer, New York, NY, USA. 77. J. Monecke, Microstructure dependence of material properties of composites, Phys. Status Solidi (B), 1989, 154(2), 805–813. ´nhegyi, Comparison of electrical mixture rules for composites, 78. G. Ba Colloid. Polym. Sci., 1986, 264(12), 1030–1050. 79. B. Hallouet, B. Wetzel and R. Pelster, On the dielectric and magnetic properties of nanocomposites, J. Nanomater., 2007, 2007, 34527. 80. B. Hallouet and R. Pelster, 3D-simulation of topology-induced changes of effective permeability and permittivity in composite materials, J. Nanomater., 2007, 2007, 80814. 81. D. R. McKenzie, R. C. McPhedran and G. H. Derrick, The conductivity of lattices of spheres. II. The body centred and face centred cubic lattices, Proc. R. Soc. Lond. Ser. A, 1978, 362(1709), 211–232. 82. N. Harfield, Conductivity of a periodic particle composite with spheroidal inclusions, Eur. Phys. J.: Appl. Phys., 1999, 6(1), 13–21. 83. N. Harfield, Bulk permittivity of a composite with coated spheroidal filler particles, J. Mater. Sci., 2000, 35(23), 5809–5816. 84. O. Levy and D. Stroud, Maxwell Garnett theory for mixtures of anisotropic inclusions: application to conducting polymers, Phys. Rev. B, 1997, 56(13), 8035. 85. D. A. G. Bruggeman, Berechnung verschiedener physikalischer kon¨tskonstanten und stanten von heterogenen substanzen, i. dielektrizita ¨higkeiten der mischko ¨rper aus isotropen substanzen, Ann. Phys, leitfa 1935, 636–664. ¨lzle, A. Enders and G. Nimtz, Numerical simulation of random 86. S. Sto composite dielectrics, J. Phys. I, 1992, 2, 401–408. ¨lzle, A. Enders and G. Nimtz, Numerical simulation of random 87. S. Sto composite dielectrics. II. Simulations including dissipation, J. Phys. I, 1992, 2, 1765–1777. 88. H. Leinders and A. Enders, Computer simulations of dielectric and magnetic composite media including dissipation, J. Phys. I, 1995, 5, 555–564. 89. C. Brosseau and A. Beroual, Dielectric properties of periodic heterostructures: a computational electrostatics approach, Eur. Phys. J. Appl. Phys., 1999, 6, 23–31. 90. F. Wu and K. W. Whites, Quasi-static effective permittivity of periodic composites containing complex shaped dielectric particles, IEEE Trans. Antennas Propag., 2001, 49(8), 1174–1182. 91. A. Spanoudaki and R. Pelster, Effective dielectric properties of composite materials: the dependence on the particle size distribution, Phys. Rev. B, 2001, 64(6), 064205. 92. E. Tuncer, On complex permittivity of dilute random binary dielectric mixtures in two-dimensions, Turkish J. Phys., 2003, 27(2), 101–105. 93. E. Tuncer, B. Nettelblad and S. M. Gubanski, Non-Debye dielectric relaxation in binary dielectric mixtures (50–50): randomness and regularity in mixture topology, J. Appl. Phys., 2002, 92(8), 4612–4624.

Polymeric Composites by Computer Modeling

453

94. C. Brosseau and A. Beroual, Computational electromagnetics and the rational design of new dielectric heterostructures, Prog. Mater Sci., 2003, 48(5), 373–456. 95. V. Myroshnychenko and C. Brosseau, Finite-element method for calculation of the effective permittivity of random inhomogeneous media, Phys. Rev. E, 2005, 71(1), 016701. 96. ANSYS Inc., ANSYS 19.2 User’s Manual, 2019. 97. C. H. Peng, C. C. Hwang, J. Wan, J. S. Tsai and S. Y. Chen, Microwaveabsorbing characteristics for the composites of thermal-plastic polyurethane (TPU)-bonded NiZn-ferrites prepared by combustion synthesis method, Mater. Sci. Eng.: B, 2005, 117(1), 27–36. 98. A. Thakur, P. Kumar, P. Thakur, K. Rana, A. Chevalier, J. L. Mattei and ´lec, Enhancement of magnetic properties of Ni0.5Zn0.5Fe2O4 P. Queffe nanoparticles prepared by the co-precipitation method, Ceram. Int., 2016, 42(9), 10664–10670. 99. S. A. Saafan, T. M. Meaz and E. H. El-Ghazzawy, Study of DC conductivity and relative magnetic permeability of nanoparticle NiZnFe2O4/PPy composites, J. Magn. Magn. Mater., 2011, 323(11), 1517–1524. 100. Master Bond Inc., Evaluating Electrically Insulating Epoxies, Hackensack, NJ, USA. http://www.adhesives.org/docs/pdfs/electrically_insulative_ epoxies.pdf?sfvrsn=0. 101. H. Lee and K. Neville, Handbook of Epoxy Resins, McGraw-Hill Inc., New York, NY, USA, 1967. 102. R. Guo, J. I. Roscow, C. R. Bowen, H. Luo, Y. Huang, Y. Ma, K. Zhou and D. Zhang, Significantly enhanced permittivity and energy density in dielectric composites with aligned BaTiO3 lamellar structures, J. Mater. Chem. A, 2020, 8(6), 3135–3144. 103. Y. Wang, Processing and Properties of Polymer-based Composites for Metamaterials Applications, Ph.D. thesis, University of Oxford, 2015. 104. M. Matsumoto and Y. Miyata, Thin electromagnetic wave absorber for quasi-microwave band containing aligned thin magnetic metal particles, IEEE Trans. Magn., 1997, 33(6), 4459–4464. 105. X. Zhang, T. Ekiert, K. M. Unruh and Q. Xiao, High frequency properties of polymer composites consisting of aligned Fe flakes, J. Appl. Phys., 2006, 99, 08M914.

CHAPTER 18

Functionalized Magnetic Nanoparticle-based Sensors for Point-of-care Applications: From the Preparation to Practical Applications AHMET ULU AND BURHAN ATES* Department of Chemistry, Faculty of Arts and Science, Inonu University, Malatya, Turkey *Email: [email protected]

18.1 Introduction There is no doubt that nanotechnology has had an important place in scientific and technological studies in recent years, and researchers have focused intensively on nanomaterials for various applications.1,2 Among the various nanomaterials, magnetic nanoparticles (MNPs) have attracted great interest since they have excellent advantages such as extremely small size, excellent magnetic behavior, large surface area/volume ratio, ability of surface modification, and high biocompatibility.3–5 Besides, they have been easily prepared and easily separated. MNPs have been commonly utilized in many different approaches including drug delivery,6 enzyme immobilization,7–13 catalysts,14 sensors,15,16 adsorbents,17 water/wastewater treatment,18–21 membrane,22 extraction,23 semiconductors,24 storage devices,25 separation,26 and magnetic resonance imaging,27 etc.28 Analytical Applications of Functionalized Magnetic Nanoparticles Edited by Chaudhery Mustansar Hussain r The Royal Society of Chemistry 2021 Published by the Royal Society of Chemistry, www.rsc.org

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Functionalized Magnetic Nanoparticle-based Sensors for Point-of-care Applications 455

MNPs meet an important demand in sensor applications since they provide accurate, sensitive, and selective determination of various analytes. Especially, easy surface functionalization of MNPs in sensor applications makes them attractive.29 Functionalized magnetic nanoparticles (fMNPs) have recently been investigated as appropriate platforms for sensing applications.30 These superior nanomaterials can be designed systematically via a combination of suitable functional components to provide useful properties of hybrid materials. fMNPbased sensors have been fabricated to detect various targets in both environmental (water, wastewater, extraction, etc.) and biological samples (blood, urine, tear, etc.). For instance, Hassen et al.31 developed an impedimetric DNA sensor based on fMNPs to detect HIV and HBV. They used streptavidin to functionalize MNPs. In another work, Rosa–Romo et al.32 prepared a flavone fMNP-based novel fluorescent sensor to determine Cu(II) ions. The suggested sensor exhibited ultra-sensitivity in sensing Cu(II) ions with a low detection limit (7.5 nM). Similarly, quercetin-functionalized MNP sensors for the determination and removal of Pb21 and Cu21 in biological samples were designed by Jiang et al.33 In addition, fhenylboronic acid-functionalized MNPs for the electrochemical determination of glycoproteins,34 amino-functionalized carbon coated MNPs for the determination of nucleic acid hybridization,35 fluorophore-modified MNPs to measure the level of heavy metal ions in water,36 and b-cyclodextrinconjugated MNPs for the determination of chlorpheniramine maleate, pseudoephedrine hydrochloride37 and tryptophan38 were reported. The quantitative measurement of different biological marker or biochemical assays in biospecimens is usually performed in central laboratories by using routine diagnostic tests. However, the results are accessible after a few hours or sometimes days.39 Point-of-care (PoC) testing technology is attractive compared to routine central laboratory tests due to advantages such as low volume samples, fast turn-around times, small form factors, and less use of reagents.39,40 Therefore, PoC has been successfully applied and commercialized to diagnose and monitor disease in hospital emergency departments.39 Recent works clearly indicated that nanomaterials display various superiorities when incorporated in a PoC device.40 The samples, targets, and typical component technologies for fully integrated mobile and wearable PoC platforms are listed in Table 18.1. This chapter is critical in order to declare current developments in this area and provide a light to researchers. Firstly, the preparation methods of MNPs and their functionalization is reviewed. Then, PoC applications are briefly introduced. After that, recent progress on fMNP-based sensors for PoC applications is intensively discussed. Finally, the conclusions section is presented.

18.2 Preparation and Functionalization of MNPs 18.2.1

Preparation of MNPs

In the preparation of MNPs, it is very important to reach narrow-sized distribution, shape-control, and high stability.41 Therefore, until now,

Summary of samples, targets, and typical component technologies for fully integrated mobile and wearable PoC systems. Reproduced from ref. 39 with permission from the Royal Society of Chemistry.

Technology Form factor

Sample handling platforms

Analyte

Body fluid sample

 Lateral flow assay  Microfluidicsbased

      

Metabolites Ions Nucleic acids Proteins Hormones Bacteria Viruses

 Sweat  Capillary blood  Interstitial fluid (ISF)  Wound exudate  Saliva  Tears  Urine

      

 Microfluidicsbased

      

Metabolites Ions Nucleic acids Proteins Hormones Bacteria Viruses

     

Wearable PoC

Band Patch Watch Eyeglasses Tattoo Bandage Wound dressing  Mouthguard  Contact lens

Sweat Capillary blood ISF Wound exudate Saliva Tears

 Exercise/absorption pad Iontophoresis/absorption pad Swabbing  Finger prick  Heel prick  Microneedle  Microdialysis  Reverse iontophoresis Microneedle  Swabbing  Microcapillary  Absorption pad  Spitting  Suction  Swabbing  Microcapillary tube  Absorption  Passive collection  Exercise/absorption pad  Iontophoresis/ absorption pad  Microneedle  Reverse iontophoresis/ absorption pad  Microneedle/capillary layer  Absorption pad  Direct contact  Direct contact

Signal transduction Optical: Colorimetry Fluorescence Electroluminescence Chemiluminescence Biochemiluminescence Surface plasmon resonance (SPR) Electrochemical: Impedimetry Amperometry Voltammetry Potentiometry

Optical: Colorimetry Electrochemical: Impedimetry Amperometry Voltammetry Potentiometry

Chapter 18

Mobile PoC Standalone Smartphoneintegrated

Sampling methods (inducing/ collecting)

456

Table 18.1

Functionalized Magnetic Nanoparticle-based Sensors for Point-of-care Applications 457 Table 18.2

The advantages and disadvantages of the preparation techniques of MNPs. Reproduced from ref. 89, https://doi.org/10.3390/nano8100810, under the terms of the CC BY 4.0 license, https://creativecommons.org/ licenses/by/4.0/.

Preparation technique Advantages Co-precipitation Hydrothermal Thermal decomposition Microemulsion Sol–gel reactions Aerosol/vapor phase Electrochemical

Disadvantages

Simple and efficient

Size distribution, poor crystallinity and aggregation Easy to control particle Long reaction time, high reaction size and shape temperature, high pressure Good control of size and High reaction temperature shape, high yield Control of particle size, Poor yield, large amounts of solvent highly homogeneous required and time consuming Precise control of size Relatively expensive, long reaction and structure time High yield Extremely high temperatures Easy control of size Reproducibility

researchers have reported various popular techniques to produce MNPs including coprecipitation,8 green synthesis,42 thermal decomposition,43 microemulsion,44 sonochemical,45 microwave-assisted,46 solvothermal,47 chemical vapor deposition,48 combustion synthesis,49 carbon arc,50 and laser pyrolysis synthesis.51 Table 18.2 shows the advantages and disadvantages of some preparation techniques of MNPs.

18.2.1.1

Co-precipitation

Co-precipitation is commonly used because it is the simplest method.52 The method involves mixing ferric and ferrous ions in an inert atmosphere at a molar ratio of 1 : 2 with the incorporation of an alkali at room temperature or higher.53 Thanks to this method, large amounts of particles can be obtained.54 This method is easier to apply than other methods, and also less harmful materials and processes are needed.55 Several authors synthesized MNPs via co-precipitation. For instance, Zarnegar and Safari56 synthesized MNPs by coprecipitation in the presence of poly (citric acid) (PCA)–poly (ethylene glycol) (PEG)–PCA as a stabilizer (Figure 18.1) and characterized through field emission scanning electron microscopy (FE-SEM), transmission electron microscopy (TEM), energy-dispersive X-ray spectroscopy (EDX), Fourier-transform infrared spectroscopy (FTIR), vibrating sample magnetometer (VSM), and X-ray diffraction (XRD). Consequently, the authors reported that uniform, nearly spherical, high purity, and ultrafine, MNPs exhibiting better magnetic behavior with a diameter of 5–10 nm could be prepared in the presence of a copolymer. Similarly, Rashid et al.57 synthesized MNPs by using an in situ precipitation method and characterized them via various techniques including FTIR, XRD, TEM, VSM, EDX, and Raman spectroscopy (RS). Besides, the zeta

458

Figure 18.1

Chapter 18

The synthesis scheme of MNPs in the presence of PCA–PEG–PCA copolymer. Reproduced from ref. 56, https://doi.org/10.1080/17518253.2017.1358769, under the terms of the CC BY 4.0 license, https://creativecommons.org/ licenses/by/4.0/.

potential and hydrodynamic diameter of the MNPs were measured. The characterization results revealed that the synthesized MNPs demonstrated a spherical morphology and have a very narrow range of particle size (9–15 nm). Magnetization saturation and zeta potential values of these MNPs were found to be 41.8 mV, and 74.615 emu, respectively.

18.2.1.2

Hydrothermal

Hydrothermal (solvothermal) synthesis involves several wet-chemical methods of crystallizing the substance in a sealed container from the high temperature aqueous or non-aqueous solution high vapor pressure.58 Besides, the hydrothermal strategy is utilized for growing dislocation-free single crystal particles, and the particles may have a better crystallinity than particles produced by other methods. Therefore, this method is prone to obtaining highly crystalline iron oxide MNPs.53 MNPs obtained by this technique were reported by several authors. For example, Kumar and co-workers59 examined the effect of different temperatures (120–180 1C for 16 hours) on synthesized PEG-400-coated Fe3O4 MNPs by using a hydrothermal synthesis method (Figure 18.2). XRD findings demonstrated that the fabricated MNPs at 160 and 180 1C displayed a singlephase cubic magnetite structure with high crystallinity, whereas the fabricated MNPs at 120 and 140 1C displayed a mixed-phase structure (a-Fe2O3 and Fe3O4). Also, the coercivity and saturation magnetization of MNPs improved in parallel with the reaction temperature. In a research study by Xiwen et al.,60 Fe3O4 MNPs were synthesized via a hydrothermal method using ferric acetylacetonate as the sole iron source, and poly (acrylic acid) as the stabilizer. The research team performed optimization of the experimental factors including the solvent, the amount of stabilizer, the pre-synthesis, and the reaction time. The synthesized MNPs had a uniform size between about 50–100 nm and were highly water dispersible. Also, the MNPs exhibited excellent magnetic properties such as 76.76% magnetite content and 39.0 emu g1 saturation magnetization.

Functionalized Magnetic Nanoparticle-based Sensors for Point-of-care Applications 459

Figure 18.2

Schematic illustration of the synthesis of PEG-400-coated Fe3O4 MNPs by using a hydrothermal method at different reaction temperatures. Reproduced from ref. 59 with permission from the Royal Society of Chemistry.

18.2.1.3

Thermal Decomposition

Despite the rapid formation of particles in the co-precipitation method, particle size and size distribution are difficult to control. To overcome these limitations, an anhydrous thermal decomposition strategy has been developed as an alternative to the co-precipitation method. In this method, the decomposition of iron precursors in the presence of hot organic surfactants allows one to obtain higher monodisperse, highly crystalline, and narrow size distribution MNPs.52,53,55 Researchers have reported the synthesis of MNPs by using a thermal de´nchez et al.61 performed the synthesis composition method. For instance, Sa of MnxGa1xFe2O4 MNPs via thermal decomposition via tetraethylene glycol as a reaction solvent. The obtained MNPs were verified by using various techniques such as XRD, VSM, TEM, etc. The MNPs obtained exhibited a spherical shape and the average particle diameter was about 5.6  1.5 nm. Besides, they exhibited superparamagnetic behavior and the magnetization values of the samples increased because of the Mn21 ion incorporation into the FeGa2O4 structure. In another work, methoxy polyethylene glycol (MPEG)-1200 and polyethylene glycol (PEG)-1000-coated MNPs via thermal decomposition were synthesized by Cao and co-workers.62 The morphologies, chemical structure,

460

Chapter 18

and phase compositions of the MNPs were confirmed by using TEM, FTIR, and XRD, respectively. In addition, the hydrodynamic size, zeta potential values and magnetic properties of the MNPs were determined. As a result, the work team reported that the negatively charged MNPs with small hydrodynamic diameter showed a longer time of dispersion in water than the MNPs produced by using PEG-1000 and the MNPs displayed superparamagnetic behavior at 300 K.

18.2.1.4

Microemulsion

The microemulsion process can be explained as the thermodynamically stable isotropic distribution of two immiscible water and oil phases under a surfactant. The reason for using surfactants is that they can form a monolayer at the interface between oil and water, thanks to hydrophilic head groups in the aqueous phase and hydrophobic tails in the oil phase. Compared to other methods, in this method, the size and composition of the particles can be highly controlled.52 Also, the NPs obtained via the microemulsion strategy are smaller in size and have a high saturation magnetization value.58 The synthesis of MNPs with microemulsion was reported in the literature. For instance, Asab et al.63 carried out production of silica-coated MNPs via a microemulsion technique by using hydrated ferric nitrate, ferrous sulfate precursors, ammonia, Tween-80 and sodium dodecyl sulfate (SDS) as the surfactant. The produced MNPs were examined through FTIR, XRD, SEM, and thermal gravimetric analysis (TGA). While the XRD results demonstrated that the produced MNPs were phase pure with a cubic inverse spinel structure, the crystallite size determined from the powder XRD data with Scherer’s equation was in the range of 7.3  0.05–10.83  0.02 nm and 16  0.14 nm for uncoated Fe3O4 and silica-coated Fe3O4 MNPs, respectively. Lu et al.64 performed an ultra-fast microwave-assisted reverse microemulsion method for the synthesis of Fe3O4@SiO2 core–shell NPs. The prepared NPs were confirmed using FTIR, TEM, XRD, TGA, and dynamic light scattering (DLS). According to the results, Fe3O4@SiO2 core–shell NPs displayed a very thin SiO2 coating layer (2.5 nm) containing single Fe3O4 NPs (8–9 nm).

18.2.1.5

Sol–Gel Method

This technique is based on metal precursors, metalloid element hydrolysis and poly-condensation reactions surrounded by different reactive ligands in order to produce a colloidal system named ‘‘sol’’. The ‘‘sol’’ is then dried by removing the solvent or by chemical reaction that causes the shaping of a liquid phase called ‘‘gel’’.65,66 This method is advantageous because the structure and size of the NPs can be checked via experimental conditions.67 This method is not very ideal for application of magnetic resonance imaging (MRI) contrast agents because it has low stability aqueous solutions, but it offers potential applications especially in the treatment of tumors (hyperthermia) by heating.65,68,69

Functionalized Magnetic Nanoparticle-based Sensors for Point-of-care Applications 461

In the literature, there are MNPs synthesized using the sol–gel method. Ziarani et al.70 synthesized SrFe12O19 MNPs via a sol–gel auto-combustion technique and confirmed them using FTIR, XRD, SEM, VSM, and Brunauer– Emmett–Teller (BET) methods. SEM images revealed that the SrFe12O19 MNPs were semi-spherical with an average particle size of 70 nm. Besides, the BET surface and magnetic saturation of SrFe12O19 MNPs were reported as 10.4  0.5 m2 g1 and about 79 emu g1, respectively. Similarly, Lemine et al.71 synthesized Fe3O4 MNPs via a sol–gel technique. Afterwards, the MNPs were verified by different methods including XRD, TEM, FE-SEM, EDX, etc. According to the characterization results, the synthesized MNPs displayed single phase and homogeneous size distribution (B8 nm).

18.2.1.6

Green Synthesis

MNPs, a class of nanomaterials, have been used for many biomedical applications and have been intensively investigated. However, the chemicals used for the synthesis of MNPs cause toxicity or health hazards. Therefore, the development of biocompatible and nature-friendly techniques in the production of MNPs is extremely important. At this point, green nanotechnology has gained tremendous interest since it involves several processes reducing and/or eliminating toxic substances to protect the environment. Green synthesis uses nature-friendly, biocompatible and reliable components in the synthesis of MNPs.52 Until now, MNPs were synthesized by using a plant extract,72,73 marine plant,74 seed,75 leaf,76 fruit peel,77 fruit,78 root,79 stolon,80 waste,81 and gum.82 Ramesh et al.83 suggested a facile and green method to fabricate superparamagnetic MNPs by aqueous leaf extract of Zanthoxylum armatum DC. The green method is illustrated in Figure 18.3. The green synthesized MNPs were analyzed via Ultraviolet (UV)–visible spectroscopy, FTIR, XRD, FE-SEM, TEM, and VSM. While surface micrographs confirmed the spherical shape of MNPs with particle size of 17 nm, XRD and VSM results revealed that the green synthesized MNPs showed a pure Fe3O4 inverse cubic spinel phase and superparamagnetism (128 emu g1). In another investigation, Sathishkumar et al.78 synthesized MNPs from the aqueous fruit extract of edible C. guianensis. The green synthesized MNPs were checked by using various techniques including UV–visible spectroscopy, FTIR, XPS, DLS and zeta potential analysis, XRD, and VSM. The analysis results demonstrated that the green synthesized MNPs had a mean diameter of 17  10 nm and a zeta potential of 26.0 mV.

18.2.2

Functionalization of MNPs

Various approaches have been utilized to functionalize MNPs. In the reported studies, various organic and inorganic compounds have been used to functionalize MNPs for their intended use. We examined these compounds

462

Figure 18.3

Chapter 18

The schematic formation mechanism of superparamagnetic MNPs from an aqueous leaf extract of Zanthoxylum armatum DC. Reproduced from ref. 83, https://doi.org/10.1080/21870764.2018.1459335, under the terms of the CC BY 4.0 license, http://creativecommons.org/ licenses/by/4.0/.

in two parts, namely organic and inorganic. Table 18.3 indicates some organic materials used for the preparation of fMNPs and their applications.

18.2.2.1

Functionalization by Using Organic Materials

18.2.2.1.1 Small Molecules and Surfactants. In order to further extend the application of MNPs, their surfaces have been functionalized with a suitable agent. For this process, the choice of solvent is essential to produce a stable colloidal solution and to obtain sufficient repulsive interactions in order to obstruct agglomeration. Small molecules and surfactants used to functionalize MNPs may be of three different types: oil soluble, water soluble, and amphiphilic.58 Mohtashami et al.84 synthesized galbanic acid-coated Fe3O4 MNPs with improved cytotoxicity against prostate cancer cells. The psychochemical

Some organic materials used for the preparation of fMNPs and their applications.

Small molecules

Surfactants

Natural Polymers

Synthetic Polymers

Preparation technique of MNPs

Organic compound

Application

Reference

Co-precipitation Co-precipitation Co-precipitation Gas-condensation method Co-precipitation Co-precipitation Hydrothermal Co-precipitation Chemical co-precipitation Co-precipitation Co-precipitation — Co-precipitation Co-precipitation Co-precipitation Chemical co-precipitation Solvothermal In situ precipitation Chemical co-precipitation One-pot solvothermal

Galbanic acid Tannic acid N-(phosphonomethyl)iminodiacetic acid L-Lysine Folic acid Oleic acid CPC Perfluoropolyether carboxylic acid Tween 80 CHS ALG CEL b-Cyclodextrin k-carrageenan Chondroitin  sulfate-A Pullulan acetate PEI PVA PVP PEG

Anticancer activity Adsorption MRI agents Cell labeling Drug delivery Catalyst Adsorption — — Enzyme immobilization Adsorption Drug delivery Drug delivery Synthesis Biomedical applications Hyperthermic effect Adsorption Catalyst MRI agents Cancer therapy

84 85 96 97 98 86 87 99 100 91 92 93 101 102 103 104 94 95 105 106

Functionalized Magnetic Nanoparticle-based Sensors for Point-of-care Applications 463

Table 18.3

464

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properties of the synthesized galbanic acid-coated Fe3O4 MNPs were checked through, FTIR, TEM, SEM, DLS, EDX, VSM, and XRD. It was found that the functionalization with galbanic acid of the surface of Fe3O4 MNPs enhanced the solubility and cytotoxicity of these MNPs. Luo et al.85 synthesized tannic acid-functionalized Fe3O4 core–shell NPs to adsorb Pb(II) and Hg(II). The obtained NPs exhibited a high maximum adsorption capacity for Pb(II) up to 1115.3 mg g1 and Hg(II) to 279.4 mg g1. Besides, thermodynamic experiments revealed that the adsorption of Pb(II) and Hg(II) was a spontaneous, chaotic degree decreasing and endothermic process. Zarghani and Batool86 prepared Fe3O4 MNPs through a co-precipitation method in the presence of oleic acid (Figure 18.4) and checked them with various methods. The Fe3O4 MNPs were on average 16 nm in size and had a cubic structure. In addition, the VSM curve indicated that the Fe3O4 MNPs displayed superparamagnetic behavior and good saturation magnetization (54.6 emu g1). Moreover, the Fe3O4 MNPs, in combination with tert-butyl hydroperoxide, catalyzed the oxidation of several benzylic and allylic C–H bonds to the corresponding carbonyl compounds in excellent yield. Guo et al.87 synthesized Fe3O4 MNPs coated with cetylpyridinium chloride (CPC), a cationic surfactant, and used them to adsorb Sb(V) from water. The authors highlighted that Sb(V) removal by the CPC-modified Fe3O4 MNPs was better than that with cetyl trimethyl ammonium bromide (CTAB). Also, they reported that the removal ability of the CPC-modified Fe3O4 MNPs was superior than that of various traditional adsorbents.

Figure 18.4

A schematic diagram for the preparation of Fe3O4 MNPs by using oleic acid as the surfactant. Reproduced from ref. 86 with permission from the Royal Society of Chemistry.

Functionalized Magnetic Nanoparticle-based Sensors for Point-of-care Applications 465

18.2.2.1.2 Natural and Synthetic Polymers. In recent years, the functionalization of MNPs using polymers has been extensively researched because of their widespread application in several research fields, including medicine, biomedical, pharmaceutical, and food industries. There are two common methods to fabricate polymer functionalized MNPs. In the in situ method, the surfaces of the MNPs have been coated with polymer during their synthesis.88 In the second method, post-annealing coating, previously synthesized MNPs are functionalized by coating with polymer.89 Especially, biocompatible and biodegradable polymers such as natural (cellulose (CEL), dextran (DEX), chitosan (CHS), alginate (ALG), etc.) and synthetic (PEG, polyvinyl alcohol (PVA), poly(e-caprolactone) (PCL), polydopamine (PDA), polyethyleneimine (PEI), polyvinylpyrrolidone (PVP), and poly(2-hydroxyethyl methacrylate) (PHEMA) polymers have commonly been used to functionalize MNPs.89,90 In our previous work,91 we synthesized Fe3O4 MNPs via a coprecipitation method. The produced Fe3O4 MNPs were then functionalized by CHS to immobilize the enzyme (Figure 18.5). In addition, we investigated the effect of a weak magnetic field on enzyme activity. According to the obtained results, we indicated that the catalytic efficiency of immobilized L-asparaginase on Fe3O4–CHS MNPs enhanced by nearly 3-fold in the weak magnetic field. Hammouda et al.92 synthesized ALG-Fe3O4 MNPs to remove 3-methylindole from aqueous solutions via the Fenton process. The results revealed that the ALG-Fe3O4 MNP catalyst displayed a good catalytic performance under optimal conditions. 3-methyl indole was totally removed within 120 min at pH 3.0 by using 0.4 g L1 of ALG-Fe3O4 and 9.8 mmol L1 of H2O2. Nasim et al.93 synthesized superparamagnetic Fe3O4 MNPs functionalized by modified CEL. Afterward, they loaded doxorubicin (DOX) on synthesized CEL-MNPs and investigated the release profiles (at pH 5.0 and pH 7.4) of the DOX. They reported that the pH of the medium has an effect on DOX release. Based on the results, the release of DOX at pH:7.4 was more slow and controlled compared to the release of DOX in the acidic state (pH:5). Tao et al.94 synthesized PEI-functionalized Fe3O4 MNPs by a solvothermal method to remove Pb21 ions from aqueous media. They reported the maximum Pb21 adsorption capacity as 60.98 mg g1 (25 1C and pH 5.0). In addition, the researchers examined the effects of temperature, pH and electrolyte of the aqueous phase on Pb21 adsorption capacity of MNPs. According to the results obtained, the Pb21 adsorption capacity increased with increasing temperature or pH while it decreased with the addition of various electrolytes. Moreover, the PEI-functionalized MNPs still displayed a high adsorption performance even after five cycles. Maleki et al.95 prepared a Fe3O4@PVA nanocomposite film as a new nanocatalyst via an in situ precipitation method. They also functionalized the surface of Fe3O4@PVA nanocomposites with sulfonic acid in order to enhance the catalysis activity (Figure 18.6). They comprehensively characterized Fe3O4@PVA–SO3H nanocomposites by using various methods. Some properties of the nanocomposite films were as follows; morphology: uniform, and spherical, size: 47 nm, magnetization saturation

466

The schematic view of the preparation steps of Fe3O4–CHS MNPs. Reproduced from ref. 91 with permission from the Royal Society of Chemistry.

Chapter 18

Figure 18.5

Functionalized Magnetic Nanoparticle-based Sensors for Point-of-care Applications 467

Figure 18.6

Preparation scheme of Fe3O4@PVA–SO3H and its catalytic performance in the synthesis of dihydropyrimidines. Reproduced from ref. 95, https://doi.org/10.1186/s13065-019-0538-2, under the terms of the CC0 1.0 license, http://creativecommons.org/ publicdomain/zero/1.0/.

value: 8.8 emu g1, surface area: 54.052 m2 g1, pore volume: 0.042 cm3 g1 and pore size: 3.48 nm. Additionally, the catalytic activity of a heterogeneous nanocatalyst was performed for the synthesis of dihydropyrimidine derivatives from an aldehyde, ß-ketoester and urea or thiourea. According to the obtained results, the heterogeneous nanocatalyst could be reused at least six times without any appreciable loss in product yield due to the fact that they could be easily separated by an external magnet.

18.2.2.2

Functionalization by Using Inorganic Materials

Although fMNPs are used in many different applications, problems such as rapid agglomeration and oxidation restrict their use. To overcome these

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restrictions, their surface has been modified with different inorganic agents. Basically, there are four main aims to functionalizing the surface of NPs:53  to ensure easy distribution of MNPs,  activating the surface of MNPs,  to enhance the physicochemical and mechanical properties of MNPs, and  to increase the biocompatibility of MNPs. Silicon dioxide, also known as silica, (SiO2), mesoporous silicas (MCM-41, SBA-15, etc.), metals (Au, Ag, Pt, etc.), and metal oxides (ZnO, TiO2, Al2O3, etc.) are the most preferred inorganic materials for the modification or functionalization of magnetic nanoparticles. Table 18.4 shows some inorganic materials used for the preparation of fMNPs and their applications. 18.2.2.2.1 Silica and Mesoporous Silicas. Silica is one of the widely used inorganic molecules for the modification of the surface of MNPs.89 Silica coating has been reported to reduce the agglomeration of MNPs, increase stability and reduce the cytotoxic effects of MNPs. It also improves biocompatibility, hydrophilicity and stability.107 Table 18.4

Silica

Some inorganic materials used for fMNPs and their applications. Preparation technique of MNPs

Inorganic compound

Co-precipitation Solvothermal Co-precipitation

SiO2 SiO2 SiO2

Mesoporous Chemical silica precipitation Incipient wetness impregnation Chemical precipitation Co-precipitation Metal

Hydrothermal Thermal decomposition Thermal decomposition Solvothermal reduction Metal oxides Hydrothermal Co-precipitation Solvothermal Hydrothermal

Application

Reference 117 118 9

MCM-41

Catalyst Adsorption Enzyme immobilization Catalysts

119

SBA-15

Drug delivery

120

SBA-15

Catalyst

121

KIT-6

122

Au Ag

Enzyme immobilization Catalytic Catalyst

123 124

Pd

Catalyst

125

Pt

Sensor

126

ZnO

Photocatalytic degradation Photocatalysis Catalyst Photocatalysis Photocatalyst

127

ZnO TiO2 TiO2 CuO

128 129 130 131

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For instance, Aslani et al.108 synthesized Fe3O4 MNPs via co-precipitating the coating by a SiO2 by sol–gel method. Afterward, they further modified the Fe3O4@SiO2 MNPs with 3-aminopropyltriethoxysilane (APTES) for immobilization of trypsin from porcine pancrease. Glutaraldehyde as a cross-linker was used to immobilize trypsin (Figure 18.7). The synthesis and immobilization process were verified by using SEM, TGA, XRD, FT-IR and EDX. After immobilization, the optimum pH and temperature of the enzyme did not change, however, the stability of the enzyme at different pH and temperature increased. Kinetic data indicated that while the Vmax of the immobilized form decreased, the Km value increased. Moreover, the immobilized form had 85% of its original activity after 6 reuses. Cai et al.109 carried out the synthesis of Fe3O4@SiO2 NPs by a green method for pH-responsive DOX release (Figure 18.8). The structure, morphology and physiochemical properties of carboxyl-modified Fe3O4@ SiO2 NPs were investigated by several measurements. BET surface area and magnetization saturation of carboxyl-modified Fe3O4@SiO2 NPs, and loading capacity of DOX were determined to be 79.9 m2 g1, 25.9 emu g1, and 34.6 mg g1, respectively. In release tests of DOX, it was 60.8% released within 72 h at pH 3.5. Kazemnejadi et al.110 synthesized a Fe3O4@SiO2@Im[Cl]Mn(III)-complex as a highly efficient magnetically recoverable nanocatalyst for selective oxidation of alcohol to imine and oxime (Figure 18.9). The catalyst was

Figure 18.7

Schematic illustration of the synthesis, and modification of Fe3O4 MNPs and immobilization of trypsin onto the Fe3O4@SiO2-NH2 NPs. Reproduced from ref. 108 with permission from Elsevier, Copyright 2018.

470

An illustration of the probable mechanism of DOX loading and release. Reproduced from ref. 109 with permission from Elsevier, Copyright 2020.

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Figure 18.8

The preparation of a Fe3O4@SiO2@Im[Cl]Mn(III)-complex. Reproduced from ref. 110 with permission from Elsevier, Copyright 2019.

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Figure 18.9

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comprehensively analyzed through different methods. Since the catalyst can be easily separated from the mixture by an external magnet, it was used for at least seven successive runs with little loss of reactivity. Roto et al.111 synthesized Fe3O4@SiO2 core–shell MNPs modified with a thiol group and they used it as the adsorbent for chloroauric ion adsorption (Figure 18.10). Firstly, Fe3O4 MNPs were prepared by co-precipitation and coated with SiO2 by acid hydrolysis of Na2SiO3 under a nitrogen atmosphere. Afterwards, the coated Fe3O4 MNPs were functionalized with a thiol group using 3-mercaptopropyltrimethoxysilane (MPTMS) through a silanization reaction. The characterization outcomes confirmed that the size of the prepared thiol modified-Fe3O4@SiO2 was 10–20 nm. It was obtained from the Langmuir isotherm model, where the maximum adsorption capacity of Fe3O4@SiO2 MNPs for chloroauric ion adsorption was 115 mg g1 and the free energy (DG1) was 24.8 kJ mol1. In a previous study, we prepared Fe3O4@MCM-41 MNPs and modified them by using MPTMS for enzyme immobilization.10 Several techniques were performed to check the thiol-functionalized Fe3O4@MCM-41 MNPs. We revealed that the thiol-functionalized Fe3O4@MCM-41 MNPs had good activity for enzyme immobilization and enhanced stability of the enzyme. In addition, we synthesized epoxy7 and chloro-11 modified Fe3O4@MCM-41 MNPs and used them for enzyme immobilization. 18.2.2.2.2 Metal. Composite materials formed by the combination of metallic NPs (Au, Pt, Ag, etc.) and MNPs have been widely used for many potential applications because of their combined physicochemical properties and potential properties.53 In a study, Thamilselvan et al.112 constructed Au@Fe3O4 MNPs for sensitive dopamine detection (Figure 18.11). The Au@Fe3O4 MNPs were verified by SEM, XRD, and TEM. The electrochemical performance of the modified electrode was examined by CV, DPV and amperometric techniques. It displayed a wide linear response (0–0.8 mM) and a low detection limit (2.7 nM). It had an excellent stability and good reproducibility. Moreover, it was successfully used to detect dopamine in human urine samples. Ma et al.113 prepared Pt-modified Fe3O4 MNPs by a simple strategy and analyzed them by using several techniques. Furthermore, the peroxidase-like catalytic activity of the prepared Pt-modified Fe3O4 MNPs was investigated. Fe3O4@Pt MNPs had a larger Kcat value than that of Fe3O4 MNPs, which is attributed to their strong affinity with the substrate. 18.2.2.2.3 Metal Oxides. Besides metals, metal oxides such as ZnO and TiO2, have been widely utilized for many potential applications because of their combined physicochemical properties and potential properties. Tan et al.114 synthesized Fe3O4@TiO2 core–shell magnetic composites for highly efficient sorption of uranium(VI) (Figure 18.12). Fe3O4@TiO2 core–shell magnetic composites as an adsorbent were prepared via a hydrothermal method and characterized by SEM, TEM, XRD, and VSM.

The preparation of thiol modified-Fe3O4@SiO2 core–shell MNPs and their use for chloroauric adsorption. Reproduced from ref. 111 with permission from Elsevier, Copyright 2016.

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Figure 18.10

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Figure 18.11

The schematic diagram of constructed Au@Fe3O4 MNPs for sensitive dopamine detection. Reproduced from ref. 112 with permission from Elsevier, Copyright 2019.

Figure 18.12

The schematic view for the preparation of Fe3O4@TiO2 core–shell magnetic composites. Reproduced from ref. 114 with permission from Elsevier, Copyright 2015.

Besides, Langmuir and Freundlich adsorption isotherms of uranium removing (VI) from aqueous solution were investigated. The maximum adsorption capacity of the Fe3O4@TiO2 composite for uranium(VI) was reported to be 118.8 mg U g1 at pH 6.0. Moreover, the thermodynamic parameters revealed that the adsorption was an endothermic and spontaneous process. Ammar et al.115 prepared core/shell Fe3O4@Al2O3–phosphomolybdic acid (PMo) magnetic nanocatalysts for the photocatalytic degradation of organic pollutants (Figure 18.13). Afterwards, PMo was immobilized on the prepared Fe3O4@Al2O3 surface. Fe3O4 MNPs, Fe3O4@Al2O3 and Fe3O4@Al2O3-PMo were confirmed by using various characterization methods. The Fe3O4@Al2O3-PMo photocatalyst displayed high degradation activity (491%)

Functionalized Magnetic Nanoparticle-based Sensors for Point-of-care Applications 475

Figure 18.13

The synthesis process of the Fe3O4@Al2O3-PMo photocatalyst. Reproduced from ref. 115 with permission from Elsevier, 2020.

Figure 18.14

Schematic illustration for the preparation of Fe3O4/ZnO core/shell MNPs and lipase immobilization. Reproduced from ref. 116 with permission from Elsevier, Copyright 2013.

in the presence of H2O2. In addition, it maintained over 83% of its activity after five cycles of the adsorption–photocatalytic degradation. Ghasemi et al.116 prepared Fe3O4/ZnO core/shell MNPs and characterized them via XRD, SEM, TGA, and FTIR. After that, lipase was immobilized by a covalent binding method on the prepared Fe3O4/ZnO core/shell MNPs (Figure 18.14) with an immobilization efficiency and yield of 94  2.5% and 86  3.5%, respectively. The thermal, pH, and reusability of the enzyme improved after immobilization. Additionally, the immobilized lipase exhibited the highest yield of the related reaction product when the immobilized lipase and seven other commercial lipases were examined for Michael addition of active methylene compounds to chalcones.

