Novel Nanostructured Materials for Electrochemical Bio-sensing Applications 9780443153341

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Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

Edited by

JAMBALLI G. MANJUNATHA FMKMC College, Mangalore University, Madikeri, Karnataka, India

Elsevier Radarweg 29, PO Box 211, 1000 AE Amsterdam, Netherlands The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, United Kingdom 50 Hampshire Street, 5th Floor, Cambridge, MA 02139, United States Copyright © 2024 Elsevier Inc. All rights reserved, including those for text and data mining, AI training, and similar technologies. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Details on how to seek permission, further information about the Publisher’s permissions policies and our arrangements with organizations such as the Copyright Clearance Center and the Copyright Licensing Agency, can be found at our website: www.elsevier.com/permissions. This book and the individual contributions contained in it are protected under copyright by the Publisher (other than as may be noted herein). Notices Knowledge and best practice in this field are constantly changing. As new research and experience broaden our understanding, changes in research methods, professional practices, or medical treatment may become necessary. Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein. In using such information or methods they should be mindful of their own safety and the safety of others, including parties for whom they have a professional responsibility. To the fullest extent of the law, neither the Publisher nor the authors, contributors, or editors, assume any liability for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions, or ideas contained in the material herein. ISBN: 978-0-443-15334-1 For Information on all Elsevier publications visit our website at https://www.elsevier.com/books-and-journals

Publisher: Candice Janco Acquisitions Editor: Charlotte Rowley Editorial Project Manager: Lindsay Lawrence Production Project Manager: Bharatwaj Varatharajan Cover Designer: Mark Rogers Typeset by MPS Limited, Chennai, India

Contents List of contributors About the editor Preface Acknowledgments

xiii xix xxi xxiii

Part 1 Fundamentals, current advancements in nanostructured electrochemical biosensors 1. Fundamentals of nanostructured materials and synthetic routes

3

S. Pratibha and Yashaswini 1.1 Introduction 1.2 Classification of nanoparticles 1.3 Synthesis of nanoparticles 1.4 Top-down approach 1.5 Bottom-up approach 1.6 Conclusion References

2. Modern trends in carbon nanostructured material-based electrochemical biosensing systems

3 5 6 7 8 15 15

21

Puneetha J., Nagaraju Kottam and Shashanka Rajendrachari 2.1 Introduction 2.2 Neurotransmitters, neurochemicals as biomolecules 2.3 Conclusion References

3. Developments in inorganic and organic based nanostructured materials for electrochemical biosensing applications

21 22 33 33

37

Adimule Vinayak 3.1 Introduction 3.2 Experiment 3.3 Results and discussion 3.4 Nanomaterials-based biosensors 3.5 Conclusion Acknowledgments

37 38 41 43 50 50

v

vi

Contents

Author contributions Conflict of interest Data availability Funding References

4. Organometallic and biomass-derived nanostructured materials for biosensing applications

50 50 50 50 51

57

Gopavaram Sumanth and Sandeep Chandrashekharappa 4.1 Introduction 4.2 Principle of biosensor 4.3 Nanotechnology 4.4 Gold nanoparticles 4.5 Magnetic nanoparticles 4.6 Metal oxide nanoparticles 4.7 Carbon nanoparticles 4.8 Conclusion Future perspectives Summary References

57 58 58 60 62 62 63 67 67 67 68

Part 2 Fabrication of nanostructured materials based bio-sensing platforms 5. Fabrication routes for metallic nanostructured electrochemical biosensors

79

Thiago C. Canevari 5.1 Introduction 5.2 Bottom-up process 5.3 Top-down process 5.4 Conclusions Websites References

6. Design of nanostructured biosensors based on organic and other composite materials

79 82 88 91 91 91

97

B. Chethan, V. Prasad, A. Sunilkumar, S. Thomas and A. Sreeharsha 6.1 Introduction to sensors

97

Contents

6.2 Conclusion References

7. Current electrochemical biosensors in market, trends, and future reliability: a case study

vii 111 114

119

S. Kalaiarasi, P. Karpagavinayagam and C. Vedhi 7.1 Introduction 7.2 Biosensors 7.3 Recent trends in biosensors 7.4 Future reliability 7.5 Conclusion References

8. An overview of stability and lifetime of electrochemical biosensors

119 120 121 122 124 124

129

Ersin Demir, Kevser Kubra Kırboga and Mesut I¸sık 8.1 Introduction 8.2 Design and principle of biosensors 8.3 Electrochemical biosensors 8.4 Reproducibility and lifetime 8.5 Conclusion References

129 130 132 135 153 153

Part 3 Applications of nanostructured electrochemical biosensors 9. Nanostructured materials-based electrochemical biosensor devices for quantification of antioxidants

161

Bruna Coldibeli and Elen Romão Sartori 9.1 Introduction 9.2 Reference analytical methods employed for the determination of antioxidants in beverages 9.3 Oxidoreductase enzymes used in the development of electrochemical biosensors for the determination of phenolic compounds (antioxidants) 9.4 General aspects of the construction of electrochemical enzymatic biosensors 9.5 Application of enzymatic biosensor for the determination of a specific antioxidant or its total content in beverages

161 163

165 168 170

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Contents

9.6 Conclusion Acknowledgments References

10. Nanostructured electrochemical biosensors for pesticides and insecticides

186 187 187

195

Yashaswini, S. Pratibha, Y.B. Vinay Kumar and K.H. Sudheer Kumar 10.1 10.2 10.3 10.4

Introduction Properties of nanostructured electrochemical biosensors Fabrication of nanostructured electrochemical biosensors Nanostructured electrochemical biosensors fabricated for the detection of pesticides and insecticides 10.5 Applications of nanostructured electrochemical biosensors 10.6 Importance of electrochemical biosensors 10.7 Challenges 10.8 Future scope 10.9 Conclusion References

195 198 198

11. Electrochemical biosensing for determination of toxic dyes

215

199 207 207 207 208 208 209

Cem Erkmen, Hülya Silah and Bengi Uslu 11.1 11.2 11.3 11.4

Introduction Dyes and pigments Electrochemical biosensors Determination of toxic dyes based on electrochemical biosensors and their applications 11.5 Conclusion and future perspectives Acknowledgment References

215 216 218 225 236 237 237

12. Electrochemical detection of pathogens in water and food samples

243

K. Soumya, P.A. Geethanjali, C. Srinivas, K.V. Jagannath and K. Narasimha Murthy 12.1 Introduction 12.2 Label-based electrochemical detection 12.3 Electrochemical detection of microorganisms 12.4 Electrochemical detection of viruses 12.5 Electrochemical detection of protozoa References

243 248 249 258 260 269

Contents

13. Electrochemical biosensors for toxic gases monitoring

ix

287

Dipak Maity, Gajiram Murmu, Tamanna Harihar Panigrahi and Sumit Saha 13.1 Introduction 13.2 Biosensors 13.3 Nanomaterial-based biosensors 13.4 Electrochemical biosensors 13.5 Detection and monitoring of toxic gases 13.6 Conclusion Acknowledgment References

14. Nanostructured materials-modified electrochemical biosensing devices for determination of neurochemicals

287 288 291 295 300 317 317 317

331

˘ Cigdem Kanbes-Dindar, Tugrul Tolga Demirta¸s and Bengi Uslu 14.1 Introduction 14.2 The properties of some neurochemicals most commonly studied by electrochemical methods 14.3 The significance of integrating nanostructured materials for electrochemical neurochemical sensing 14.4 Application of a nanostructured electrochemical sensor for neurochemical detection 14.5 Challenges and conclusion Acknowledgment References

15. Real-time utilization of nanostructured biosensors for the determination of food toxins

331 334 336 338 355 356 356

367

Deepadarshan Urs, Anil Madesh, Karrar Mahmood, Nagaraja Sreeharsha and K.K. Dharmappa 15.1 Introduction 15.2 Types of toxins in foods 15.3 Conclusion References Further Reading

16. Nanostructured electrochemical biosensors for estimation of pharmaceutical drugs

367 369 374 376 378

379

Ersin Demir, Nida Aydogdu Ozdogan and Muharrem Olcer 16.1 Introduction 16.2 Electrochemical biosensors

379 383

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Contents

16.3 Conclusion Abbreviations References

17. Advanced nanostructured material-based biosensors in clinical and forensic diagnosis

417 418 419

429

Saima Aftab and Sevinc Kurbanoglu 17.1 Introduction 17.2 Nanostructured materials 17.3 Applications of nanobiosensors in clinical and forensic diagnosis 17.4 Conclusion References

429 431 438 447 448

18. Detection of toxic metals using nanostructured biosensing platforms

463

Raghad Alhardan, Nur Melis Kilic, Sevki Can Cevher, Saniye Soylemez, Dilek Odaci and Sevinc Kurbanoglu 18.1 18.2 18.3 18.4

Introduction Toxic metals Nanomaterials that are used as a detection platform Applications of toxic metals detection using nanostructured platforms 18.5 Conclusion References

19. Nanostructured materials-based electrochemical biosensors for hormones

463 465 469 476 486 487

505

Gnanesh Rao, Raghu Ningegowda, B.P. Nandeshwarappa, M.B. Siddesh and Sandeep Chandrashekharappa 19.1 19.2 19.3 19.4 19.5 19.6 19.7 19.8 19.9

Introduction Principle of electrochemical biosensors for detection of hormones Electrochemical detection of hormones Amino acid derivatives Adrenaline or epinephrine and noradrenaline or norepinephrine Melatonin Triiodothyronine and thyroxine Dopamine Steroids and eicosanoids