18.3 Point-of-care Approaches Health management needs to be improved to provide a better healthcare service to patients.132–134 For example, higher health management standards may be provided through timely decisions based on rapid diagnostics, smart

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data analysis, and information processing analysis. Therefore, smart therapeutics, analytical devices and diagnostic systems are always in demand for improving public health.135–137 A therapy process may differ among patients. At this point, determining the patient profile is vital for managing disease in terms of progress and monitoring evaluation. Moreover, disease progression/monitoring is very important for epidemic understanding and management. To achieve this aim, further research is required to design and develop intelligent diagnostic systems that can perform according to patient profiles and enable personalized health care.135–139 Point-of-care (PoC) systems are platforms that can enable rapid detection and reliable diagnosis wherever the patient is.40 The key to a PoC test is that it is user-friendly and very simple, so even those without any laboratory or medical experience can use it and understand its response.40,140 It is well known that early diagnosis is crucial to the effectiveness of treatment. Therefore, PoC systems are promising in the design of physical and biochemical micro sensors thanks to their advantages such as excellent sensitivity, easy portability, compact device integration and low power consumption.140,141 In addition, PoC systems need to be developed in an inexpensive, small, portable, light, and implantable way to ensure that they can be easily obtained by anyone and everywhere.40,140 Other characteristics that PoC tests should have are selectivity (capability to respond to a unique analyte or parameter and not be affected by interference), sensitivity (quality to discriminate similar values), and robustness (ability to resist changes in environmental conditions).40 With the development of nanotechnology, nanomaterials are advantageous to PoC systems by adapting them into different sections of available detection platforms or by proposing highly innovative sensing platforms.40

18.4 fMNP-based Sensors for PoC Applications MNPs are suitable candidates to prepare biosensors for PoC systems. In particular, g-Fe2O3 and Fe3O4 MNPs have been widely used in sensor applications since they have good chemical stability, a large active surface, ease of surface functionalization, and rapid reaction kinetics.142,143 The advantages of MNPs provide simple, accurate, ease of use, rapid, and cheap detection for PoC. These advantages are as follows:142  Simple magnetic withdrawal and high surface affinity parts provide immobilization and purification of biomolecules through the magnetic area, and also reduced the matrix effect.  Since MNPs can speed up signal transmission and strengthen analyte sensing, they can enhance the overall detection sensitivity of biosensors.  The spontaneous properties of MNPs make magnetic probes perfect for reading signals for ultrasonic, suitable and real-time analysis.  In addition, MNPs are especially appropriate for integration into microfluidic devices to design laboratory bioassays on-chip for PoC.144

Functionalized Magnetic Nanoparticle-based Sensors for Point-of-care Applications 477

We have reported the developments in MNP-based biosensors used in PoC systems below. Fernandez and co-workers145 developed a disposable PoC detection system specific for salivary cortisol detection. They used a macrocyclic catalyst ink-based printed electrode capable of electrochemically reducing salivary cortisol captured by aptamer fMNPs. The sensors were printed using a special multi-walled carbon nanotube–copper porphyrin on a photo-paper substrate (Figure 18.15). The developed platform displayed high selectivity to salivary cortisol against a background of four steroid samples including corticosterone, cortisone, progesterone, and, triamcinolone. Yang et al.146 prepared Fe3O4/Au nanoparticles and modified them with poly(acrylic acid) (PAA). PAA-coated gold MNPs (PGMNs) were then characterized by using several methods. The researchers fabricated a new lateral flow immunoassay strip test system in which recombinant Treponema pallidum antigens (r-Tp) were conjugated with PGMNs to create a particle probe in order to detect anti-Tp antibodies (Figure 18.16). As a result, the authors stated that the developed test system displayed significantly excellent specificity and sensitivity values for all clinical tests (higher than 97%) and also reported that the PoC test style is an appropriate approach for syphilis screening.

Figure 18.15

(a) Schematic of the disposable printed sensor which is enclosed in a plastic lamination with openings for contact pads and sensing area. A magnetic disk (r ¼ 3 mm; t ¼ 5 mm) is aligned and laminated at the back of the working electrode of the sensor. (b) Photograph of the sensor. (c) The MNP/aptamer/cortisol complex is populated at the sensing electrode via magnetic enrichment where the reduction of cortisol occurs. Reproduced from ref. 145, https://doi.org/10.1038/s41598-017-17835-8, under the terms of the CC BY 4.0 license, https://creativecommons. org/licenses/by/4.0/.

478

Figure 18.16

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(A) A schematic diagram of the surface modification of PGMNs and synthesis of the particle probes of PGMNs. (B) The principles for anti-Tp antibody detection and the apparatus employed for PGMNs-rTp LFIA. Reproduced from ref. 146 with permission from American Chemical Society, Copyright 2013.

Alhogail et al.147 designed MNP-based biosensors for the fast colorimetric detection of Pseudomonas aeruginosa (P. aeruginosa), which is an opportunistic pathogen, in clinical isolates. The limit of detection of the designed biosensor was as low as 102 colony-forming units (CFU)/mL within one min. Consequently, the researchers reported that this biosensor can be used as a fast PoC platform to diagnose P. aeruginosa-related infections. PoC and economic determination are very important for the early diagnosis and control of Staphylococcus aureus (S. aureus) infections, which are one of the main causes of foodborne disease. Therefore, Eissa and Zourob148

Functionalized Magnetic Nanoparticle-based Sensors for Point-of-care Applications 479

Figure 18.17

Schematic illustration of a dual electrochemical/colorimetric MNP/ peptide-based platform for the detection of Staphylococcus aureus. Reproduced from ref. 148 with permission from the Royal Society of Chemistry.

fabricated a dual electrochemical/colorimetric MNP/peptide-based platform for the detection of S. aureus (Figure 18.17). The detection limit of the electrochemical assay was 3 CFU mL1 after 1 min. In addition, the fabricated biosensor could specifically distinguish S. aureus from other food- and waterborne bacteria such as Escherichia coli and Listeria by using the dual-mode colorimetric and electrochemical detection. Consequently, the authors reported that the fabricated system may be able to provide a rapid and reliable detection of S. aureus and show great promise for PoC diagnosis. Tonthat et al.149 designed an easy and fast determination platform for oral bacteria in the liquid phase for PoC diagnostics via MNPs. The authors determined the calibration curves of typical bacteria such as Streptococcus mutans, Escherichia coli, Pseudomonas aeruginosa and Porphyromonas gingivalis. Afterwards, they determined the concentration of P. gingivalis cultured in saliva collected from the elderly people in a geriatric health service. The detection limit and detection time were reported as 103 CFU mL1 and nearly 1 hour, respectively. In another study, Cihalova et al.150 determined S. aureus, methicillinresistant S. aureus (MRSA) and Klebsiella pneumoniae via a quantum dotbased barcode assay. They utilized MNPs and quantum dots to detect bacteria by using bacteria-specific genes such as wcaG, fnbA, and mecA (Figure 18.18). According to the obtained results, the developed system was able to determine concentrations of bacteria as low as 102 CFU mL1. Finally, the authors stated that antibody-free detection of infectious bacteria is possible via a quantum dot-based barcode assay. Similarly, Liong et al.151 designed magnetic nanoprobes to fabricate a magnetic barcoding method to determine Mycobacterium tuberculosis (MTB).

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Figure 18.18

Scheme of bacteria determination by multiplex barcoding. Reproduced from ref. 150 with permission from Elsevier, Copyright 2017.

Figure 18.19

Giant magnetoresistive nanosensor chip on a printed circuit board. Reproduced from ref. 153 with permission from Elsevier, Copyright 2019.

It remains a challenge to quickly identify patients infected with MTB.151 Therefore, there is a need for a sensitive, highly efficient and low cost PoC platform. The authors designed a system to determine nucleic acids by a magnetic barcoding method. The magnetic barcode strategy is based on the detection of Polymerase Chain Reaction (PCR)-amplified mycobacterial genes on microspheres specific to the array, labeled by magnetic nanoprobes and detected by nuclear magnetic resonance. In conclusion, this platform can be used to determine MTB and identify drug-resistance strains from mechanically processed sputum samples within 2.5 h. A novel, miniaturized diagnostic magnetic resonance (DMR) system for multiplexed, quantitative and fast analysis was developed by Lee et al.152 They used the ability of the DMR system for the determination of bacteria with high sensitivity, to analyze a small number of cells and molecular management in real time, and to measure a series of protein biomarkers in parallel. Therefore, the authors noted that DMR technology shows potential as a robust and portable diagnostic device. In a recent study, Ng et al.153 fabricated a magneto-nanosensor smartphone system to detect human immunodeficiency virus (HIV) and leukocytosis at the PoC (Figure 18.19). They used magneto-nanosensor arrays and

Functionalized Magnetic Nanoparticle-based Sensors for Point-of-care Applications 481

MNPs to detect HIV in saliva and leukocytosis in plasma and whole blood. The researchers quantitatively measured HIV and leukocytosis by the PoC system with 16 minute test times. Moreover, they were able to detect HIV with 80% accuracy in saliva and leukocytosis in plasma with 90% accuracy. As a result, they reported that the developed platform may offer users with pleasant user-experience while exhibiting robust, precise, and specific multiplexed measurement and detection of common diseases.

18.5 Conclusions Nanotechnology is very crucial to shorten the treatment process of various diseases and provide more effective treatment. We anticipate that this chapter will contribute to an overview of recent trends in the preparation and application of fMNP-based sensors for PoC applications. We briefly explained the preparation methods of MNPs and outlined some case studies. We then summarized and highlighted some recent approaches for MNPs functionalized with organic and inorganic materials. In conclusion, multidisciplinary collaborations such as between biological, engineering and clinical fields are still needed for the development of new generation, integrable PoC systems that can easily diagnose and treat infectious diseases worldwide.

Important Websites https://www.nanoprobes.com/products/Magnetic-Nanoparticles.html https://www.cd-bioparticles.com/t/Properties-and-Applications-of-MagneticNanoparticles_55.html https://www.addondata.com/2017/10/what-is-point-of-care-poc-technology/ https://www.human.de/products/poc-dx/ https://www.pointofcare.abbott/us/en/about-us/benefits-of-point-of-caretesting

References ¨yu ¨ktiryaki and C. M. Hussain, TrAC, Trends Anal. Chem., 1. R. Keçili, S. Bu 2019, 110, 259. 2. R. Keçili and C. M. Hussain, Int. J. Anal. Chem., 2018, 2018, 8503853. 3. M. T. K. Al-Jabri, M. G. Devi and M. Al Abri, Appl. Water Sci., 2018, 8, 1. 4. D. Sharma and C. M. Hussain, Arabian J. Chem., 2020, 13, 3319. ¨yu ¨ktiryaki, R. Keçili and C. M. Hussain, TrAC, Trends Anal. Chem., 5. S. Bu 2020, 127, 115893. 6. S. C. McBain, H. H. P. Yiu and J. Dobson, Int. J. Nanomed., 2008, 3, 169. 7. A. Ulu, I. Ozcan, S. Koytepe and B. Ates, Int. J. Biol. Macromol., 2018, 115, 1122. ¨ytepe, O. Yesilada and B. Ates- , Int. J. 8. A. Ulu, E. Birhanli, F. Boran, S. Ko Biol. Macromol., 2020, 150, 871.

482

Chapter 18

9. S. A. A. Noma, A. Ulu, S. Koytepe and B. Ates- , Biocatal. Biotransform., 2020, 38, 392. 10. A. Ulu, S. A. A. Noma, S. Koytepe and B. Ates, Artif. Cells, Nanomed., Biotechnol., 2018, 46, 1035. 11. A. Ulu, S. A. A. Noma, S. Koytepe and B. Ates, Appl. Biochem. Biotechnol., 2019, 187, 938. 12. T. Tarhan, A. Ulu, M. Sariçam, M. Çulha and B. Ates, Int. J. Biol. Macromol., 2020, 142, 443. ¨ . Acet, R. Sanz, E. S. Sanz-Pe ´rez, M. Odabas- i and 13. S. A. A. Noma, A. Ulu, O B. Ates- , New J. Chem., 2020, 44, 4440. 14. C. Sappino, L. Primitivo, M. De Angelis, M. O. Domenici, A. Mastrodonato, I. Ben Romdan, C. Tatangelo, L. Suber, L. Pilloni, A. Ricelli and G. Righi, ACS Omega, 2019, 4, 21809. 15. T. A. P. Rocha-Santos, TrAC, Trends Anal. Chem., 2014, 62, 28. 16. J. Sengupta and C. M. Hussain, TrAC, Trends Anal. Chem., 2019, 114, 326. 17. V. Devi, M. Selvaraj, P. Selvam, A. A. Kumar, S. Sankar and K. Dinakaran, J. Environ. Chem. Eng., 2017, 5, 4539. 18. A. M. Gutierrez, T. D. Dziubla and J. Z. Hilt, Rev. Environ. Health, 2017, 32, 111. 19. C. M. Hussain and R. Keçili, Environmental Pollution and Environmental Analysis, in Modern Environmental Analysis Techniques for Pollutants, ed. C. M. Hussain and R. Keçili, Elsevier, 2020, pp. 1–36. 20. C. M Hussain, Magnetic nanomaterials for environmental analysis, in Advanced Environmental Analysis-Application of Nanomaterials, ed. C. M. Hussain and B. Kharisov, The Royal Society of Chemistry, 2017. ¨yu ¨ktiryaki, Y. Su ¨mbelli, R. Keçili and C. M. Hussain, Lab-on-chip 21. S. Bu platforms for environmental analysis, in Encyclopedia of Analytical Sci´, Academic ence, ed. P. Worsfold, C. Poole, A. Townshend and M. Miro Press, 3rd edn, 2019, pp. 267–273. ¨yu ¨ktiryaki and C. M. Hussain, Membrane applications of 22. R. Keçili, S. Bu nanomaterials, in Handbook of Nanomaterials in Analytical Chemistry: Modern Trends in Analysis, Elsevier, 2019, pp. 159–182. ¨mbelli, R. Keçili, F. Ghorbani-Bidkorbeh and C. M. Hussain, Lab23. Y. Su on-chip for chromatographic techniques, in Handbook on Miniaturization in Analytical Chemistry Application of Nanotechnology, Elsevier, 2020, pp. 129–137. 24. A. I. Savchuk, A. Perrone, A. Lorusso, I. D. Stolyarchuk, O. A. Savchuk and O. A. Shporta, Appl. Surf. Sci., 2014, 302, 205. ¨tten, Nat. Mater., 2005, 4, 725. 25. G. Reiss and A. Hu 26. R. Keçili and C. M. Hussain, Mechanism of Adsorption on Nanomaterials in Nanomaterials in Chromatography Current Trends in Chromatographic Research Technology and Techniques, Elsevier, 2018, pp. 89–115. 27. H. Fatima and K. S. Kim, Adv. Powder Technol., 2018, 29, 2678. 28. H. Lai, F. Xu and L. Wang, J. Mater. Sci., 2018, 53, 8677.

Functionalized Magnetic Nanoparticle-based Sensors for Point-of-care Applications 483

29. D. Issadore, Y. I. Park, H. Shao, C. Min, K. Lee, M. Liong, R. Weissleder and H. Lee, Lab Chip, 2014, 14, 2385. 30. J. H. Jung, J. H. Lee and S. Shinkai, Chem. Soc. Rev., 2011, 40, 4464. 31. W. M. Hassen, C. Chaix, A. Abdelghani, F. Bessueille, D. Leonard and N. Jaffrezic-Renault, Sens. Actuators, B, 2008, 134, 755. ´n, A. Olivas-Sarabia and 32. L. M. De La Rosa-Romo, M. T. Oropeza-Guzma G. Pina-Luis, Sens. Actuators, B, 2016, 233, 459. 33. W. Jiang, S. Yang, X. Sun, W. Lu, D. Jiang, L. Xu, H. Xu, B. Gao, M. Ma and F. Cao, Anal. Methods, 2018, 10, 2494. 34. S. Sun, L. Xiong, Y. Li and X. He, Anal. Lett., 2015, 48, 2357. 35. C. Altay, R. H. Senay, E. Eksin, G. Congur, A. Erdem and S. Akgol, Talanta, 2017, 164, 175. 36. M. Wang, G. Meng, Q. Huang, Y. Lu and Y. Gu, Sens. Actuators, B, 2013, 185, 47. 37. A. A. Moustafa, M. A. Hegazy, D. Mohamed and O. Ali, J. Anal. Methods Chem., 2019, 2019, 6947042. 38. H. Wang, Y. Zhou, Y. Guo, W. Liu, C. Dong, Y. Wu, S. Li and S. Shuang, Sens. Actuators, B, 2012, 163, 171. 39. S. Shrivastava, T. Q. Trung and N. E. Lee, Chem. Soc. Rev., 2020, 49, 1812. ´lez and A. Merkoçi, Chem. Soc. Rev., 2018, 47, 40. D. Quesada-Gonza 4697. 41. A. Akbarzadeh, M. Samiei and S. Davaran, Nanoscale Res. Lett., 2012, 7, 144. 42. I. Bibi, N. Nazar, S. Ata, M. Sultan, A. Ali, A. Abbas, K. Jilani, S. Kamal, F. M. Sarim, M. I. Khan, F. Jalal and M. Iqbal, J. Mater. Res. Technol., 2019, 8, 6115. 43. M. Unni, A. M. Uhl, S. Savliwala, B. H. Savitzky, R. Dhavalikar, N. Garraud, D. P. Arnold, L. F. Kourkoutis, J. S. Andrew and C. Rinaldi, ACS Nano, 2017, 11, 2284. 44. K. Kekalo, K. Koo, E. Zeitchick and I. Baker, Mater. Res. Soc. Symp. Proc., 2012, 1416, 61. 45. Y. Wang, I. Nkurikiyimfura and Z. Pan, Chem. Eng. Commun., 2015, 202, 616. 46. S. Riaz, R. Ashraf, A. Akbar and S. Naseem, IEEE Trans. Magn., 2014, 50(8), 2201504. 47. S. Li, T. Zhang, R. Tang, H. Qiu, C. Wang and Z. Zhou, J. Magn. Magn. Mater., 2015, 379, 226. 48. S. Park, S. Lim and H. Choi, Chem. Mater., 2006, 18, 5150. 49. X. Wang, M. Qin, F. Fang, B. Jia, H. Wu, X. Qu and A. A. Volinsky, Ceram. Int., 2018, 44, 4237. ´-Aguayo and E. Bertran, Appl. Sci., 50. M. Sanaee, S. Chaitoglou, N. Aguilo 2016, 7, 26. 51. E. Popovici, F. Dumitrache, I. Morjan, R. Alexandrescu, V. Ciupina, G. Prodan, L. Vekas, D. Bica, O. Marinica and E. Vasile, Appl. Surf. Sci., 2007, 254, 1048.

484

Chapter 18

52. S. Majidi, F. Zeinali Sehrig, S. M. Farkhani, M. Soleymani Goloujeh and A. Akbarzadeh, Artif. Cells, Nanomed., Biotechnol., 2016, 44, 722. 53. W. Wu, Z. Wu, T. Yu, C. Jiang and W. S. Kim, Sci. Technol. Adv. Mater., 2015, 16(2), 023501. 54. M. A. Willard, L. K. Kurihara, E. E. Carpenter, S. Calvin and V. G. Harris, Int. Mater. Rev., 2004, 49, 125. 55. T. K. Indira and P. K. Lakshmi, Int. J. Pharm. Pharm. Sci., 2010, 3(3), 1035. 56. Z. Zarnegar and J. Safari, Green Chem. Lett. Rev., 2017, 10, 235. 57. H. Rashid, M. A. Mansoor, B. Haider, R. Nasir, S. B. Abd Hamid and A. Abdulrahman, Sep. Sci. Technol., 2020, 55, 1207. 58. W. Wu, Q. He and C. Jiang, Nanoscale Res. Lett., 2008, 3(11), 397. 59. P. Kumar, H. Khanduri, S. Pathak, A. Singh, G. A. Basheed and R. P. Pant, Dalton Trans., 2020, 49, 8672. 60. X. Yang, W. Jiang, L. Liu, B. Chen, S. Wu, D. Sun and F. Li, J. Magn. Magn. Mater., 2012, 324, 2249. ´nchez, D. A. Corte ´s-Herna ´ndez, J. C. Escobedo-Bocardo, J. M. Almanza61. J. Sa ´n, P. Bartolo-Pe ´rez and Robles, P. Y. Reyes-Rodrı´guez, R. A. Jasso-Tera ´n-Prado, J. Magn. Magn. Mater., 2017, 427, 272. L. E. De-Leo 62. X. Cao, B. Zhang, F. Zhao and L. Feng, J. Nanomater., 2012, 2012, 607296. 63. G. Asab, E. A. Zereffa and T. A. Seghne, Int. J. Biomater., 2020, 2020, 4783612. 64. C. Y. Lu, T. Puig, X. Obradors, S. Ricart and J. Ros, RSC Adv., 2016, 6, 88762. 65. S. Shabestari Khiabani, M. Farshbaf, A. Akbarzadeh and S. Davaran, Artif. Cells, Nanomed., Biotechnol., 2017, 45, 6. 66. S. Kalia, S. Kango, A. Kumar, Y. Haldorai, B. Kumari and R. Kumar, Colloid Polym. Sci., 2014, 292, 2025. 67. A. B. Salunkhe, V. M. Khot and S. H. Pawar, Curr. Top. Med. Chem., 2014, 14, 572. 68. R. Qiao, C. Yang and M. Gao, J. Mater. Chem., 2009, 19, 6274. ´nchez-Torres, D. A. Corte ´s69. M. M. G. Saldı´var-Ramı´rez, C. G. Sa ´ndez, J. C. Escobedo-Bocardo, J. M. Almanza-Robles, A. Larson, Herna ´ndiz-Herna ´ndez and I. O. Acun ˜ a-Gutie´rrez, J. Mater. Sci.: P. J. Rese Mater. Med., 2014, 25, 2229. 70. G. Mohammadi Ziarani, Z. Kazemi Asl, P. Gholamzadeh, A. Badiei and M. Afshar, J. Sol-Gel Sci. Technol., 2018, 85, 103. 71. O. M. Lemine, K. Omri, B. Zhang, L. El Mir, M. Sajieddine, A. Alyamani and M. Bououdina, Superlattices Microstruct., 2012, 52, 793. 72. A. Azizi, J. Inorg. Organomet. Polym. Mater., 2020, 30, 3552. 73. Y. P. Yew, K. Shameli, M. Miyake, N. B. B. Ahmad Khairudin, S. E. B. Mohamad, T. Naiki and K. X. Lee, Arabian J. Chem., 2020, 13, 2287. 74. Y. P. Yew, K. Shameli, M. Miyake, N. Kuwano, N. B. Bt Ahmad Khairudin, S. E. Bt, Mohamad and K. X. Lee, Nanoscale Res. Lett., 2016, 11, 276.

Functionalized Magnetic Nanoparticle-based Sensors for Point-of-care Applications 485

75. S. Venkateswarlu, B. Natesh Kumar, C. H. Prasad, P. Venkateswarlu and N. V. V. Jyothi, Phys. B, 2014, 449, 67. 76. K. D. Sirdeshpande, A. Sridhar, K. M. Cholkar and R. Selvaraj, Appl. Nanosci., 2018, 8, 675. 77. S. Bano, S. Nazir, A. Nazir, S. Munir, T. Mahmood, M. Afzal, F. L. Ansari and K. Mazhar, Int. J. Nanomed., 2016, 11, 3833. 78. G. Sathishkumar, V. Logeshwaran, S. Sarathbabu, P. K. Jha, M. Jeyaraj, C. Rajkuberan, N. Senthilkumar and S. Sivaramakrishnan, Artif. Cells, Nanomed., Biotechnol., 2018, 46, 589. 79. V. A. Niraimathee, V. Subha, R. S. Ernest Ravindran and S. Renganathan, Int. J. Environ. Sustain. Dev., 2016, 15, 227. 80. F. Buazar, M. H. Baghlani-Nejazd, M. Badri, M. Kashisaz, ¨rke, 2016, 68, 796. A. Khaledi-Nasab and F. Kroushawi, Starch – Sta 81. A. Khataee, B. Kayan, D. Kalderis, A. Karimi, S. Akay and M. Konsolakis, Ultrason. Sonochem., 2017, 35, 72. ´ndez van Raap, M. Alvarez and 82. M. F. Horst, D. F. Coral, M. B. Ferna V. Lassalle, Mater. Sci. Eng., C, 2017, 74, 443. 83. A. V. Ramesh, D. Rama Devi, S. Mohan Botsa and K. Basavaiah, J. Asian Ceram. Soc., 2018, 6, 145. 84. L. Mohtashami, N. Ghows, Z. Tayarani-Najaran and M. Iranshahi, Planta Med., 2019, 85, 169. 85. H. Luo, S. Zhang, X. Li, X. Liu, Q. Xu, J. Liu and Z. Wang, J. Taiwan Inst. Chem. Eng., 2017, 72, 163. 86. M. Zarghani and B. Akhlaghinia, RSC Adv., 2016, 6, 38592. 87. W. Guo, Z. Fu, Z. Zhang, H. Wang, S. Liu, W. Feng, X. Zhao and J. P. Giesy, Sci. Total Environ., 2020, 710, 136302. 88. Z. Shaterabadi, G. Nabiyouni and M. Soleymani, Mater. Sci. Eng., C, 2017, 75, 947. 89. N. Zhu, H. Ji, P. Yu, J. Niu, M. U. Farooq, M. W. Akram, I. O. Udego, H. Li and X. Niu, Nanomaterials, 2018, 8, 810. 90. B. Ates, S. Koytepe, A. Ulu, C. Gurses and V. K. Thakur, Chem. Rev., 2020, 120, 9304. ¨ytepe, S. A. Ali Noma, V. S. Kolat and T. Izgi, RSC 91. B. Ates, A. Ulu, S. Ko Adv., 2018, 8, 36063. 92. S. Ben Hammouda, N. Adhoum and L. Monser, J. Hazard. Mater., 2015, 294, 128. 93. N. Movagharnegad, P. Najafi Moghadam, A. Nikoo and Z. Shokri, Polym.-Plast. Technol. Eng., 2018, 57, 1915. ¨ and H. Zhao, Appl. Sci., 2020, 10, 948. 94. Y. Tao, C. Zhang, T. Lu 95. A. Maleki, M. Niksefat, J. Rahimi and Z. Hajizadeh, BMC Chem., 2019, 13, 19. 96. A. M. Demin, A. G. Pershina, A. S. Minin, A. V. Mekhaev, V. V. Ivanov, S. P. Lezhava, A. A. Zakharova, I. V. Byzov, M. A. Uimin, V. P. Krasnov and L. M. Ogorodova, Langmuir, 2018, 34, 3449. 97. A. M. Demin, A. V. Mekhaev, O. F. Kandarakov, V. I. Popenko, O. G. Leonova, A. M. Murzakaev, D. K. Kuznetsov, M. A. Uimin, A. S. Minin,

486

98. 99. 100.

101. 102. 103. 104. 105. 106. 107. 108. 109. 110. 111. 112. 113. 114. 115. 116. 117. 118. 119. 120. 121.

Chapter 18

V. Y. Shur, A. V. Belyavsky and V. P. Krasnov, Colloids Surf., B, 2020, 190, 110879. S. Rana, N. G. Shetake, K. C. Barick, B. N. Pandey, H. G. Salunke and P. A. Hassan, Dalton Trans., 2016, 45, 17401. H. Cui, D. Li and Z. Zhang, Mater. Lett., 2015, 143, 38. ´rez, F. G. Ruiz-Hernandez, C. Chapa-Gonzalez, H. G. J. A. Roacho-Pe Martı´nez-Rodrı´guez, I. A. Flores-Urquizo, F. E. Pedroza-Montoya, E. N. ˜ o, M. Bautista-Villarea, P. E. Garcı´a-Casillas and C. N. Garza-Trevin ´nchez-Domı´nguez, Polymers, 2020, 12, 300. Sa L. Huang, H. Wang, B. Li, E. Li, Y. Zhou, Y. Yang, C. Dong and S. Shuang, J. Inclusion Phenom. Macrocyclic Chem., 2014, 80, 209. S. Rostamnia, B. Zeynizadeh, E. Doustkhah, A. Baghban and K. O. Aghbash, Catal. Commun., 2015, 68, 77. ´th, E. Ille ´s, M. Szekeres and E. Tomba ´cz, J. Magn. Magn. Mater., I. Y. To 2015, 380, 168. F. Gao, Y. Cai, J. Zhou, X. Xie, W. Ouyang, Y. Zhang, X. Wang, X. Zhang, X. Wang, L. Zhao and J. Tang, Nano Res., 2010, 3, 23. N. Arsalani, H. Fattahi and M. Nazarpoor, Express Polym. Lett., 2010, 4, 329. G. Yuan, Y. Yuan, K. Xu and Q. Luo, Int. J. Mol. Sci., 2014, 15, 18776. M. Abbas, B. Parvatheeswara Rao, M. Nazrul Islam, S. M. Naga, M. Takahashi and C. Kim, Ceram. Int., 2014, 40, 1379. E. Aslani, A. Abri and M. Pazhang, Colloids Surf., B, 2018, 170, 553. W. Cai, M. Guo, X. Weng, W. Zhang, G. Owens and Z. Chen, Mater. Sci. Eng., C, 2020, 112, 110900. M. Kazemnejadi, S. A. Alavi, Z. Rezazadeh, M. A. Nasseri, A. Allahresani and M. Esmaeilpour, J. Mol. Struct., 2019, 1186, 230. R. Roto, Y. Yusran and A. Kuncaka, Appl. Surf. Sci., 2016, 377, 30. A. Thamilselvan, P. Manivel, V. Rajagopal, N. Nesakumar and V. Suryanarayanan, Colloids Surf., B, 2019, 180, 1. M. Ma, J. Xie, Y. Zhang, Z. Chen and N. Gu, Mater. Lett., 2013, 105, 36. L. Tan, X. Zhang, Q. Liu, X. Jing, J. Liu, D. Song, S. Hu, L. Liu and J. Wang, Colloids Surf., A, 2015, 469, 279. S. H. Ammar, A. Ibrahim Elaibi and I. S. Mohammed, J. Water Process Eng., 2020, 37, 101240. S. Ghasemi, M. Heidary, M. A. Faramarzi and Z. Habibi, J. Mol. Catal. B: Enzym., 2014, 100, 121. Z. Wu, C. Sun, Y. Chai and M. Zhang, RSC Adv., 2011, 1, 1179. F. Wang, L. Zhang, Y. Wang, X. Liu, S. Rohani and J. Lu, Appl. Surf. Sci., 2017, 420, 970. H. Kefayati, S. J. Bazargard, P. Vejdansefat, S. Shariati and A. M. Kohankar, Dyes Pigm., 2016, 125, 309. A. M. Alkafajy and T. M. Albayati, Mater. Today Commun., 2020, 23, 100890. J. Mondal, T. Sen and A. Bhaumik, Dalton Trans., 2012, 41, 6173.

Functionalized Magnetic Nanoparticle-based Sensors for Point-of-care Applications 487

122. R. Amin, A. Khorshidi, A. F. Shojaei, S. Rezaei and M. A. Faramarzi, Int. J. Biol. Macromol., 2018, 114, 106. 123. Y. Xing, X. H. Bai, Y. Gong, M. L. Peng, Y. Y. Zhang, X. R. Ma and Y. Zhang, J. Magn. Magn. Mater., 2020, 510, 166951. 124. M. Sahu, M. Shaikh, A. Rai and K. V. S. Ranganath, J. Inorg. Organomet. Polym. Mater., 2020, 30, 1002. 125. C. Biglione, A. L. Cappelletti, M. C. Strumia, S. E. Martı´n and P. M. Uberman, J. Nanoparticle Res., 2018, 20, 127. 126. T. Madrakian, K. D. Asl, M. Ahmadi and A. Afkhami, RSC Adv., 2016, 6, 72803. 127. Q. Feng, S. Li, W. Ma, H. J. Fan, X. Wan, Y. Lei, Z. Chen, J. Yang and B. Qin, J. Alloys Compd., 2018, 737, 197. 128. S. B. Atla, W. R. Lin, T. C. Chien, M. J. Tseng, J. C. Shu, C. C. Chen and C. Y. Chen, Mater. Chem. Phys., 2018, 216, 380. 129. J. E. Gholtash and M. Farahi, RSC Adv., 2018, 8, 40962. 130. J. Ma, S. Guo, X. Guo and H. Ge, Appl. Surf. Sci., 2015, 353, 1117. 131. J. Ding, L. Liu, J. Xue, Z. Zhou, G. He and H. Chen, J. Alloys Compd., 2016, 688, 649. 132. V. Bhardwaj and A. Kaushik, Micromachines, 2017, 8, 298. 133. A. Kaushik, A. Yndart, S. Kumar, R. D. Jayant, A. Vashist, A. N. Brown, C. Z. Li and M. Nair, Sci. Rep., 2018, 8, 9700. 134. A. Kaushik, R. Kumar, S. K. Arya, M. Nair, B. D. Malhotra and S. Bhansali, Chem. Rev., 2015, 115, 4571. 135. A. Kaushik, R. D. Jayant, S. Tiwari, A. Vashist and M. Nair, Biosens. Bioelectron., 2016, 80, 273. 136. A. Kaushik, S. Tiwari, R. Dev Jayant, A. Marty and M. Nair, Biosens. Bioelectron., 2016, 75, 254. 137. A. Kaushik, A. Vasudev, S. K. Arya, S. K. Pasha and S. Bhansali, Biosens. Bioelectron., 2014, 53, 499. 138. A. Kaushik and M. A. Mujawar, Sensors, 2018, 18, 4303. 139. C. Liu, Q. Zhu, K. A. Holroyd and E. K. Seng, J. Syst. Software, 2011, 84, 2022. 140. S. Jung, T. Ji and V. K. Varadan, Smart Mater. Struct., 2006, 15, 1872. 141. L. Wang, D. Fine, D. Sharma, L. Torsi and A. Dodabalapur, Anal. Bioanal. Chem., 2006, 384, 310. 142. Y. Xianyu, Q. Wang and Y. Chen, TrAC, Trends Anal. Chem., 2018, 106, 213. 143. V. Nabaei, R. Chandrawati and H. Heidari, Biosens. Bioelectron., 2018, 103, 69. 144. K. Choi, A. H. C. Ng, R. Fobel, D. A. Chang-Yen, L. E. Yarnell, E. L. Pearson, C. M. Oleksak, A. T. Fischer, R. P. Luoma, J. M. Robinson, J. Audet and A. R. Wheeler, Anal. Chem., 2013, 85, 9638. 145. R. E. Fernandez, Y. Umasankar, P. Manickam, J. C. Nickel, L. R. Iwasaki, B. K. Kawamoto, K. C. Todoki, J. A. M. Scott and S. Bhansali, Sci. Rep., 2017, 7, 17992.

488

Chapter 18

146. D. Yang, J. Ma, Q. Zhang, N. Li, J. Yang, P. A. Raju, M. Peng, Y. Luo, W. Hui, C. Chen and Y. Cui, Anal. Chem., 2013, 85, 6688. 147. S. Alhogail, G. A. R. Y. Suaifan, F. J. Bikker, W. E. Kaman, K. Weber, D. Cialla-May, J. Popp and M. M. Zourob, ACS Omega, 2019, 4, 21684. 148. S. Eissa and M. Zourob, Analyst, 2020, 145, 4606. 149. L. Tonthat, S. Takahashi, H. Onodera, K. Okita, S. Yabukami, K. Yokota, M. Furuya, H. Kanetaka, Y. Miura, H. Takahashi, Y. Watanabe and R. Akiyama, AIP Adv., 2019, 9, 125325. 150. K. Cihalova, D. Hegerova, A. M. Jimenez, V. Milosavljevic, J. Kudr, S. Skalickova, D. Hynek, P. Kopel, M. Vaculovicova and V. Adam, J. Pharm. Biomed. Anal., 2017, 134, 325. 151. M. Liong, A. N. Hoang, J. Chung, N. Gural, C. B. Ford, C. Min, R. R. Shah, R. Ahmad, M. Fernandez-Suarez, S. M. Fortune, M. Toner, H. Lee and R. Weissleder, Nat. Commun., 2013, 4, 1752. 152. H. Lee, E. Sun, D. Ham and R. Weissleder, Nat. Med., 2008, 14, 869. 153. E. Ng, C. Yao, T. O. Shultz, S. Ross-Howe and S. X. Wang, Nanomed. Nanotechnol. Biol. Med., 2019, 16, 10.

CHAPTER 19

Fourth Industrial Revolution (4IR) and Functionalized MNPs PAOLO DI SIA (

0000-0002-6405-0483)a,b

a

University of Padova, School of Science, Department of Chemical Science & Department of Physics and Astronomy, Via Marzolo 8, I-35131 Padova, Italy; b University of Padova, School of Medicine, Department of Neurosciences, Via Giustiniani 2, I-35128 Padova, Italy Email: [email protected]

19.1 Introduction Today we are witnessing a huge revolution, defined as the fourth industrial revolution. Researchers are deeply studying the functioning of human intelligence, in order to apply it to machines, computers, applications and much more. Digitization is changing the global industry and companies are focusing on it to be competitive on the market and improve their efficiency. Furthermore, consumer needs are becoming increasingly important and businesses must therefore be more transparent and change the way they have always acted. Machines will be an aid to humans and there will be a collaboration leading to an increase in overall efficiency. The use of these smart appliances will generate improvement in all areas1 (Figure 19.1). Nanotechnology is one of the six Key Enabling Technologies (KETs), considered a fundamental tool of the European Commission’s Horizon 2020 program, launched to stimulate growth and industrial competitiveness in the near future.2–4 The six KETs are: 1. Nanotechnology; 2. Micro/nanoelectronics; Analytical Applications of Functionalized Magnetic Nanoparticles Edited by Chaudhery Mustansar Hussain r The Royal Society of Chemistry 2021 Published by the Royal Society of Chemistry, www.rsc.org

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Figure 19.1

3. 4. 5. 6.

Industry revolution.

Photonics; Advanced materials; Industrial biotechnology; Advanced production technologies.

The growing attention created around Artificial Intelligence (AI) is motivated by the results achievable thanks to its technological maturity, both in computational calculation and in the ability to analyze in real-time and in a short time huge quantities of data in any form. AI is a great hope for the future in all fields, including the medical one, by highlighting early any risks associated with the patient’s health and lightening and speeding up the task of clinical analysis of doctors. In parallel with the intensification of studies on nanoparticles, it has been also seen a marked increase in the fields of application in which they are used. One of the key points is the concept of functionalization, which is fundamental to understanding how nanoparticles can be used in different areas.5

19.2 On Industry 4.0 Industry 4.0 goes beyond automation and digitalization of the factory and represents a real new economic model for the industrial world. There are many elements that influence the change: – Ability to innovate: one of the key success factors is the ability to innovate and quickly adapt to new technologies, since we live in a time with continuous technological evolution. – Flexibility: is an important factor, allowing one to dynamically adapt production activities, increase the variety of products and reduce production costs.

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– Product customization: nowadays the stakeholder with the most power in the market is the consumer and no longer the supplier; industries must focus on demand and adapt to customer needs. – Decentralization: companies must redefine their organizational structure; centrally controlled organizations are unable to support rapid decision-making activities needed in a flexible production system. – Resource efficiency: the scarcity of resources implies the need to improve the efficiency both economically and ecologically. New advances in automation, digitization and networking are becoming a valid support in various business areas such as healthcare, manufacturing, banking, etc. The fourth industrial revolution is characterized by a fusion of technologies, superposing the lines between the physical, digital and biological world. Today’s revolution is strongly characterized by speed, scope and impact.6 It is generally briefly summarized in the concept of adopting Cyber-Physical systems, improving the fundamental role played by the interconnection between hardware and software, by the interaction between physical objects and IT systems. There are distinctive principles that allow the labeling of a solution as 4.0: – Interoperability: the ability of Cyber Physical Systems, human beings and intelligent factories to connect and communicate with each other, in order to increase their competitiveness. – Virtualization: the ability to create a virtual copy of the intelligent factory by connecting data collected by sensors on physical objects and processes to models of virtual plants or simulation models. – Real-time processing: the ability to collect and analyze data and provide real-time information, so that the system can immediately tackle any problem and management can always be updated. – Decentralization: the ability of cybernetic systems to make decisions on their own, a decentralization of the decision-making process. – Service orientation: the tendency to offer services in addition to physical products, therefore the service becomes an integral part of the product. – Modularity: the tendency to operate with modules, which can be adjusted, replaced, repeated or expanded flexibly in relation to the changing needs and requirements of customers. – Interconnection: interconnected people and objects share information, creating a joint collaboration to achieve common goals. Wireless communication technologies have a key function to increase the interactions between actors and the development of common communication standards. – Information transparency: thanks to sensoristics, data on physical processes can be collected for realizing virtual perspectives of reality and the information of results can allow a transparent decision-making process. – Technical assistance: in intelligent factories, the role of workers passes from an operational one to that of a flexible problem solver. In an

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environment where cyber–physical systems work by creating complex networks, humans need to be supported by assistance systems, in order to address urgent problems or perform unsafe and unpleasant activities in hostile working environments (for example through the use of robots).7,8

19.3 Enabling Technologies The fourth industrial revolution is represented by a series of enabling technologies that represent its engine. Numerous opportunities arise from these, as enabling new business models, mass customization, optimization in resource management, better management of the product life cycle, reduction of time to the market, and the possibility of knowing consumer needs in real time. The digitalization of processes, IoT, objects and people constantly generates data that pass from the physical world to the cybernetic one, generating a huge flow of data that traditional databases are not able to manage. In the cyber world, Big Data technologies allow data collected by extracting information with value in terms of knowledge to be analyzed. Applying analytics to archived data can have a significant impact on production quality, energy savings and maintenance. Big Data and Analytics are key tools for Industry 4.0, allowing the storage of a huge volume of different types of data from multiple sources.9 – Cloud computing: cloud computing infrastructures are large data centers that allow the users to have the resources they need with a pay-per-view formula. The customer can access the services remotely, without the need for installation, updating and backup or maintenance of the infrastructure. Cloud computing allows us to have easy and selective, distributed and on demand access to a series of resources related to the IT or production world. – Augmented reality: augmented reality allows one to extend the normal sensory perception of man through information generally electronically conveyed, which would not be perceptible with the five senses. Through the use of particular wearable devices, it is possible to visualize the real world enriched with virtual objects that allow the operator to get a much greater amount of data than those to which they would have access without using the aforementioned devices. This allows the drastic simplification of complex operations such as maintenance and repairs. Augmented reality does not aim to replace reality, but to increase it in interactive and real-time ways.10 – Additive manufacturing: also referred to as 3D printing, this technology has the ability to produce three-dimensional products from virtual models. This technology enables decentralized production and reduces shipping distances and inventory levels. A goal is to constantly reduce the distance between computer processing and human cognitive processes.11

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– Cybersecurity: the increase of safety levels is a fundamental step for the safety of production chains. This increase is particularly important in a moment of strong transformation, as the 4IR, which will increase the integration between the companies belonging to a chain, consequently increasing the attack surface. A higher level of connectivity through the application of common standards will greatly increase the risk for companies. – Internet of Things (IoT): IoT is the network of physical objects, systems, platforms and applications containing electronics, software, actuators and connectivity, which allows these devices to communicate and share information with each other, with the external environment and with people. The object receives the acquired data on a server from the external environment which, after processing them, formulates the outputs to be sent to the smart object. IoT represents one of the major drivers of productivity and growth for the next few years, allowing the reinvention of entire industrial sectors with a total weight corresponding to at least two thirds of the global market. It is opening new markets, such as telematics, home automation and the Smart City, improving the ability to manage environmental and production resources for sustainable development.12–14 – Internet of Service (IoS): when the value derives from services, which exploit the integration of IoT devices to meet a particular need, we are talking about IoS. Each device connected to the Internet is expected to have a range of intelligent services, creating thus the Internet of Services. – Internet of People (IoP): IoP includes Internet-enabled personal electronics. It is rapidly spreading in the fabric of society, giving a new expansion to increase the consistent growth of mobile phones, tablets and other conventional electronic devices and associated networks and services. Many Internet-enabled peripherals are incorporated into tissues and products. – Internet of Energy (IoE): IoE is the integrated network infrastructure based on standard and interoperable communication protocols that interconnect the energy network with the Internet. IoE can help in achieving great energy savings, thanks to remote monitoring and defining the energy production in relation to the actual demand, calculated through the information collected by IoT, IoS and IoP.15

19.4 On Artificial Intelligence and Machine/Deep Learning This simulation illustrates how the modeled object/system works over time. It is used in many contexts, in order to show the possible real effects of alternative conditions and the consequences of a different course of action.

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It is also very useful in technology for achieving performance optimization or in the product development phase. In most of I4.0 documents dealing with simulation, it is used for the creation and modification of different versions of a new emerging product, for better aligning with customer needs and in the early stages of the product life cycle. With simulation it is possible to intervene on the system without altering the real physical product and with great advantage in terms of costs, time and complexity. Robotic process automation (intelligent automation) is the combination of artificial intelligence and automation and is starting to change the way of doing business. Intelligent automation systems can automate entire work processes, learning and adapting to the changing ecosystems within which they operate. Advances in AI, including machine learning, natural language processing, artificial vision and increased power computing, are creating a new generation of hardware and software robots with practical applications in many different sectors.16 Machines are connected using an interdisciplinary approach based on mathematics, physics, computer science, linguistics, and psychology, allowing a mix suitable for the desired functions to be obtained. AI includes several technologies that allow computers: – to perceive the world (artificial vision, audio processing, sensor processing, etc.); – to analyze and understand the collected information (natural language processing, knowledge representation, etc.); – to make informed decisions (inference engines, forecasts, expert systems, etc.); – to learn and tune in (machine learning, deep learning, etc.). Machine learning makes computers learn and act like humans, improving their learning autonomously over time. The basic premise is the construction of algorithms capable of receiving input data and, using statistical analysis, to predict updating outputs as new data becomes available. The combinations of Machine Learning algorithms consist of: – representation: a set of classifiers or the language a computer understands; – evaluation: scoring function; – optimization: both standard and custom optimization methods are used. Learning machines are useful to humans because, with all their processing power, they are able to highlight faster or find models with huge amounts of data. Machine learning is a tool that can be used to improve human’s ability to solve a wide range of problems, from diagnosing diseases to finding solutions for global climate change.17 Deep Learning is a particular type of Machine Learning that achieves great power and high flexibility. It involves studying and planning machine algorithms for learning a good data representation at multiple levels of abstraction

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(unsupervised algorithms), used for more complex processing tasks than supervised learning systems, including image recognition, text-to-speech and natural language generation. These neural networks work by analyzing millions of examples of training data and automatically identifying often subtle correlations between many variables. Once trained, the algorithm can use its association bank to interpret new data.18 Recently, machines are performing many more intelligent activities using cognitive intelligence as opposed to the natural intelligence shown by humans and animals. Companies around the world are leveraging AI to optimize their processes. The main application areas are: – E-commerce: AI technology provides a competitive advantage for e-commerce businesses and is becoming readily available for companies of any size and budget. The AI software labels, organizes and visually searches the contents by labeling the characteristics of the image or video. – Communication in the workplace: AI helps companies in improving inner and outer communication, allowing individual customization, greater focus and productivity. – Human resources management: AI and Machine Learning are drastically changing the way human resources and recruitment work in every company. It might essentially eliminate all negative elements of any HR professional job (worldly screening, long paperwork and annoying data entry), as well as providing powerful tools and insights. – Healthcare: AI will have a major impact on the healthcare industry, improving reliability, predictability and consistency in terms of patient quality and safety. While it cannot replace doctors and nurses, it can make them more effective, efficient and happier at work as it takes away the cognitive load, reducing stress. – Logistics and supply chain: AI allows companies to act on consumer data for promoting improvements in many areas of supply chain operations. Consumers demand shorter delivery times from retailers and retailers expect the same from manufacturers and distribution centers. Robotic picking systems are allowing supply chains to meet demand seven days a week. – Simplified production: large amounts of data are streamed in milliseconds from the machine, helping to reduce non-productive machine downtimes and predict failures.19–21

19.5 Nanotechnology: Applications of Functionalized Nanoparticles In recent years, parallel to the intensification of studies on nanoparticles, a marked increase in the fields of application in which they are used have also been seen. One of the key points in this field is the concept of functionalization, fundamental to understanding how these can be used in different areas.

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Metallic nanoparticles (whether they consist of oxides or pure metals) basically constitute the core of the nanomaterial, while other compounds are used as the coating to exploit the properties of both. Normally the core is protected by one or more layers of materials (for example silicon, carbon, biological molecules, etc.) which also act as binders for any further coatings that guarantee the functionalization of nanoparticles.22–24 Depending on the applications, the size and uniformity can also be of fundamental importance, because the intrinsic properties of nanoparticles are heavily related to their size and because the application requires specific details (as is the case in which a particle must be able to penetrate a cell membrane). Among the applications in which the use of magnetic nanoparticles are more affirming, we have: – Diagnostic imaging: diagnostic imaging refers to the characterization and measurement of biological processes at the cellular or molecular level. Among the various ways used are optical bioluminescence, fluoroscopy, ultrasound, magnetic resonance, magnetic resonance spectroscopy, single photon emission tomography and positron emission tomography. This has led to the development of techniques based on the combination of two or more types of diagnostics; appropriately functionalized nanomaterials are used to make this possible.25 – Magnetic nanoparticles as contrast agents in Magnetic Resonance Imaging (MRI): this is one of the most powerful and less invasive methods of imaging diagnostics used in medicine. – MRI and optical imaging diagnostics: this is a well-known method which normally involves the use of organic dyes for facilitating an easier evaluation of obtained images. – MRI and Positron Emission Tomography (PET): PET is an imaging technique based on the reception of the signal emitted by radio-drugs formed by tracer isotopes capable of emitting positrons that are injected or inhaled. Once the drug is entered into the physiological system, it reaches a determined concentration within the tissue to be analyzed. The isotope decays very quickly and emits a positron with very short life that annihilates with an electron and emits a pair of gamma photons in opposite directions. These electrons reach a scintillator where a photomultiplier allows the detection of the light field created by photons. From the revelation of photons it is possible to identify the area from which they come. Among the elements capable of emitting positrons we have carbon, nitrogen, oxygen and fluorine.26 – MRI and computed tomography: this is an imaging diagnostics method, which uses ionizing radiation (X-rays) and allows one to reproduce sections or layers (tomography) of a patient’s body and carry out threedimensional processing; the image production requires the intervention of a data processor. The image is made by measuring the attenuation undergone by an X-ray beam passing through the sample.

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19.6 Targeted Transport of Medicines (Drug Delivery) and Genes Magnetic nanoparticles have proven to have a high effectiveness in order to obtain the targeted transport of drugs, for example for cancer treatment. There are many types of materials used for this purpose, such as macromolecules, micelles, liposomes, and various types of polymers. In these systems the substances are bound, trapped, absorbed or encapsulated inside or on the surface of nanomatrices. However, nanoparticles have proven to be a viable alternative to all these methods. Nanoparticles coated with various substances can be functionalized in a way to be easily absorbed by particular types of tissues or can be directed to some areas thanks to the action of an external magnetic field; this is the case of nanoparticles functionalized with contrast agents, used for diagnostic imaging. Evolutions have also occurred in the field of gene therapy, where DNA or RNA are transported within cells for the treatment of many diseases. There are several methods of transporting genetic material, such as microinjection, electroporation, co-precipitation of calcium–phosphate and technologies related to liposomes. As in many other cases, the use of magnetic nanoparticles is much more effective and efficient.27

19.7 Physiological Tissues Treatment Another important field of application of functionalized nanoparticles is the use in order to reproduce physiological tissues including bone surface. Natural bones have a substantially porous surface with a roughness in the order of hundreds of nm. If the surface of artificial bones is left completely smooth, there is the possibility that the body tries to reject them, and that fibrous tissues try to cover the surface causing inflammation and, in the worst case, rejection. Creating surface porosities on prostheses (for example of a hip or knee), decreases the chance of rejection and there is a stimulation to the production of osteoblasts, responsible for the growth of the internal matrix structure of bones. The effect has been widely verified with the use of materials such as metals, polymers and ceramics. Among the most used materials for the creation of prostheses is titanium, which has a high fracture point as well as a reduced weight. Unfortunately, osteoblasts fail to adhere to its surface. To remedy this problem, apatite coatings are used (apatites are minerals with the generic formula Ca5(PO4)3 [F, Q, OH]; Ca5(PO4)3(OH) is hydroxyapatite, the main component of bones). Initially these coatings were created with types of processes that led to poor adhesion and a not uniform thickness of the external coating. Subsequently, it has been used for a slow controlled growth process of nanocrystals of approximately 60 nm in size. This film

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has a uniform thickness and adheres much more firmly to titanium, guaranteeing higher mechanical resistance.28

19.8 Metals – Iron: is a ferromagnetic material with a high magnetic moment density (220 emu g1). Nanoparticles with a size smaller than 20 nm are superparamagnetic. The preparation of iron nanoparticles is complex because they often contain impurities or oxidize easily. – Cobalt: is a ferromagnetic material and occurs in two allotropic forms with centered body and centered faces respectively. The transition temperature between the two phases is 449 1C. – Nickel: is a ferromagnetic material that looks like a crystal lattice with centering faces. A deep interest is focusing on it, given the various potential medical applications. This material is interesting for the realization of solutions that are physiologically compatible. – Iron–Cobalt: Iron–Cobalt alloy has a centered body cubic structure. It is excellent as a magnetic material with a practically negligible crystallographic anisotropy. The magnetization of saturation reaches its maximum value when it has a cobalt content of 35%. – Iron–Nickel: Iron–Nickel alloys are non-magnetic or slightly ferromagnetic if the Nickel quantity is over 30%. Iron–Nickel nanoparticles have a very low saturation magnetization whatever the ratio between metals. With a quantity of nickel equal to 37%, a low value for the Curie temperature is obtained and crystals have a cubic structure with centered faces. Particles are obtained with around 12–80 nm in size, and are superparamagnetic in a very wide range of temperature. – Iron–Platinum: nanoparticles formed from an Iron–Platinum alloy are made up of a tetragonal structure with centered faces and have a very high value of magneto-crystalline anisotropy, equal to 10 times that of a normal Cobalt–Chromium alloy. They also exhibit very high coercivity at room temperature even for particles of only a few nanometers in size, a characteristic that makes them possible candidate particles for the next generation of storage devices and permanent magnets. – Metal oxides: are used in a wide range of applications, and occur in various structures and states. With regard to their magnetic and chemical properties, there is a clear dependence on size and degree of hydration. Superparamagnetic particles of iron oxide are classified according to their size in SPIOs (Superparamagnetic Iron Oxide), with a diameter of above 30 nm, and USPIOs (Ultrasmall Superparamagnetic Iron Oxide), with a diameter of less than 30 nm. The latter ones find many applications in the medical field thanks to their scarce toxicity, high saturation magnetization and high magnetic susceptibility. Magnetite (Fe3O4) has interesting characteristics, especially for the presence of iron cations in the two valence states Fe21 and Fe31. They are interesting in terms of the medical field, despite some obstacles.29–32

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19.9 Conclusions AI is one of the most promising technologies of our time, as it has the ability to save lives, to elaborate forecast purchases, and to increase productivity in agriculture. It can benefit the whole society, in all sectors, both in daily life and in people’s work. It can redefine different sectors such as health and supply chain. Doctors can rely on software to have precise diagnoses in a short time. The entire healthcare sector will improve thanks to the different devices available to the patient who is then not forced to go to the doctor for any problem. The digitization of supply chain leads to an improvement of the entire production chain and logistics, with waste elimination. AI today represents a reality, and no longer a hypothesis, determining a big impact on the social and economic reality.33 With the increase in potentially automated activities, it is possible that there will be an increase in unemployment. Recent studies claim that the 4IR will lead, in less than 10 years, to a loss of millions of jobs, involving the most developed world economies. Some experts and researchers do not share this pessimistic view, highlighting that the introduction of mechanization in agriculture pushed many workers towards cities to find a job in industry and how automation and globalization determined the movement of many workers from the industrial sector to the service one. They argue that the crisis of a sector generally leads to the development of a new one (sometimes unexpected) and to the creation of new needs to satisfy, thus opening up new economic prospects. The use of robots absolves the staff from carrying out repetitive and standardized activities, allowing people to have more productive specialized knowledge and skills gained over years of work. Both positions (pessimistic and optimistic) agree on the fact that it will be necessary to direct many efforts in the adaptation of training, both professional and of the school system, in order to develop intellectual and personal skills that allow new generations to work optimally and take advantage by the new smart machines. Alongside these undoubted advantages, there are a number of risks for humanity, closely related to the use of AI applications and the use of robots, such as drones with weapons used for military missions (which could be responsible for humanitarian violations), AI systems that could put in crisis companies, industries and entire countries from an economic and financial point of view. Hence there is the need to define appropriate principles for the design of AI systems who work independently, so that they are reliable and safe for humanity; it is necessary that these systems respect legality and follow appropriate ethical principles in making decisions and processing data. These aspects have been defined as roboethics, or ethics applied to robotics, whose purpose is to develop universally shared scientific, cultural and technical tools and knowledge for promoting and encouraging the development of robotics towards the well-being of society and people and for preventing their use against humans.34

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In relation to nanotechnology, despite the various progress made in the synthesis processes, the production of nanoparticles with well-defined characteristics and a complete understanding of mechanisms that regulate the synthesis processes (dictated by complex physical–chemical interactions) still represent a work in progress. Furthermore, the synthesis of magnetic nanoparticles often requires the use of toxic or expensive reagents. Research is looking towards synthesis processes which are more respectful of the environment and economically sustainable and efficient.35 The way in which the individual nanoparticles interact with each other has led to the production of complex nanostructures with fruitful applications in many areas. Complex three-dimensional structures can be created, demonstrating that the refinement of the synthesis techniques guarantees a complete control over their response to various magnetic, electrical, optical and mechanical stimuli. The functionalization is necessary to protect magnetic nanoparticles in the event that these ones present high reactivity or toxicity. It is therefore necessary to refine the techniques aimed at the functionalization of nanoparticles, to ensure stability at high temperatures and in highly acidic or basic media, as well as the possibility of obtaining solutions that are physiologically compatible.36 Another fundamental direction of research is that of the production of structures composed of several different materials that exhibit multiple properties (magnetic-optical-electric-thermal properties) and allow bonds with particular substances such as DNA, antibodies and proteins to be obtained. Functionalization therefore no longer has a protective purpose, but is an active part in the world of nanoparticles. In biomedical sectors, nanoparticles are occupying a key role replacing many techniques that have been established for years and bringing substantial improvements in many other areas of research and diagnostics.37–51

Websites of Interest – https://www.plantautomation-technology.com/articles/industrialnanotechnology-the-major-revolutionizer-of-the-fourth-industrialrevolution#:B:text=Industrial%20Nanotechnology%20%2D%20The% 20Major%20Revolutionizer,be%20micro%20or%20macro%20size. – https://www.tsecny.org/the-fourth-industrial-revolution-explained/ – https://genesisnanotech.wordpress.com/2016/05/14/nanotechnologyand-the-fourth-industrial-revolution-solving-our-biggest-challengeswith-the-smallest-of-things/ – https://www.boldbusiness.com/digital/leveraging-nanotechnologyapplications-manufacturing/ – https://innovate.ieee.org/innovation-spotlight-ieee-fueling-fourthindustrial-revolution/ – https://www.weforum.org/agenda/2017/02/lessons-from-nanotech-forthe-4th-industrial-revolution/

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References 1. K. Schwab, The Fourth Industrial Revolution, New York, 2017, Currency. 2. P. Di Sia, The Nanotechnologies World: Introduction, Applications and Modeling, in Nanotechnology, Fundamentals and Applications, ed. S. Sinha and N. K. Navani, Studium Press, Houston, 2013, vol. 1, http:// www.studiumpress.in/indetail.asp?id=210. 3. P. Di Sia, Present and Future of Nanotechnologies: Peculiarities, Phenomenology, Theoretical Modelling, Perspectives, Rev. Theor. Sci., 2014, 2(2), 146–180. 4. P. Di Sia, Present and Future of Nano-Bio-Technology: Innovation, Evolution of Science, Social Impact, Online J. Educ. Technol., 2015, 2, 442. 5. J. Gao, H. Gu and B. Xu, Multifunctional Magnetic Nanoparticles: Design, Synthesis and Biomedical Applications, Acc. Chem. Res., 2009, 42(8), 1097–1107. 6. K. Kumar Pabbathi, Quick Start Guide to Industry 4.0: One-stop Reference Guide for Industry 4.0, Create Space Independent Publishing Platform, 2018. 7. P. Di Sia, Looking at the Quantum Internet, Int. Acad. J. E-methodol., 2017, 4, 31–35. 8. L. J. Wells, J. A. Camelio, C. B. Williams and J. White, Cyber-physical security challenges in manufacturing systems, Manuf. Lett., 2014, 2(2), 74–77. ¨hlke, Human-machine9. D. Gorecky, M. Schmitt, M. Loskyll and D. Zu interaction in the industry 4.0 era, in 12th IEEE International Conference on Industrial Informatics (INDIN), Porto Alegre, Brazil, 2014, http://doi. org/10.1109/INDIN.2014.6945523. 10. N. Y. Kim, S. Rathore, J. H. Ryu and J. H. Park, A Survey on Cyber Physical System Security for IoT: Issues, Challenges, Threats, Solutions, J. Inform. Process. Syst., 2018, 14(6), 1361–1384. ´nez, L. Romero, I. A. Domı´nguez, M. del Mar Espinosa and 11. M. Jime M. Domı´nguez, Additive Manufacturing Technologies: An Overview about 3D Printing Methods and Future Prospects, Complexity, 2019, 30. 12. M. Barlow and C. Levy-Bencheton, Smart Cities, Smart Future: Showcasing Tomorrow, Wiley, Hoboken, 1st edn, 2019. 13. T. M. Siebel, Digital Transformation: Survive and Thrive in an Era of Mass Extinction, RosettaBooks, New York, 2019. 14. M. Curley and B. Salmelin, Open Innovation 2.0: The New Mode of Digital Innovation for Prosperity and Sustainability (Innovation, Technology, and Knowledge Management), Springer, Berlin, 2018 edition, 1st edn, 2017. 15. The Internet of People, Things and Services: Workplace Transformations, ed. C. A. Simmers and M. Anandarajan, Routledge, New York, 2018. 16. G. Blokdyk, Intelligent Process Automation – A Complete Guide, 5STARCooks, London, 2018. 17. A. Burkov, The Hundred-page Machine Learning Book, Andriy Burkov, 2019.

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18. K. M. Lynch and F. C. Park, Modern Robotics: Mechanics, Planning, and Control, Cambridge University Press, Cambridge, 1st edn, 2017. 19. P. Mckinnon, Robotics: Everything You Need to Know about Robotics from Beginner to Expert, CreateSpace Independent Publishing Platform, 2016. 20. P. Di Sia, Analytical Nano-Modelling for Neuroscience and Cognitive Science, J. Bioinform. Intell. Control, 2014, 3(4), 268–272. 21. P. Di Sia, Relativistic nano-transport and artificial neural networks: details by a new analytical model, Int. J. Artif. Intell. Mechatronics, 2014, 3(3), 96–100. 22. P. Di Sia, A new analytical transport model for (nano)physics, Int. Res. J. Eng. Technol., 2015, 2(7), 1–4. 23. P. Di Sia, Mathematics and Physics for Nanotechnology – Technical Tools and Modelling, Pan Stanford Publishing, 2019, http://www.panstanford. com/books/9789814800020.html. 24. A.-H. Lu, E. L. Salabas and F. Schuth, Magnetic Nanoparticles: Synthesis, Protection, Functionalization and Application, Angew. Chem., Int. Ed., 2007, 46(8), 1222–1244. 25. R. Hao, R. Xing, Z. Xu, Y. Hou, S. Gao and S. Sun, Sunthesis, Fuctionalization and Biomedical Applications of Multifunctional Magnetic Nanoparticles, Adv. Mater., 2010, 22, 2729–2742. 26. P. Di Sia, Advances in Analytical Modelling for (Nano)medicine, Int. J. Innovative Sci., Eng. Technol., 2016, 3(5), 511–515. 27. P. Di Sia, Interesting Details about Diffusion of Nanoparticles for Diagnosis and Treatment in Medicine by a new analytical theoretical Model, J. Nanotechnol. Diagn. Treat., 2014, 2(1), 6–10. ´ and M. R. Ibarra, Magnetic Nanoparticles for 28. G. F. Goya, V. Grazu Cancer, Curr. Nanosci., 2008, 4, 1–16. 29. P. Di Sia, Nanotoxicology and human health, World Sci. News, 2018, 100, 86. 30. A. G. Roca, R. Costo, A. F. Rebolledo, S. Veintemillas-Verdaguer, P. Tartaj, T. Gonzalez-Carreno, M. P. Morales and C. J. Serna, Progress in the preparation of magnetic nanoparticles for applications in biomedicine, J. Phys. D: Appl. Phys., 2009, 42, 224002. 31. N. A. Frey, S. Peng, K. Cheng and S. Sun, Magnetic Nanoparticles: Synthesis, functionalization and applications in bioimaging and magnetic energy storage, Chem. Soc. Rev., 2009, 38, 2532–2542. 32. P. Di Sia, On surface electron mobility of nanomaterials for cancer nanotechnology, Int. J. Appl. Adv. Sci. Res., 2018, 3(2), 46–50. 33. Beyond the Internet of Things: Everything Interconnected, ed. J. M. Batalla, G. Mastorakis, C. X. Mavromoustakis and E. Pallis, Springer, Berlin, 2017 edition, 1st edn, 2016. 34. P. Rubin, Future Presence: How Virtual Reality Is Changing Human Connection, Intimacy, and the Limits of Ordinary Life, HarperOne, New York, 2018. 35. P. Di Sia, Nanotechnologies among Innovation, Health and Risks, Procedia Soc. Behav. Sci. J., 2017, 237, 1076.

Fourth Industrial Revolution (4IR) and Functionalized MNPs

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36. J. Zaleski, Connected Medical Devices: Integrating Patient Care Data in Healthcare Systems, HIMSS Publishing, Boca Raton, 1st edn, 2015. 37. P. Di Sia, Quantum-Relativistic Velocities in Nano-Transport, Appl. Surf. Sci., 2018, 446, 187–190. 38. H. Zhou and S. B. Bhaduri, 3D printing in the research and development of medical devices, in Biomaterials in Translational Medicine - A Biomaterials Approach, Woodhead Publishing Series in Biomaterials, 2019, pp. 269–289, https://doi.org/10.1016/B978-0-12-813477-1.00012-8. 39. R. Tong, Wearable Technology in Medicine and Health Care, Academic Press, London, 1st edn, 2018. 40. P. Di Sia, Graphene nanostructures for gas and biological sensors, in Toxic Gas Sensors and Biosensors, ed. Inamuddin, R. Boddula and A. M. Asiri, Materials Research Forum, USA (to appear in 2021). 41. C. M. Hussain, Magnetic Nanomaterials for Environmental Analysis, in Advanced Environmental Analysis-Application of Nanomaterials, ed. C. M. Hussain and B. Kharisov, The Royal Society of Chemistry, 2017. 42. D. Sharma and C. M. Hussain, Smart nanomaterials in pharmaceutical analysis, Arabian J. Chem., 2018, 13(1), 3319–3343. 43. R. Keçili and C. M. Hussain, Recent Progress of Imprinted Nanomaterials in Analytical Chemistry, Int. J. Anal. Chem., 2018, 8503853. ¨yu ¨ktiryaki and C. M. Hussain, Advancement in bioana44. R. Keçili, S. Bu lytical science through nanotechnology: Past, present and future, TrAC, Trends Anal. Chem., 2019, 110, 259–276. ¨yu ¨ktiryaki, Y. Su ¨mbelli, R. Keçili and C. M. Hussain, Lab-On-Chip 45. S. Bu Platforms for Environmental Analysis, in Encyclopedia of Analytical Sci´, Academic ence, ed. P. Worsfold, C. Poole, A. Townshend and M. Miro Press, 3rd edn, 2019, pp. 267–273. 46. J. Sengupta and C. M. Hussain, Graphene and its derivatives for Analytical Lab on Chip platforms, TrAC, Trends Anal. Chem., 2019, 114, 326–337. 47. C. M. Hussain, Nanomaterials in Chromatography: Current Trends in Chromatographic Research Technology and Techniques, Elsevier, 2018. 48. C. M. Hussain and R. Keçili, Modern Environmental Analysis Techniques for Pollutants, 1st edn, 2019, Elsevier. 49. C. M. Hussain, Handbook of Nanomaterials in Analytical Chemistry: Modern Trends in Analysis, Elsevier, 2019. ¨yu ¨ktiryaki, R. Keçili and C. M. Hussain, Functionalized nanoma50. S. Bu terials in dispersive solid phase extraction: Advances & prospects, TrAC, Trends Anal. Chem., 2020, 127, 115893. 51. C. M. Hussain, Handbook on Miniaturization in Analytical Chemistry: Application of Nanotechnology, Elsevier, 2020.

Section 6: Toxicity, Safety and Risk and Legal Aspects of Functionalized Magnetic Nanoparticles

CHAPTER 20

Important Aspects of Safety, Risk & ELSI of Functionalized Magnetic Nanoparticles for Analytical Purposes ˘ LU, FATMA GO ¨ ZDE YU ¨ CE AND HATI¨CE DURAN* SENEM ÇI¨TOG

Department of Materials Science and Nanotechnology Engineering, TOBB University of Economics and Technology, Ankara 06560, Turkey *Email: [email protected]

20.1 Introduction Nanomaterials can possess different toxic behavior than that of their bulk form due to nanoscale size effects. The potential hazards of nanomaterials are a major concern that limits their use. Advancements in nanoscience, increasing interest in magnetic nanoparticles (MNPs) having a wide range of potential applications, and availability of MNPs in daily life products (such as MagVigent which is a type of MNP for DNA capture and purification, and MyQuVigent which is combination of MNPs and quantum dots for imaging, manipulation and detection)1 has alarmingly raised the concerns on the potential risks and toxic effects of the MNPs on the environment and human beings, and make comprehensive toxicity and risk assessment an essential requirement prior to its end use to guarantee safety and avoid potential health hazards upon exposure. Nanoparticles (NPs) can be exposed on purpose during their use in biomedical and environmental applications, as well as Analytical Applications of Functionalized Magnetic Nanoparticles Edited by Chaudhery Mustansar Hussain r The Royal Society of Chemistry 2021 Published by the Royal Society of Chemistry, www.rsc.org

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unintentionally before or after their use. Not only direct exposure to NPs during the intended application responsible for the toxicity of the NPs but also remaining nanoparticles after their use can cause biological adverse effects on organisms and the environment. When NPs enter and accumulate in an organism or the environment, they may undergo many transformations such as dissolution, aggregation, surface degradation, interaction with biomacromolecules or environmental pollutants, which results in changed physicochemical characteristics of the NPs, which could influence the toxicity of functionalized magnetic nanoparticles (FMNPs). Besides, the presence of surface coating on FMNPs can alter these transformations. Therefore, to evaluate the potential toxic risks of the FMNPs, the toxicity of nanomaterials as a whole and each component as well as the transformation-related toxic effects of the NPs need to be examined. Among all the types of FMNPs, iron oxide nanoparticles (IONPs) are the most commonly used in application fields such as drug delivery, water treatment, hypothermia applications, imaging, cancer diagnosis and treatment. The main types of IONPs used in environmental and biomedical fields can be listed as magnetite (Fe3O4), hematite (a-Fe2O3) and maghemite (g-Fe2O3) due to their controllable size and surface area, magnetism, biocompatibility, and the ability to be produced to have different shapes and coatings. IONPs are used in the form of superparamagnetism which are called superparamagnetic iron oxide nanoparticles (SPION). This chapter will focus on the major points concerning FMNP toxicity, and explain the mechanisms responsible for FMNP toxicity and possible scenarios regarding the environmental and human hazards and risks issues of FMNPs, and then will address some of the most recent studies on in vitro and in vivo toxicity of the FMNPs with potential use for analytical applications.

20.2 Toxicity of FMNPs FMNPs are of great interest in analytical chemistry applications due to their unique magnetic properties, which have the potential to improve the performance of existing methodologies. However, increasing production and applications of MNPs have raised great concerns about their impact and potential risks on the environment and to human health due to their nanoscale properties. NPs can enter into the host systems via different pathways. The main routes of the entry of NPs are inhalation, skin penetration, intravenous injection and ingestion.2 The small size of NPs which is comparable to biomolecules, cells and cellular organelles enables them to penetrate the cell membrane easily, to diffuse from blood vessels and to be sequestered into various body systems. The physical and chemical characteristics of NPs such as size, shape and surface properties play a decisive role on the fate of the NPs and on their toxicity. Modifying NPs with neutral and hydrophilic compounds (i.e., polyethylene glycol (PEG), polysaccharides, etc.) extends the circulation half-life in the blood stream from minutes to hours and even days.3 Smaller NPs show relatively higher uptake than larger

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ones and positively charged NPs generally have faster blood clearance than neutral ones due to the high affinity with plasma proteins and rapid clearance of macrophages. Positively charged NPs are usually taken up into the cells more efficiently as a result of the electrostatic interactions between the negatively charged cell membrane and NPs. Therefore, they tend to increase toxicity. It was reported that 10 nm PEGylated IONPs exhibited relatively higher cellular uptake and tumor accumulation than 30 nm ones.4 Also, PEIcoated IONPs with a positive surface charge were internalized more efficiently than neutral PEGylated IONPs with the same particle size and had stronger cytotoxicity, faster clearance, and less tumor distribution compared to PEGylated ones. These studies clearly demonstrate that surface charges whether positive or negative increase liver uptake compared to neutral NPs. PEGylated IONPs remained in the liver and spleen after two weeks of administration, which had slower degradation and removal than positively charged IONPs.4 Negatively charged NPs, on the other hand, can also enter the cells and they show lower toxicity with respect to positively ones. Additionally, increased reactivity of NPs at the nanoscale may make them more reactive toward surrounding biological components and cause a change in their biocompatibility. The degree of biocompatibility varies with different shapes, surface modifications, NP concentration and type of cell culture medium. The different morphologies of NPs cause different cell interactions with NPs, which can help facilitate their potential internalization into cells and effect the toxicity. For example, a study5 reported that rod-shaped IONPs were more toxic than spherical ones due to high surface area to volume ratio of the rod-shaped NPs, which relate closely to cytotoxicity. Additionally, rodlike NPs showed much more efficient cellular uptake (Hela and caco-2 cells), compared to the lower aspect ratio NPs.6 Toxicity of NPs is also nanoparticle concentration and exposure timedependent. Bayat et al.7 investigated the effect of cell type on the toxicity of IONPs and found the endothelial cells were more sensitive than keratinocytes for four IONPs with different surface functionalization (tri-sodium citrate (TSC), polyethylenimine (PEI), aminopropyl-triethoxysilane (APTES) and chitosan). On the other hand, in vitro toxicity of IONPs is dosedependent.8,9 At doses below 100 mg ml1, IONPs were generally found to have low or no cytotoxicity.10 The lack of observable toxicity at lower doses of the IONPs is due to the clearance of the IONPs from the body. In the case of high dose exposure, IONPs may trigger cellular stress and altered response. The type of cell culture medium is another important factor that determines the cytotoxicity.11 Proteins and other nutrients in cell culture medium may be adsorbed onto the NPs and become inaccessible for cellular activities, thus the changes in cell growth and viability are observed. Furthermore, cell culture medium may influence the colloidal stability of the NPs and the NP–cell interactions. For instance, negatively charged NPs can bind to the serum proteins of the medium and lead to protein denaturation, which can cause cytotoxicity.

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As a result, surface properties of the MNPs can exert vigorous effects on NP size, aggregation, stability, and therefore impact on cellular interaction, eventually affecting the fate and uptake of the MNPs. Cytotoxicity can be substantially minimized by an appropriate choice of surface material, size and shape of MNPs.

20.3 Biodistribution and Bioelimination of Nanoparticles Size, surface properties and shape of the NPs are the most important parameters on the fate of biodistribution and bioelimination phenomenon. From the magnetic properties view, larger MNPs provide greater magnetization than smaller ones owing to decreased disordering of the surface spins. Therefore, larger MNPs are more desirable for biomedical applications due to their better magnetic properties. However, the physiological and cellular barriers which determine biodistribution and clearance of the MNPs do not allow usage of large sizes. For example, it is reported that MNPs diameters larger than 100 nm are readily taken up by the reticuloendothelial system (RES) (i.e., liver, spleen) while the ones smaller than 10 nm are excreted renally.12 Even accumulation of medium-sized MNPs in the bone marrow, heart, kidney and stomach is reported.13 The biodistribution patterns of MNPs have been defined as 80–90% in the liver, 5–8% in the spleen and 1–2% in bone marrow.14 Therefore, in order to avoid rapid clearance of MNPs through kidneys and RES and to provide them with prolonged blood circulation half-life, the hydrodynamic size of the MNPs after surface modification should stay in the range of 10–100 nm after surface modification. Interface chemistry, such as charge type, charge distribution and hydrophobicity, can also affect biodistribution of NPs. Charged NPs are easily recognizable by RES due to their opsonization. This causes the removal of NPs from circulation and results in short circulation time.13 Positively charged NPs can bind to non-targeted cells because of their electrostatic interaction with the negatively charged cell membrane. This leads to undesired non-specific internalization. On the other hand, hydrophobic surface groups of the NPs induce agglomeration and cause rapid removal of them by the RES.13 The NP shape effect was the least investigated parameter on the biodistribution and bioelimination. Nevertheless, it has been reported that MNPs with a shape of a high-aspect ratio had enhanced blood circulation times compared to spherical NPs.13 Non-spherical NPs can avoid bioelimination better than spherical ones. Shape and size of the NPs also influence cellular uptake of NPs. The elliptic or cylindrical NPs have a higher surface area than the spherical NPs, which facilitates multivalent interaction of them with the cell surface. Therefore, those NPs showed higher cellular uptake than spherical ones with the same diameter.15 On the other hand, smaller NPs can escape better from RES compared to the larger ones, and they are taken up more efficiently into the cell.15

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20.4 Mechanism of NP Toxicity Toxicity assessment is a critical point in developing nanoformulations and determining the potential adverse biological effects, and safety and risk issues associated with NPs and therefore, it should be examined thoroughly and carefully. Understanding the toxicity mechanisms of NPs is essential to determine their effects on living organisms and the environment during and/or after their use in a wide variety of applications. The major toxicity mechanisms of NPs may arise from three factors: (i) direct association of NPs with the cell membrane of an organism, where the membrane can be damaged or initiate internal signaling pathways that damage the cell, (ii) dissolution of the NPs, releasing toxic ions that impact the organism, generally through impairing important enzyme functions or through direct interaction with a cell’s DNA, and (iii) the generation of reactive oxygen species (ROS) and subsequent oxidative stress on an organism, which can also damage important enzymes or an organism’s genetic material.16 Figure 20.1 shows possible toxicity effects of MNPs. Figure 20.2 represents possible toxicity mechanisms for iron-based NPs, which are the most commonly used MNPs in analytical applications. One of the possible ways that NPs induce toxicity is through direct interaction with the cell surface. When NPs interact with single-celled organisms (such as bacteria), they mostly stay on the cell surface, where they can cause lipid membrane deterioration, initiation of internal signaling pathways that damage the cell, and dissolution of NPs which release cell-permeable toxic

Figure 20.1

Potential toxicity effects of MNPs. Adapted from ref. 14, https://doi.org/10.3390/molecules25143159, under the terms of the CC BY 4.0 license, https://creativecommons.org/licenses/ by/4.0/.

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Possible mechanisms of iron-based nanoparticle-induced toxicity at the cellular level. Reproduced from ref. 18 with permission from Elsevier, Copyright 2017.

ions at the bacterial surface, potentially resulting in cell death.16 Cellular uptake of NPs is also a possible interaction mechanism between NPs and bacterial cells, inducing the toxicity by damaging mitochondria or nuclei.17 For multicellular organisms, strong NP–cell interactions can lead to NP uptake by cells. For instance, when IONPs are injected intravenously, they may interact with plasma proteins and release ferrous ions (Fe21). They may later be internalized into cells. Alternatively, they are efficiently internalized by cells via passive diffusion and/or endocytosis directly because of their fine size. Following internalization, the IONPs can easily enter into the nuclear membrane and may cause direct DNA damage resulting in ROS generation. Furthermore, the released ROS leads to nucleic acid damage and causes breaking of H-bonding in a DNA structure when its concentration reaches an excess level. The other possibility is that the IONPs may presumably be degraded into iron ions by hydrolysis within the lysosomes. The free iron in the form of Fe21 ions can potentially cross the nuclear or mitochondrial membrane barrier through the divalent metal transporter-1 (DMT1) into the cytosol. Then, they undergo the Fenton reaction with H2O2 and O2 produced by the mitochondria to form highly reactive –OH radicals and ferric ions. The generated –OH radicals can indirectly damage DNA, proteins and lipids and it can result in altered expression of various genes such as those involved in cell cycle regulation, iron homeostasis and pancreatic functioning.9,10,19 The potential mechanisms responsible for in vitro toxicity of IONPs is the generation of excessive ROS such as O2 and H2O2. ROS can be generated by four different ways in response to IONPs: (i) direct generation from the NP

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surface; (ii) altering mitochondrial and other organelle functions, (iii) induction of cell signaling pathways and (iv) production via leaching of Fe21 ions.11 Normally, ROS generation is counterbalanced by the action of antioxidant enzymes and other redox molecules. When its production reaches excess levels, an imbalance between free radicals and antioxidants occurs, which is known as oxidative stress. While low levels of oxidative stress enhance transcription of defense genes and cause elevated levels of antioxidant enzyme expression to combat ROS, excess levels of it can cause lipid peroxidation, DNA strand breaks, alteration in gene transcription, decline in physiological function and eventually causes cell death.19,20 The IONPs may also cause plasma membrane toxicity. They can stimulate the redox reactions and up-regulate plasma membrane proteins, resulting in cellular stress and ultimately cell death.9 Another mechanism by which IONPs can trigger toxicity is via iron overload. It is well known that to be used in medicine IONPs are required to be targeted to a specific tissue/organ. However, excessive accumulation of IONPs in the target tissue results in high concentration of free iron ions, which can lead to homeostatic imbalance, oxidative stress, cellular damage and even DNA damage. Excess iron is also associated with an increasing risk of cancer, especially in the liver.11 It is also thought that up-regulation of ferritin and down-regulation of transferrin receptors in cells may protect them from possible cytotoxicity.21 Another possibility is that IONPs can be degraded and cleared from circulation by the endogenous iron metabolic pathways.

20.5 Toxicity Effect on the Environment: Nanoecotoxicity NPs can exist in the environment from both natural sources (such as volcanic emissions, forest fires, mineral composites, viruses) and anthropogenic sources (such as diesel exhaust, welding fumes, and industrial effluents). Considering the concerns about environmental NP toxicity (nanoecotoxicity), which refers to the toxic effects of nanomaterials on plants, fungi, animals, microbes and is intimately linked with humans, nanoecotoxicity mainly arises from produced nanomaterials. There are three scenarios for environmental NP emission: they can be released into the environment (i) during their production, (ii) during their use, or (iii) after disposal of products containing them (waste handling).22 Once NPs are released into the environment, they may accumulate in air, soil, and water, and may disrupt abiotic components such as pH, and ionic strength, which may pose serious threats to plants, animals, and organisms that live in them, and ultimately can affect the functioning of ecosystems.23,24 NPs can also interact with environmental pollutants such as heavy metals and organic pollutants, which may cause a change in the environmental behavior and toxicity of these pollutants.25–27 For instance, Cd phytotoxicity reduction induced by magnetite (Fe3O4) and maghemite (g-Fe2O3) NPs in four plant species (tomato, cucumber, carrot and lettuce) was reported.28 The interaction may also alter the physicochemical property and toxicity of the NPs.29 In air, soil and water, NPs

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may undergo physical (aggregation, deposition, adsorption), chemical (dissolution, reduction) and/or biological (bacterial oxidation, sulphidation) transformations which are determined predominantly by environmental factors (i.e., such as pH, ions, dissolved oxygen and natural organic matter) (Figure 20.3). The type of these transformations depends on both the physicochemical properties of the NPs and the environmental factors. Physicochemical properties (size, shape, surface charge, chemical composition, coating material) of the functionalized NPs are of utmost importance to determine the fate and ecotoxicological potential of the NPs. Transformation of NPs in the environment can result in altered NP toxicity which may be different from that of pristine particles.30 For example, zerovalent iron particles have a tendency to turn into their oxide forms due to their high reactivity,31 which affects dissolution, stability and toxicity of the NPs. NPs in air can present in an aerosol form and the aerosolized NPs tend to agglomerate or undergo redox reaction depending on the properties of the NPs. Although aerosolized NPs have not yet been considered as a primary public health concern, their high mobility and availability to humans require investigation of the environmental behaviors of these NPs and their toxic effects on biological systems.30 Aerosolized NPs can react with living organisms in the air, resulting in their biological transformation. For example, iron-oxidizing bacteria may accelerate zero-valent iron corrosion by reducing Fe21 to Fe31.18 Also, aquatic organisms interact with NPs, leading to them undergoing the transformations as mentioned.

Figure 20.3

Schematic representation of the mechanisms responsible for toxicity alterations of environmentally transformed NPs, showing how MNPs and pristine NPs may induce different adverse effects. MNPs undergo environmental transformation, resulting in alteration of their physicochemical properties, interactions with environmental pollutants and biomacromolecules. Reproduced from ref. 30 with permission from the Royal Society of Chemistry.

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Transportation of free NPs can cause environmental adverse effects and induce developmental and hereditary toxicity in airborne, soil and aquatic organisms (Figure 20.4). They also exert toxic effects on cells, leading to membrane damage, mitochondria dysfunction, lysosome dysfunction and DNA damage. Therefore, it is crucial to assess the toxicity of individual components of the NPs along with their transformation-related toxic effects. Up to the present day, little has been known about the consequences of the exposure of aquatic organisms to MNPs and there are knowledge gaps regarding their health, safety and environment (HSE) impacts. In a study,32 colloidal stability and ecotoxicity of dimercaptosuccinic acid coated g-Fe2O3 NPs and, fresh and aged unfunctionalized g-Fe2O3 NPs towards three typical aquatic organisms (Raphidocelis, Lemna and Daphnia) were investigated and the results revealed that the NPs have a certain hazard potential to aquatic organisms. In other study,33 the toxicity of single and multicore g-Fe2O3 NPs coated with dimercaptosuccinic acid/citric acid and PEG were investigated using in-vitro cell culture models (Hep G2 and Caco-2 cell lines) and an in vivo X. laevis embryo model. In vitro cytotoxicity tests showed that all the functionalized NPs did not significantly reduce the cell viability up to 160 mg mL1 Fe concentration after 24 h of treatment. Surface modification with PEG decreased the internalization of the NPs by the cells due to shielding their surface charge. On the other hand, in-vivo experiments showed that these functionalized g-Fe2O3 NPs (0.25–1 mg L1) after exposure for 72 h altered the development of X. laevis tadpoles. Additionally, PEG

Figure 20.4

Schematic representation of the mechanism responsible for toxicity alterations of environmentally transformed NPs, showing that MNPs and pristine NPs may induce different adverse effects. MNPs undergo environmental transformation, resulting in alteration their physicochemical properties, interactions with environmental pollutants and biomacromolecules. Reproduced from ref. 30 with permission from the Royal Society of Chemistry.

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coating for each type of NP decreased the toxic effects on X. laevis tadpoles. Recently, the risk assessment of gluconic acid-coated IONPs (GLA-IONPs) in an aquatic ecosystem where Biomphalaria glabrata was studied as the model was performed. The freshwater snails (Biomphalaria glabrata) were exposed to the GLA-IONPs and their dissolved counterpart (FeCl3) at environmentally relevant concentrations (1.0, 2.5, 6.2 and 15.6 mg L1) for 28 days. Then, the bioaccumulation, mortality rate, behavior impairments, morphological alterations, fecundity and fertility of snails were analyzed. The results showed that GLA-IONPs induced high iron bioaccumulation in the entire soft tissue section. The GLA-IONPs also caused some behavioral impairments in snails, such as avoiding water, shell reclusion, and swimming on the water surface, and chronic exposure to them increased the behavioral impairments compared to iron ions and control groups. Both iron forms (iron from IONPs and their dissolved counterpart) reduced fecundity and fertility, as well as parental exposure induced developmental delays in the first generation. Mortality was observed only after the exposure to GLA-IONPs at 15.6 mg L1.34 Exposure of zebrafish to nickel NPs caused skeletal muscle abnormalities and head defects35 and cumulative mortality.36 Although the acute toxicity of NiO NPs on adult zebrafish was found to be low, long-term NiO exposure (30 days) causes increased toxicity by accumulation in the tissues.37 A study on cobalt ferrite NP toxicity on wheat plants38 revealed that cobalt ferrite NPs did not affect seed germination, but caused plant stress which reduced photosynthetic pigments. The study also showed that ferrofluid ferrite NPs were more toxic than the powder one. Marimon–Bolivar et al.39 evaluated the effects of releasing glutathione-coated MNPs (Fe3O4) (Glutathione@MNPs) to the environment, and their in vitro distribution on an animal model of the nematode Caenorhabditis elegans, for the purpose of their use in pollutant removal from wastewater. It was observed that under the studied concentrations (10–200 mg L1) of green MNPs, they do not seem to produce adverse effects on the animal model studied in the end points of growth, mortality and gene expression associated with oxidative stress. However, a correlation was found between the contraction of the NP and the fertility of the nematodes with a reduction of up to 52% and 25% of fertility with assays at a nanomaterial concentration of 200 mg L1. In another study, the effects of zinc oxide (ZnO)- and carbon nanotube (CNT)-coated IONPs (Fe3O4) on aquaculture wastewater treatment and the treatment toxicity were investigated. To determine treatment toxicity, Daphnia magna zooplankton was exposed to aquaculture wastewater for 12 h after removal of the NPs by a magnet from the wastewater.40 The findings showed that the treated wastewater did not cause significant differences in the survival of Daphnia magna. Clearly, although significant progress has been made towards the environmental toxicity assessment of FMNPs, there are still knowledge gaps regarding their long-term effect on the environment. Nanoecotoxicity depends on NP properties, behavior and NP transformation in the environment, and assessing the risk of NPs in the environment requires understanding of their surface properties, mobility, ecotoxicity and persistence.

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20.6 Toxicity Effect on Human Health 20.6.1

In Vitro Research on FMNPs

FMNPs are promising materials to improve the existing analytical methodologies due to their ability to be controlled magnetically, which provides superiority to the traditional methodologies. Among them all, IONPs have attracted the most attention and to the best of our knowledge, they are the most preferred MNPs in analytical applications due to their biocompatibility and biodegradability. Surface functionalization is widely used for rapid and sensitive detection of various analytes. Au, Ag, SiO2, graphene oxide, b-cyclodexrin and polymer (i.e., chitosan, polypropylene) coated MNPs, graphene-based nanocomposites and nanohybrid structures consisting of some of the aforementioned materials are the materials commonly used in the literature. Here, we will summarize recent literature on in vitro toxicity of functionalized MNPs with potential use for analytical applications. The toxicity of iron-based functionalized NPs has been studied extensively in the past decade. In a study,41 multifunctional graphene oxide/APTES/iron oxide NPs (GO-Fe3O4) (260 nm) were developed for magnetic targeted drug delivery dual magnetic resonance/fluorescence imaging and cancer sensing. The toxicity of three different formulations (GO-Fe3O4, doxorubicin (DOX) conjugated GO-Fe3O4 and free DOX at the same concentrations of DOX derived from loading on DOX-GO-Fe3O4 and up to 15 mg mL1 imaging concentration of GO-Fe3O4) on three different cell lines (HeLa – Human cervical carcinoma, MCF-7 – Human breast cancer, and HEK-293 – Human embryonic kidney fibroblast) were investigated using a 3-(4,5-dimethylthiazol-2-yl)2,5-diphenyltetrazolium bromide (MTT) assay. The results showed that GO-Fe3O4 NPs have low cytotoxicity comparable to that of GO at imaging concentrations of 15 mg mL1 and they can conduct pH sensing in regular in vitro experiments. The efficacy of DOX-conjugated GO-Fe3O4 NPs was evaluated using an MTT assay in HeLa cells via determining cellular internalization and cell viability in the presence of DOX-GO-Fe3O4 against a DOX-only control. GO-Fe3O4 NPs provide efficient intracellular delivery of DOX with considerable drug loading and over 2.5-fold improvement in its efficacy over free drug at low concentrations. Another study7 evaluated the effect of IONPs functionalized with trisodium citrate (TSC), polyethylenimine (PEI), aminopropyl-triethoxysilane (APTES) and chitosan on human keratinocytes (HaCaT) and endothelial cells (HMEC-1). Cell toxicity, genotoxicity, oxidative stress, cellular morphology, and integrated nanoimpact index (INI) of the NPs were investigated. PEI-IONPs showed the strongest effects in both cell types while TSC-IONPs were the most biocompatible. None of the functionalized IONPs cause any increase in the ROS level and the superoxide production at any of the NP concentrations (0, 50, 100 and 200 mg L1) and cell types after 24 h exposure. Uptake of the NPs on both cell lines was also examined by transmission electron microscopy, which indicated IONPs localized inside vesicles across

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the cytoplasm possibly through active transport endocytosis and/or pinocytosis. All NPs except PEI-IONPs caused DNA strand damage in HMEC-1 cells, whereas in HaCaT cell only core–, APTES– and chitosan–IONPs caused significant DNA damage. PEI–IONPs were suggested as the most potent IONPs in both cell types. The study revealed the importance of surface coatings, cell type and initial cell density on the toxicity, and presented a strategy based on the integration of well-established early warning signals in an index that could reveal the relationship between the FMNPs physicochemical properties and their impact in the exposure. Izadiyan et al.42 investigated the cytotoxicity effects of the core–shell Fe3O4/ Au NPs (6.08  1.06 nm) at various concentrations (1–500 mg mL1) on mouse embryonic fibroblast cell lines (NIH-3T3) and human colorectal adenocarcinoma cell line (HT-29) after 72 h. In vitro assays showed that the core–shell NPs had no significant toxicity on the normal cell line, while they had toxic effects on the cancerous cell line with an estimated inhibitory concentration of 235 mg mL1. The inhibitory concentration was estimated to be 235 mg mL1 for the cancerous cell line. The core–shell NPs did not cause significant effects on the morphology of fibroblasts. The study emphasized the potential of developing their NPs into an anticancer compound. Another multi-functional core–shell Fe3O4@Au NP (Fe3O4@-Au-DOX-mPEG/ PEG-FA NPs) (18 nm) which was conjugated with doxorubicin (DOX), methoxy poly(ethylene glycol) (mPEG), and folic acid-linked poly-(ethylene glycol) (PEGFA) showed higher cytotoxicity on Hela cells than that of FA-free NPs after 48 h, indicating that the developed multi-functional NPs have a tumor targeting ability.43 Both types of NPs were taken up by the HeLa cells via the endocytic mechanism and subsequently released the DOX in the cytosolic regions. When the cytotoxicity of the NPs on the HeLa cells was assessed under laser light, the cell viability was reduced to 25%, which is considerably lower than that of the cells incubated with only the NPs. The amount of DOX released from the NPs was also found to be higher at acidic pH (pH 5.6) than that at pH 7.4. The study showed that the NPs were promising for the combined MR/CT imaging, photothermal, and chemotherapy of various tumors. A study44 determined the cellular toxic effects of b-cyclodextrin-coated IONPs (rod shaped, 45 nm) in vitro (24h, 48 h, and 72 h exposure of 40–100 mg mL1 NPs) as well as in vivo (on rats, with a dose of 2000 mg kg1 NPs, for 14 days). The b-cyclodextrin-coated IONPs did not show any cytotoxic indications on the mouse fibroblast cell line (NIH 3T3) using MTT and Lactate dehydrogenase (LDH) assays. Complete uptake of IONPs within 24 h was revealed by Prussian blue staining. Histopathological examination of heart, liver, kidneys and spleen which were treated with the FMNPs did not show any abnormalities at the highest dose of 2000 mg kg1. In vivo toxicity of the NPs was evaluated by measuring the concentration of the liver enzymes. The results showed that the b-cyclodextrin-coated IONPs did not have any significant toxicity at the cellular level. Similarly, in vitro toxicity of dextranstabilized IONPs (o25 nm) on L929 Fibroblast cells was investigated.45 The FMNP concentrations varied up to 800 mg mL1 for 24 h. The NPs did not

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seem to induce oxidative stress mediated toxicological effects and did not cause altered physiological processes or behavior changes or visible pathological lesions. There were no observable signs of tissue damage in the kidney, liver or spleen. In a recent study, polyvinylpyrrolidone-coated manganese ferrite (PVP-MnFe2O4) NPs (0–150 mg mL1) synthesized for controlled drug delivery applications demonstrated negligible cytotoxicity on Hela cells after 24 h treatment.46 The PVP-MnFe2O4 NPs were also loaded with DOX and they exhibited a pH-dependent release behavior which released DOX at acidic and alkaline conditions in the first 24 h at a much higher level than that at neutral conditions. Another study47 showed that trisodium citrate coated copper ferrite (CuFe2O4) NPs (1–200 mg mL1) induce cell viability reduction, membrane damage and oxidative stress in human breast cancer cells (exposed for up to 3 days) and the degree of induction was dose- and time-dependent. It was suggested that copper ferrite NPs induced cell death through a mitochondrial pathway. Also, the potential in vitro toxicity of four different ferrite NPs (magnetite and zinc, nickel and nickel–zinc ferrites NPs) with similar size (o30 nm) and shape were evaluated in human erythrocytes and peripheral blood mononuclear cells by exposure to different NP concentrations (50, 100 and 200 mg mL1).48 The toxicity was evaluated in humans by determining red blood hemolysis, by measuring the content of total proteins, and by assaying catalase and glutathione-S-transferase activities. The nickel–zinc ferrite NPs (200 mg mL1) lead to hemolysis in human erythrocytes. Magnetite (50 mg mL1), zinc ferrite (50 and 100 mg mL1) and nickel–zinc ferrite (200 mg mL1) NPs significantly increase Glutathione-S-transferase activity in human erythrocytes. But none of the ferrite NPs changed catalase activity or total protein content in human erythrocytes up to 200 mg mL1. Also, none of the ferrite NPs have a significant toxic effect on human peripheral blood mononuclear cells after 24 h. The study indicated that the presence of zinc and/or nickel in ferrite NPs may increase toxicity and produce oxidative stress. Very recently, in vitro toxicity of core–shell SiO2 and 3-[2-(2-aminoethylamino)ethylamino]propyl-trimehoxysilane (AAAPTS) coated Fe3O4 NPs (Fe3O4@SiO2@AAAPTS), which were prepared for the extraction and preconcentration of the Gd31 ion-containing contrast agent Omniscan (gadodiamide) by acting as a novel and effective adsorbent from aqueous solutions, was examined.49 Viability of human breast adenocarcinoma cells treated for 24 h with various concentrations (1–1000 of mg mL1) of Fe3O4@SiO2@AAAPTS NPs was tested. Concentration-dependent cellular toxicity was observed at concentrations as low as 10 mg mL1. At concentrations above 300 mg mL1, an increase in the NP concentration resulted in significant cytotoxicity that may limit in vivo applications. Results all of these studies clearly show that the surface functionalization can impact on cellular interaction and uptake of the FMNPs, thus controls their toxicity behavior. Moreover, the responses of various tested cell lines to FMNPs can be quite different. Among all FMNPs, IONPs are the most

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promising materials to be used commonly for various analytical applications such as water remediation, drug delivery or cancer detection.

20.6.2

In Vivo Research on FMNPs

The usage of MNPs in the field of nanomedicine is limited due to the hysteresis losses and strong tendency to aggregation if their surface is not modified. When the externally applied magnetic field disappears, the magnetization of pristine MNPs is not zero. Because of these properties, magnetization causes aggregation of MNPs and causes serious problems in in vivo studies. Therefore, it is necessary to (i) attach polymer brushes on the surface for steric stabilization or induce surface charges for electrostatic repulsing among particles, (ii) reduce the size below the critical diameter to have superparamagnetic properties that magnetization returns to zero when the external magnetic field is removed to be used in biomedicine. There are very limited studies in the literature on the in vivo investigations of functional MNPs. A recent study investigated in vivo toxicity of pristine, PEG and citrate-coated cobalt ferrite NPs by applying a single dose intraperitoneally to healthy albino rats.50 Histopathological investigations revealed slight inflammatory changes produced in the normal parenchyma tissues of the liver, spleen and kidney, whereas no severe damage was observed. Kidney and liver enzymes showed elevated levels on the first day, while a transient decrease was observed until day 8. Apoferritin studies reveal partial filling of protein with cobalt ions from cobalt ferrite NPs. PEG-coated NPs were effectively eliminated without causing any damage to liver function. The results showed that PEG-coated NPs are relatively safer in experimental animals in comparison with bare and citrate-coated NPs.

20.7 Risk Assessment of FMNPs It should be noted that the risk analysis of all types of NPs is a very important issue but is still an evolving field. Functional MNPs are not the exceptions. Developments in this direction are rather slow because there is no consensus on the toxic and hazard analysis of even the same type of NPs. Nevertheless, many governmental institutions, private sectors and research institutes across Europe and in the USA are working diligently and urgently to have standard risk assessments. Since there are not enough research studies for FMNPs, it is quite difficult to make a full risk characterization. Similar to other NPs, the toxicity of FMNPs varies depending on the changing particle features (size, shape, magnetism, surface charge, surface modification) and in vivo and in vitro experiment parameters (cell type, organism type, exposure concentration and time).51 The risk assessment traditionally consists of four steps: (i) hazard assessment, (ii) dose–response assessment, (iii) exposure assessment, and (iv) risk characterization. In the risk assessment of NPs, hazards and routes of exposure for humans are identified first. And then, the likelihood of exposure is

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predicted. The relative risk is characterized by comparing quantified dose response and exposure. During the risk assessment, possible negative effects and risks should be weighed against the benefits of NPs.52,53 In order to collect data to make a risk assessment, researches are required in areas such as toxicology, exposure measurement and various calculation methods. Risk communication and processes are essential elements for the risk assessment process. When conducting risk assessment specifically for NPs, the safety of the employee during the production of NPs, the safety of people using the products containing these particles, the safety of people living in that area due to the release of NPs from the production facilities, and the potential environmental and human health risks during disposal or recycling of NPs are the necessary points.54,55 The focal point in the risk assessment of FMNPs, which are designed and synthesized for using in biomedical applications or exposed by releasing to the environment, is to carry out toxicology studies in animals and simple living organisms in a systematic approach in order to evaluate the hazard, to determine the dose–response relationship and to detect possible damages. Identifying the critical information needed in this process can provide an advantage to reduce uncertainties in predicting the potential hazards and risks of exposure to FMNPs. In order to make a qualified and reliable risk assessment, the design, and the quantitative and qualitative analysis of toxicology studies should be planned based on the type of MNP, the nature of the surface chemical groups (charged, neutral, chain density etc.), the particle number-based dose and experimental conditions (i.e., temperature, pH).56

20.7.1

Dose–Response Assessment

Dose–response relationships determine the relationship between the dose and the observed effects on an organism. It may be established by doing experiments in the laboratory or using mathematical models. However, it may not be straight forward for FMNPs. Because, dose based on mass concentration and different NP preparations can result in differences in surface reactivity and thus different response and toxicity.51

20.7.2

Exposure Assessment

Exposure assessment includes the entire life-cycle of NPs from synthesis to disposal.57 Knowledge on production, purification, functionalization, packaging, transport and nanowaste disposal are necessary. Having empirical data or procedures are important to predict the persistence and mobility of the NPs in air, soil, and water.51,52

20.8 Ethical Issues As nanotechnology progresses and develops, ethical issues begin to emerge. Ethical issues have arisen not only with the risk of misuse of NPs but also with their general use. Although technology is developed mostly to improve

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the living standards of people, to purchase more reliable food, clean water and higher quality services, high-tech products developed in recent years should not be used for the interests of countries that will harm other countries. Especially in recent years, products fabricated with the development of nanotechnology have started to be used in military/military fields. Attention should be paid to the use of these products only for defense and security purposes. These applications have to be open to the public. In addition, experts in this field need to have responsibility and awareness of issues such as ecological balance and environmental safety.58,59 While undertaking nanotechnology and nanomaterial research, one should be careful about choosing reliable sources. The production of these products should be carried out by taking into account issues such as the source of money for production, toxic agents released to the environment, fairly distributed income, and lawful production. Responsible development, education and consciousness of working workers, accurate and reliable information flow, suitability of developed infrastructures to modern technology and openness to development should be the main targets in nanotechnology research.60,61 As nanotechnology evolves, some worrying problems have arisen with the increasing usage. Especially with FMNPs applications in biomedicine as stated in previous sections, intervention to the human body or test animals, increased mechanization and potential ecotoxic impacts should be considered as ethical risks by all end users.62 It seems clear that nanotechnology is very useful for many applications where it is used. It is also possible to resolve or eliminate these problems, even if nanotechnology causes some ethical concerns and has some risks, as mentioned above. It seems to be the most effective method to be prepared for the good and bad impacts that nanotechnology brings, to take necessary precautions and to take action to reduce the risks, and to overcome the ethical problems of nanotechnology.

20.9 Conclusion and Future Trends FMNPs combine the advantages of MNPs and functionalized surfaces, offering unique opportunities such as high sensitivity and rapid extraction for a wide variety of analytical applications from water remediation to biomedical applications such as MRI and drug delivery. On the other hand, there is a concern that they may cause toxic effects on humans and the environment during and/or after these applications due to their small size and surface properties. It is very important to investigate the toxicity of FMNPs and their long-term effects on the environment and humans even if they have biocompatible surface functionalization due to fact that they may interact with biomolecules and environmental factors which cause altered surface properties and toxicity. Moreover, to envision the hazards and risk of the FMNPs, their complete life cycle should be scrutinized from their production to storage, and from their distribution to intended commercial uses and ultimate disposal.

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To date, there are not any specific and standardized tests for the toxicity assessment of nanomaterials, making it difficult to compare results and consensus on their toxicity. More research is needed for a better and deeper understanding of the toxicity mechanisms and long-term effects of FMNPs. The development of laws and policies to safely manage all aspects of nanomaterial production, use and recycling is important to minimize their potential hazard and risks for human and environmental health. One of the main reasons for divergence in the literature in terms of toxicity and hazard assessments is that the particles are tested in various chemical composition, size and morphology. In parallel with this, the types of interaction and interaction power with biological systems and magnetic properties change. As a result, their toxic behavior may also differ. More systematic and comprehensive research studies (especially in vivo) are needed especially before being used in biomedical and nanomedicine applications.

Abbreviations APTES CNT DMT1 DNA DOX Fe3O4 FMNPs HaCaT HEK-293 HeLa HMEC-1 HSE IONPs LDH MCF-7 MNPs mPEG MTT NIH 3T3 NPs PEG PEG-FA PEI RES ROS TSC ZnO g-Fe2O3

aminopropyl-triethoxysilane carbon nanotubes divalent metal transporter-1 deoxyribonucleic acid doxorubicin magnetite functionalized magnetic nanoparticles human keratinocytes human embryonic kidney fibroblast human cervical carcinoma endothelial cells health, safety and environment iron oxide nanoparticles lactate dehydrogenase human breast cancer magnetic nanoparticles methoxy poly(ethylene glycol) 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide mouse fibroblast cell line nanoparticles polyethylene glycol folic acid-linked poly(ethylene glycol) polyethylenimine reticuloendothelial system reactive oxygen species tri-sodium citrate zinc oxide maghemite

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Acknowledgements H.D. gratefully acknowledges the Max-Planck-Gesellschaft (MPG) for financial support of the MPIP-TOBB ETU Partner Group Program.

References 1. https://www.nvigen.com/products/#maxvigen, (accessed 21 July 2020). 2. V. De Matteis, Toxics, 2017, 5(4), 29. ´ndez-Pacheco, M. R. Ibarra and J. Santamarı´a, Nano 3. M. Arruebo, R. Ferna Today, 2007, 2, 22–32. 4. Q. Feng, Y. Liu, J. Huang, K. Chen, J. Huang and K. Xiao, Sci. Rep., 2018, 8, 2082. 5. J. H. Lee, J. E. Ju, B. Il Kim, P. J. Pak, E.-K. Choi, H.-S. Lee and N. Chung, Environ. Toxicol. Chem., 2014, 33, 2759–2766. 6. S. E. A. Gratton, P. A. Ropp, P. D. Pohlhaus, J. C. Luft, V. J. Madden, M. E. Napier and J. M. DeSimone, Proc. Natl. Acad. Sci. U. S. A., 2008, 105, 11613 LP–11611618. 7. N. Bayat, V. R. Lopes, M. Sanchez-Dominguez, R. Lakshmanan, G. K. Rajarao and S. Cristobal, Environ. Sci. Nano, 2015, 2, 380–394. 8. E. R. L. de Freitas, P. R. O. Soares, R. de, P. Santos, R. L. dos Santos, ´o, E. C. de, O. Lima, P. C. Morais and J. R. da Silva, E. P. Porfirio, S. N. Ba L. A. Guillo, J. Nanosci. Nanotechnol., 2008, 8, 2385–2391. 9. R. M. Patil, N. D. Thorat, P. B. Shete, P. A. Bedge, S. Gavde, M. G. Joshi, S. A. M. Tofail and R. A. Bohara, Biochem. Biophys. Rep., 2018, 13, 63–72. 10. N. Singh, G. J. S. Jenkins, R. Asadi and S. H. Doak, Nano Rev., 2010, 1. 11. L. Li, L.-L. Jiang, Y. Zeng and G. Liu, Chin. Phys. B, 2013, 22, 127503. 12. F. M. Kievit and M. Zhang, Acc. Chem. Res., 2011, 44, 853–862. 13. O. Veiseh, J. W. Gunn and M. Zhang, Adv. Drug Delivery Rev., 2010, 62, 284–304. 14. N. Malhotra, J.-S. Lee, R. A. D. Liman, J. M. S. Ruallo, O. B. Villaflores, T.-R. Ger and C.-D. Hsiao, Molecules, 2020, 25. 15. S. Salatin, S. Maleki Dizaj and A. Yari Khosroushahi, Cell Biol. Int., 2015, 39, 881–890. 16. J. T. Buchman, N. V. Hudson-Smith, K. M. Landy and C. L. Haynes, Acc. Chem. Res., 2019, 52, 1632–1642. 17. S. H. Joo and S. Aggarwal, J. Environ. Manage., 2018, 225, 62–74. 18. C. Lei, Y. Sun, D. C. W. Tsang and D. Lin, Environ. Pollut., 2018, 232, 10–30. 19. M. Nedyalkova, B. Donkova, J. Romanova, G. Tzvetkov, S. Madurga and V. Simeonov, Adv. Colloid Interface Sci., 2017, 249, 192–212. 20. U. S. Patil, S. Adireddy, A. Jaiswal, S. Mandava, B. R. Lee and D. B. Chrisey, Int. J. Mol. Sci., 2015, 16, 24417–24450. 21. Y. Liu and J. Wang, Toxicol. Sci, 2012, 131, 521–536. ¨derwald, M. S. McKee, G. Metreveli, 22. M. Bundschuh, J. Filser, S. Lu G. E. Schaumann, R. Schulz and S. Wagner, Environ. Sci. Eur., 2018, 30, 6.

Important Aspects of Safety, Risk & ELSI of Functionalized Magnetic Nanoparticles

525

23. P. K. Rai, V. Kumar, S. Lee, N. Raza, K.-H. Kim, Y. S. Ok and D. C. W. Tsang, Environ. Int., 2018, 119, 1–19. 24. Y. Hashimoto, S. Takeuchi, S. Mitsunobu and Y. S. Ok, J. Hazard. Mater., 2017, 322, 318–324. 25. L. Canesi, C. Ciacci and T. Balbi, Mar. Environ. Res., 2015, 111, 128–134. 26. Y. Liu, Y. Nie, J. Wang, J. Wang, X. Wang, S. Chen, G. Zhao, L. Wu and A. Xu, Ecotoxicol. Environ. Saf., 2018, 162, 92–102. 27. R. Deng, D. Lin, L. Zhu, S. Majumdar, J. C. White, J. L. Gardea-Torresdey and B. Xing, Nanotoxicology, 2017, 11, 591–612. 28. M. Wang, L. Chen, S. Chen and Y. Ma, Ecotoxicol. Environ. Saf., 2012, 79, 48–54. 29. X. Cui, B. Wan, L.-H. Guo, Y. Yang and X. Ren, Environ. Sci. Technol., 2016, 50, 12473–12483. 30. J. Zhang, W. Guo, Q. Li, Z. Wang and S. Liu, Environ. Sci. Nano, 2018, 5, 2482–2499. 31. H.-S. Kim, J.-Y. Ahn, K.-Y. Hwang, I.-K. Kim and I. Hwang, Environ. Sci. Technol., 2010, 44, 1760–1766. ¨ser, J. Filser and 32. Y.-Q. Zhang, R. Dringen, C. Petters, W. Rastedt, J. Ko S. Stolte, Environ. Sci. Nano, 2016, 3, 754–767. ´n, L. Gutie ´rrez, E. Lozano-Velasco, 33. M. Marı´n-Barba, H. Gavila I. Rodrı´guez-Ramiro, G. N. Wheeler, C. J. Morris, M. P. Morales and A. Ruiz, Nanoscale, 2018, 10, 690–704. ´jo, C. C. Rodrigues, B. B. Gonçalves, O. A. Arau ´jo, 34. M. B. Caixeta, P. S. Arau G. B. Bevilaqua, G. Malafaia, L. D. Silva and T. L. Rocha, J. Hazard. Mater., 2021, 401, 123398. 35. C. Ispas, D. Andreescu, A. Patel, D. V. Goia, S. Andreescu and K. N. Wallace, Environ. Sci. Technol., 2009, 43, 6349–6356. ´, D. Zeljenkova ´, E. Rollerova ´, E. Szabova ´ 36. J. A. Kovrizˇnych, R. Sotnı´kova ´, Interdiscip. Toxicol., 2013, 6, 67–73. and S. Wimmerova ´, D. Zeljenkova ´, E. Rollerova ´ and 37. J. A. Kovrizˇnych, R. Sotnı´kova ´, Interdiscip. Toxicol., 2014, 7, 23–26. E. Szabova ´pez-Luna, M. M. Camacho-Martı´nez, F. A. Solı´s-Domı´nguez, 38. J. Lo ´lez-Cha ´vez, R. Carrillo-Gonza ´lez, S. Martinez-Vargas, M. C. Gonza O. F. Mijangos-Ricardez and M. C. Cuevas-Dı´az, J. Toxicol. Environ. Health A, 2018, 81, 604–619. ˜ez-Avile ´s and D. De De ´n 39. W. Marimon-Bolı´var, L. P. Tejeda-Benı´tez, C. A. Nu ´on-Pe ´rez, Environ. Nanotechnol. Monit. Manag., 2019, 12, 100253. Le 40. H. Nezhadheydari, K. Rezaei Tavabe, A. Mirvaghefi, A. Heydari and M. Frinsko, Environ. Technol. Innov., 2019, 15, 100414. 41. R. Gonzalez-Rodriguez, E. Campbell and A. Naumov, PLoS One, 2019, 14, e0217072. 42. Z. Izadiyan, K. Shameli, M. Miyake, S.-Y. Teow, S.-C. Peh, S. E. Mohamad and S. H. Mohd Taib, Mater. Sci. Eng., C, 2019, 96, 51–57. 43. S. Rajkumar and M. Prabaharan, Colloids Surf., B, 2019, 174, 252–259. 44. R. Shelat, S. Chandra and A. Khanna, Int. J. Biol. Macromol., 2018, 110, 357–365.

526

Chapter 20

45. N. S. Remya, S. Syama, A. Sabareeswaran and P. V. Mohanan, Int. J. Pharm., 2016, 511, 586–598. 46. G. Wang, D. Zhao, Y. Ma, Z. Zhang, H. Che, J. Mu, X. Zhang and Z. Zhang, Appl. Surf. Sci., 2018, 428, 258–263. 47. M. Ahamed, M. J. Akhtar, H. A. Alhadlaq and A. Alshamsan, Colloids Surf., B, 2016, 142, 46–54. ´rez and Z. I. Gonza ´lez-Sa ´nchez, Toxicol. 48. N. L. Martı´nez-Rodrı´guez, S. Tava In Vitro, 2019, 57, 54–61. 49. M. Naghizadeh, M. A. Taher, A.-M. Tamaddon, S. Borandeh and S. S. Abolmaali, Environ. Nanotechnol. Monit. Manage., 2019, 12, 100250. 50. K. Akhtar, Y. Javed, Y. Jamil and F. Muhammad, Appl. Nanosci., 2020, 10, 3659–3674. 51. P. Laux, J. Tentschert, C. Riebeling, A. Braeuning, O. Creutzenberg, A. Epp, V. Fessard, K. H. Haas, A. Haase, K. H. Rinke, N. Jakubowski, ¨rmer, P. Kearns, A. Lampen, H. Rauscher, R. Schoonjans, A. Sto ¨hle and A. Luch, Arch. Toxicol., 2018, 92(1), A. Thielmann, U. Mu 121–141. 52. S. Rana and P. T. Kalaichelvan, ISRN Toxicol., 2013, 2013, 574648. 53. A. Kushwaha, R. Rani and V. Agarwal, in Advanced Nanomaterials for Wastewater Remediation, ed. R. K. Gautam and M. C. Chattopadhyaya, 1st edn, 2016, pp. 387–404. 54. A. D. Maynard, in Assessing Nanoparticle Risks to Human Health, ed. G. Ramachandran and W. Andrew, UK, USA, 1st edn, 2011, pp. 1–16. 55. S. Singh and H. S. Nalwa, J. Nanosci. Nanotechnol., 2007, 7, 3048–3070. 56. E. D. Kuempel and V. Castranova, in Assessing Nanoparticle Risks to Human Health, ed. G. Ramachandran and W. Andrew, UK, USA, 2nd edn, 2018, pp. 1–31. 57. J. S. Tsuji, A. D. Maynard, P. C. Howard, J. T. James, C. Lam, D. B. Warheit and A. B. Santamaria, Toxicol. Sci, 2005, 89, 42–50. 58. E. B. Soutoab, J. Dias-Ferreiraa, R. Shegokarc, A. Durazzod and A. Santinie, in Drug Delivery Aspects, ed. R. Shegokar, C. GmbH and Zimmern, Germany, 1st edn, 2020, pp. 157–168. 59. S. J. Florczyk and S. Saha, J. Long-Term Eff. Med. Implants., 2007, 17, 271. 60. A. E. Sweeney, Sci. Eng. Ethics, 2006, 12, 435. 61. J. Lopez, Health Law Rev., 2004, 12, 24. 62. R. Purohita, A. Mittala, S. Dalelaa, V. Warudkara, K. Purohitb and S. Purohitc, Mater. Today Proc., 2017, 4, 5461.

CHAPTER 21

Functionalized Magnetic Nanoparticles (MNPs): Toxicity, Safety and Legal Aspects of Functionalized MNPs LADAN RASHIDI Associate Prof, Department of Food and Agricultural Products, Food Technology and Agricultural Products Research Center, Standard Research Institute (SRI), Karaj, Iran Email: [email protected]

21.1 Introduction Metal nanoparticles (i.e., Fe2O3, Tio2, ZrO2, ZnO, NiO, Al2O3, etc.) are important efficient materials in nanotechnology because of special properties including high surface area and small size for higher binding capacities of the desired compound, biostability, unique optical and electronic features and facile functionalization.1,2 For example, magnetic nanoparticles (MNPs) can be applied as nanomaterials in analytical chemistry, nanoparticles in extraction techniques, semiconductor transistors, catalysis, dyes to glass and ceramics for sintering additives, fluids for heat transfer, materials for optical fibers and lasers, optical device capacitors, biomaterials, transparent conductive coatings, nanocomposites, and additives for different types of material, etc.3–5 One of the unique properties of new functionalized-MNPs is in the selective extraction of the target compounds from complex matrices including environmental, food, beverage and biological samples.6,7 MNPs are natural components in living Analytical Applications of Functionalized Magnetic Nanoparticles Edited by Chaudhery Mustansar Hussain r The Royal Society of Chemistry 2021 Published by the Royal Society of Chemistry, www.rsc.org

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systems that are synthesized in the cells of fish, humans, birds, and bacteria. These nanoparticles have been found in different cells, including the heart, liver, brain, spleen, bone tissue, and tumors, but the role of MNPs in the body is not fully understood.8 Different studies show that a concentration of iron up to 100 mg ml1 results in nontoxic effects and iron toxicity occurs only at a high dosage of iron. Iron has catalytic actions and involves the generation of free radicals, which lead to nucleic acid modification, peroxidation of membrane lipids and protein oxidation.9 High concentrations of iron in the tissues cause an imbalance in homeostasis, leading to undesired abnormal cellular responses, including DNA damage, oxidative stress and inflammatory responses, which induce carcinogenesis.10 The biocompatibility of MNPs depends on the coating or functionalization, the targeted delivery mechanism, the stability of nanoparticle colloidal solutions, the chemical nature, the solubility, the surface phenomena chemistry, pharmacokinetics, injected nanoparticle amount and their potential distribution into a patient’s body without adverse effects on clinical manifestations and inducing the cellular or tissue response essential for achievement of optimal therapeutic effect and shape the compatibility of MNP surfactants with the environment and biodegradability.11,12 Nanoparticles without biocompatibility disrupt cellular and tissue metabolism; therefore, investigation of MNPs and their functionalization should be considered for their application in biomedicine.13 It is noticeable that there is no sufficient data about the long-term safety of metal nanoparticles in medicine. It can be challenging to obtain a suitable synthesis route that provides easily repeatable results, with many nanoparticle synthesis approaches generating a range in both shape and size of nanoparticles or not fabricating the nanomaterials in a sufficiently large quantity to make it economically stable.13,14 Surface modification of MNPs plays a significant role in the successful application of these particles in the biomedical field, including drug delivery,15 thermal therapy of cancer,16 as bioprobes and sensors,17,18 and in enhanced imaging.19 Figure 21.1 shows various applications of MNPs in medicine. If suitable coatings are used for the MNPs surface, most of the mentioned applications could be performed. It was found that MNPs have a high surface energy, hence tend to aggregate quickly. In this way, core–shell architectures allow researchers to incorporate multiple functionalities on a single nanoparticle.11 It was reported that MNPs possess extraordinary properties, including high biocompatibility, and lack of toxicity to humans. Also, it was found that their superparamagnetic properties with secure aggregation may change their magnetic efficiency and adsorption characteristics. Therefore, these nanoparticles have been coated by an inorganic or organic layer to prevent their aggregation. The coating of a NP’s surface not only stabilizes the MNPs but can also be readily applied for further functionalization. Surface modification of MNPs has an essential role in successful biological application of MNPs by improving agglomeration prevention, improving bioavailability, biocompatibility and stability, and providing targeted drug delivery.8,11 MNPs are hydrophobic and their surface can be functionalized by ligand exchange or encapsulated into a phospholipid bilayer to make them hydrophilic.20 As with any similar new therapy, when MNPs are

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Figure 21.1

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Schematic of the current applications of functionalized MNPs. Reproduced from ref. 10, https://doi.org/10.1186/s11671-019-3019-6, under the terms of the CC BY 4.0 license http://creativecommons.org/ licenses/by/4.0/.

functionalized with organic or inorganic materials designed to allow the specific attachment of drugs or bioactive agents, cytotoxicological testing is essential before moving to animal models. In the traditional form, in vitro toxicity testing concentrates on whether or not exposure to a possibly toxic agent leads to cell death. This chapter presents an overview of research studies of the cytotoxicity effects and safety issues of various functionalized MNPs investigated in vitro or in vivo. Besides, overall regulations encompassing the legal aspects for MNPs and their functionalization are taken into account in this chapter.

21.2 Physicochemical Properties of Functionalizedand Unfunctionalized-MNPs and Their Influence on Toxicity Toxicity assays are essential for functionalized- and unfunctionalized-MNPs intended for biomedicine usage and have limited their application to clinical situations. Optimization of the physicochemical parameters is more effective in minimizing the functionalized or unfunctionalized-MNP toxicity and their immune response. For MNPs, characteristics including size, shape, surface-to-volume ratio, surface functionalization and stability on biological media, among other parameters, have been confirmed to influence the toxicological profile of the nanomaterial structures and their biocompatibility in general.21 Non-coated MIONs with a negative charge cause

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denaturation of proteins when attached to serum proteins in culture medium. It was found that the protein corona formation around the surface of nanoparticles because of interaction with cellular media leads to changes in their physical characteristics and aggregates and sediments of them. It was found that coating or functionalization of MNPs such as poly(N-(2-aminoethyl)acrylamide) and poly(acrylic acid)-decorated gold nanoparticles (GNPs, 5–20 nm), with a positive and negative charge, respectively, could reduce the toxicity effects of these nanoparticles.22 For the coated-MNPs or functionalized-MNPs, chemical composition and amount of coating material, length of coating, size, hydrophobicity and charge could be influenced on the biocompatibility and toxicological properties of nanoparticles. In a study, it was reported that polystyrene (PS) nanoparticles with a size of 140 nm decorated with amine or carboxyl groups showed various binding capacities to human serum protein and the total amount of corona protein on carboxyl-decorated PS nanoparticles was higher than the number on their amine-decorated counterparts.23 Besides, the protein binding in nanoparticles with a negative charge could be adjusted by parameters such as ligand species and charge densities. Poly(methacrylic acid)-decorated iron oxide nanoparticles with a negative charge tended to adsorb more proteins from fetal bovine serum (FBS) than that adsorbed by citric acid-decorated iron oxide nanoparticles.24 The number of protein molecules which adsorbed onto nanoparticles enhanced with the hydrophobicity of the nanoparticle. PEG decoration of iron oxide nanoparticles reduced the adsorption of BSA and IgG.25 Studies showed that different coating materials including silica, dextran, alginate, chitosan, polyvinylpyrrolidone (PVP), polysaccharide, polydopamine (PDA), polyamidoamine (PAMAM), polyethylene glycol (PEG), polyphenol, amino acids, lipids, polyethylene oxide (PEO), poloxamers, and polyamines could be used.13,26–28 Figure 21.2 shows the different natural and synthetic polymers, organic and inorganic materials used for stabilization and modification of MNPs.29,30 Without a doubt, the cytotoxicity of MNPs can be reduced and kept under control with suitable surface modifications and coatings. Surface modifications of MNPs may influence their physicochemical characteristics and might develop risks toward biota. Also, the surface coating of MNPs is an efficient route of preventing the release and dissolution31 of toxic ions.

21.3 Toxicological Testing Toxicity issues are the primary concern and significant agents in tissue engineering, regenerative medicine, and drug delivery. Toxicology is defined as the study of the adverse effects of biological, chemical, and physical agents in people, environment, plants, and animals.32,33 The cytotoxicity of functionalized MNPs was determined in both in vitro and in vivo conditions. In vitro tests are preferred as they allow the material to be investigated safely without subjecting humans or animals to the possible toxic side effects of nanoparticles. 32,33

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Figure 21.2

21.3.1

531

Surface modification materials applied for coating MNPs.

In Vitro Testing of Functionalized-MNPs

Cell cytotoxicity testing is applied as the first step for the screening of nanoparticles, including MNPs and they are functionalized. Cell toxicity tests are necessary for safety trials of nanoparticles, which are in contact with blood and tissue in the body and are applied as additional tests for novel drugs, including for genotoxicity assays, etc.33 In vitro cytotoxicity tests are conducted using culture cells as the initial screening for toxicity or as an alternative way to animal tests. It was found that there is a high correlation between cytotoxicity in skin models and dermal irritancy gained from cultured cells. The degree of toxicity alters depending on the cell type reflecting specific cell line biology and genetics.33 Cell cytotoxicity of functionalized MNPs is defined by their physical actions and properties, which induce cell death or prevent cell functions such as cell proliferation. Effects of cellular toxicity are translated into membrane leakage, impaired mitochondrial activity and morphological changes, which can have harmful effects on proliferation, cell viability, impair the therapeutic efficiency of the therapy and transplants within the body and metabolic activity. It was found that biomolecules, including lipids or proteins, may be absorbed by functionalized MNPs affecting not only the biological effect of the nanoparticles but also their original synthetic structures.34 In vitro toxicity assays are aimed at studying vital cellular activity, including cell viability and cell death. Different methods have been applied to evaluate the cytotoxicity of adherent or floating cells for various purposes. These methods can be categorized into counting colonies of proliferating cells, evaluating the viability of cells indirectly via quantifying the optical or radiolabeling of substances in cells and counting cells directly.

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The common in vitro tests for functionalized or bare MNPs are MTT (3-(4,5dimethylthiazol-2-yl)2,5-diphenyl tetrazolium bromide)), PI (propidium iodide), for example, live/dead assay, and trypan blue stains, but other popular tests including BrdU (5-bromo-2 0 -deoxyuridine) assay and LDH (lactate dehydrogenase)35 for metabolic activity are applied. In addition, trypan blue stain is used for the identification of dead cells, but not living cells, as living cells can block the penetration of the dyes and dead cells cannot do so. The comet assay or single-cell gel electrophoresis (SCGE) is used for genotoxicity, cellular DNA repair and cytotoxicity of MNPs. Among all the mentioned toxicity assays, MTT, LDH, and PI are commonly used for indicating cell death or apoptosis and BrdU and MTT assays are used for evaluation of cell proliferation. The neutral red uptake assay (NRU) shows the ability of viable cells (lysosomal matrix) to incorporate and bind the supravital dye neutral red. Besides, a TUNEL assay for apoptosis detection,36 a cell-life-cycle assay using flow cytometry for detection of cellular DNA content, different redox assays37 and immunochemistry for markers of apoptosis or necrosis38 have been applied for evaluation of cell toxicity. Besides, the survival rate can be assessed by adenosine triphosphate (ATP) detection, which is a substance detected only in living cells. Besides the mentioned methods, the colony formation method is also applied for the estimation of cell proliferation. In vitro tests are particularly convenient for initial evaluation of toxicity and biocompatibility of functionalized MNPs, which provide little information on the mechanism of toxicity or the cause of cell death. Figure 21.3 presents an overview of cell toxicity assays used for

Figure 21.3

An overview of in vitro cytotoxicity assays.

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evaluating the toxicity of functionalized or bare MNPs. In vitro test studies have had a more rapid development of new treatments and many nanoparticles can be studied at one time.

21.3.2

In Vivo Toxicity of Functionalized MNPs

In vivo studies are necessary to find out how the body as a whole will respond to MNPs, or coated MNPs. Despite the ethical, cost, and time considerations, in vivo tests in relevant animal models are critical for investigating biological effects that cannot be modeled in vitro. These tests provide information about the systematic toxicities to be clarified, including neurological, cardiovascular, reproductive, immunological, and developmental, and any carcinogenic effects involved.38 In vivo tests include hemolysis using erythrocytes, coagulation tendencies using conventional clinical assays such as activated clotting time (ACT), prothrombin time (PT), and activated partial thromboplastin time (APTT). Inflammatory response is determined by the degree of chemokines and proinflammatory cytokines showing potential oxidative stress,38 and gene expression for transcription factors associated with oxidative stress can determine toxicity effects39 of MNPs and their functionalized forms (Figure 21.4). In vivo toxicity of magnetic iron oxide nanoparticles (MIONPs) is observed by free radicals of MNPs, including nonradical hydrogen peroxide, hydroxyl radicals, and superoxide anions.

Figure 21.4

In vivo toxicity parameter evaluation when applied to nanoparticles.

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21.4 Comparison Between In Vitro and In Vivo Toxicity Studies of Coated and Bare MNPs 21.4.1

In Vitro Toxicity Comparative Studies of Coated and Bare MNPs

Currently, in vitro cytotoxicity assays determine cell viability through colorimetric methods. These methods can be categorized into tests that measure mitochondrial activity and the plasma membrane integrity of cells. The coating surface of superparamagnetic iron oxide nanoparticles (SPIONs) can stabilize iron oxide nanoparticles and avoid agglomeration of them and also prevent the dissolution and release of toxic ions.40 The interaction of various types of MNP surface with proteins and coating is an essential consideration for assessing in vitro toxicity. It was found that after adding MNPs to culture media, some nutrients and media proteins may be adsorbed onto MNPs leading to their unavailability for cellular activities, which has natural implications on cell viability and growth.32 Different researchers applied various cell lines with altered culturing conditions, which made things further complicated, as direct comparisons between available research studies and also their results are not validated. For working on MNPs such as SPIONs, the reported toxicity taken into account includes diminished mitochondrial activity, the cellular stress-mediated creation of reactive oxygen species (ROS), inflammation, and chromosome condensation.40 In this regard, the cytotoxicity of SPIONs and its coating by a thin silica shell (Fe3O4/SiO2NPs) on cell lines of A549 and Hella was evaluated by Malvindi et al. (2014)41 in which thin silica shell-coated SPIONs reduced the oxidative stress and iron homeostasis modification, and also, both of the SPIONs and its coating showed similar cell internalization. Their study indicated that the toxicity of unfunctionalized nanoparticles was as a result of their more influential in situ degradation with higher intracellular Fe31 release in comparison with surface passivated shell-coated SPIONs, hence surface engineering of Fe3O4/SiO2NPs is necessary for improving particle stability in biological environments reducing cytotoxic and genotoxic effects.42 Silica-coated iron oxide nanoparticles showed low cytotoxicity on human neuronal SHSY5Y cells at the highest concentration or most extended exposure tested time.43 In addition, DNA damage, glutathione peroxidase (GPX) activities, superoxide dismutase (SOD) activities, mitochondrial membrane potential, the levels of ROS, intracellular glutathione, and cell membrane potential of uncoated SPIONs and coated SPIONs by D-mannose or with poly-lysine on murine neural stem cells (NSCs) were analyzed and the results showed that the effects of all tested SPIONs on the NSCs were similar in which mitochondrial homeostasis is the primary cellular target.44 Also, the effects of uncoated and coated SPIONs with polyvinyl alcohol (PVA) on a primary mouse fibroblast (L929) cell line were investigated and the results showed that coated SPIONs showed acceptable levels of cell viability at highest doses of 400 Mm and at this dose of coated

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SPIONs, cell-cycle modifications and apoptosis was seen due to formation of protein corona and DNA damage.45 The toxicity of PEG-coated iron oxide and its uncoated iron oxide with both live–dead and MTT assays and also the effects of these nanoparticles on cell adhesion and morphology on human fibroblasts (HTERT-BJ1) were investigated.46,47 The uncoated nanoparticles, in comparison with PEG-coated nanoparticles, showed a 25 to 50% decrease in cell viability starting at a concentration of 250 mg ml1. Also, a significant decrease in cell adhesion and a disruption in the cell membrane and disorganized cytoskeleton from endocytosis were observed in treated cells by uncoated nanoparticles. Moreover, no adverse effects on morphology were observed in treated cells by PEG-coated particles.47 PEGylated iron oxide nanoparticles within copper-mediated atom transfer radical polymerization were synthesized and then exposed to mouse macrophage cells (RAW 264.7), the live cell count was more than 93% of the control cell count indicating no toxic effect at a concentration of 0.2 mg ml1 over a 5 day period which in comparison with uncoated iron oxide nanoparticles showed a 30% loss in cell viability the second day but on the fifth day, the cell viability improved to 90%.48 Gold nanorods were synthesized using hexadecyltrimethylammonium bromide (CTAB), which is toxic and remains on the surface, then the surface was coated by the polyelectrolyte including polystyrene sulfonate (PSS) or through PEGylation for reducing toxic effects of CTAB.49 An MTS assay was applied for evaluation of toxicity of coated and non-coated gold nanorods exposed to cell lines, including human mammary adenocarcinoma (SKBR3), Chinese Hamster Ovary cells (CHO), mouse myoblast (C2C12) and human leukemia cells (HL60). The results showed that filtered nanorods displayed 100% cell death at all specified concentrations, while at the low concentrations of coated nanorods by PSS, the cell viability was higher than 80%, which was decreased compared with at high concentrations. The PEGylated nanorods, except for human leukemia cells (HL60), displayed high cell viability and can be considered nontoxic.49 The amine-modified poly(vinyl alcohol) (PVA) coated magnetic nanoparticles showed significant interaction with melanoma cells over 24 hours but no cytotoxicity was observed after 2 hours. Cytotoxicity analysis by MTT assay showed toxicity at high concentrations of PVA.50 MNPs covered with a silica shell (MSPs) and their functionalization with anti-Met oncogene (anti-Met/ HGFR) monoclonal antibody (mAb) were performed and their cytocompatibility with the GTL-16 human gastric carcinoma and L929 standard fibroblast cell lines was analyzed using MTT assay.51 The results showed a slight reduction of cell viability when cells were exposed to the MNPs and this reduction was in a dose-dependent manner and always higher than 80% while GTL-16 exposed to mAb-MNPs showed that more than 95% of cells were fully viable at the highest dose of 50 mg ml1. In the case of GTL-16 treated by mAb-MSNPs, the cell viability was decreased, to lower than 80%. Covalent attachment of fluorescein isothiocyanate onto magnetic polymeric nanoparticles functionalized with chitosan was synthesized and applied for labeling the living organ and blood-related cancer cells, including Hela, Hep G2, and K562 cell

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lines. MTT assay showed a high cell viability of more than 90% without morphological change for treated cells with magnetic polymeric nanoparticle-chitosan/fluorescein isothiocyanate.52 Ebrahiminezhad et al. (2015)53 investigated the cytotoxicity of iron oxides (IONs), functionalized with L-lysine and 3-aminopropyltriethoxysilane, on the HepG2 cell line using MTT assay. The results showed that the growth of HepG2 cells promoted by IONs and also IONs functionalized with L-lysine and 3-aminopropyltriethoxysilane. IONs and chitosan oligosaccharide-coated IONs were synthesized to evaluate the toxicity of them on human cervix carcinoma (Hela), human lung carcinoma (A549), and human embryonic kidney (Hek293) cell lines using MTT assay along with flow cytometry study.53 Chitosan oligosaccharide-coated IONs indicated a decrease in cellular damage, reduced ROS production and decreased the cytotoxicity of bare IONs in tumor cells.54 Yang et al. (2013) synthesized MNPs and coated the surface of nanoparticles with different materials, including tetraethylorthosilicate (TEOS) and 3-aminopropyltrimethoxysilane (APTMS). The cytotoxicity evaluation of all MNPs showed less cytotoxicity and genotoxicity in fibrosarcoma cells at concentrations lower than 500 mg ml1, while APTMS-coated MNPs showed higher than 10% toxicity against normal cells.55 Also, APTMS- or TEOS/APMTS-coated MNPs induced DNA aberrations irrespective of cell type.55 In other research, Fe3O4 NPs functionalized with Gemcitabine improved the cytotoxicity effects of the chemotherapeutic material on BT 474 breast ductal carcinoma, HepG2 hepatocellular carcinoma and MG 63 osteosarcoma cells. The hemolysis assay indicated no damage to erythrocytes.56 Wydra et al. (2016) synthesized monosaccharide-coated IONPs and these targeted nanoparticles were internalized into CT26 cells, then cells containing nanoparticles were exposed to an AMF for the determination of the potential for transport therapy. It was found that cellular ROS generation and apoptotic cell death were increased with field exposure. The coated NPs showed negligible ROS generation in comparison with bare NPs.57 Fe3O4 coated by poly L-lactic acid (PLLA) and polyethylene glycol (PEG) (Fe3O4–PLLA–PEG–PLLA) particles showed low cytotoxicity in comparison with uncoated MNPs at the cellular level. In addition, Fe3O4–PLLA–PEG–PLLA indicated low genotoxic and immunotoxicity at the molecular level, and the low toxicity of these nanoparticles provides the application of them in medicine.58 MNP-coated polyethylene oxide (PEO) triblock copolymers (PEO–COOH–PEO) (PEO tail lengths above 2 kDa) were synthesized and the particles coated with 15 kDa PEO tail block copolymers had low toxicity on different cell lines including prostate cancer cell lines (PC3 and C4-2), human umbilical vein endothelial cells (HUVECs), and human retinal pigment epithelial cells (HRPEs).59 This research confirmed that the length of coating influenced the toxicity of nanoparticles and particles coated with 0.75 kDa tail block copolymers were the most toxic.59 The effect of SPIONs with different surface chemistries on various cell lines showed that the SPIONs uptake and their side effects are dependent on the type of cell.31 It was reported that IONPs and their physicochemical features, including surface charges, size, coatings and shape influenced their

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cytotoxicity, for example, IONPs lower than 10 nm are more toxic than larger ones and SPIONs fabricated by Fe2O3 (51.88 nm) indicated neurotoxic effects in a PC12 cell line (dose 60–200 mg ml1).60 SPIONs (10–50 nm) coated by dextran were indicated to be safer and did not destroy the hippocampal cell viability at rare doses.61 MNPs coupled with a GFP-carrying plasmid have indicated the capacity for enhancement transfection efficiencies by magnetic fields for the attraction of MNPs toward the osteosarcoma fibroblast (MG-63) cell membrane and were then taken up by the cells. Then the DNA is separated from the MNPs and then the DNA can be expressed without any effects on the viability of the MG-63 cell line.62 In addition, MNPs coupled with the plasmid coding for green fluorescent protein (GFP) were applied for transfection NIH3T3 cells, which enhanced overall transfection efficiency compared with lipid-mediated gene delivery without any effect on the viability and morphology of NIH3T3 cells.63 SPION coated by polyethyleneimine (PEI) (SPION–PEI) synthesized for small interfering RNA (siRNA) delivery and the cytotoxicity effects of these nanoparticles on the cell viability of HSC-T6 were determined by MTT assay which showed low toxic effects.64 Bovine serum albumin-coated iron oxide nanoparticles provide the stable and biocompatible shell and inhibit the cytotoxicity of the magnetic core.65 It was reported that a high dose of SPIONs caused interference with the actin cytoskeleton resulting in reduced cell proliferation, but SPION encapsulated in the liposome indicated a direct effect on the actin cytoskeleton architecture leading to the formation of focal adhesion complexes and reduced cell proliferation ability.66,67 The cellular uptake in both murine 3T3 fibroblast and C17.2 neural progenitor cells was 95.63  5.83 pg Fe and 87.46  5.62 pg Fe per cell after 24 h, respectively. In other research, Muller et al. reported that the cytotoxicity was only conferred after internalization in the cells.68 Research showed that SPIONs are taken up by tumor cells, fibroblasts and macrophages, and the surface composition and charge of the SPION have a more considerable influence on the cellular uptake.66

21.4.2

In Vivo Toxicity Comparative Studies of Coated and Bare MNPs

Studies showed that MNPs, especially SPION after administration entered into the liver and spleen69,70 but coated SPIONs with oleic acid or Pluronic were accumulated into the liver of rats.71,72 The accumulation of dextrancoated SPIONs was observed inside the lysosomes. However, the iron oxides are broken into iron ions through the pH change and finally inserted into hemoglobin and the dextranase enzyme breaks down the dextran coating and facilitates the degradation.73 It was found that there is a low correlation between in vivo and in vitro toxicity of MNPs, which is related to the changes in pH, chemical position and ionic strength of the circulating blood with the kidney and liver hemostasis in the body.74 It was found that after a single intravenous injection of SPION–PEI/siRNA to rat, the accumulation of these nanoparticles was observed in the liver and spleen and no irreversible

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histopathological damage in any of the organs tested (including lungs, liver, spleen, kidneys and heart) was found.64 In vivo assays show several advantages for the toxicity study of MNPs, including determination of the toxico-kinetics in the body and studying the neurological, immunological, reproductive, cardiovascular and developmental toxicities to measure the chronic systemic toxicity.75 Dextran-coated SPIONs (Ferumoxtran-10) with a dose of 2.6 mg kg1 in rats promoted no hemodynamic changes in animals but dose elevation up to 13 mg Fe kg1 cause intensified aortic blood flow while significantly exerting no respiratory or cardiovascular toxicity.38 Starch-coated, PEGylated and heparin-functionalized iron oxide magnetic nanoparticles (DNPH) showed a long-circulating half-life compared with that of heparin-coated MNPs. Then PEGylated (HP) improved the plasma stability, enabling extended DNPH exposure to tumor lesions.76 Up to 31.36 mg, Fe g1 of tissue for DNPH and 4.27 mg Fe g1 of tissue for HP were determined after injection to the mouse. Besides, mAb-coupled MNPs and bare MNPs were injected into tumors expressing Met/HGFR. The results showed that mAb-coupled MNPs could target more efficiently than bare MNPs tumor cells and have a better dispersion within tumor mass.51 Moreover, with in vivo biodistribution of Fe3O4 NPs functionalized with Gemcitabine, Gemcitabine’s delivery improves the cytotoxicity effects compared with free Gemcitabine in the BT474 and HepG2 cells.56 Besides, DNA aptamer-functionalized gold-coated MNPs (AGMNPs) (with a size of 50 nm) were exposed to a low frequency altering magnetic field applied for selective tumor cell elimination in mice and the results showed apoptosis followed by necrosis of tumor cells without heating of the tumor cells, nearby healthy cells or tissues.76 All in vivo toxicity studies showed that functionalized or coated MNP uptake and their side effects are dependent on the type of tissue. The primary site of accumulation of coated or functionalized MNPs is in the liver and spleen of the body.

21.5 Legal Aspects of Functionalized MNPs In general, nanomaterials have properties including higher bioavailability, high chemical bioactivity and reactivity, cellular, organ, and tissue penetration ability, which support their application in biomedical fields. Usually, a foreign substance is blocked by human skin, but some organs such as the lungs and gastrointestinal tract are susceptible to foreign substances.77,78 Agglomeration or aggregation, size, morphology, and composition, are the characteristic properties of nanoparticles which are applied to classify them. Due to the biomedical applications of nanomaterials, regulations via legislation, rules and laws have been implemented by various government organizations to optimize or prevent risks associated with nanomaterials (NMs).77,78 Nowadays, the USA and the European Union (EU) possess authoritative regulatory bodies and guideline legislation to govern the possible risks of NMs.

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Local, systemic, oral and topical administrations are all methods that have been approved by the Food and Drug Administration (FDA) for nanoparticle/microparticle delivery depending on the target site or favorable application. Therapeutic and diagnostic nanoparticles are categorized into two groups (a) organic nanoparticles (e.g., micelles, polymeric, liposomes, etc.) and inorganic nanoparticles (e.g., silica, iron oxide, gold, titanium, etc.). Inorganic nanoparticles have been successfully applied in preclinical studies. Nowadays, the US Food and Drug Administration has confirmed 3 tesla magnetic field strengths, as the spatial resolution of human body imaging, is limited to almost 1 mm. All nanoparticle-conjugated drugs or bioactive agents should be evaluated for immunotoxicity during development. It is considered that all NPs are intended for degradation and dissolution within the human body, such as nanocrystals and liposomes.79 It was found that immunotoxicity evaluation of NPs is governed by the ICH S8 and ICH S6 guidelines which are presented by the FDA for the low molecular weight drugs and products containing a biotechnology-derived material, respectively. The FDA has participated since 2000 in the National Nanotechnology Initiative (NNI), which is a federal research and development program to coordinate governmental multi-agency research studies in nanoscale engineering, technology and science. FDA approved 51 products in nanomedicine and 77 products in clinical trials.80 The approval process in nanomedicine products is estimated to take approximately 10–15 years and the invention/discovery of the products; the preclinical phase of testing involves animal studies to prove the safety, toxicity profile, and efficacy and to know suitable dose ranges. Table 21.1 presents a list of FDA-approved functionalized MNP products applied in nanomedicine or clinical trials. INFeds, Dexferrums, Venofers, Ferrlecits, and Ferahemes are applied to treat anemia related to kidney disease (CKD), as each of these products is composed of an iron oxide core coated by hydrophilic polymers including sucrose, and dextran, for the creation of slow dissolution of the iron following intravenous injection that leads to fast administration of significant doses without an increase of iron in the blood to a level which makes it toxic.80 Ferahemes is an imaging agent. In 2010, Nanothermt, which is the SPIONs coated by aminosilane approved by EU-wide regulations and applied for tumor therapy (glioblastoma) in late-stage clinical trials in the US. Nowadays, Feridex and GastroMARK have been withdrawn from the market. The Food and Drug Administration (FDA) has determined that magnetic inducing fields up to 8 T do not have any considerable physiological risk for adults.81 Feridex (USA), also called Endorem (EU), is an example of FDA-approved iron-based MRI contrast factor which is on the market.82 These MNPS have an iron oxide core with a size of between 50 nm and 180 nm in diameter with a negative charge, which have biocompatible and biodegradable properties.83

540

Table 21.1

List of functionalized MNPs approved by the FDA.80

Commercial product name

Formulation

Indication

Company name

Year of production

Inorganic and metallic nanoparticles Nanotherms (MagForce) GastroMARKt; umirems (AMAG pharmaceuticals) Ferrlecits (Sanofi Avertis)

SPIONs coated aminosilane SPION coated with silicone Sodium ferric gluconate Iron dextran (low MW) Iron sucrose

Allows cell uptake and introduces superparamagnetism Superparamagnetic character

Glioblastoma

2010

Imaging agent

2001 (2009)

Iron deficiency in chronic kidney disease (CKD) Iron deficiency in chronic kidney disease (CKD) Iron deficiency in chronic Kidney disease (CKD) Imaging agent

1999

INFeDs (Sanofi Avertis) Venofers (Luitpold Pharmaceuticals) Feridexs/Endorems (AMAG pharmaceuticals) DexIrons/Dexferrums (Sanofi Avertis) Ferhemet/ferumoxytol (AMAG pharmaceuticals)

SPION coated with dextran Iron dextran (high MW) Ferumoxytol SPION with Polyglucose sorbitol Carboxymethylether

Allows increased dose Allows increased dose Allows increased dose Superparamagnetic character Allows increased dose Magnetite suspension allows for prolonged steady release Decreasing number of doses

Iron deficiency in chronic kidney disease (CKD) Deficiency anemia iron Deficiency in chronic Kidney disease (CKD)

1957 2000 1996 (2008) 1957 2009

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541

21.6 Conclusion The evaluation and study of the in vitro toxicity of bare MNPs and coatedMNPs is a highly in demand research in recent times. However, there is no more data about in vivo toxicity of bare MNPs and functionalized-MNPs. Although the application of functional or multifunctional MNPs with the potential for medicine is going to increase the coincident diagnosis and local therapeutic applications, two significant issues are necessary to be taken into account when choosing bare- or functionalized-MNPs for in vivo applications. At first, the relevant side effects and the fate of applied nanoparticles including retention time or elimination approach in the system of the body if these nanoparticles are biodegradable because once the surface-derivatized nanoparticles are inside the cells, the coating is digested, leaving the bare MNPs exposed to other organelles and cellular components, thereby possibly affecting the overall cell integrity. The second one is nanoparticle destabilization because of the plasma protein adsorption and their non-specific cellular uptake by the RES, which may cause agglomeration and recognition with the innate immune system, respectively. Some researchers presumed that hard coatings are good candidates to overcome these shortcomings. The research advancements have reported some toxic effects of MNPs in living systems. The decoration of coating material, combinatorial surface decoration and ligands of different charge and hydrophobicity could tune different cytotoxicity-related bioeffects. Positively charged and hydrophobic nanoparticles are more likely to be internalized by the cells and induce autophagy, oxidative stress and apoptosis than are negatively charged or hydrophilic nanoparticles. The same coated-MNPs must be tested with different cell lines using the same protocol/method, which would gain real comparison and estimation of the experimental blunder between various research teams. In this review, the toxicity tests applied for evaluation of the toxicity effects of functionalized MNPs are investigated. Besides, the toxicity effects of functionalized MNPs are compared with non-functionalized MNPs with regards to the effects of functionalization of a bare MNP surface by various functional groups on the reduction of their toxicity.

Abbreviations ACT APTMS APTT ATP BrdU CHO CKD CTAB EU FDA

activated clotting time 3-aminopropyltrimetoxysilane activated partial thromboplastin time adenosine triphosphate 5-bromo-2 0 -deoxyuridine Chinese Hamster Ovary cells chronic kidney disease hexadecyltrimethylammonium bromide European Union Food and Drug Administration

542

GFP IONs LDH MIONPs MNPs MTT NMs NNI PAMAM PDA PEG PEI PEO PI PLLA PSS PT PVA PVP SPIONs SRB TEOS

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green fluorescent protein iron oxides lactate dehydrogenase magnetic iron oxide nanoparticles magnetic nanoparticles 3-(4,5-Dimethylthiazol-2-yl)2,5-diphenyl tetrazolium bromide nanomaterials the National Nanotechnology Initiative polyamidoamine polydopamine polyethylene glycol polyethylenimine polyethyleneoxide propidium iodide poly L-lactic acid polystyrene sulfonate prothrombin time poly(vinyl alcohol) polyvinylpyrrolidone superparamagnetic iron oxide nanoparticles Sulphorhodamine B tetraethylorthosilicate

Websites of Interest https://www.fda.gov https://www.usda-eu.org https://www.nano.gov

References ¨yu ¨ktiryaki and C. M. Hussain, TrAC, Trends Anal. Chem., 1. R. Keçili, S. Bu 2019, 110, 259. 2. C. M. Hussain, Handbook of Nanomaterials in Analytical Chemistry: Modern Trends in Analysis, Elsevier, 2019. 3. K. Wu, D. Su, J. Liu, R. Saha and J.-P. Wang, Nanotechnology, 2019, 30, 502003. 4. C. M. Hussain, Magnetic Nanomaterialsfor Environmental Analysis, Advanced Environmental Analysis-Application of Nanomaterials, ed., C. M. Hussain and B. Kharisov, The Royal Society of Chemistry, 2017, ch. 11, p. 284. 5. R. Keçili and C. M. Hussain, Int. J. Anal. Chem., 2018, 8503853. 6. C. M. Hussain, Nanomaterials in Chromatography: Current Trends in Chromatographic Research Technology and Techniques, Elsevier, 2018. 7. C. M. Hussain and R. Keçili, Modern Environmental Analysis Techniques for Pollutants, 1st edn, 2019, Elsevier.

Toxicity, Safety and Legal Aspects of Functionalized MNPs

543

8. G. S. Zamay, T. N. Zamay, K. A. Lukyanenko and A. S. Kichkailo, J. Biomed., 2020, 8, 59. 9. S. Natarajan, K. Harini, G. P. Gajula, B. Sarmento, M. T. Neves-Petersen and V. Thiagarajan, BMC Mater., 2019, 1:2, 22. 10. B. A. Ankamwar, T. C. Lai, J. H. Huang, R. S. Liu, M. Hsiao, C. H. Chen and Y. K. Hwu, Nanotechnology, 2010, 21, 75102. 11. W. Schaertl, Nanoscale, 2010, 2(829), 43. ¨yu ¨ktiryaki, R. Keçili and C. M. Hussain, Functionalized nanoma12. S. Bu terials in dispersive solid phase extraction: Advances & prospects, TrAC, Trends Anal. Chem., 2020, 127, 115893. 13. C. M. Hussain, Handbook on Miniaturization in Analytical Chemistry: Application of Nanotechnology, Elsevier, 2020. 14. S. D. Anderson, V. V. Gwenin and C. D. Gwenin, Nanoscale Res. Lett., 2019, 14(188), 1–16. 15. H. A. Panahi, S. Nourbakhsh and F. Siami, Adv. Polym. Technol., 2018, 37(8), 3659. 16. A. Vegerhof, M. Motei, A. Rudinzky, D. Malka, R. Popvtzer and Z. Zalevsky, Biomed. Opt. Express, 2016, 7, 4583. 17. J. Devkot, J. Wingo, T. T. T. Mai, X. P. Nguyen, N. T. Huong, P. Mukherjee, H. Srikanth and M. H. Phan, J. Appl. Phys., 2014, 115, 17B503. 18. P. Qin, D. Huang, Z. Xu, Y. Guan, Y. Bing and A. Yu, Open Chem., 2019, 17, 1301. 19. Y. Ludan, S. Chen, C. H. T. Kwong and R. Wang, J. Mater. Chem. B, 2020, 8, 2749. 20. B. Khan, A. Rehman, A. Hayat and S. Andreescu, Magnetochem, 2019, 5(63), 1–22. 21. B. Saifullah and M. Z. B. Hussein, Int. J. Nanomed., 2015, 10, 5609. 22. Z. J. Deng, M. Liang, I. Toth, M. Monteiro and R. F. Minchin, Nanotoxicology, 2012, 7, 314. ¨nder and 23. M. Kokkinopoulou, J. Simon, K. Landfester, V. Maila I. Lieberwirth, Nanoscale, 2017, 9, 8858. 24. W. Mekseriwattana, S. Srisuk, R. Kriangsaksri, N. Niamsiri and K. Prapainop, AAPS PharmSciTech, 2019, 20, 55. ´rez-Herna ´ndez, M. Monge, L. Gutie ´rrez and 25. G. Stepien, M. Moros, M. Pe R. M. Fratila, et al., ACS Appl. Mater. Interfaces, 2018, 10, 4548. 26. J. Xie, G. Liu, H. S. Eden, H. Ai and X. Chen, Acc. Chem. Res., 2011, 44, 883. 27. N. Zhu, H. Ji, P. Yu, J. Niu, M. U. Farooq, M. Waseem Akram, I. O. Udego, H. Li and X. Niu, Nanomaterials, 2018, 8, 810. ¨yu ¨ktiryaki, R. Keçili and C. M. Hussain, TrAC, Trends Anal. Chem., 28. S. Bu 2020, 127, 115893. 29. W. Wu, Z. Wu, T. Yu, C. Jiang and W.-S. Kim, Sci. Technol. Adv. Mater., 2015, 16, 023501. 30. W. Ling, M. Wang, C. Xiong, D. Xie, Q. Chen, X. Chu, X. Qiu, Y. Li and X. Xiao, Int. J. Mater. Res., 2019, 34, 1828.

544

Chapter 21

31. R. Vakili-Ghartavol, A. A. Momtazi-Borojeni, Z. Vakili-Ghartavol, H. T. Aiyelabegan, M. R. Jaafari, S. M. Rezayat and S. ArbabiBidgoli, Artif. Cells Nanomed. Biotechnol. J., 2020, 48, 443. 32. H. Markides, M. Rotherham and A. J. E. Haj, J. Nanomater., 2012, 614094, 11. ´rez, B. Pelaz, S. J. Soenen, B. B. Manshian, W. J. Parak, 33. F. Joris, D. Valdepe S. C. D. Smedt and K. Raemdonck, J. Nanobiotechnol., 2016, 14(1), 69. 34. J. H. Shannahan, X. Lai, P. C. Ke, R. Podila, J. M. Brown and F. A. Witzmann, PLoS One, 2013, 8(9), e74001. 35. H. Sun, J. Cuijuan, L. Wu, X. Bai and S. Zhai, Front. Bioeng. Biotechnol., 2019, 7, 414. ¨feli and M. Mahmoudi, Adv. Colloid Interface 36. S. Laurent, S. Dutz, U. O. Ha Sci., 2011, 166, 8. 37. M. Mahmoudi, M. A. Sahraian, M. A. Shokrgozar and S. Laurent, ACS Chem. Neurosci., 2011, 2, 118. 38. S. Sharifi, S. Behzadi, S. Laurent, M. Laird Forrest, P. Stroeve and M. Mahmoudi, Chem. Soc. Rev., 2012, 41, 2323. 39. M. Mahmoudi, H. Hosseinkhani and M. Hosseinkhani, et al., Chem. Rev., 2011, 111, 253. 40. H. Shagholani, S. M. Ghoreishi and S. H. Sharifi, J. Drug Delivery Sci. Technol., 2018, 45, 373. 41. M. A. Malvindi, V. De Matteis and A. Galeone, et al., PLoS One, 2014, 9(1), e85835. 42. B. Laffon, N. Fernandez-Bertolez and C. Costa, et al., Cellular and Molecular Toxicology of Nanoparticles, Berlin, 2018, pp. 199–213. ´ndez-Berto ´lez, E. Pa ´saro, J. P. Teixeira, 43. G. Kiliç, C. Costa, N. Ferna B. Laffon and V. Valdiglesiasa, Toxicol. Res., 2016, 5, 235. 44. R. S. Varma, Sustainable Chem. Process., 2014, 16, 2027. 45. J. Mosayebi, M. Kiyasatfar and S. Laurent, Adv. Healthcare Mater., 2017, 6(23), 1700306. 46. A. K. Gupta and A. S. G. Curtis, Biomaterials, 2004, 25, 3029. 47. A. K. Gupta and S. Wells, IEEE Trans. Nanobiosci., 2004, 3, 66. 48. F. X. Hu, K. G. Neoh, L. Cen and E. T. Kang, Biomacromolecules, 2006, 7, 809. 49. R. G. Rayavarapu, W. Petersen, L. Hartsuiker, P. Chin, H. Janssen and F. W. B. Leeuwen, et al., Nanotechnology, 2010, 21, 10. 50. A. Petri-Fink, M. Chastellain, L. Juillerat-Jeanneret, A. Ferrari and H. Hofmann, Biomaterials, 2005, 26, 2685. ´, 51. F. Oltolina, D. Colangelo, I. Miletto, N. Clemente, M. Miola, E. Verne M. Prat and A. Follenzi, Nanomaterials, 2019, 9(11), 1575. 52. C. Kaewsaneha, K. Jangpatarapongsa, T. Tangchaikeeree, D. Polpanich and P. Tangboriboonrat, J. Biomater. Appl., 2014, 29(5), 761. 53. A. Ebrahiminezhad, V. Varma, S. Yang, Y. Ghasemi and A. Berenjian, Nanomaterials, 2016, 6, 1. 54. S. Shukla, A. Jadaun, V. Arona, R. K. Sinha, N. Biyani and V. K. Jain, Toxicol. Rep., 2015, 2, 27.

Toxicity, Safety and Legal Aspects of Functionalized MNPs

545

55. W. J. Yang, J. H. Lee, S. C. Hong, J. Lee, J. Lee and D.-W. Han, Materials, 2013, 6(10), 4689–4706. ˘, A. Boldeiu, 56. R. C. Popescu, E. Andronescu, B. S. Vasile, R. Trusca ˘ L. Mogoanta, G. D. Mogosanu, M. Temelie, M. Radu, A. M. Grumezescu and D. Savu, Molecules, 2017, 22(1080), 1. 57. R. J. Wydra, C. E. Oliver, K. W. Anderson, T. D. Dziubla and J. Z. Hilt, RSC Adv., 2015, 5, 18888. 58. A.-Z. Chen, X.-F. Lin, S.-B. Wang, L. Li, Y.-G. Liu, L. Ye and G.-Y. Wang, Toxicol. Lett., 2012, 212, 75. ¨feli, J. S. Riffle, A. Carmichael-Baranauskas, L. Harris59. U. O. Ha Shekhawat, F. Mark, J. P. Dailey and D. Bardenstein, Mol. Pharm., 2009, 6, 1417. `, F. A. Ruffinatti, I. Stura , M. Argenziano, 60. S. A. M. K. Ansari, E. Ficiara O. Abollino, R. Cavalli, C. Guiot and F. D’Agata, Materials, 2019, 12(3), 465. 61. M. K. Khalid, M. Asad, P. Henrich-Noack, M. Sokolov, W. Hintz, L. Grigartzik, E. Zhang, A. Dityatev, B. Wachem and A. Sabel, Int. J. Mol. Sci., 2018, 19, 2613. 62. M. A. Fouriki, N. Clements, J. Farrow and J. Dobson, J. Tissue Eng. Regener. Med., 2012, 8, 169. 63. A. Fouriki and J. Dobson, Materials, 2013, 6(1), 255. 64. Q. Yu, X.-Q. Xiong, L. Zhao, T.-T. Xu, H. Bi, R. Fu and Q.-H. Wang, Curr. Med. Sci, 2018, 38, 1096. 65. M. A. Abakumov, A. S. Semkina, A. S. Skorikov, D. A. Vishnevskiy, A. V. Ivanova, E. Mironova, G. A. Davydova, A. G. Majouga and V. P. Chekhonin, J. Biochem. Mol. Toxicol., 2018, e22225. 66. R. M. Patil, N. D. Thorat, P. B. Shete, P. A. Bedge, S. Gavde, M. G. Joshi, S. A. M. Tofail and R. A. Bohara, Biochem. Biophys. Rep., 2018, 13, 63. 67. S. J. H. Soenen, E. Illyes, D. Vercauteren, K. Braeckmans, Z. Majer and S. C. De Smedt, et al., Biomaterials, 2009, 30, 6803. ¨ller, J. N. Skepper, M. Posfai, R. Trivedi, S. Howarth and C. Corot, 68. K. Mu et al., Biomaterials, 2007, 28, 1629. 69. N. D. Thorat, R. A. Bohara, M. R. Noor, D. Dhamecha, T. Soulimane and S. A. M. Tofail, ACS Biomater. Sci. Eng., 2017, 3, 1332. 70. I. Raynal, P. Prigent, S. Peyramaure, A. Najid, C. Rebuzzi and C. Corot, Invest. Radiol., 2004, 39, 56. 71. C. C. Compton, P. Jacobs, R. Weissleder, D. D. Stark, B. L. Engelstad and B. A. Bacon, et al., AJR. Am. J. Roentgenol., 2016, 152, 167. 72. P. Bourrinet, H. H. Bengele, B. Bonnemain, A. Dencausse, J.-M. Idee and P. M. Jacobs, et al., Invest. Radiol., 2006, 41, 313. 73. D. L. J. Thorek, A. K. Chen, J. Czupryna and A. Tsourkas, Ann. Rev. Biomed. Eng., 2006, 34, 23. 74. A. Moore, E. Marecos and A. Bogdanov, et al., Radiology, 2000, 214(2), 568–574. 75. N. Lewinski, V. Colvin and R. Drezek, Small, 2008, 4(1), 26. 76. J. Zhang, M. C. Shin, A. E. David, J. Zhou, K. Lee, H. He and V. C. Yang, Mol. Pharm., 2013, 10(10), 3892.

546

Chapter 21

77. I. V. Belyanina, T. N. Zamay, G. S. Zamay, S. S. Zamay, O. S. Kolovskaya, T. I. Ivanchenko, V. V. Denisenko, A. K. Kirichenko, Y. E. Glazyrin, I. V. Garanzha, V. V. Grigorieva, A. V. Shabanov, D. V. Veprintsev, A. E. Sokolov, V. M. Sadovskii, A. Gargaun, M. V. Berezovski and A. S. Kichkailo, Theranostics, 2017, 7(13), 3326. 78. D. Sharma and C. M. Hussain, Arabian J. Chem., 2020, 13, 3319. 79. J. Jeevanandam, A. Barhoum, Y. S. Chan, A. Dufresne and M. K. Danquah, Beilstein J. Nanotechnol., 2018, 9, 1050. 80. S. Bancos, K. M. Tyner and J. L. Weaver, in Handbook of Immunological Properties of Engineered Nanomaterials, ed. M. A. Dobrovolskaia and S. E. McNeil, World Scientific Publishing Ltd, Singapore, 2013, p. 671. 81. D. Bobo, K. J. Robinson, J. Islam, K. J. Thurechtand and S. R. Corrie, Pharm. Res., 2016, 33(10), 2373. 82. S. M. Cromer Berman, P. Walczak and J. W. Bulte, Nanomed. Nanobiotechnol., 2011, 3, 343. 83. A. L. Jasmin, A. L. M. Torres and H. M. P. Nunes, et al., J. Nanobiotechno1., 2011, 9, 4.

Section 7: Conclusion: The Future of Analytical Chemistry

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Functionalization of Magnetic Nanoparticles for Tomorrow’s Applications ADITYA NARAYAN SINGH*a AND CHAUDHERY MUSTANSAR HUSSAINb a

Center for Superfunctional Materials, Department of Chemistry, Ulsan National Institute of Science and Technology (UNIST), 50, UNIST-gil, Ulsan 44919, Republic of Korea; b Department of Chemistry and Environmental Science, New Jersey Institute of Technology, Newark, NJ 07102, USA *Email: [email protected]

22.1 Introduction The civilization journey of homo sapiens began at no exact date fastened in history; however, it is believed that several thousands of centuries passed before what we see today as our modern society. It is believed that homo sapiens began their journey as a hunter-gatherer. Gradually, the art of alloy1 making by Sumerians in the third millennium B.C.2 allowed them to develop weapons that were very pointed, handy, and sharp, which facilitated their hunting ability. The art of alloy design with better-equipped tools allowed the initially nomadic and barbarian sects to settle down at a place for quite a long time, and slowly transformed into a society. Later on, these societies turned themselves into an agricultural society.3 Historically, agriculture evolved as an outcome of a longterm evolutionary process of socio–economic significance. Societies began agriculture with the aid of tools made of iron and also used them in warfare.4 Theories about the influence and origin of iron on human society has a long Analytical Applications of Functionalized Magnetic Nanoparticles Edited by Chaudhery Mustansar Hussain r The Royal Society of Chemistry 2021 Published by the Royal Society of Chemistry, www.rsc.org

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history. Sensing the enormous potential of iron, prehistoric societies straight away changed from stone age to iron age. However, heating iron in the presence of charcoal gave birth to a much stronger alloy than iron, it gave birth to steel. Ancestors using iron switched to steel which had exceptional properties. Just as prehistoric civilizations experienced a rapid advancement during and after the Iron Age, it is the fourth industrial revolution that has changed the dynamics of the markets and industries of iron once again. Today, iron again might be a revolutionary material due to its marriage with nanomaterials. The world of nanomaterials refers to anything that is one-billionth of a meter, or a few tens of a nanometer, or anything less than few microns in size. Also, some define it as one of the dimensions should be in the nanoscale, or it can also be defined with two or three dimensions confined within a nanometer scale.6 Having seen a wide-ranging definition of a nanomaterial, it gives ample space to material scientists to explore several possibilities yet to remain under the nanoscale. The past few decades have witnessed unprecedented development in the field of magnetic nanomaterials (Figure 22.1). Functionalized magnetic nanoparticles (MNPs) have wide-ranging applications in many scientific fields, including material sciences,7–10 physics,11,12 chemistry,13–16 catalysis,17–20 biomedicine,21–25 pharmaceuticals,26 thermal management,27,28 electronics,29,30 magneto-resistance sensors,31 magnetic resonance imaging,32,33 data storage,34 spintronics,35 environmental remediation,36,37 superalloys,38–42 and water treatment,43 that have garnered intense research interest these days. MNPs are ubiquitous and can be found almost everywhere, even inside us.

Figure 22.1

The number of published papers per year over the last 5 years mentioning ‘‘magnetic nanoparticles’’. These statistics have been obtained from the Web of Science database collection. These results were obtained using the keywords ‘‘magnetic nanoparticles’’ in the title (the statistics for 2020 was not complete).

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It is believed that the human brain itself containsB108 MNPs of iron oxide per gram of tissue.44 Ferritin is another well-known protein that stores iron and is found in almost every living cell. Classification of a magnetic particle depends upon how strongly they are influenced under the external applied magnetic field. Ideally, every material responds to the applied magnetic field to a certain extent. Based on their influence, they can be classified as ferromagnetic, diamagnetic, paramagnetic, antiferromagnetic, and ferrimagnetic. The antiferromagnetic, and ferrimagnetic classification can be further clubbed to a broad category of ferromagnetic materials. Thus, ferrimagnetic and antiferromagnetic materials show a strong attraction toward a magnet. However, diamagnetic and paramagnetic materials show repulsion and a weak attraction, respectively, under the influence of an applied external magnetic field. Magnetic susceptibility (Xm) is generally used to describe the strength of a magnetic material, and to describe the magnetic materials category to which it falls. For diamagnetic materials, the Xm is o0 (negative) and is temperatureindependent while for paramagnetic materials Xm40 (positive), its value decreases with an increase in temperature. However, when Xm describes a ferromagnetic material, it displays an exceptionally high value (106) compared to those of dia- and paramagnetic materials. It is generally believed that a ferromagnetic material shows a permanent magnetic moment, even in the absence of an external field. The magnetization curve of ferromagnetic, paramagnetic, and diamagnetic materials is shown in Figure 22.2. The magnetic properties of a material are a strong function of the interatomic distance and exchange coupling forces between them. Furthermore, it is known that temperature, which is directly related to materials entropy,45 has a significant role in determining the magnetic properties. Whenever temperature increases, the arrangement of atomic spin experiences a random orientation, i.e., the entropy of the system increases, which results in

Figure 22.2

Schematic representation of field dependence on magnetization for ferromagnetic, paramagnetic, and diamagnetic materials.

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yielding a decrease in saturation magnetization (MS). Since MS is a function of temperature, a critical temperature that ensures MS to become zero is known as the Curie temperature (TC). Often, the material turns out to be paramagnetic at TC.

22.1.1

Intriguing Features of Nanoparticles

Primarily two fundamental aspects dominate the magnetic properties of nanoparticles (NPs): the first being their surface and the other being finite-size effects, which give rise to various intriguing features, summarized46 in Figure 22.3. Both features have a separate origin, which will be discussed in brief. Nanomaterials as we all know have at least one of their dimensions in nanometers. Since particles are confined and are extremely small, their crystal symmetry is broken at the boundary of each particle. This boundary-breaking

Figure 22.3

Schematic representation of magnetic effects exhibited by MNPs. (a) The spin arrangements inside ferromagnetic materials. (b) The spin arrangements inside antiferromagnetic materials. (c) An enlarged version of (a) demonstrating the possibilities of the material with two different phases (marked by a larger rectangular area and smaller rectangular area). The novel material can be based on high coercivity (Hc) and high remanence magnetization (Mr). (d) A schematic representation of magnetic moments inside a superparamagnet. (e) Demonstration of the exchange bias effect arising due to the interaction between the interface of an antiferromagnet and ferromagnet. (f) The magnetization plot of an ideal antiferromagnetic NP. The uncompensated spins (marked in b, arrows marked on the top surface of the cuboid) could lead to a net magnetization along with a superparamagnetic relaxation inside a pure antiferromagnetic material. Reproduced from ref. 46 with permission from John Wiley & Sons, Copyright r 2007 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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gives immense surface exposure. In contrast, finite-size effects evolve from most appreciated quantum confinement effects.47 We encourage our reader to read more independent reviews on magnetism elsewhere.48–50 Before moving indepth on the MNP discussion, we make a general agreement that considers the size limits for nanoparticles to be diameters ranging from 1 to 100 nm. This is because there is no general agreement among the scientific community on the size boundaries of NPs.

22.1.1.1

Surface Effect of Nanoparticles

As we move toward a reduction in the particle size, a significant fraction of the atoms acquire a tendency to occupy the surface, which implies that now surface and bulk effects become more prominent. For instance, in face-centered cubic (FCC) cobalt, having acquired a diameter of B1.6 nm, it is believed to possess 60% of the total number of spins originating from surface spins.48 This imbalance of surface to bulk atomic ratio leads to a bigger contribution of surface spins in magnetic property determination of NPs. Furthermore, the band structure also experiences a change arising due to the local breaking of the symmetry. This may also lead to altering the lattice constant and atomic coordination. A few other surface-dominated effects come into the picture including surface anisotropy or bulk–surface exchange anisotropy.

22.1.1.2

Finite-size Effect of Nanoparticles

As the particle tends to achieve nanometric size, the Newtonian mechanism no longer governs their behavior. They now become a proprietary of Quantum mechanics. Their properties are governed by the Quantum confinement effects. Few notable features that are studied widely based on finite-size are as follows: superparamagnetic limit and the single domain limit.51 The superparamagnetic limit is an important phenomenon arising in MNPs when particle size reduces considerably. When particle size decreases beyond a specific limit, the magnetic anisotropy energy per particle responsible for holding the magnetic moment along specific directions becomes comparable to the thermal energy. When this state is achieved, the thermal fluctuations are now capable of inducing random flipping of the magnetic moment with time, and the nanoparticles lose their stable magnetic order and become superparamagnetic.52,53 In this condition, the material loses its hysteresis. A multidomain structure exists in a magnetic particle which consists of a uniform magnetization region well separated by their domain walls. Fundamentally these domains are formed as a result of minimizing the magnetostatic energy (Ed ¼ HdM). These domains are said to be in equilibrium when magnetostatic energy (Ed is proportional to the volume of the materials) attains a balance with domain-wall energy (Edw), which is a linear function of the interfacial area between the domain wall. When particle size appreciably reduces below a certain critical diameter (Dc), it becomes

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relatively difficult to sustain the formation of domain wall and to support external magnetostatic energy equally. Thus, in this reduced space (typically of the order of few nanometers), there exists only a single-domain. In the single-domain limit, all the particles are uniformly magnetized, with almost all the spins aligned in the same direction.

22.1.2

Synthesis of Magnetic Nanoparticles

There are several routes (Figure 22.4) to achieving highly stable, narrow size distribution, and shape-controlled MNPs.54 Few popular methods can be listed as, co-precipitation, sol–gel reaction, electrochemical methods, wet chemistries, microemulsion, flame spray pyrolysis, laser pyrolysis, pulsed laser ablation, thermal decomposition, polyol method, vapor methods, flow injection synthesis, and so on. However, here a few of the most widely used methods will be discussed.

22.1.2.1

Co-precipitation Method

Of the several variants of iron oxide MNPs, for instance, Fe3O4 (popularly known as magnetite), a-Fe2O3 (commonly known as hematite as it is weakly antiferromagnetic/ferromagnetic), e-Fe2O3, b-Fe2O3, g-Fe2O3 (maghemite, behaves as a ferrimagnetic), and FeO (wustite, antiferromagnetic), maghemite and magnetite are the popular candidates owing to their biocompatibility.55 A co-precipitation, as the name suggests, is a facile technique of obtaining the desired product from an aqueous solution containing a precursor salt of Fe21/Fe31 under a controlled inert atmosphere while adding a suitable base to regulate the pH of the solution.56 The shape, size, and composition of the final MNPs obtained are entirely dependent upon the type of the precursor salts used (e.g., nitrates/chlorides/sulfates), the ratio of Fe21/Fe31, the pH value, the ionic strength of the solvent, and most importantly the reaction temperature. To reproduce the synthesized product, it is highly desirable that the synthetic procedures and conditions are fixed. The other important question after synthesis is their stability. MNPs have a propensity to agglomerate and are not stable under ambient conditions. Under ambient conditions, they are prone to get oxidized. However, this is less of an issue in maghemite as it is ferrimagnetic in nature and reluctant to oxidations. Therefore, to extend the time of agglomerations, the synthesized magnetite NPs can be deliberately oxidized to convert them into maghemite. This oxidation can be achieved by dispersing the synthesized MNPs in acidic media, followed by the addition of Fe(NO3)3. Thus, the final product (maghemite) obtained is then chemically stable in acidic and alkaline environments. Even if strategies have been developed to obtain stable particles by deliberately oxidizing them in maghemite after the initial formation of MNPs, the experimental challenge still lies ahead in precisely controlling their particle size to achieve a narrow particle-size distribution (PSD). Furthermore, the blocking temperarture57 (blocking temperature is defined as the minimum temperature at which thermal energy

Functionalization of Magnetic Nanoparticles for Tomorrow’s Applications

Various synthesis techniques used for the synthesis of magnetic nanoparticles. Reproduced from ref. 54 with permission from the Royal Society of Chemistry.

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Figure 22.4

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becomes minimum so as to block the magnetic moments) is another factor that aggravates the situation. Furthermore, it is known that blocking temperature depends upon particle size, and a wide PSD will ultimately result in a wide range of blocking temperatures, thereby making the synthesized MNPs display a non-ideal magnetic behavior forbidding it from many applications. Thus, the MNPs synthesized via a co-precipitation technique, unfortunately, tend to display a polydisperse feature. Recently, monodisperse MNPs have been obtained by the use of various stabilizing agents. Polymers like polyvinyl alcohols (PVAs) in conjunction with silica coating have been adapted to obtain monodisperse super MNPs.58 MNPs with sizes ranging in between B4–10 nm can be stabilized for a long duration by keeping them in an aqueous solution of PVA (1 wt%). However, MNPs were found to agglomerate in PVA (0.1 mol%) with carboxyl groups as the stabilizing agent.59 These two results indicate the importance of the proper selection of stabilizing agents. Organic polymers are widely used to stabilize MNPs via the formation of surface complexes. This mechanism of stabilization by organic stabilizers proceeds in two steps: first, the complex formation inhibits the nucleation, and second, particle growth is impeded by the adsorption of additives on nuclei. All these facts make co-precipitation the most widely used excellent synthetic route to obtain magnetic iron oxide nanoparticles. Though there are several beneficial aspects of using co-precipitations, there are specific issues with this method. Since the size of MNPs obtained via this route is extremely small, they have a tendency to quickly agglomerate owing to their large specific area and energy. Furthermore, the use of pH imposes another issue on this method as it requires precise control of the desired pH, which is indeed a tedious task. In the absence of uncontrolled pH, the product can be of varying composition, which restricts their usage.

22.1.2.2

Hydrothermal

The hydrothermal process can suitably obtain a wide range of MNPs. This technique has an added advantage of obtaining the desired NPs with/without specific surfactants. Recently, a one-step hydrothermal technique was used to obtain highly crystalline magnetite nanoparticles (40 nm) without using surfactants.60 In another report on hydrothermal synthesis of superparamagnetic magnetite nanoparticles with a controlled size B20 nm with 3,4-dihydroxyhydroxycinnamic acid (DHCA).61 The original size could be controlled and tuned, ranging from B50 to 400 nm by controlling the reaction time.

22.1.2.3

Microemulsion Technique

A microemulsion is a thermodynamically stable state of two immiscible liquids with isotropic dispersion, where the microdomain of liquids (either one or can be both) is/are stabilized by an interfacial film of surfactant molecules.62 The microemulsion phase of water-in-oil (W/O) consists of an

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aqueous phase dispersed as microdroplets very well surrounded by a monolayer of a continuous hydrocarbon phase. Recently, magnetite and silica-coated (Fe3O4) magnetite NPs were synthesized by a W/O microemulsion technique using the precursor salts of hydrated ferric nitrate, ferrous sulfate, and ammonia as a precipitating agent with the assistance of Tween-80 and sodium dodecyl sulfate (SDS) acting as surfactants.63 Several other MNPs have been synthesized using this technique, such as gold-coated Pt/Co alloys, Co (metallic), and Pt/Co NPs in reverse micelles of cetyltrimethylammonium bromide (C19H42BrN), assisted with 1-butanol (co-surfactant) and octane as the oil phase.64 Microemulsions are also known as ‘‘nanoreactors’’ to produce several NPs. In addition to basic MNPs, the interest has grown in the synthesis of mixed metallic MNPs with their broader application in biomedical/electronics.65 To explore this direction, these nanoreactors can assist in the synthesis of these novel compounds. To start with, TMFe2O4 (TM: the first row of transition metals) NPs with a particle size ranging from B4–15 nm are successfully synthesized via water–toluene inverse micelles containing aqueous solutions of Mn(NO3)2 and Fe(NO3)3 as starting precursors and SDS as a surfactant. This method yields particles with either spheroids, rectangular crosssection, or in a tube shape.66 Furthermore, this technique can be extended for the synthesis of various TM (Zn, Cu, Mn, Ni, Co, and so on) based MNPs. With a slight modification in the synthesis route, spinel ferrites (MnFe2O4) with controllable sizes can also be synthesized through the formation of the inverse micelles (water-in-toluene) with sodium dodecylbenzene sulfonate (NaDBS) as the surfactant.67 To obtain ferritic cobalt fluid, first sodium dodecyl sulfate was treated either with cobalt acetate solution or with iron chloride to obtain in situ formed cobalt and iron dodecyl sulfate, which were further reacted to obtain the desired fluid.68 Though the microemulsion technique has numerous advantages as compared to other synthetic methods for obtaining MNPs. Its versatility stems from the use of less sophisticated equipment, which requires very little training. Furthermore, it offers a variety of control parameters to precisely tune the particle composition, size, and shape, with the desired crystallinity. It is further appreciated by its use of benign synthetic conditions of pressure and temperature.69

22.1.2.4

Wet Chemistries

Wet chemistry is popularly known as wet chemical synthesis. It is bifurcated into two broad categories consisting of the bottom-up approach and the topdown approach. The bottom-up approach further includes sol–gel and precipitation methods, where materials containing the desired precursor salt are mixed in a controlled manner to form a colloidal solution. Whereas, in the topdown approach, large single crystals are imprinted in an aqueous solution for producing NPs, or sometimes these large sizes can be even ores of the materials as well. For instance, a recent technique has been developed to produce

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MNPs from the ores of natural iron oxide (magnetite) or obtaining porous silicon via the electrochemical etching process. Briefly, in a sol–gel technique, a continuous liquid phase can be obtained via the formation of colloidal suspension and gelation of the sol. To obtain these colloidal suspensions, the precursor salt consists of the desired metal and metalloid with various other reactive ligands. These precursors are further treated to form a dispersible oxide to slowly turn them into a sol in water/ethanol/acid environments. These sols are stirred vigorously/slowly as per the requirements at a specific optimized temperature to remove excess liquids to obtain the gel. Particle size is controlled via the addition of various capping agents and stabilizing agents during this process. These gels are then transferred into a Petri dish and are allowed to dry in a vacuum oven overnight. These dried gels are then transferred to an alumina crucible for further calculations at a predetermined temperature or at an optimized temperature to obtain a desired shape/size/ morphology. The sol–gel approach for synthesizing oxides of MNPs is a widely adopted strategy among chemists. Once the powders are obtained after calcination, they can be characterized by a series of characterization techniques, for instance, high-resolution powder X-ray diffraction (HR-PXRD), scanning electron microscopy (SEM), high-resolution transmission electron microscopy (HR-TEM), and so on. Laser ablation strategies are another extensively used method for the preparation of MNPs. In this process, a powerful laser is used for the primary source of excitation for generating clusters directly from a solid sample in wide-ranging applications. The versatility of this method to obtain small sized particles and thick films of ceramic material makes it an obvious choice for bulk production.

22.1.3 Stabilizing Magnetic Nanoparticles 22.1.3.1 Polymer Coatings Polymers are versatile compounds often used in various fields to stabilize synthesized materials for their long-duration applications. Their wide applications can be traced right from energy storage to energy conversion devices,71 environmental analysis,72 biomedical applications,73 and in general for stabilization and dispersion techniques.74 During the nanomaterial synthesis, it is of utmost importance that particles are stopped from coalescencing or agglomerating. The NMs have a strong tendency to agglomerate due to their highly reactive larger surface area. Thus, several polymers or surfactants are often used to passivate the surface of the NPs after the synthesis or even during the synthesis to impede agglomerations. To avoid their agglomerations, various polymeric coating techniques have been used. To stabilize MNPs, water-soluble polymers are also predominately used these days. For instance, highly monodispersed magnetite NPs can be prepared in organic solvents and then subsequently transferred to water using a biocompatible amphiphilic polymer. These particles can also be stabilized with oleic acid acting as a primary surfactant, subsequently poly(ethylene glycol) methyl ether-poly(3-caprolactone) (mPEG-PCL) amphiphilic block

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copolymer to act as a secondary surfactant. This configuration allows NPs to form a hydrophobic inner shell and hydrophilic outer surface.75 Similarly, magnetite NPs synthesized through co-precipitation techniques unavoidably consist of multiple ions of the form Fe21 and Fe31 in NH3 or NaOH environments and are usually negatively charged, resulting in coalescence or agglomeration. To stabilize these particles with multiple charges, MNPs must be peptized.76 Peptization is a process of dispersing MNPs in a colloidal state by the addition of surfactants such as oleic acid, perchloric acid, and tetramethylammonium hydroxide.77 In another technique, ferrofluids of MNPs are another way to stabilize them. In this technique, MNPs are acidified with HNO3 solution and subsequently treated with Fe(NO3)3 to further oxidize to maghemite. Once these suspensions are centrifuged, the obtained positively charged g-Fe2O3 are dispersed in water to stop agglomeration. This agglomeration is impeded due to the fact that the surface hydroxy group is protonated in acidic78 media (HNO3). For the commercial applications of ferrofluids, polymers or surfactants are chemically anchored on the surface of MNPs to improve their stability in acidic (pHo5) and basic environments (pH48). Toward deployment of MNPs in seawater applications, an extensive study has been carried out by coating with various stabilizing agents, namely carboxymethyldextran (CMD-MNP), gum Arabic (GA-MNP), and dextran (D-MNP).79 The colloidal stability was evaluated after 48 h. Surprising results appeared demonstrating that the hydrodynamic diameters were kept constant only in GA-coated MNPs, the polydispersity indexes, however, remain reasonably low for all the MNPs, and all of the coated particles demonstrated improved colloidal stability as obtained from the zeta-potential value of 30 mV. The better colloidal stability of GA-coated MNPs is attributed to the negatively charged surface of the MNPs, which creates repulsive forces between them, alleviating the effect of particle agglomeration. Similarly, MNPs coated with copolymers of vinyl sulfonic acid, acrylic acid, and styrene sulfonic acid have been studied.80 Exciting results were obtained from these studies. It was found that polymers possessing a low molecular weight result in the formation of clusters larger than 50 nm. This is because high molecular weight polymers act as a bridge between the particle and results in patches like structures, while low molecular weight polymers are incapable of screening van der Waals attractive forces and also result in thin coatings. This improper section of polymers leads to reduced stability of MNPs. However, when an appropriate molecular weight is selected, the conditions change entirely. Furthermore, when a secondary polymer is additionally added, it covers the entire magnetite and the cluster now becomes completely stable even in high concentrations (45 M NaCl solution). Though polymer coating assists in improving the MNP stability, it is incapable of protecting highly reactive MNPs. Another drawback of polymercoated MNPs is the relatively low intrinsic stability of the coating, particularly at higher temperatures. This situation is aggravated further by a possible catalytic reaction of the cores present in MNPs. Therefore, it is urgently required to devise other methods to protect various precious MNPs against deterioration and agglomeration.

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22.1.3.2

Chapter 22

Silica Coating

As discussed in the previous section, though the polymer coating effectively improves the stability of the MNPs, it is their core which reacts and degrades their stability. Therefore, to further improve the stability of MNPs, silica coatings are employed to impede the agglomeration of synthesized MNPs. Coating with silica shells not only protects the magnetic cores but also restricts the direct contact of the magnetic core in MNPs with external agents often associated with the silica surface, thus avoiding unwanted side reactions. Silica coating is of prime importance in suppressing the luminescence quenching arising due to direct attachments of dye on the surface of MNPs. To evade this situation, silica coating was first employed on the core of the MNP and then the dye molecules were grafted on the silica shell.81 What makes the silica shell so useful is their stability even under appreciable acidic media, even their surface can be easily functionalized, while they also offer better interparticle control feasibility both in structure and in solution via variations in their shell thickness. Having discussed the benefits of silica, we would move to the coating methodologies of a silica shell on MNPs. Of the several coating techniques, sol–gel and Stober methods are often the most opted choices for coating silica shells over MNPs.82,83 Coating thickness can be tailored by varying the amount of ammonium, the ratio of H2O to tetraethoxysilane (TEOS). The other advantage of silica coating is its hydrophilic surface, which can be easily functionalized with other moieties.84 This functionalization assists in broadening the applicability of silica-coated MNPs for their potential application in targeted drug delivery,85 bio-labeling,86 cholesterol oxidase (COD).84 For enzyme immobilization, g-Fe2O3 MNPs were synthesized via a co-precipitation technique.84 Under the controlled reaction conditions of the alkaline ammonia atmosphere, MNPs were coated with silica. Then, the surface functionalization of the silica-coated primary MNPs was achieved by coating it with organosilane immediately followed by glutaraldehyde activation, a bifunctional crosslinker in order to improve protein immobilization. This double functionalization of MNPs improves the particle agglomerations. The functionalization reactions proceed via two steps. Firstly, the silane coupling agents undergo condensation reactions to form silane polymers. Secondly, the resultant polymers interact with silanol groups (Si–OH) available on the surface of maghemite silica nanospheres by forming covalent siloxane (Si–O–Si) type bonds. These terminal amino groups of silanes can then probably react with other functional, active groups such as the aldehyde group. In addition to this encapsulation of magnetic cores by Si–O–Si, they also assist in biocompatibility. The MNPs functionalized with a silica shell are capable of binding cholesterol oxidase and showed an enhanced catalytic activity much higher than the non-functionalized counterpart.

22.1.3.3

Carbon Coatings

Though several efforts have been vested in deploying silica and polymers to stabilize MNPs, very few efforts have been devoted to carbon coating.

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Carbon coating has an extensive application area and it is hard to imagine our surroundings without carbon.87–89 They have an advantage over other protecting materials in terms of their thermal stability, biocompatibility, and mostly their chemical inertness. Right after the discovery of buckminsterfullerene,90 a resurgence of interest took place in carbon-based materials. Since then, research in carbon-based materials has never been decelerated. These well-developed graphitic carbon layers88 were proven to be an effective layer and indeed a guard against corrosion even in harsh acidic environments, which are indeed very crucial to many important applications. The advantages of carbon coating can be inherited in MNPs as well to enhance their functionalities. Additionally, carbon-coated NPs are usually in the metallic state, and thus have a higher degree of magnetic moment than their oxide counterparts. Recently carbon-coated FeCo NPs have been synthesized to systematically tackle tumor ablation in mice.91 These non-iron oxide magnetic particles are excellent imaging (MPI) tracers. It is also important to note that it is not only the coating, but also the proper size control of MNPs that is important to obtain sufficient signals from these biomaterials. Thus, FeCo@C NPs with a core size diameter of 10 nm produces a bright MPI signal compared to many of the commercial MPI tracers. A high level of MPI signal is believed to originate from a high saturation magnetization (192 emu g1) endowed by FeCo@C MNPs. Similarly, air-stable cobalt NPs via a sonochemical technique were obtained for important applications.92 The high stability is attributed to the formation of a carbon shell on the MNP surface. However, the NPs obtained were not uniformly distributed and rather are polydisperse in nature. Though carbon-coated MNPs offer many beneficial properties, their synthesis roots and poor understanding of the mechanism is still not explored, which makes particles often agglomerate and form clusters. Thus, the synthesis of carbon-coated, uniformly dispersible NPs in an isolated form is one of the prime challenges in this field.

22.1.4

Application of Magnetic Nanoparticles

There are several aspects that drive the application of MNPs in the modern day (Figure 22.5). For instance, their precise targeted drug delivery, ability to be controlled by an external magnetic field, less dosage amount, reduced side effects, and better efficacy.

22.1.4.1

Biomedical Application

Without a doubt, it can be reiterated that MNPs have served no other field better than biomedicine. Its innumerable applications are a vindication to the potential of MNPs owing to their strong ability to improve the diagnosis, reduction in size, and targeted drug delivery. Using MNPs as a drug carrier has incredible features as they can be externally directed and localized under an external magnetic field.93 Though there are several magnetic nanoparticles,

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Figure 22.5

Chapter 22

Schematic representation of the various application fields of magnetic nanoparticles.

superparamagnetic iron oxide nanoparticles (SPIONs) have proven to be the most lucrative as a therapy, polymer-modified as an effective drug delivery system, and as a diagnostic agent. Polymer functionalization, biomolecule addition, and organic additives with SPION further improves their performance capability. As targeted drug delivery is the need of the hour, SPION technology can assist in maneuvering those possibilities in a more precise way. In this direction, dextran or polyethylene glycol are further coated to Fe3O4 (magnetite) or g-Fe2O3 (maghemite) particles to improve their therapeutic handles and boost their circulation through the blood.94 It is essential that drug-loading inside MNPs should not compromise its functionality, yet it should be delivered at the targeted spot. Drug loading is either achieved via coencapsulating drug molecules along with MNPs inside the coating material or conjugating the therapeutic molecules on the surface of SPIONs. Furthermore, several other techniques with improved efficacies have been developed over time. In this direction, polymer nanocomposites demonstrating superparamagnetic properties have been recognized as a promising candidate material to achieve targeted drug delivery under the influence of an applied external magnetic field. Release of a therapeutic drug at a predefined target with a controlled rate is successfully achieved by means of these composite nanocomposites/nanoparticles, which include a carrier, the binding material/encapsulated bioactive payload, and modifiers. Despite all the means and methods used in the drug delivery system using SPION or any other technique, the underlying principle of working always remains the same. SPIONs have an inorganic and organic coating, which acts as a drug loading center, and they are then guided by an external applied magnetic field to release at their target tissue/cell/desired locations. SPIONs inherently show superparamagnetic behavior, which is extremely

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important in drug delivery systems as they can be transported by an applied electrical/magnetic field to their desired place, and they remain intact at the target site even when the magnetic field is removed.

22.1.4.2

MRI

Magnetic resonance imaging (MRI), as the name indicate, is a technique primarily based on the balance between protons present in biological tissue to a magnetic moment on a proton that displays an appreciable change in the presence of an applied magnetic field.95 MRI has been extensively used as a powerful and non-invasive clinical diagnosis tool due to its threedimensional (3D) resolution with high contrast, and appropriate permeation depth.96,97 It is used progressively to achieve better resolution between healthy and diseased tissues without the use of ionized radiation. Before moving on to discuss the application of MRI, we would like to highlight the impact of magnetic moments arising from the presence of Fe21 and Fe31 ions on MRI contrast. As discussed previously, a ferrimagnetic material consists of a large number of Fe21 and Fe31 ions, which align in a similar direction under the influence of an applied magnetic moment; however, between domains, these magnetic alignments are in a random fashion.98,99 However, when the particle size reduces below a critical diameter B20 nm, the domain boundaries no longer exist. At this time, the magnetic dipole becomes free to move, and as a consequence, the particle starts behaving like a paramagnetic (Fe21 and Fe31) atom. It is critically important to understand how MRI generates contrast between tissues. MRI contrast in soft tissue is due to differences in proton density, spin–lattice relaxation time (t1) and spin–spin relaxation time (t2) of protons. t1 signifies the time constant of the exponential recovery process of magnetization having a magnitude (M0) along the z-direction after a radio frequency (RF) pulse.99 An intensified signal is achieved along the z-direction due to fast relaxing protons (short t1), whereas protons taking a longer time usually results in less intensity signals and exhibits a saturation effect. Thus, whenever a clear image of tissue is required, it is always preferable to obtain t1 weighted images. Moving to another time constant parameter (t2) which denotes exponential decay of transverse magnetization (Mxy). This time constant denotes the time required to align in the xy-plane randomly. Having understood the contrast features in MRI, we would be further interested in revealing how SPION influences MRI contrast further. SPION primarily targets the t2 protons of water molecules surrounding the tissues. When these SPIONs present inside the tissues are subjected to an external applied magnetic field, they try to create a heterogeneous field gradient along which these water protons diffuse. Eventually, the protons present in water and protons of tissues create a magnetic dipole spin dephasing effect,100 creating a decline in signal intensity accompanying t2 relaxation. Interestingly this contrast is termed negative contrast enhancement due to high concentrations of SPIONs appearing dark on the MR image.

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22.1.4.3

Chapter 22

Oil Removal

The discharge and wastewater from industries, laboratories, small-scale organizations, domestic usage, and from several water-consuming bodies contain oils in the form of either petroleum products, fats, or lubricants. This oil in the discharge has imposed a severe threat to aquatic life.101 Oil spills in the last few years have surged, as can be witnessed in the reports from various agencies.102–104 Quite often, this oil present inside the water bodies acquires emulsion which makes them even more difficult to separate. Thus, serious action must be taken to retaliate these conditions in the future. So far, techniques like sorbent removal, coagulation, coalescence, membrane filtration, cellulose, fibers, and adsorption have been used worldwide. However, these conventional techniques are well suited to a normal oil spill in small water bodies. However, due to growing complexities in technologies, these have become obsolete methods and their high cost further pushes them back in the line of novel and modern cost-effective oil removal techniques. Recently, a novel technique has been developed to remove oil from discharged water.105 This technique used amine-functionalized magnetite NPs for the removal of oil droplets. The aminefunctionalized MNPs lie in between B21–255 nm. This method effectively removes oil (0.25 wt%) to as low as 99.9%. The effectiveness of this method is attributed to its effective binding of MNPs to the droplet surface. This perfect binding arises due to the functionalization of MNPs that create a negatively charged atmosphere of oil-in-water emulsion and a positive surface of MNPs. The charges of opposite polarity propel oils to aggregate with electrical neutral oil droplets. Similarly, polystyrene-coated Fe3O4 NPs denoted as (Fe3O4@PS) were synthesized for removing oil from water.106 This nanocomposite absorbs oilsBthree times its weight, demonstrating a remarkable adsorption capability. This efficient removal of oil is attributed to its uniquely combined organic– inorganic counterparts from inside the nanocomposite. Due to which the oil attaches perfectly and is easily removed by a magnetic counterpart. Fe3O4 is a potential candidate of the MNP family and has been found to be widely used for diverse applications such as magnetic separation, catalysis reactions, magnetic storage, and so on. A combination with polymers, which have a larger surface area, functionalization capability, better chemical stability, and hydrophobicity, further improves the properties of MNPs.

22.1.4.4

Toxicity Removal

The rapid growth in modern civilization has propelled industries to discharge copious dyes, heavy metals, and other colored toxic effluents directly into water bodies. The existence of these toxic dyes in water, even in trace amounts, is highly harmful to the aquatic life-cycle.107 These dye pigments are not only toxic to health and aquatic life, but they are also resistant to detergent, light, water, and weather. Furthermore, to make matters worse, the dyes are neither biodegradable or if they degrade, it occurs at a very slow rate via conventional biological processes. So adequate care must be taken to produce these dyes with ultra-care and to their discharge. So far, the

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methods adopted to remove these dyes include, adsorption, which is a costeffective and more comfortable process, and other methods including the oxidation process.108 Recently, a novel technique has been developed to remove anionic dyes from aqueous solution using sulfobetaine-modified MNPs.109 Sulfobetaine is an analog of betaine comprising a sulfonium and carboxylate ion. It is often used in aquatic feed as bait and as a medication in tumor inhibiton.110 It has reduced toxicity compared with betaine and the price of industrial-grade sulfobetaine is economical. Due to the high absorption capability, the adsorption isotherms are attained quickly, removing amaranth (AM) and methyl blue (MB) from aqueous solution. The added advantage that makes it quite unique is its ability to be recycled and its facile synthesis by a green chemistry route. Similarly, magnetite (Fe3O4)-based nanomaterials are another class of widely explored adsorbent due to their fairly simple technique, easy availability, environmental friendliness, and, most importantly, due to their reduced prices.111 Very similar to maghemite, these magnetite-based nanomaterials are easily separable from aqueous solution under the influence of a magnetic field. Due to this, they have been widely employed in the removal of heavy metals.112,113 To effectively remove heavy metals for instance, Mn(II), Cu(II), Zn(II), and Pb(II), in a batch mode, MNPs were synthesized via a co-precipitation technique.114 The synthesized magnetite NPs demonstrated a contrasting effect on the adsorption of various metals. Excitingly, the adsorption efficacy for Pb was the best, and the lowest was for Mn. To trace the origin of such disparity in the adsorption behavior of heavy metals, their hydrated ionic radii were examined. It was found that hydrated ionic radii greatly influence the adsorption capability of adsorbent sites. When ionic radii increase on sufficient hydration, the distance between the active adsorbing surfaces would increase leading to weakening of the adsorption capability. Thus, Pb(II) has the lowest hydrate ionic radii, it is the most effective in adsorption due to its competing proton. It is by far now established that adsorption is an economical and easy way to remove dyes and heavy metals.114 Furthermore, the other technique that has a resonance in the global community is the oxidation process using the photocatalyst to generate hydroxyl radicals. Most importantly, it is implacable to remove NPs completely from water after purification resulting in leaching of NPs to discharge in the environment. This leaching process is tedious due to the very small particle size and high reactivity of NPs. However, some techniques must be developed to overcome this issue. In this direction, magnetic separation has proved its potential to quickly treat a large volume of water and purify it and has shown to be cost-effective. In a study on dye removal using MNPs using Fe3O4@SiO2 starch-graft-poly(acrylic acid) hydrogels, it was revealed that high sensitivity could be achieved using this technique.115 The magnetic nanocomposite hydrogels demonstrate a high affinity toward magnetic sensitivity under an applied external magnetic field. This makes the separation quite easy and no secondary polluting agents are further added to the environment. The removal of colored dyes using this technique improves efficiency to 485%.

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Chapter 22

Hyperthermia

Hyperthermia is a promising approach in cancer therapy and is based on the philosophy that heat generated during the hysteresis loss of MNPs under the influence of an applied alternating magnetic field can be used to treat diseased cells.116 It is believed and been found that cancer cells can survive up to 43 1C and are destroyed at temperatures above that, while normal cells remain at temperatures even higher117 than 43 1C. Application of MNPs which interact with a living organism should essentially be non-toxic in nature and biocompatible. Thus with proper selection of MNPs which exhibit a high-power magnetic field under the influence of an applied magnetic field even a small quantity of MNPs would serve the purpose.

22.1.4.6

Data Storage

Apart from biomedical applications, MNPs offer tremendous opportunities in other fields of science and technology as well. One such important field is data storage.118,119 To this, multi-millimeter large self-organized FeCo (Figure 22.6) short-ranged ordered structures were synthesized in solution media.119 The induced sharp ridges (Figure 22.6a) indicate that FeCo are self-organized into long range superstructures. These superstructures assist in radiofrequency applications. It is also interesting to note that when precursors from initial 1 equiv. hexadecylamine and 1 equiv. oleic acid (used as the reaction medium) are changed to 1 equiv. stearic acid, though the long range superlattice structure existed, they were revealed as broken edges of face-centered-cubic packing. This is also an indication of how important the selection of medium in the synthesis of MNPs. Self-assembly or self-organization is perceived as nature’s ‘‘free ride’’ towards achieving economical and well-defined ordered structures rather than using highly expensive ion-beam lithography or any other techniques.13

Figure 22.6

(a) SEM image of FeCo supercrystals. (b) SEM image of broken FeCo supercrystals. Adapted from ref. 119 with permission from Springer Nature, Copyright 2005.

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Although self-assembly is a free ride for atoms to arrange themselves into a particular order, they also require a certain degree to tune those fine-structures with uniform distribution.120 For instance, the self-assembly of FePt NPs down to 4 nm with remarkable uniaxial anisotropy to demonstrate enhanced thermal stability.121 What makes these self-assemblies important to data storage is their ability to be packed with a very high density. This high-density atomic packing enables writing with sufficiently low writing-fields and ensuring data storage capability over 10 years with a highly reduced price.

22.1.5

Future Prospects

MNPs are potential emerging materials that have grabbed substantial attention from researchers/academics/industrialists. Though there have been several improvements in their synthesis technique, their mechanistic study has been explored by various studies, several noteworthy coatings have been used, and numerous bio-labeling, and other functionalized materials have been developed. However, the rapid growth in biomedical applications requires highly developed advanced sensors, tools, and diagnostic instruments, which urgently ask for more developments from the MNPs. Though several benefits like facile surface functionalization of MNPs, biocompatibility, and capability to remove wide-ranging toxic dyes have added commercial importance to these MNPs. Their broader applicability in the fields of analytical techniques still has a long way to go and needs development in several aspects. The incorporation of MNPs in various allied techniques has improved their sensitivity, data acquisition, and selectivity. However, further developments in their better particle size tunability by coating materials will offer better control to integrate with far reaching technologies. Furthermore, it is also essential to develop suitable analytical practices to carry out the synthesis of novel MNPs and their functionalization for better employment in the analysis process. Finally, there are still plenty of challenges in developing on-site monitoring tools and devices where MNPs can significantly incorporate enhanced usability and practical applicability.

22.2 Conclusion To conclude, we have presented a brief yet important synthesis route, prevailing functionalization techniques, size control aspects, features of MNPs, and, most importantly, their applications. Having been discussed so far, it seems that the future is highly encouraging allied with several challenges, and thus novel research ideas are urgently required to improve the functionalities of MNPs. Iron oxide, along with various other MNPs, exhibits a strong candidature for aqueous/non-aqueous phase solubility with excellent potential in biomedical applications. To successfully achieve this, numerous factors play a key role, including the judicious selection of appropriate precursor salts, pH of the working environments, coating agents, molecular weights of polymers, and solvents for the synthesis of MNPs.

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Websites of Interest https://tlo.mit.edu/technologies/magnetic-nanoparticles-microfluidicseparation-pathogens-blood https://www.cd-bioparticles.com/t/Properties-and-Applications-ofMagnetic-Nanoparticles_55.html https://www.nano.gov/you/nanotechnology-benefits

Acknowledgements I greatly acknowledge Mrs. Nivedita Singh, my better half for her constant encouragement and support throughout the journey of completing this chapter. Her benign nature gave me the mental support and strength to finish this chapter amid this COVID-19 pandemic. I also extend my deepest gratitude to elder father, my parents, my family for their support, and last but not least to the Almighty for his blessing to shape this chapter in this present form.

References 1. A.-V. Ruzette and L. Leibler, Nat. Mater., 2005, 4, 19–31. 2. A. N. Singh, R. D. Thakre, J. C. More, P. K. Sharma and Y. K. Agrawal, Polym. Plast. Technol. Eng., 2015, 54, 1077–1095. 3. N. Singh and A. N. Singh, Comput. Electron. Agric., 2020, 171, 105328. 4. N. L. Erb-Satullo, J. Archaeol. Res., 2019, 27, 557–607. 5. F. Engels, The Origin of the Family, Private Property and the State, Penguin UK, 2010. 6. Editorial, Nat. Nanotechnol., 2019, 14, 193. 7. A. Akbarzadeh, M. Samiei and S. Davaran, Nanoscale Res. Lett., 2012, 7, 144. 8. R. Keçili and C. M. Hussain, Int. J. Anal. Chem., 2018, 2018. ¨yu ¨ktiryaki, R. Keçili and C. M. Hussain, TrAC, Trend. Anal. Chem., 9. S. Bu 2020, 115893. ¨ . B. U ¨ nlu ¨er, F. Ghorbani-Bidkorbeh, R. Keçili and C. M. Hussain, in 10. O Handbook on Miniaturization in Analytical Chemistry, ed. C. M. Hussain, Elsevier, 2020, pp. 277–296. 11. Y. Bao, T. Wen, A. C. S. Samia, A. Khandhar and K. M. Krishnan, J. Mater. Sci., 2016, 51, 513–553. 12. A. N. Singh, Appl. Spectrosc. Rev., 2016, 51, 359–378. 13. S. Singamaneni, V. N. Bliznyuk, C. Binek and E. Y. Tsymbal, J. Mat. Chem, 2011, 21, 16819–16845. 14. A. N. Singh and V. Bhat, Bioinspired, Biomimetic Nanobiomater., 2018, 7, 37–43. 15. C. M. Hussain, Nanomaterials in Chromatography: Current Trends in Chromatographic Research Technology and Techniques, Elsevier, 2018. 16. C. M. Hussain, Handbook of Nanomaterials in Analytical Chemistry: Modern Trends in Analysis, Elsevier, 2019.

Functionalization of Magnetic Nanoparticles for Tomorrow’s Applications

569

17. A. M. Abu-Dief and S. M. Abdel-Fatah, Beni-Suef Univ. J. Basic Appl. Sci., 2018, 7, 55–67. 18. S. Sultan, J. N. Tiwari, A. N. Singh, S. Zhumagali, M. Ha, C. W. Myung, P. Thangavel and K. S. Kim, Adv. Energy Mater., 2019, 9, 1900624. 19. J. N. Tiwari, A. N. Singh, S. Sultan and K. S. Kim, Adv. Energy Mater., 2020, 10, 2000280. 20. P. Thangavel, M. Ha, S. Kumaraguru, A. Meena, A. N. Singh, A. M. Harzandi and K. S. Kim, Energy Environ. Sci., 2020, 13(10), 3447– 3458. 21. A. Tarangelo and S. J. Dixon, Nat. Nanotechnol., 2016, 11, 921–922. 22. G. Vallejo-Fernandez, O. Whear, A. Roca, S. Hussain, J. Timmis, V. Patel and K. O’Grady, J. Phys. D: Appl. Phys., 2013, 46, 312001. 23. M. Ebrahimi, Nanomed. J., 2016, 3, 155–158. ¨ttner, W. Bodnar and E. Burkel, in Encyclopedia of 24. K. Witte, C. Gru Nanotechnology, ed. B. Bhushan, Springer, Netherlands, Dordrecht, 2016, pp. 1842–1850. ¨yu ¨ktiryaki and C. M. Hussain, TrAC, Trends Anal. Chem., 25. R. Keçili, S. Bu 2019, 110, 259–276. 26. D. Sharma and C. M. Hussain, Arabian J. Chem., 2020, 13, 3319–3343. 27. Q. Li, W. Lian, H. Sun and Y. Xuan, Int. J. Heat Mass Transfer, 2008, 51, 5033–5039. 28. V. Chaudhary and R. Ramanujan, Sci. Rep., 2016, 6, 1–9. ¨yu ¨ktiryaki, Y. Su ¨mbelli, R. Keçili and C. M. Hussain, Encycl. Anal. 29. S. Bu Sci., 2019, 267–273. 30. J. Sengupta and C. M. Hussain, TrAC, Trends Anal. Chem., 2019, 114, 326–337. 31. R. Ueki, T. Okada, M. Masuzawa, K. Tsuchiya, T. Kawamoto, K. Umemori, E. Kako, T. Konomi and H. Sakai, IEEE Trans. Appl. Supercond., 2020, 30, 1–4. 32. H. Yang, X. Li, H. Zhou, Y. Zhuang, H. Hu, H. Wu and S. Yang, J. Alloys Compd., 2011, 509, 1217–1221. 33. M. M. Yallapu, S. F. Othman, E. T. Curtis, B. K. Gupta, M. Jaggi and S. C. Chauhan, Biomaterials, 2011, 32, 1890–1905. 34. N. A. Frey, S. Peng, K. Cheng and S. Sun, Chem. Soc. Rev., 2009, 38, 2532–2542. ´ny, P. Pirro 35. A. Hirohata, K. Yamada, Y. Nakatani, I.-L. Prejbeanu, B. Die and B. Hillebrands, J. Magn. Magn. Mater., 2020, 509, 166711. 36. C. M. Hussain and B. Kharisov, Advanced Environmental Analysis: Applications of Nanomaterials: Volume 1, Royal Society of Chemistry, 2016. 37. C. M. Hussain and R. Kecili, Modern Environmental Analysis Techniques for Pollutants, Elsevier, 2019. 38. A. N. Singh, A. Moitra, P. Bhaskar, G. Sasikala, A. Dasgupta and A. K. Bhaduri, Metall. Mater. Trans. A, 2017, 48, 3269–3278. 39. J. Han, S.-H. Kang, S.-J. Lee, M. Kawasaki, H.-J. Lee, D. Ponge, D. Raabe and Y.-K. Lee, Nat. Commun., 2017, 8, 751.

570

Chapter 22

40. A. N. Singh, A. Moitra, P. Bhaskar, A. Dasgupta, G. Sasikala and A. K. Bhaduri, J. Mater. Eng. Perform., 2018, 27, 3812–3823. 41. A. Domashenkov, A. Plotnikova, I. Movchan, P. Bertrand, N. Peillon, B. Desplanques, S. Saunier and C. Desrayaud, Addit. Manuf., 2017, 15, 66–77. 42. A. N. Singh, A. Moitra, P. Bhaskar, G. Sasikala, A. Dasgupta and A. K. Bhaduri, Mater. Sci. Eng., A, 2018, 710, 47–56. 43. C. Baresel, V. Schaller, C. Jonasson, C. Johansson, R. Bordes, V. Chauhan, A. Sugunan, J. Sommertune and S. Welling, Heliyon, 2019, 5, e02325. 44. J. Kirschvink, Magnetite biomineralization in the human brain, Proc. Natl. Acad. Sci. U. S. A., 1992, 89, 7683–7687. 45. Y.-J. Ke, X.-Q. Zhang, Y. Ma and Z.-H. Cheng, Sci. Rep., 2016, 6, 19775. ¨th, Angew. Chem., Int. Ed., 2007, 46, 46. A.-H. Lu, E. L. Salabas and F. Schu 1222–1244. 47. W. Jiang, F. T. Birk and D. Davidovic´, Sci. Rep., 2013, 3, 1200. 48. X. Batlle and A. l. Labarta, J. Phys. D: Appl. Phys., 2002, 35, R15–R42. 49. C. Sorensen, in Nanoscale Materials in Chemistry, ed. K. J. Klabunde, Wiley, New York, NJ, 2001, 169–221. 50. A. Akbarzadeh, M. Samiei and S. Davaran, Nanoscale Res. Lett., 2012, 7, 144. 51. Q. Li, C. W. Kartikowati, S. Horie, T. Ogi, T. Iwaki and K. Okuyama, Sci. Rep., 2017, 7, 9894. 52. S. Chikazumi, Physics of Ferromagnetism, Oxford University Press, New York, 1997, pp. 503–508. 53. V. Skumryev, S. Stoyanov, Y. Zhang, G. Hadjipanayis, D. Givord and ´s, Nature, 2003, 423, 850–853. J. Nogue ´zquez, Y. Pen ˜ a and 54. B. I. Kharisov, H. V. R. Dias, O. V. Kharissova, A. Va ´mez, RSC Adv., 2014, 4, 45354–45381. I. Go 55. C.-W. Lu, J.-K. Hsiao, H.-M. Liu and C.-H. Wu, Sci. Rep., 2017, 7, 3587. 56. S. Gul, S. B. Khan, I. U. Rehman, M. A. Khan and M. Khan, Front. Mater, 2019, 6, 179. ´lis, M. Pilar Calatayud, G. F. Goya and 57. I. Bruvera, P. Mendoza Ze ´nchez, J. Appl. Phys., 2015, 118, 184304. F. H. Sa 58. L. Maurizi, A. Claveau and H. Hofmann, J. Nanomater., 2015, 2015, 732719. 59. J. Lee, T. Isobe and M. Senna, Colloids Surf., A, 1996, 109, 121–127. 60. J. Wang, J. Sun, Q. Sun and Q. Chen, Mater. Res. Bull., 2003, 38, 1113–1118. 61. T. Togashi, T. Naka, S. Asahina, K. Sato, S. Takami and T. Adschiri, Dalton Trans., 2011, 40, 1073–1078. 62. D. Langevin, Annu. Rev. Phys. Chem., 1992, 43, 341–369. 63. G. Asab, E. A. Zereffa and T. Abdo Seghne, Int. J. Biomater., 2020, 2020, 4783612.

Functionalization of Magnetic Nanoparticles for Tomorrow’s Applications

571

64. E. E. Carpenter, C. T. Seip and C. J. O’Connor, J. Appl. Phys., 1999, 85, 5184–5186. ´rrez, R. Costo, C. Gru ¨ttner, F. Westphal, N. Gehrke, D. Heinke, 65. L. Gutie A. Fornara, Q. A. Pankhurst, C. Johansson and S. VeintemillasVerdaguer, Dalton Trans., 2015, 44, 2943–2952. 66. S. F. Hasany, N. H. Abdurahman, A. R. Sunarti and R. Jose, Curr. Nanosci., 2013, 9, 561–575. 67. C. Liu, B. Zou, A. J. Rondinone and Z. J. Zhang, J. Phys. Chem. B, 2000, 104, 1141–1145. 68. N. Moumen and M. Pileni, J. Phys. Chem., 1996, 100, 1867–1873. 69. H. Zhao, R. Liu, Q. Zhang and Q. Wang, Mater. Res. Bull., 2016, 75, 172–177. 70. G. Priyadarshana, N. Kottegoda, A. Senaratne, A. de Alwis and V. Karunaratne, J. Nanomater., 2015, 2015, 317312. 71. A. N. Singh, S. Kajal, J. Kim, A. Jana, J. Y. Kim and K. S. Kim, Adv. Energy Mater., 2020, 10, 2000768. 72. C. M. Hussain, Advanced Environmental Analysis: Applications of Nanomaterials, RSC, 2016, p. 13. 73. A. Gopanna, K. P. Rajan, S. P. Thomas and M. Chavali, Materials for Biomedical Engineering, Elsevier, 2019, pp. 175–216. 74. A. Y. W. Sham and S. M. Notley, Soft Matter, 2013, 9, 6645–6653. 75. M. Rutnakornpituk, S. Meerod, B. Boontha and U. Wichai, Polymer, 2009, 50, 3508–3515. 76. S. P. Rwei, L. Y. Wang and M. J. Chen, J. Nanomater., 2013, 2013, 745746. 77. ˆ a. L. Andrade, J. D. Fabris, J. D. Ardisson, M. A. Valente and J. M. F. Ferreira, J. Nanomater., 2012, 2012, 454759. 78. D. Zins, V. Cabuil and R. Massart, J. Mol. Liq., 1999, 83, 217–232. 79. E. Kadar, ´I. L. Batalha, A. Fisher and A. C. A. Roque, Sci. Total Environ, 2014, 487, 771–777. 80. A. Ditsch, P. E. Laibinis, D. I. C. Wang and T. A. Hatton, Langmuir, 2005, 21, 6006–6018. ´nomme´e, G. Enright, T. Veres and 81. D. Ma, J. Guan, F. Normandin, S. De B. Simard, Chem. Mater., 2006, 18, 1920–1927. 82. Y. Lu, Y. Yin, B. T. Mayers and Y. Xia, Nano Lett., 2002, 2, 183–186. 83. Y. Han, Z. Lu, Z. Teng, J. Liang, Z. Guo, D. Wang, M.-Y. Han and W. Yang, Langmuir, 2017, 33, 5879–5890. ˇ. Knez, J. Magn. Magn. Mater., 84. F. ˇ Sulek, M. Drofenik, M. Habulin and Z 2010, 322, 179–185. 85. A. Taufiq, A. Nikmah, A. Hidayat, S. Sunaryono, N. Mufti, N. Hidayat and H. Susanto, Heliyon, 2020, 6, e03784. 86. G. Wang and X. Su, Analyst, 2011, 136, 1783–1798. 87. M. Fronczak, O. Łabe˛dz´, W. Kaszuwara and M. Bystrzejewski, J. Mater. Sci., 2018, 53, 3805–3816. 88. J. N. Tiwari, A. M. Harzandi, M. Ha, S. Sultan, C. W. Myung, H. J. Park, D. Y. Kim, P. Thangavel, A. N. Singh and P. Sharma, Adv. Energy Mater., 2019, 9, 1900931.

572

Chapter 22

89. D. K. Yi, S. T. Selvan, S. S. Lee, G. C. Papaefthymiou, D. Kundaliya and J. Y. Ying, J. Am. Chem. Soc., 2005, 127, 4990–4991. 90. H. W. Kroto, J. R. Heath, S. C. O’Brien, R. F. Curl and R. E. Smalley, Nature, 1985, 318, 162–163. 91. G. Song, M. Kenney, Y.-S. Chen, X. Zheng, Y. Deng, Z. Chen, S. X. Wang, S. S. Gambhir, H. Dai and J. Rao, Nat. Biomed. Eng., 2020, 4, 325–334. 92. S. I. Nikitenko, Y. Koltypin, O. Palchik, I. Felner, X. N. Xu and A. Gedanken, Angew. Chem., 2001, 113, 4579–4581. ´n, J. Arias, V. Gallardo and A. Delgado, J. Pharm. Sci., 2008, 97, 93. J. Dura 2948–2983. 94. Wahajuddin and S. Arora, Int J. Nanomed., 2012, 7, 3445–3471. 95. A. D. Elster and J. H. Burdette, Questions and Answers in Magnetic Resonance Imaging, Mosby, 2001. 96. J. R. Hesselink, R. R. Edelman and M. Zlatkin, Clinical Magnetic Resonance Imaging, Saunders, 1990. 97. S. Shabestari Khiabani, M. Farshbaf, A. Akbarzadeh and S. Davaran, Artif. Cells, Nanomed., Biotechnol., 2017, 45, 6–17. 98. S. Bedanta and W. Kleemann, J. Phys. D: Appl. Phys., 2008, 42, 013001. 99. Z. R. Stephen, F. M. Kievit and M. Zhang, Mater. Today, 2011, 14, 330–338. 100. M. W. Marashdeh, B. Ababneh, O. M. Lemine, A. Alsadig, K. Omri, L. El Mir, A. Sulieman and E. Mattar, Results Phys., 2019, 15, 102651. 101. H. Fragoso ados Santos, G. A. S. Duarte, C. T. d. C. Rachid, R. M. Chaloub, E. N. Calderon, L. F. d. B. Marangoni, A. Bianchini, A. H. Nudi, F. L. do Carmo, J. D. van Elsas, A. S. Rosado, C. B. e. Castro and R. S. Peixoto, Sci. Rep., 2015, 5, 18268. 102. I. Berenshtein, C. B. Paris, N. Perlin, M. M. Alloy, S. B. Joye and S. Murawski, Sci. Adv., 2020, 6, eaaw8863. 103. T. Bakke, J. Klungsøyr and S. Sanni, Mar. Environ. Res., 2013, 92, 154–169. 104. D. Yuewen and L. Adzigbli, J. Oceanogr. Mar. Res., 2018, 6, 1000179. 105. S. Ko, E. S. Kim, S. Park, H. Daigle, T. E. Milner, C. Huh, M. V. Bennetzen and G. A. Geremia, J. Nanopart. Res., 2017, 19, 132. 106. M. Chen, W. Jiang, F. Wang, P. Shen, P. Ma, J. Gu, J. Mao and F. Li, Appl. Surf. Sci., 2013, 286, 249–256. 107. S. Gita, A. Hussan and T. Choudhury, Environ. Ecol., 2017, 35, 2349– 2353. 108. K. Barquist and S. C. Larsen, Microporous Mesoporous Mater., 2010, 130, 197–202. 109. J. Qiao, S. Gao, J. Yao, L. Zhang and N. Li, AIP Adv., 2019, 9, 065308. 110. K. Nakajima, Y. Nakajima and S. Tsujiwaki, Anticancer Res., 2015, 35, 1475–1480. 111. Y.-M. Hao, C. Man and Z.-B. Hu, J. Hazard. Mater., 2010, 184, 392–399. 112. M. P. Watts, V. S. Coker, S. A. Parry, R. A. Pattrick, R. A. Thomas, R. Kalin and J. R. Lloyd, Appl. Geochem., 2015, 54, 27–42.

Functionalization of Magnetic Nanoparticles for Tomorrow’s Applications

573

113. M. E. Mahmoud, M. S. Abdelwahab and A. E. Abdou, Sep. Sci. Technol., 2016, 51, 237–247. ´n, Adsorption, 2013, 19, 114. L. Giraldo, A. Erto and J. C. Moreno-Piraja 465–474. 115. A. Pourjavadi, S. H. Hosseini, F. Seidi and R. Soleyman, Polym. Int., 2013, 62, 1038–1044. 116. Z. Ma and H. Liu, China Particuol., 2007, 5, 1–10. 117. A. K. Gupta and M. Gupta, Biomaterials, 2005, 26, 3995–4021. ¨tten, Nat. Mater., 2005, 4, 725–726. 118. G. Reiss and A. Hu 119. C. Desvaux, C. Amiens, P. Fejes, P. Renaud, M. Respaud, P. Lecante, E. Snoeck and B. Chaudret, Nat. Mater., 2005, 4, 750–753. 120. C. Carbone, S. Gardonio, P. Moras, S. Lounis, M. Heide, G. Bihlmayer, ¨gel and S. Vlaic, Adv. Funct. Mater., N. Atodiresei, P. H. Dederichs, S. Blu 2011, 21, 1212–1228. 121. S. Sun, C. B. Murray, D. Weller, L. Folks and A. Moser, Science, 2000, 287, 1989–1992.

CHAPTER 23

Future of Functionalized Magnetic Nanoparticles in Analytical Chemistry RAMSHA KHAN,a SAURABH SHUKLA,*a ACHLESH DAVEREYb AND CHAUDHERY MUSTANSAR HUSSAIN*c a

Faculty of Civil Engineering, Institute of Technology, Shri Ramswaroop Memorial University, Barabanki-225003, UP, India; b School of Environment and Natural Resources, Doon University, Uttarakhand 248001, India; c Department of Chemistry and Environmental Science, New Jersey Institute of Technology, University Heights, Newark, NJ 07102, USA *Emails: [email protected]; [email protected]

23.1 Introduction The extensive growth in population and the resultant over-exploitation of resources have affected our environment in a very detrimental manner. The extent of anthropogenic intrusion is evident from the pace of depletion in environmental quality.1,2 The various types of pollutants including heavy metals, organic compounds, industrial effluents, agricultural waste (fertilizers, herbicides, and pesticides), etc. are contributors to the increasing levels of contamination in our environment.3 The over-utilization of inorganic fertilizers which contain nitrogen as one of the major constituents for enhanced crop yield is a matter of concern. Excessive application, with non-coherent time for application of fertilizers, can possibly contaminate the subsurface water sources through leaching.4 The potential risk of

Analytical Applications of Functionalized Magnetic Nanoparticles Edited by Chaudhery Mustansar Hussain r The Royal Society of Chemistry 2021 Published by the Royal Society of Chemistry, www.rsc.org

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biomagnification of heavy metals in the food chain creates serious viable health issues in humans.5 Thus, the requisite of novel methods for remediation of soil sediments, air and water has been fulfilled through consistent efforts by researchers from multidisciplinary fields, however, still has scope for improvement. The variability in the composition, with low reactivity and high volatility of various pollutants makes the processes of remediation a crucial activity. A variant set of tools and technologies has been studied and designed for the remediation and reinstatement of our environment, and ‘Nanotechnology’ has proved to be a technique with a sustainable approach.6 Nanotechnology has emerged as an integration of innovative development and applied management of materials at the nanoscale.7 It has been used in several multidisciplinary fields such as industrial waste management, water, and soil pollution management, biomedical, and biochemistry. The efficacy of nanomaterials can be due to their distinctive surface properties aiming at the required contaminant molecule.8 The higher surface-to-volume ratio enhances the reactivity of nanoparticles (NPs) in comparison to other voluminous options.9,10 The various fields of science and technology have experienced transformations through the inputs from nanotechnology.11 The simplification of analytical processes, through conjunctive application of analytical chemistry and nanotechnology has proved very efficient.12,13 Nanotechnology in integration with analytical chemistry has presented novel inputs and outputs for researchers.14,15 The growth in the field of nanoprobes has consequently developed a pathway for research and investigation on the concepts of functionalization of NPs in various imaging methods.16 Functionalization includes the surface modification of NPs, through coalesce of chemicals17 or bio-particles to the surface (e.g., biotin molecules, folic acid, antibodies, etc.) for enhancement of performance and efficacy.17–20 Functionalized NPs possess non-corrosive, anti-agglomeration, and other effective physical properties, thereby leading to elaborate research studies to explore their applications.21–23 The development of magnetism in analytical chemistry has gained impetus owing to its practical applications and scope.24 The expansion of NPs, magnetic composites, and hybrid magnetic (nano)particles (MNPs), has tremendously molded the efficacy of nanotechnology in analytical chemistry.25 MNPs are a type of NPs which can be modified with the help of magnetic fields.26 These particles contain two parts including a magnetic component, usually iron, cobalt, and nickel, in coherence with a chemical constituent which provides functionality. The increased employment of MNPs as effective aiding tools for catalysts has gained investigation22 impetus. The magnetic particles of various sizes are at the nano and macro scale with variant compositions resulting in variant magnetization including diamagnetic, paramagnetic, antiferromagnetic, ferromagnetic and superparamagnetic.27 The MNPs have found broader application as a product of synthetization in the reinstatement of the environment, magnetic resonance imaging (MRI), and catalysis.28,29 The advantage of magnetic forces includes

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their unaffected nature of working regardless of the influencing variables (composition, pH, surface charges) and their control over the fluid motion in chromatographic separations is notable. These have been widely accepted in the various fields of medical sciences,30,31 and in the various spheres of biotechnology.32 The usage of MNPs in radiopharmaceuticals,33 delivery of drugs,34 genetics,35 theranostics,36 and modification of proteins and cells has gained momentum.37 The superparamagnetic MNPs are attracted to a magnetic field but do not keep any residual magnetism after removal of the field. Thus, the separation of superparamagnetic particles in adherence with analytes is eased without requiring any external magnetic field. The superparamagnetic iron oxide nanoparticles (SPIONs) have gained use as contrast agents for magnetic resonance imaging (MRI) owing to their less toxic nature and biocompatibility for medical field applications. Various studies have studied and elaborated the increased use of NPs in various fields, and some relevant studies have been illustrated in Figure 23.1. The instability owing to particles in this range of size is an issue which leads to agglomeration. Additionally, the exposed metallic nanoparticles are chemically very active causing oxidization and consequent loss of magnetism and dispersibility. Some methods to stabilize the exposed MNPs include inorganic layer covering, surfactant coatings, polymer coatings, etc.38 The functionalization of NPs provides a platform to modify the properties of NPs in accordance with requisites.39 If we specifically consider the betterment of image quality (molecular imaging techniques), functionality plays a very vital role. The functionalization of NPs can also be performed with other NPs to nurturing their properties. Previously, the layering of magnetite NPs with silica NPs followed by further functionalization through dyes at the magnetite layer has been done for broader implementation of NPs. Thus, the silica NP which is usually not used as contrast agents without functionalization can be employed in optical imaging and MRIs after functionalization. Thus, the viable interdependence of NP functionalization and imaging methodologies is evident.40 The emphasized research interest in NPs and their characteristics (composition, magnetic properties, toxicity) has also played a role in its enhanced applications in industries and biomedical field.41 The various types of MNPs have been illustrated in Figure 23.2. The notable feature of functionalized MNPs includes the integrated benefits of MNPs and altered layers in sample preparation, chemo sensing techniques and methods of ‘enantioseparation’. The enhanced sensitivity and improved rate of extraction are a result of higher surface area and volume ratio in smaller MNPs. The speed and efficacy of the separation process through employment of MNPs are simplified through their magnetism. Thus, based on the various fields of applications a variety of functionalized MNPs are required. Some advantages of functionalized MNPs have been stated in Figure 23.3. Moreover, some variants of functionalized MNPs with their field of applications have been explained in Table 23.1.

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Figure 23.1

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Some relevant studies towards the development of NPs.

The numerous existing applications of functionalized MNPs have paved the way for future roles at the variant stages of analytical processes including:    

Treatment of samples Pre-concentration, separation processes, capture of analytes Sensors and detection Imaging

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Figure 23.2

A broad classification of MNPs.12

Figure 23.3

Advantages of functionalized MNPs.11

Thus, the roles of functionalized MNPs through conjunction with other NPs in other fields including microfluids, micro-flow analysis etc. are very optimistic.43

Future of Functionalized Magnetic Nanoparticles in Analytical Chemistry Table 23.1

Some functionalized MNPs with relevant areas of application.

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S. no. Functionalized MNPs

Suitable applications

1.

Selective extraction of organic analytes from complex matrices Ionic compounds Hydrophobic organic compounds including phthalates, pesticides, and PAHs. Enantioseparation techniques

2. 3. 4. 5.

Surfactant or polymers-coated MNPs LDH-modified MNPs C18-modified MNPs

Functionalized MNPs with suitable chiral selector (b-CD) Carbon-based functionalized Hydrophilic compounds including MNPs sulfonates or esters

23.2 Future Scope of Functionalized Magnetic Nanoparticles in Analytical Applications The viable possibilities of implementation in current and novel areas for functionalized MNPs have been illustrated in Figure 23.4.

23.2.1

Application of Functionalized MNPs in Sample Preparation

The development of modern techniques towards synthetization and functionalization of novel MNPs needs attention and further research. The elaborate analysis towards drafting new MNPs with enhanced lifespan, selectivity, improved physical and chemical properties is very vital. The future novel and modified fields of application will include the various stages of analytical processes including sample preparation, separation, extraction, and detection.42 Various studies have been conducted for improving the analytical methodologies to obtain information about analytes in the Solid Phase Extraction (SPE) method. The utilization of MNPs in SPE has decreased the time duration of the extraction process through reduction of the number of steps. The Magnetic Solid Phase Extraction (MSPE) for sample preparation has found great acceptance. The magnetic materials are diffused in the sample solutions for a rapid extraction process owing to their recovery through a magnet, thereby overcoming the shortcomings with the conventional SPE process. Thus, the future scope of Magnetic Solid Phase Extraction (MSPE) in the extraction process is very bright considering their efficacy and sustainable approach. The MNPs effectively cause isolation of the various types of analyte from simplified inorganic compounds to nexus biomolecules. The enhanced properties of MNPs therefore have a great scope in future applications after management of some issues associated with them. The foremost issue includes the isolation of small quantities of analytes from complex models specifically in biological samples. Thus, some remedial measures which can be implemented include betterment of existing methods through synthetization of MNPs. This will help in managing the shape of MNPs and obtain polymers with molecules carrying the same degree of polymerization or similar

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Figure 23.4

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Future scope of functionalized MNPs in various areas.

molecular mass. Greater emphasis needs to be given on the development of novel coatings for efficient shielding of the magnetic core, thereby leading to wide functional MNPs and improved dispersity in solutions. The accurate designing of methods to promote manageable interactions between the surface with enhancement of the physical and chemical properties of MNPs to terminate and minimize the background signal as a result of indifferent binding. The necessity of the development of specific analytical methods for the synthetization and functionalization of MNPs with coherence work on the improvement of the extraction process needs to be dealt with in the future. Thus, the development of online-MSPE systems for employment of NPs in constant laboratory analysis of various samples is an area with working scope in the future.44 The conjunction of functionalized magnetic nanoparticles with analytical tools has broadened their applications in qualitative and quantitative assessment. The motion of these MNPs can be controlled along with their properties, through the application of a magnetic field. This helps in transforming and evaluating the particles at their molecular levels. MNPs have integrated their superparamagnetic performance with a smaller or relative dimension scale as that of biomolecular structures increasing their use in modifying analytes, imaging methods and chemical sensors. Considering the ‘heterofunctionalized nanoparticles’ that can, hence, provide various analytical probes inside the same nanoscale vehicle. There has been a significant

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growth in this field in the past few years, but further scope of improvement cannot be ignored.41

23.2.2

Scope of Functionalized MNPs in Biological Synthesis

The advancements of Green Chemistry in conjunction with nanotechnology has gained impetus across the multidisciplinary fields of research.45 The application of modified chemicals for reducing or eliminating hazardous materials added to the environment form an integral part of Green Chemistry.46 The synthesis of metallic nanomaterials based on various plant components has emerged as a vital area of interest for researchers. The associated benefits of green methods include sustainability, and nonhazardous to the environment, therefore gaining huge importance in the field of biomedicals. The employment of microbes, fungi, enzymes, and plant composites as environment friendly alternatives for synthetization of NPs is widespread.47 The sources for biological synthesis of NPs are plants consisting of reducing agents including ascorbic acid, citric acid, and unrefined enzymes (reductases and dehydrogenases etc.).48 But some issues associated with plant-based synthesis include:  Low rate of synthesis owing to smaller quantities of secreted proteins from plants  Resultant time taking culture of microbes  Complexities in the management of shape and size of NPs  Providing monodispersing of NPs Thus, the technique of biological synthesis of NPs has emerged in addition to green methods but the need of advancements cannot be overlooked. The issues of low quantities of plant excretions, and unsuitability of all plants for biological synthesis provide an area for necessary attention.49

23.2.3

Use of Functionalized MNPs in the Medical Field

The future of functionalized MNPs is very optimistic with great opportunities for researchers to explore and present improvements. The application in drug delivery systems owing to their specific properties capable of managing target variant cell types is notable. The challenges and requisite of novel research ideas for managing the current limitations in the therapy of various diseases need to be dealt with. The iron oxide MNPs hold capabilities for aqueous and/or nonaqueous phase solubility with expansive scope in the field of biomedical applications. Many parameters need to be considered for the synthesis of MNPs. The employment of water-soluble surface functionalization agents through precipitation, thermal decomposition, and other high-temperature methods etc. for enhancing the aqueous phase solubility is effective. The technique of non-invasive imaging (MRI) suitably used for studying the subject’s anatomical part is aided by the biocompatible NPs for

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elaborate images to obtain a correct and detailed diagnosis. The employment of MNPs as contrasting agents is a huge challenge which needs to be encountered in the future. Some other improvements may include labeling the MNPs with a fluorescent protein, for example green fluorescent protein or red fluorescent protein. This labeling will brighten the target area under study through a distinct color. However, this area of research lacks the elaborate analysis of biocompatibilities along with any detrimental negating side effects related to the injection of MNPs.

23.2.3.1

Role of Functionalized MNPs in Drug Delivery

The initiation of the application of ‘magnetic drug delivery’ dates back to the 1970s and since then has emerged as a very efficient technique.50 The initiation of the process includes attachment of drug molecules to MNPs which succeeded by diverting these particles to the required field working under the effect of a localized magnetic field till the achievement of the process and final withdrawal.51 The loss of magnetic moment occurs from paramagnetic particles and transformation of superparamagnetic particles to non-magnetic particles as a result of the displacement of the external field, although they gain momentum on availability of an external field. The advantage associated with MNPs in the field of drug delivery includes the carriage of huge doses of drugs for attaining greater local concentration, and minimization of the hazardous effects due to accumulation of huge doses of drugs in various parts of the entity.52 Elaborate in-depth studies have clearly stated the complexities associated with the clinical trials including:     

Physiological factors Control of size Biocompatibility Stability Coating-layer for drug binding

The primary goal in the development or betterment of drug delivery systems is to provide controlled medications to targeted body parts and managing through chemical or physiological initiators.53 The micelles and polymeric microspheres emerged to be efficient in preventing the biochemical degradation of medicines, specifying the drug target, enhancing the rate of absorption, and reducing the associated drug toxicity.54,55 The dendrimers and biodegradable polymer-based investigative targeted drug delivery systems also provided optimal results. The suitability of dendrimers is due to composition and size and their ability to act as good carriers in coherence with their biodegradation nature. The issue associated with dendrimers is their unsatisfactory role as coating materials for MNPs.56 The adaptable materials for a drug delivery system can be NPs micelles, emulsions, and dendrimers etc. The drug delivery system includes providing drugs via non-toxic vehicle materials into the bodies for treatment of cancer. But, the adaption and non-toxic behavior of

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NPs, along with their suitable size and targeted actions make them successful vehicle materials. The fundamental magnetic properties of nanosized materials increase their potential to be used for drug delivery. These properties include superparamagentism at room temperature, high magnetic susceptibility, and the property of magnetization.41 The concept of surface functionalization through biological and chemical methods provides increased stability and coexistence of MNPs without any harm to the subject. The vital reference of MNPs in drug delivery systems is the targeted delivery of drugs under controllable conditions with external magnetic fields. The effects of various parameters including temperature, pH, strength of the externally applied magnetic field, etc. also need to be considered for optimal delivery of a drug.57 The designing of a magnetic targeted drug delivery system must consider the following factors, as illustrated in Figure 23.5. Thus, the goal of the magnetically targeted drug delivery systems is to provide drugs at the required target while maintaining the optimal rate during treatment. The scope of betterment through enhancement of targeted delivery within the stipulated time and at the most suitable rate regardless of external factors including temperature, pH, etc. cannot be ignored. Hence, future studies should consider enhancement methodologies. The application of graphene quantum dot (GQD) dependent platforms for drug delivery has also gained momentum. Although the issues in the utilization of GQDs include development of enhanced quality products for implementation in nanomedical applications. The current methods of synthesis contribute to the development of GQDs at a small scale with wider size distribution. The future targets for enhanced implementation of GQDs include easier purification techniques and innovative techniques for higher yields along with termination of materials at initiation. The effect of size and shape on the physical and chemical properties of GQDs is considerable. The conventional methods of laboratory detection should be replaced by novel techniques of GQD-based fluorescence detection tools, thus requiring indepth study and expanded research. The necessity of research towards GQDbased immunosensing instead of non-immunosensing is a very vital area of research for the future. The lack of research based on immunosensors relative to GQDs increases the requisite of novel studies for cancer biomarkers, and cell line detection. The development of novel synthetic technologies can be relevant in addition to ultrasensitive immunosensor diagnostics vital for cancer therapies. The advancements in the photoluminescence (PL) properties of GQDs are still slow, with the proposal of viable mechanisms including the effect of size, surface modification, and mixing with various elements. The employment of GQDs because of their lower quantum yields is restricted in immunosensing. The advancements in usage of GQDs for immunosensing applications are still in its early stages, requiring focus on research-oriented actions for future developments and applications. Moreover, novel techniques based on surface modifications are also required for applications in immunosensing. Thus, the novelty of GQDs creates a wide platform for their use in

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Figure 23.5

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Some factors affecting the targeted drug delivery using MNPs.58

multidisciplinary application platforms including conjunction with the various fields of physics, chemistry, and biomedical and significantly immunosensing. Thus, we can summarize that GQD-based nanomaterials provide a very optimistic broad applicative future in collaboration with relevant efforts towards researches.

23.2.3.2

Role of Functionalized MNPs in Imaging Techniques

One of the most vital modern applications of NPs in the optimization of human health-related remedial technologies is in imaging. It is the process of employing iron oxide MNP referenced preparations as a contrasting agent in MRI.59 The growth in diagnostic imaging techniques is remarkable and paves the way for future applications in more advanced and enhanced systems. The detection of damaged tissues, cysts, tumors, and neurological disorders has witnessed tremendous improvement through employment of MNPs. The diagnostic technique of imaging includes MRI which has proved its worth in the field of biomedical applications and is highly opted for, in comparison to other methods. The issue of wrong diagnosis in various medical conditions

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while using an X-ray technique has also promoted the use of MRI considering its enhanced contrast properties, through utilization of a medium referred to as a contrast agent. In general, the contrast agents constitute of a metal-based core, and this core has an external coating of some biocompatible material. This contrast agent functions to intensify the contrast of the images obtained through MRI, which enhances the optimal diagnosis.

23.2.3.3

A Step Forward in ‘Theranostics’

The term ‘theranostics’ was initiated in the year 2006 and is explained as ‘‘Future nanotechnology developments will most likely include the capability of designing and fabricating multifunctional nanoparticles to combine imaging and therapeutic capabilities’’.60 The field of theranostics has emerged as an advanced conjunction of diagnosis and therapy creating new ways in the field of bio-medics. The exemplary initiative of theranostics is based on the uniqueness of NPs and their remarkable abilities of imaging and treatment of contusions parallelly. The iron oxide MNPs have gained impetus considering the intrinsic magnetic properties and their application as optimal cytotoxic agents against tumors. Moreover, their suitability as efficient magnetic resonance imaging contrasting agents is noteworthy. The application of imaging and treatment parallelly along with various sensory systems for treatment is an additive benefit of NPs. The radio sensitization of NPs in various formulations has enriched the influence of cytotoxicity at in vitro set-ups for radio- and chemo-therapies. Hence, radio sensitization aids in laser ablation of tumors, lesions etc. in an efficient manner.61 The results extend the aspects of auxiliary management of diagnostics and various forms of therapy in conjunction. Photoablation therapy has successfully been applied for cancer treatment. The classification of photoablation therapy is broadly split into two types including photodynamic therapy (PDT) and photothermal therapy (PTT).62 PTT employs photo-induced heat for termination of cancerous cells and has proven to be an effective cancer treatment therapy.63 The specific characteristics of PDT include its target specific working, non-invasiveness, less side effects and low energy light requisite. The shortcomings of PDT treatment include a less soluble drug with exposure to visible light radiations of certain wavelengths. The shortcomings overtake the benefits of PDT, thereby its prospects include improvement of drug delivery systems. While PTT is a highly recommended technique considering the associated advantages i.e., less encroaching nature, no risk to non-targeted sites, and speedy recovery. The generation of heat through placement in a fluctuating magnetic field owing to the magnetic hysteresis loss by MNPs, made scientists apply these to hyperthermia treatment which has emerged as an additional treatment to chemotherapy, radiation, and associated surgeries in cancer therapy.64 The generation of heat via currents, through fluctuating magnetic field application to MNPs is the concept of magnetic induction hyperthermia. Owing to this concept, the magnetic fluids on exposure to alternating magnetic field,

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transformed the fluids into effective sources of heat. Considering the sensitivity of tumor cells to temperatures441 1C in comparison to their various other counterparts.33 Although the disadvantages of PTT cannot be ignored including the requisite of high-power lasers and the thermal extinction of cancer selective cell lines. Photoacoustic imaging has emerged as another successful technique integrating the acoustic and optical imaging of burns and analyzing the blood vessels, malignant melanoma areas, etc. The benefit of photoacoustic imaging includes elaborate assessment of various tissues including brain cancerous cells, and breast cancer cells with coherent monitoring.65 The use of gold NPs has evolved as effective non-invasive contrasting agents to promote timely detection of tumors through photoacoustic imaging. Computed tomography CT or CAT is a scan that assists in internal assessment of body parts for medical purposes through an integrated use of X-ray and computer systems for creating images of organs, bones, and other tissues. The cost effectiveness, efficacy, high spatial resolution, and internal tissue penetration are some benefits associated with this technique. Gold NPs are employed as contrasting agents owing to less toxicity, high X-ray absorption, and steady clearance inside the body. The replacement of traditional iodine-based contrasting agents by gold NPs showed speedy excretion and lesser nephritic toxicity. The superior stability, biocompatibility of gold NPs in CT or CAT in tumor imaging is noteworthy. The technique of ultrasound imaging is employed due to its portability, economic nature, and non-invasiveness. The use of contrasting agents gives resultant improved results in ultrasound imaging. Usually, microscale fluorocarbon bubbles are employed as contrasting agents, and the features which should be possessed by the contrasting agents include:    

easy administration, easy fabrication, excellent echogenicity, and high biosafety

Thus, the scope of functionalized MNPs in ‘theranostics’ holds immense potential with a constant need of exploring novel NPs with optimal application efficacy.

23.2.3.4

The Way Forward in Atherosclerosis

The crucial disease of ‘Atherosclerosis’, is amongst the leading causes of deaths around the globe.26 The serious inflammation and alteration cause abnormal narrowing of blood vessels i.e., aorta, the primary artery which transports blood from the heart to the rest of the human body. In some conditions it occurs at a rapid pace causing ischemia. Recently, the pathway towards research for diagnosis, prognostication of medical options and relevant treatment have experienced rapid growth.66 The implementation of advanced novel contrasting agents in magnetic resonance imaging for

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detecting atherosclerosis in pathologies is being thoroughly researched and has a futuristic scope through exploration of improved and more efficient contrasting agents. Various techniques are employed for the detection of initial stage atherosclerosis including CT or CAT, single-photon emission computed tomography positron emission tomography, fluorescence molecular tomography and photoacoustic tomography with various advantages and disadvantages. The benefits of optimal sensitivity are overtaken by low resolution or in some cases the advantage of impressive resolution is discredited by lower sensitivity. The MNPs have emerged as very promising tools through their capability of binding to required target surfaces, thereby decreasing the time for detection.67

23.2.4 23.2.4.1

Other Applications of Magnetic Nanoparticles Applications in Biological Sample Preparation

In the field of medicine and biotechnology, MNPs are employed for the purpose of isolation, purification, and immobilization of a variety of biomolecules including deoxyribonucleic acid (DNA), ribonucleic acid (RNA) along with multiple biological fluids from bacteria and viruses.68 The advantage with MNPs in comparison to traditional techniques include reduction in the time of separation for analytes and decrement in the quantity of hazardous reagents in comparison to chloroform/phenol-based methods with automation. The efficacy of MNPs in the separation of cells from complex matrixes is noteworthy.69 The technique of magnetic separation is comparatively easier than traditional methodologies and presents a quick technology for the preparation of samples for electromigration or chromatographic assessment. The simplification of the accurate procedures in which fluctuating the buffer conditions along with constant washing process is vital. An advantage of using MNPs is that a specific cell population can be increased, which is not the case in cytometric methodologies. These isolated cells are usually found to be clear, alive, and unchanged through the process. The separation of proteins and peptides through employment of MNPs eliminates the requisite of pre-treatment of the sample. Moreover, it depends upon the other components including antigen and antibody as well. Furthermore, it can rapidly and efficiently remove peptides from samples which are highly polluted. Although for effective extraction the nature of the antibody and type of MNP should be properly controlled. The MNPs are also utilized to isolate organic/inorganic compounds from biological samples in several bioanalysis techniques. The assessment of biological samples is a very crucial challenge for analysts, considering the complex matrices which saliva, blood, bile, urine, and sperm possess. The biological samples consist of salts, proteins, bases, acids, and other complex organic compounds with similar chemical structures for targeting analytes. The potential scope of interaction among the functional groups of compounds including benzodiazepines and steroids is also prevalent. The affinity between analytes and

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sorbents used for extraction is decreased through such interactions. The traditional extraction techniques are uneconomical, and time consuming and often provide lower recovery rates for analytes specifically in cases of isolation of small size molecules. Thus, research towards the higher applicability of functionalized MNPs in the diagnosis of biological samples has a great future prospective considering the increasing population and resultant need for medical facilities.

23.2.4.2

Future Scope in Environmental Remediation

The uniqueness of every environmental contaminant in terms of composition, nature, and structure make the process of remediation very complex. The diversity of environmental samples is due to their complex compounds for analysis complemented by the site conditions and interfering substances in the succeeding steps of the analytical processes.70 Thus, the preparation of samples for analysis is very vital. A variety of solid-phase-based methods for the preparation of environmental samples including MEPS, SBSE, and SPME exist.71 In comparison with particles in the ‘mm’ size range, the MNPs provide a relatively higher ratio between surface area and volume, with a shorter way for diffusion resulting in higher extraction capacity and efficiency. The MNPs are employed for isolation and enrichment of carcinogenic compounds, PAHs, antibiotics, pesticides, surfactants, drugs, etc. Various MNPs with coatings on surfaces along with functional groups are used for the extraction of analytes from contaminated water samples. Hence, the need of functionalized MNPs for remediation of water sources is a very broad area of application and possesses huge scope of improvement through introduction of cost effective MNPs suitable for various contaminants.

23.2.4.3

Application in Food Sample Preparation

The presence of chemical contaminants in food is a matter of concern for individuals and authorities. The stringent monitoring of the presence of chemical pollutants in products to be consumed is very vital. The chemical pollutants in food variate in physicochemical properties, and food samples carry very complex matrices. The up-surging issue in evaluation include the naturally occurring materials occurring in various food samples in decreasing the limit of detection (LOD) for analytes. The matrix interferences include proteins, sugars, pigments, and fatty acids, which emerge as a restraining factor in the detection and measurement of target analytes. The linkage of various biomolecules like aptamers and antibodies at the surface of MNPs makes the process of isolation of analytes more simple, selective, and rapidly decreases the use of organic solvents.44 The optimal extraction process depends upon several factors which include, (i) the quantity of MNPs, (ii) ionic strength, (iii) pH, (iv) time taken in extraction, and (v) nature of the eluent.72

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The research towards the application of magnetite MNPs in SPE towards the isolation of pollutants in food samples is highly needed considering the various existing challenges. The analysis of the potential risks of MNPs to human health also need to be assessed as a part of future research ideas. Various studies towards the improvement of current analytical techniques and drafting novel methods for the analysis of the various analytes are needed. The employment of MNPs in SPE has resultantly decreased the time span of the analysis by the reduction of the various stages in the extraction process. The coherent isolation and improvement of analytes promote separation of the sorbent with analytes. These analytes are adsorbed on the surface, using an external magnetic field. Furthermore, the MSPE helps in reducing the use of organic solvents which subsequently prevents the formation of toxic and hazardous waste. All of which is in accordance with the principles of green chemistry as well. Mostly, the MNPs are used in isolation with various types of analytes, which varies from some simple inorganic compounds to some very complex biomolecules. The excellent properties and varying degree of applications of these MNPs present a very promising hope for their future use in various fields. However, there are still some limiting factors preventing the extensive applications of MNPs. One of the major challenges being the isolation of trace amounts of analytes from their complex matrix, e.g., biological samples. Hence, an important scope of improvement in existing methods of synthesizing these MNPs will be to obtain monodispersity and a better control over the shape of these MNPs. Further attention should also be paid to develop certain new coatings, which will ensure an efficient protection of the magnetic core. This will also improve their dispersity especially in aqueous solutions and obtaining some multifunctional MNPs. Investments in designing and developing novel strategies will also allow control over the interactions between the analyte and the surface. This will in turn improve the physicochemical properties of MNPs. Moreover, this will also help in preventing and reducing the background signal caused by the non-specific binding. It becomes increasingly important to develop some appropriate analytical procedures which carry out the synthetization and functionalization of MNPs, and work of the conditions of extraction processes simultaneously. More importantly, there is still a huge challenge in terms of developing an online-MSPE, which will enable the NPs to be used in routine laboratory analysis.

23.3 Conclusion The scope of functionalized MNPs in the various analytical processes is remarkable. The conjunction of MNPs with analytical processes has developed novel possibilities in various qualitative and quantitative analysis. The implementation of magnetic fields for modifying the motion and properties of MNPs has led to manipulation and analysis at the molecular level, thereby

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promoting application in separation science (analyte modification, chromatographic techniques, etc.). The use of functionalized MNPs in the field of targeted drug delivery systems holds great momentum, owing to their exemplary properties including accurate target recognition and application irrespective of their diverse nature. The areas of improvement in drug delivery include wider applicability for therapy in more diseases. A constant need to overcome the shortcomings in their applications owing to various conditions needs to be catered for. The use of functionalized MNPs in various diagnostic applications as contrast agents holds a wide scope owing to the efficacy of results. The wide usage of functionalized MNPs in the various fields include environmental remediation, theranostics, atherosclerosis, biological samples, food sample preparation, imaging techniques (MRI), etc. All the areas of application for functionalized MNPs have witnessed significant growth with the scope of introducing various novelties in terms of modified structure, properties, economics, and reusability. The future holds the scope of introducing new stationary phases of functionalized MNPs with wider selectivity promoting their wider analytical applications as an independent field.

References 1. S. Shukla, R. Khan and C. M. Hussain, Nanoremediation, in The Handbook of Environmental Remediation, Royal Society of Chemistry, 2020, pp. 443–467, Available from: https://pubs.rsc.org/en/content/chapter/ bk9781788013802-00443/978-1-78801-380-2. 2. C. M. Hussain Magnetic Nanomaterials for Environmental Analysis, 2016. 3. F. I. Khan and A. K. Ghoshal, Removal of Volatile Organic Compounds from polluted air, J. Loss Prev. Process. Ind., 2000, 13(6), 527–545. 4. S. Shukla and A. Saxena, Sources and leaching of nitrate contamination in groundwater, Curr. Sci., 2020, 118(6), 883–891. 5. R. Khan, A. Saxena and S. Shukla, Evaluation of heavy metal pollution for River Gomti, in parts of Ganga Alluvial Plain, India, SN Appl. Sci., 2020, 2(8), 1–12. 6. P. G. Tratnyek and R. L. Johnson, Nanotechnologies for environmental cleanup, Nano Today, 2006, 1(2), 44–48. 7. C. M. Hussain, Nanomaterials in Chromatography, 2020, https://doi.org/ 10.1016/C2016-0-04157-8. 8. D. Sharma and C. M. Hussain, Smart nanomaterials in pharmaceutical analysis, Arabian J. Chem., 2020, 13, 3319–3343. 9. K. J. Shah and T. Imae, Selective Gas Capture Ability of Gas-AdsorbentIncorporated Cellulose Nanofiber Films, Biomacromolecules, 2016, 17(5), 1653–1661. 10. F. D. Guerra, G. D. Smith, F. Alexis and D. C. Whitehead, A Survey of VOC Emissions from Rendering Plants, Aerosol. Air Qual. Res., 2017, 17(1), 209–217.

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11. J. Sengupta and C. M. Hussain, Graphene and its derivatives for Analytical Lab on Chip platforms, TrAC, Trends Anal. Chem., 2019, 114, 326–337. 12. R. Keçili and C. M. Hussain, Recent Progress of Imprinted Nanomaterials in Analytical Chemistry, Int. J. Anal. Chem., 2018, DOI: 10.1155/2018/ 8503853. 13. P. Worsfold, A. Townshend, C. Poole and M. Miro, Encyclopedia of Analytical Science, Elsevier, 3rd edition, 2019. ¨yu ¨ktiryaki and C. M. Hussain, Advancement in bioana14. R. Keçili, S. Bu lytical science through nanotechnology: Past, present and future, TrAC, Trends Anal. Chem., 2019, 110, 259–276. 15. C. M. Hussain and R. Kecili, Modern Environmental Analysis Techniques for Pollutants, 1st edn, 2020, Available from: https://www.elsevier.com/ books/modern-environmental-analysis-techniques-for-pollutants/ mustansar-hussain/978-0-12-816934-6. 16. R. Thiruppathi, S. Mishra, M. Ganapathy, P. Padmanabhan and ´s, Nanoparticle Functionalization and Its Potentials for B. Gulya Molecular Imaging, Adv. Sci., 2017, 4(3), 1600279. 17. F. Herranz and J. Pellico Covalent Functionalization of Magnetic Nanoparticles for Biomedical Imaging, 2012. 18. S. D. Anderson, V. V. Gwenin and C. D. Gwenin, Magnetic Functionalized Nanoparticles for Biomedical, Drug Delivery and Imaging Applications, Nanoscale Research Letters, Springer, New York LLC, 2019, vol. 14, pp. 1–16. Available from: https://doi.org/10.1186/s11671-019-3019-6. 19. R. Bushra, Functionalized nanomaterials for chromatography, in Nanomaterials in Chromatography: Current Trends in Chromatographic Research Technology and Techniques, Elsevier, 2018, pp. 403–414. 20. K. Riehemann, S. W. Schneider, T. A. Luger, B. Godin, M. Ferrari and H. Fuchs, Nanomedicine – Challenge and perspectives, Angew. Chem., Int. Ed., 2009, 48, 872–897. 21. R. Subbiah, M. Veerapandian and K. Yun, Nanoparticles: Functionalization and Multifunctional Applications in Biomedical Sciences, Curr. Med. Chem., 2011, 17(36), 4559–4577. 22. A. M. Abu-Dief and S. M. Abdel-Fatah, Development and functionalization of magnetic nanoparticles as powerful and green catalysts for organic synthesis, Beni-Suef. Univ. J. Basic Appl. Sci., 2018, 7(1), 55–67. 23. S. Angioletti-Uberti, Theory, simulations and the design of functionalized nanoparticles for biomedical applications: A Soft Matter Perspective, npj Comput. Mater., 2017, 3, 1–15. 24. C. M. Hussain, Handbook of Nanomaterials in Analytical Chemistry, 1st edn, 2020, Available from: https://www.elsevier.com/books/handbook-of-nano materials-in-analytical-chemistry/mustansar-hussain/978-0-12-816699-4. 25. L. Xie, R. Jiang, F. Zhu, H. Liu and G. Ouyang, Application of functionalized magnetic nanoparticles in sample preparation, Anal. Bioanal. Chem., 2014, 406(2), 377–399. 26. Y. Chen, M. Ma, H. Chen and J. Shi, Multifunctional Hollow Mesoporous Silica Nanoparticles for MR/US Imaging-Guided Tumor Therapy, 2016, 189–222.

592

Chapter 23

27. E. C. Njagi, H. Huang, L. Stafford, H. Genuino, H. M. Galindo and J. B. Collins, et al., Biosynthesis of iron and silver nanoparticles at room temperature using aqueous sorghum bran extracts, Langmuir, 2011, 27(1), 264–271. 28. A. Farrukh, A. Akram, A. Ghaffar, S. Hanif, A. Hamid and H. Duran, et al., Design of polymer-brush-grafted magnetic nanoparticles for highly efficient water remediation, ACS Appl. Mater. Interfaces, 2013, 5(9), 3784–3793. 29. Z. Li, L. Wei, M. Gao and H. Lei, One-pot reaction to synthesize biocompatible magnetite nanoparticles, Adv. Mater., 2005, 17(8), 1001– 1005. 30. C. Xu, O. U. Akakuru, J. Zheng and A. Wu, Applications of iron oxidebased magnetic nanoparticles in the diagnosis and treatment of bacterial infections, Front. Bioeng. Biotechnol., 2019, 7, 141. 31. K. Wu, D. Su, J. Liu, R. Saha and J.-P. Wang, Magnetic nanoparticles in nanomedicine: a review of recent advances, Nanotechnology, 2019, 30(50), 502003. 32. W. Z. Shen, S. Cetinel and C. Montemagno, Application of biomolecular recognition via magnetic nanoparticle in nanobiotechnology, J. Nanoparticle Res., 2018, 20(5), 130. 33. D. Jankovic, M. Radovic´, M. Mirkovic´, A. Vukadinovic, M. Peric´ and D. Petrovic´, et al. 90Y-labeled of phosphates-coated magnetic nanoparticles as a potential tumor treatment radiopharmaceuticals, 2018, Available from: https://posterng.netkey.at/eanm/viewing/index.php? module=viewing_poster&task=&pi=3404. 34. G. Mohammadi Ziarani, M. Malmir, N. Lashgari and A. Badiei, The role of hollow magnetic nanoparticles in drug delivery, RSC Adv., 2019, 9, 25094–25106. 35. D. Kami, S. Takeda, Y. Itakura, S. Gojo, M. Watanabe and M. Toyoda, Application of magnetic nanoparticles to gene delivery, Int. J. Mol. Sci., 2011, 12, 3705–3722. 36. N. Ahmed, H. Fessi and A. Elaissari, Theranostic applications of nanoparticles in cancer, Drug Discovery Today, 2012, 17, 928–934. 37. Y. Pan, X. Du, F. Zhao and B. Xu, Magnetic nanoparticles for the manipulation of proteins and cells, Chem. Soc. Rev., 2012, 41(7), 2912–2942. ¨th, Magnetic nanoparticles: Synthesis, 38. A. H. Lu, E. L. Salabas and F. Schu protection, functionalization, and application, Angew. Chem., Int. Ed., 2007, 46, 1222–1244. 39. C. M. Hussain, Handbook on Miniaturization in Analytical Chemistry, 1st edn, 2020, Available from: https://www.elsevier.com/books/ handbook-on-miniaturization-in-analytical-chemistry/hussain/978-0-12819763-9. 40. H. Qu, S. Tong, K. Song, H. Ma, G. Bao and S. Pincus, et al., Controllable in situ synthesis of magnetite coated silica-core water-dispersible hybrid nanomaterials, Langmuir, 2013, 29(33), 10573–10578.

Future of Functionalized Magnetic Nanoparticles in Analytical Chemistry

593

41. J. S. Beveridge, J. R. Stephens and M. E. Williams, The Use of Magnetic Nanoparticles in Analytical Chemistry, Ann. Rev. Anal. Chem., 2011, 251–275. 42. M. Faraji, Recent analytical applications of magnetic nanoparticles, Nanochem. Res., 2016, 1(2), 264–290. ¨yu ¨ktiryaki, R. Keçili and C. M. Hussain, Functionalized nanomater43. S. Bu ials in dispersive solid phase extraction: Advances & prospects, TrAC, Trends Anal. Chem., 2020, 127, DOI: 10.1016/j.trac.2020.115893. 44. M. Wierucka and M. Biziuk, Application of magnetic nanoparticles for magnetic solid-phase extraction in preparing biological, environmental and food samples, TrAC, Trends Anal. Chem., 2014, 59, 50–58. 45. E. Maryanti, D. Damayanti, I. Gustian and S. S. Yudha, Synthesis of ZnO nanoparticles by hydrothermal method in aqueous rinds extracts of Sapindus rarak DC, Mater. Lett., 2014, 118, 96–98. 46. M. Y. Nassar, I. S. Ahmed, T. Y. Mohamed and M. Khatab, A controlled, template-free, and hydrothermal synthesis route to sphere-like a-Fe2O3 nanostructures for textile dye removal, RSC Adv., 2016, 6(24), 20001– 20013. 47. M. Shah, D. Fawcett, S. Sharma, S. K. Tripathy and G. E. J. Poinern, Green synthesis of metallic nanoparticles via biological entities, Materials, 2015, 8, 7278–7308. 48. A. Baranwal, K. Mahato, A. Srivastava, P. K. Maurya and P. Chandra, Phytofabricated metallic nanoparticles and their clinical applications, RSC Adv., 2016, 6, 105996–106010. 49. S. Gul, S. B. Khan, I. U. Rehman, M. A. Khan and M. I. Khan, A Comprehensive Review of Magnetic Nanomaterials Modern Day Theranostics, Front. Mater., 2019, 6(July), 1–15. 50. S. Iravani, Green synthesis of metal nanoparticles using plants, Green Chem., 2011, 13(10), 2638–2650. 51. A. M. Awwad, N. M. Salem and A. O. Abdeen, Green synthesis of silver nanoparticles using carob leaf extract and its antibacterial activity, Int. J. Ind. Chem., 2013, 4(1), 29. 52. R. Langer, New methods of drug delivery, Science, 1990, 249(4976), 1527– 1533. 53. V. V. Mody, A. Cox, S. Shah, A. Singh, W. Bevins and H. Parihar, Magnetic nanoparticle drug delivery systems for targeting tumor, Appl. Nanosci., 2014, 4, 385–392. ´rez and 54. O. V. Kharissova, H. V. R. Dias, B. I. Kharisov, B. O. Pe ´rez, The greener synthesis of nanoparticles, Trends Biotechnol., V. M. J. Pe 2013, 31, 240–248. 55. D. S. Seeli and M. Prabaharan, Guar gum oleate-graft-poly(methacrylic acid) hydrogel as a colon-specific controlled drug delivery carrier, Carbohydr. Polym., 2017, 158, 51–57. 56. W. Yu, T. W. Sun, Z. Ding, C. Qi, H. Zhao and F. Chen, et al., Copperdoped mesoporous hydroxyapatite microspheres synthesized by a microwave-hydrothermal method using creatine phosphate as an

594

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58. 59.

60.

61.

62.

63.

64.

65.

66.

67.

68.

69.

Chapter 23

organic phosphorus source: application in drug delivery and enhanced bone regeneration, J. Mater. Chem. B., 2017, 5(5), 1039–1052. O. Veiseh, J. W. Gunn and M. Zhang, Design and fabrication of magnetic nanoparticles for targeted drug delivery and imaging, Adv. Drug Delivery Rev., 2010, 62(3), 284–304. C. Funke and A. J. Szeri, Osmolarity as a contributing factor in topical drug delivery, APS, 2017, E5.004. Available from. M. B. Fish, C. A. Fromen, G. Lopez-Cazares, A. W. Golinski, T. F. Scott and R. Adili, et al., Exploring deformable particles in vascular-targeted drug delivery: Softer is only sometimes better, Biomaterials, 2017, 124, 169–179. Z. Sun, M. Worden, J. A. Thliveris, S. Hombach-Klonisch, T. Klonisch and J. van Lierop, et al., Biodistribution of negatively charged iron oxide nanoparticles (IONPs) in mice and enhanced brain delivery using lysophosphatidic acid (LPA), Nanomedicine, 2016, 12(7), 1775– 1784. L. Bissonnette and M. G. Bergeron, Next revolution in the molecular theranostics of infectious diseases: microfabricated systems for personalized medicine, Expert Rev. Mol. Diagn., 2006, 6(3), 433–450. Y. Zheng, D. J. Hunting, P. Ayotte and L. Sanche, Radiosensitization of DNA by gold nanoparticles irradiated with high-energy electrons, Radiat. Res., 2008, 169(1), 19–27. S. Her, D. A. Jaffray and C. Allen, Gold nanoparticles for applications in cancer radiotherapy: Mechanisms and recent advancements, Adv. Drug Delivery Rev., 2017, 109, 84–101. I. Marangon, A. A. K. Silva, T. Guilbert, J. Kolosnjaj-Tabi, C. Marchiol and S. Natkhunarajah, et al., Tumor stiffening, a key determinant of tumor progression, is reversed by nanomaterial-induced photothermal therapy, Theranostics, 2017, 7(2), 329–343. D. Sakellari, K. Brintakis, A. Kostopoulou, E. Myrovali, K. Simeonidis and A. Lappas, et al., Ferrimagnetic nanocrystal assemblies as versatile magnetic particle hyperthermia mediators, Mater. Sci. Eng. C, 2016, 58, 187–193. A. Yildirim, R. Chattaraj, N. T. Blum and A. P. Goodwin, Understanding Acoustic Cavitation Initiation by Porous Nanoparticles: Toward Nanoscale Agents for Ultrasound Imaging and Therapy, Chem. Mater., 2016, 28(16), 5962–5972. A. J. Brown, Z. Teng, P. C. Evans, J. H. Gillard, H. Samady and M. R. Bennett, Role of biomechanical forces in the natural history of coronary atherosclerosis, Nat. Rev. Cardiol., 2016, 13, 210–220. T. R. Sarkar and J. Irudayaraj, Carboxyl-coated magnetic nanoparticles for mRNA isolation and extraction of supercoiled plasmid DNA, Anal. Biochem., 2008, 379(1), 130–132. M. Kuhara, H. Takeyama, T. Tanaka and T. Matsunaga, Magnetic cell separation using antibody binding with protein A expressed on bacterial magnetic particles, Anal. Chem., 2004, 76(21), 6207–6213.

Future of Functionalized Magnetic Nanoparticles in Analytical Chemistry

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´tima Alpendurada, Solid-phase microextraction: A promising 70. M. De Fa technique for sample preparation in environmental analysis, J. Chromatogr., A, 2000, 3–14. 71. C. Hu, M. He, B. Chen, C. Zhong and B. Hu, Polydimethylsiloxane/ metal-organic frameworks coated stir bar sorptive extraction coupled to high performance liquid chromatography-ultraviolet detector for the determination of estrogens in environmental water samples, J. Chromatogr. A, 2013, 1310, 21–30. 72. X. Zhao, W. Gao, H. Zhang, X. Qiu and Y. Luo, Graphene quantum dots in biomedical applications: Recent advances and future challenges, in Handbook of Nanomaterials in Analytical Chemistry: Modern Trends in Analysis, Elsevier Inc., 2019, pp. 493–505, http://dx.doi.org/10.1016/B9780-12-816699-4.00020-7.

Subject Index activated carbon-based magnetic materials, 91–93 aerosol/vapor-phase-based synthesis, 245, 266 allotropic forms of carbon-based MNPs, for organic analyte extraction, 134–141 AMR. See anisotropy magnetoresistance (AMR) sensors analyte extraction, 200–211 MNPs for, 204–210 biological applications of, 209–210 environmental applications of, 205–207 food applications of, 207–209 sample pre-treatment for, 203–204 anisotropy magnetoresistance (AMR) sensors, 373 aptamers, 185–186 artificial intelligence, 493–495 assays, for magnetoresistance-based biosensors competitive, 385–386 direct, 381–384 sandwich, 384–385 atherosclerosis, 586–587 augmented reality, 492 BAM. See boronate affinity materials (BAM) bare MNPs, toxicity of in vitro, 534–537 in vivo, 537–538

biocompatibility, 38 of magnetoresistance-based biosensors, 380 biodistribution of nanoparticles, 510 bioelimination of nanoparticles, 510 biological applications of magnetic solid phase extraction, 228–230 of MNPs, in analyte extraction, 209–210 biological macromolecule extraction, graphene-based magnetic sorbents for, 194 biological sample preparation, MNPs applications in, 587–588 biological synthesis, FMNPs applications in, 581 biomedical applications of FMNPs, 38–45, 561–563 biosensors, 39–40 magnetic hyperthermia, 43–45 MRI contrast agents, 41–42 protein purification/bioseparation, 40–41 targeted drug delivery, 42–43 biomolecules, detection of, 292–293 biosensors FMNPs-based, 39–40, 324–340 cholesterol-based biosensors, 338–339 electrochemical biosensors, 328–331 enzyme-based biosensors, 335–336 future trends of, 339–340

Subject Index

glucose-based biosensors, 336–338 magnetic field biosensors, 334–335 optical biosensors, 331–333 piezoelectric biosensors, 333–334 magnetoresistance-based, 369–392 magnetoresistive sensors, 371–378 MNPs in, 378–380 boronate affinity materials (BAM), 184–185 capillary electrochromatography (CEC), 266–270 carbon-based magnetic materials activated, 91–93 sample pre-treatment, 91 carbon coatings, 560–561 carbon nanotube (CNT)-based magnetic materials, 94–95, 97 carboxylate graphene-MNPs, 9 CEC. See capillary electrochromatography (CEC) cells, detection of, 292–293 cetyltrimethylammonium bromide (CTAB), 28 chemical composition, 32 chemical vapor deposition (CVD), 175 chemiluminescence enzyme immunoassay (CLEIA), 293 chip-based chromatography, 270–274 cholesterol-based biosensors, 338–339 chromatography, 246–254 applications of FMNPs, 262–274 preparation techniques, 263–274 capillary electrochromatography, 266–270

597

chip-based, 270–274 effective separation, considerations for, 250–251 gas, 251–252 liquid, 252–254 CLEIA. See chemiluminescence enzyme immunoassay (CLEIA) cloud computing, 492 CNT. See carbon nanotube (CNT)based magnetic materials coated MNPs, toxicity of in vitro, 534–537 in vivo, 537–538 cobalt MMNPs chemical design of, 25 COFs. See covalent organic framework (COFs) coatings colloidal stability, of magnetoresistance-based biosensors, 380 colorimetric detection using gold nanoparticles and surfaces, 355–356 using peroxidase-like activity reporters, 350–355 competitive assays, for magnetoresistance-based biosensors, 385–386 coprecipitation method, 179–180, 244–245, 264, 457–458, 554–556 covalent organic framework (COFs) coatings for organic analyte extraction, 146–152 CTAB. See cetyltrimethylammonium bromide (CTAB) CVD. See chemical vapor deposition (CVD) cyber-physical systems, 491 cybersecurity, 493 data storage, 566–567 deep eutectic solvents (DESs), 7, 183–184 deep learning, 493–495

598

DESs. See deep eutectic solvents (DESs) detection analysis, MNPs applications in, 292–295 biomolecules and cells, 292–293 ions and inorganic compounds, 294–295 organic compounds, 294 direct assays, for magnetoresistancebased biosensors, 381–384 direct magnetization, 179 disease biomarkers, MIP-decorated MNPs in, 420 dispersion polymerization, 127 dispersive solid-phase microextraction (DSPME), 177 dose–response assessment, 521 drug delivery, 497, 582–584 DSPME. See dispersive solid-phase microextraction (DSPME) electrochemical biosensors, 328–331 electrochemical sensing-based analytical strategies, 362–365 electrochemical sensing, transduction methods in, 282–286 electrochemical sensors, MIP-decorated MNPs for magnetic capture onto magneto-actuated electrodes, 415 modification with magnetic MIPs by drop-casting/coating, 414–415 electro-magnetic wave, fundamental of, 435–436 emulsifier-free emulsion polymerization, 128 emulsion polymerization, 127–128 enabling technologies, 492–493 environmental applications of magnetic solid phase extraction, 226–227 of MNPs, in analyte extraction, 205–207

Subject Index

environmental remediation, 588 enzyme-based biosensors, 335–336 exposure assessment, 521 Fe-nAp characterization, 64–66 Fe3O4@MIPs, synthesis of, 128, 129 Fe3O4@SiO2–G preparation, 139, 140 finite-size effect of NPs, 553–554 flow injection synthesis, 245, 265 FMNP-based sensors, 454–481 functionalization of, 461–475 using inorganic materials, 467–475 using organic materials, 462–467 point-of-care approaches, 475–481 preparation of, 455–461 co-precipitation method, 457–458 green synthesis, 461 hydrothermal synthesis, 458–459 microemulsion, 460 sol–gel method, 460–461 thermal decomposition, 459–460 FMNP-modified polymeric composites by computer modeling, characterization of, 429–447 cubic nanoparticle distribution, effect of, 441–444 effective permittivity, 437–438 analytical calculation, 439 electro-magnetic wave, fundamental of, 435–436 nanocomposites, modeling of, 439–441 orientation effect, 444–445 permeability, 437–438 analytical calculation, 439 randomly distributed nanoparticle model, 445–446 shape effect, 444–445 FMNPs. See functionalized magnetic nanoparticles (FMNPs)

Subject Index

food applications of magnetic solid phase extraction, 227–228 of MNPs, in analyte extraction, 207–209 quality and safety evaluation, 310–321 international certification, 311 MNP-based sensors, 315–321 NP-based sensors, NP properties for, 315 sensor classification and properties, 312–315 sample preparation, 588–589 food safety MIP-decorated MNPs for biomarkers, 417 pesticides, 417–418 toxins, 418 force interactions between analytes and sorbents, 10 functionalized magnetic nanoparticles (FMNPs), 6–7 advantages of, 578 analytical applications of, 3–11 force interactions between analytes and sorbents, 10 magnetic solid phase extraction, 5–10 sample preparation techniques, 4–5 in analytical chemistry, future of, 574–590 biocompatibility, 38 biomedical applications, 38–45 chemical design of, 23–30 chromatographic applications of, 262–274 design of, 20–46 physicochemical features of, 30–35 in sample pre-treatment, 79–106

599

synthetic route to, 22–23 for tomorrow’s applications, 549–567 functionalized nanoscale magnetic particles preparation of, 59–60 gas chromatography (GC), 248 FMNPs in, 251–252 GC. See gas chromatography (GC) giant magnetoresistance (GMR) sensors, 335, 373–375 glucose-based biosensors, 336–338 GMR. See giant magnetoresistance (GMR) sensors GMS. See Graphene-based magnetic sorbents (GMS) GO. See graphene oxide (GO) gold-based coating, 37–38 gold nanoparticles and surfaces, colorimetric detection using, 355–356 graphene-based magnetic nanoparticles, 92, 94, 96 graphene-based magnetic sorbents (GMS) characterization of, 186–189 functionalization of, 182–186 aptamers, 185–186 boronate affinity materials, 184–185 deep eutectic solvents, 183–184 inorganic pollutant extraction, 193–194 ionic liquids, 183–184 metal–organic frameworks, 183 miscellaneous functionalities, 186 molecularly imprinted polymers, 183 supramolecules, 185 modern applications of, 189–194

600

graphene-based magnetic sorbents (GMS) (continued) biological macromolecule extraction, 194 organic pollutant extraction, 191–193 preparation of, 178–182 coprecipitation method, 179–180 direct magnetization, 179 hydrothermal method, 180 solvothermal method, 180–181 sonochemical method, 181–182 graphene-based sorbents, for modern magnetic solid-phase extraction techniques, 174–195 graphene-based magnetic sorbents. See graphene-based magnetic sorbents (GMS) graphene oxide (GO), 332 nanosheets, 281 green synthesis, 461 Hall effect-based magnetic biosensors, 335 HGMS. See high gradient magnetic separation (HGMS) high gradient magnetic separation (HGMS), 221 hydrothermal synthesis, 180, 244, 265, 458–459, 556 hyperthermia, 566 imaging techniques, FMNPs applications in, 584–585 Industry 4.0, 489–500 inorganic coating materials gold-based coating, 37–38 silica-based coating (silanization), 37 inorganic compounds, detection of, 294–295

Subject Index

inorganic pollutant extraction, graphene-based magnetic sorbents for, 193–194 interfacial interactions, 33 Internet of Energy (IoE), 493 Internet of People (IoP), 493 Internet of Service (IoS), 493 Internet of Things (IoT), 493 IoE. See Internet of Energy (IoE) ionic liquids-coated MNPs for magnetic solid-phase extraction, 183–184 for organic analyte extraction, 152–157 ions, detection of, 294–295 IoP. See Internet of People (IoP) IoS. See Internet of Service (IoS) IoT. See Internet of Things (IoT) iron-containing hydroxyapatite preparation of, 58–59 iron MMNPs chemical design of, 24–25 iron oxide magnetic nanoparticles preparation of, 56–58 KETs. See Key Enabling Technologies (KETs) Key Enabling Technologies (KETs), 489–490 LaMer model, 23 LC. See liquid chromatography (LC) legal aspects of FMNPs, 538–540 LGMS. See low gradient magnetic separation (LGMS) liquid chromatography (LC), 248 FMNPs in, 252–254 low gradient magnetic separation (LGMS), 221 luminescence sensing, 356–360 machine learning, 493–495 magnetic behavior, 80–82 magnetic core, 221–222 magnetic-dispersive solid-phase extraction (m-dSPE), 122–123, 125, 126

Subject Index

magnetic field biosensors, 334–335 magnetic field flow fractionation (MgFFF), 220 magnetic field sensing, transduction methods in, 290–292 magnetic field sensor, 387 magnetic field source, 389 magnetic hyperthermia, 43–46 magnetic molecularly imprinted polymer (MMIP), 294 magnetic nanomaterials adsorbing properties improvement by bioorganic substratemediating synthesis, 54–69 Fe-nAp characterization, 64–66 Mnp@YM4 characterization, 61–62 Mnp@YM10 characterization, 61–62 SBO–Fe-nAp characterization, 64–66 SBO–Fe-nAp nanocomposites, bi-metal (Pb(II) and Cu(II)) adsorption on, 68–69 SBO–FenAp nanocomposites, enhanced Cu adsorption maximum uptake on, 66–67 SBO-Fen-Ap nanocomposites, enhanced Pb adsorption maximum uptake on, 67–68 YM–iron oxide magnetic nanoparticles, 62–64 magnetic nanoparticles, definition of, 402 magnetic nanoparticles, preparation of functionalized nanoscale magnetic particles, 59–60 template iron-containing hydroxyapatite (SBOFe-nAp) nanoparticle synthesis, 60

601

YM extract-coated magnetite nanoparticle synthesis, 60 iron-containing hydroxyapatite, 58–59 iron oxide magnetic nanoparticles, 56–58 magnetic nanoparticles, properties of, 241, 327 magnetic nanoparticles, stabilizing carbon coatings, 560–561 polymer coatings, 558–559 silica coating, 560 magnetic nanoparticles, synthesis of, 327 aerosol/vapor-phase-based synthesis, 245 coprecipitation technique, 244–245, 554–556 flow injection synthesis, 245 hydrothermal synthesis, 244, 556 microemulsion-based synthesis, 245, 556–557 sol–gel synthesis, 243–244 thermal deposition technique, 243 wet chemistries, 557–558 magnetic resonance imaging (MRI), 563 magnetic solid phase extraction (MSPE), 4, 5–6 application of, 7–10 biological applications of, 228–230 environmental applications of, 226–227 extraction techniques, graphene-based sorbents for, 174–195 food applications of, 227–228 pharmaceutical applications of, 228–230 sample pre-treatment, 105 food and beverage samples, 255–256

602

magnetic solid phase extraction (MSPE) (continued) separation techniques, applications in, 254–256 biological samples, 256 environmental samples, 255 magnetic tags, 387 magnetism, 33–35 magnetoresistance-based biosensors, 369–392 assays for competitive, 385–386 direct, 381–384 sandwich, 384–385 device concept, 386–391 magnetic field sensor, 387 magnetic field source, 389 magnetic tags, 387 microfluidic channel, 389 readout electronic, 389–391 sensor surface passivation and functionalization, 387–388 functionalization of, 380–381 future perspectives of, 391–392 magnetoresistive sensors. See magnetoresistive sensors MNPs in, 378–380 biocompatibility, 380 colloidal stability, 380 high magnetic moment, 379–380 magnetoresistive sensors, 371–378 AMR sensors, 373 GMR sensors, 373–375 pseudo spin-valves, 378 spin values, 378 TMR sensors, 376–377 MAMNs. See metal alloy-based magnetic nanostructures (MAMNs) MC/NMNs. See metallic carbides and nitride-based magnetic nanostructures (MC/NMNs)

Subject Index

m-dSPE. See magnetic-dispersive solid-phase extraction (m-dSPE) medical field, FMNPs applications in, 581–587 metal alloy-based magnetic nanostructures (MAMNs) chemical design of, 25–26 metal-based magnetic nanoparticles (MMNPs) chemical design of, 24–25 metallic carbides and nitride-based magnetic nanostructures (MC/NMNs) chemical design of, 27–28 metal organic framework coatings, for organic analyte extraction, 141–146 metal–organic frameworks (MOFs), 183 metal oxide-based magnetic nanoparticles (MOMNPs) chemical design of, 26–27 metals, 498 MgFFF. See magnetic field flow fractionation (MgFFF) microemulsion-based synthesis, 245, 265, 460, 556–557 microfluidic channel, 389 miniaturization devices, 279–295 MIP-decorated MNPs analytical applications of, 399–424 disease biomarkers, 420 food safety, 417–418 medical treatment and drugs, 420–423 pollutants, 419 characterization of adsorption characterization, 410–411 magnetic characterization, 410 morphological characterization, 409–410 structural characterization, 410

Subject Index

decoration of preparation, 408–409 pre-synthesis, 407–408 for dispersive solid-phase extraction, application of, 411–414 principle, 412 reusability, 414 significant factors, 412–413 sorption thermodynamic, 413–414 modification of, 407 preparation of, 407 for sensing electrochemical sensors, 414–415 optical sensors, 415–417 MIPs. See molecularly imprinted polymers (MIPs) MMIP. See magnetic molecularly imprinted polymer (MMIP) MMNPs. See metal-based magnetic nanoparticles (MMNPs) MNMNs. See multifunctional nanoparticle-based magnetic nanostructures (MNMNs) MNP-based sensor development, for food quality and safety evaluation, 310–321 Mnp@YM4 characterization, 61–62 Mnp@YM10 characterization, 61–62 modern separation techniques, FMNPs in, 239–257 applications of magnetic solid phase extraction, 254–256 chromatography, 246–254 effective separation, considerations for, 250–251 gas, 251–252 liquid, 252–254 magnetic nanoparticles, synthesis of aerosol/vapor-phasebased synthesis, 245

603

coprecipitation technique, 244–245 flow injection synthesis, 245 hydrothermal synthesis, 244 microemulsion-based synthesis, 245 sol–gel synthesis, 243–244 thermal deposition technique, 243 MOFs. See metal–organic frameworks (MOFs) molecularly imprinted polymers (MIPs), 128, 183 approaches, 403–404 components of, 404–407 definition of, 402–403 history of, 403 MOMNPs. See metal oxide-based magnetic nanoparticles (MOMNPs) monomeric ligand-based coatings, 36 MRI contrast agents, 41–42 MRI. See magnetic resonance imaging (MRI) MSPE. See magnetic solid phase extraction (MSPE) multifunctional nanoparticle-based magnetic nanostructures (MNMNs) chemical design of, 28–30 classes of, 29 multi-walled carbon nanotubes (MWCNTs), 134, 139 MWCNTs. See multi-walled carbon nanotubes (MWCNTs) nanoecotoxicity, 513–516 nanotechnology, 495–496 ´el relaxation time, 34 Ne nickel NPs chemical design of, 25 NP crystallinity, 31–32

604

NP size, 30–31 NP toxicity, mechanism of, 511–513 octadecylsilane (ODS) modified magnetite nanoparticles sample pre-treatment, 86, 88–91 ODS. See octadecylsilane (ODS) modified magnetite nanoparticles oil removal, 564 optical biosensors, 331–333 optical sensing-based analytical strategies luminescence sensing, 356–360 surface enhanced Raman spectroscopy, 360–362 UV–visible absorbance, 349–356 colorimetric detection, using gold nanoparticles and surfaces, 355–356 colorimetric detection, using peroxidase-like activity reporters, 350–355 optical sensing, transduction methods in, 286–288 optical sensors, MIP-decorated MNPs, 415–417 chemiluminescence, 416–417 fluorescence, 416 UV–Vis spectrophotometry, 416 organic analyte extraction, FMNPs applications in, 122–161 allotropic forms of carbonbased MNPs, 134–141 covalent organic framework coatings, 146–152 ionic liquids, 152–157 metal organic framework coatings, 141–146 miscellaneous, 157–161 polymeric magnetic nanoparticles, 126–134

Subject Index

organic coating materials monomeric ligand-based coatings, 36 polymeric ligand-based coatings, 36–37 organic compounds, detection of, 294 organic/inorganic coatings, surface stability via, 35–36 organic pollutant extraction, graphene-based magnetic sorbents for, 191–193 PDMS. See poly(dimethylsiloxane) (PDMS) PEG. See polyethylene glycol (PEG) peroxidase-like activity reporters, colorimetric detection using, 350–355 pharmaceutical applications of magnetic solid phase extraction, 228–230 phenyl-modified MNPs, 9 physicochemical properties, 529–530 physiological tissues treatment, 497–498 piezoelectric sensing, transduction methods in, 288–290 pollutants, MIP-decorated MNPs in, 419 poly(dimethylsiloxane) (PDMS), 272–274 polyethylene glycol (PEG), 36 polymer coatings, 558–559 polymeric ligand-based coatings, 36–37 polymeric magnetic nanoparticles, for organic analyte extraction, 126–134 polymer-modified magnetic nanoparticles sample pre-treatment, 101–103 protein purification/bioseparation, 40–41 readout electronic, 389–391 RES. See reticuloendothelial system (RES)

Subject Index

reticuloendothelial system (RES), 510 risk assessment, 520–521 dose–response assessment, 521 ethical issues of, 521–522 exposure assessment, 521 future trends of, 522–523 sample preparation, FMNPs applications in, 579–581 sample pre-treatment, FMNPs in, 79–106 activated carbon-based magnetic materials, 91–93 analyte extraction, 203–204 carbon-based magnetic materials, 91 carbon nanotube-based magnetic materials, 94–95, 97 extraction techniques, 80–82 magnetic solid-phase extraction, 105 solid-phase extraction, 103–105 graphene-based magnetic nanoparticles, 92, 94, 96 magnetic behavior, 80–82 magnetic materials, types of, 84 necessity of, 82–83 octadecylsilane modified magnetite nanoparticles, 86, 88–91 polymer-modified magnetic nanoparticles, 101–103 silica-coated FMNPs, 84–87 surfactant-modified magnetic materials, 98–101 techniques, 83–84 sandwich assays, for magnetoresistance-based biosensors, 384–385 SBO-Fe-nAp nanocomposites bi-metal (Pb(II) and Cu(II)) adsorption on, 68–69 characterization of, 64–66 enhanced Cu adsorption maximum uptake on, 66–67

605

enhanced Pb adsorption maximum uptake on, 67–68 sensing applications. See sensing applications MIP-decorated MNPs for electrochemical sensors, 414–415 optical sensors, 415–417 transduction methods in, 281–292 electrochemical, 282–286 magnetic field, 290–292 optical, 286–288 piezoelectric, 288–290 sensing applications, 347–365 electrochemical sensing-based analytical strategies, 362–365 optical sensing-based analytical strategies luminescence sensing, 356–360 surface enhanced Raman spectroscopy, 360–362 UV–visible absorbance, 349–356 sensor surface passivation and functionalization, 387–388 silica-based coating (silanization), 37 silica-coated FMNPs sample pre-treatment, 84–87 silica coating, 560 sol–gel synthesis, 243–244, 265, 460–461 solid phase extraction (SPE), 4, 6, 217–230 magnetic biological applications of, 228–230 environmental application of, 226–227 food application of, 227–228 pharmaceutical applications of, 228–230

606

solid phase extraction (SPE) (continued) material selection and design magnetic core, 221–222 particle coating and functionalization, 222–226 MIP-decorated MNPs for, application of, 411–414 principle, 412 reusability, 414 significant factors, 412–413 sorption thermodynamic, 413–414 principles and methods of, 219–221 sample pre-treatment, 103–105 solvothermal method, 180–181 sonochemical method, 181–182 SPE. See solid phase extraction (SPE) supramolecules, 185 surface effect of NPs, 553 surface enhanced Raman spectroscopy, 360–362 surface functionalization, 35–38 surface potential, 32–33 surface stability, via organic/ inorganic coatings, 35–36 surfactant-modified magnetic materials, 98–101 suspension polymerization, 127 targeted drug delivery, 42–43 template iron-containing hydroxyapatite (SBO–Fe-nAp) nanoparticle synthesis, 60 theranostics, 585–586 thermal decomposition, 263–264, 459–460 TMR. See tunnel magnetoresistance (TMR) sensors toxicity of bare MNPs

Subject Index

in vitro, 534–537 in vivo, 537–538 of coated MNPs in vitro, 534–537 in vivo, 537–538 effect on human health in vitro research on FMNPs, 517–520 of FMNPs, 508–510 in vivo research on FMNPs, 520 nanoecotoxicity, 513–516 of NPs, mechanism of, 511–513 removal, 564–565 toxicological testing, 530–533 in vitro, 531–533 in vivo, 533 tunnel magnetoresistance (TMR) sensors, 376–377 UV–visible spectrophotometry absorbance, 349–356 colorimetric detection, using gold nanoparticles and surfaces, 355–356 colorimetric detection, using peroxidase-like activity reporters, 350–355 MIP-decorated MNPs, 416 VOCs. See volatile organic compounds (VOCs) volatile organic compounds (VOCs), 246 wet chemistries, 557–558 YM extract-coated magnetite nanoparticle synthesis, 60 YM-iron oxide magnetic nanoparticles, adsorbing properties of, 62–64