505 506 507 507 507 508 508 509 509

Contents

19.10 Testosterone 19.11 Estrogen 19.12 Cortisol 19.13 Progesterone 19.14 Calcitriol 19.15 Proteins/peptides 19.16 Adiponectin 19.17 Follicle-stimulating hormone 19.18 Human chorionic gonadotropin 19.19 Insulin 19.20 Leptin 19.21 Prolactin 19.22 Conclusion References

20. Safety, health, and regulation issues of nanostructured biosensors

xi 509 509 510 510 511 511 511 511 512 512 512 513 513 513

525

P.V. Vijayarani, P. Karpagavinayagam, B. Kavitha, N. Senthilkumar and C. Vedhi 20.1 Introduction 20.2 Biosensors 20.3 Recent development in nanostructured biosensors 20.4 Issues: safety 20.5 Issues: health 20.6 Issues: food 20.7 Issues: agriculture 20.8 Regulations 20.9 Conclusion References

21. Advances in green synthesis of nanostructured biosensors

525 526 530 532 532 533 533 535 535 536

541

Didem Nur Unal, Ipek Kucuk, Cem Erkmen and Bengi Uslu 21.1 Introduction 21.2 Fabrication of electrochemical nanobiosensors 21.3 Conclusions and future perspectives Acknowledgments References

541 547 563 565 565

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Contents

22. Future sustainability and sensitivity of nanostructured material
based electrochemical biosensors over other technologies

575

R. Rajkumar, J. Antony Rajam, P. Karpagavinayaga, M. Kavitha and C. Vedhi 22.1 Biosensor 22.2 Types of biosensors 22.3 Nanowire-based biosensors 22.4 Receptor for DNA and RNA 22.5 Receptor for viruses 22.6 Nanorod-based biosensors 22.7 Carbon nanotube
based biosensors 22.8 Carbon nanotube
modified electrodes 22.9 Nanostructured material
based electrochemical biosensor 22.10 Conclusion and future prospects References Index

575 576 577 577 577 578 579 580 582 589 590 597

List of contributors Saima Aftab Department of Chemistry, Ghazi University, Dera Ghazi Khan, Punjab, Pakistan Raghad Alhardan Faculty of Pharmacy, Department of Analytical Chemistry, Ankara University, Ankara, Türkiye Nida Aydogdu Ozdogan Faculty of Pharmacy, Department of Analytical Chemistry, Afyonkarahisar Health Sciences University, Afyonkarahisar, Türkiye Thiago C. Canevari LabNaHm: Multifunctional Hybrid Nanomaterials Laboratory, Engineering School, Universidade Presbiteriana MAckenzie, São Paulo, Brazil Sevki Can Cevher Institute of Computational Physics, Zurich University of Applied Sciences (ZHAW), Winterthur, Switzerland Sandeep Chandrashekharappa Department of Medicinal Chemistry, National Institute of Pharmaceutical Education and Research (NIPER-R), Raebareli Transit Campus, Lucknow, Uttar Pradesh, India B. Chethan Department of Physics, Indian Institute of Science, Bangalore, Karnataka, India Bruna Coldibeli Laboratory of Electroanalytical and Sensors, Department of Chemistry, Center of Exact Sciences, State University of Londrina, Londrina, Parana, Brazil Ersin Demir Faculty of Pharmacy, Department of Analytical Chemistry, Afyonkarahisar Health Sciences University, Afyonkarahisar, Türkiye ˘ Tugrul Tolga Demirta¸s Faculty of Pharmacy, Department of Basic Pharmaceutical Sciences, Erciyes University, Kayseri, Türkiye K.K. Dharmappa Inflammation Research Laboratory, Department of Studies & Research in Biochemistry, Mangalore University, Jnana Kaveri Post Graduate Campus, Kodagu, Karnataka, India Cem Erkmen Faculty of Pharmacy, Department of Analytical Chemistry, Ankara University, Ankara, Türkiye; Faculty of Science, Department of Chemistry, Hacettepe University, Ankara, Türkiye P.A. Geethanjali Department of Microbiology, Field Marshal K.M. Cariappa College, A Constituent College of Mangalore University, Madikeri, Karnataka, India

xiii

xiv

List of contributors

Mesut I¸sık Faculty of Engineering, Department of Bioengineering, Bilecik Seyh Edebali University, Bilecik, Türkiye Puneetha J. Department of Chemistry, JSS Academy of Technical Education (Affiliated to Visvesvaraya Technological University, Belgaum), Bangalore, Karnataka, India K.V. Jagannath Department of Studies in Chemistry, Central College Campus, Bengaluru City University, Bangalore, Karnataka, India S. Kalaiarasi PG and Research Department of Chemistry, A.P.C. Mahalaxmi College for Women, Thoothukudi, Tamil Nadu, India Cigdem Kanbes-Dindar Faculty of Pharmacy, Department of Analytical Chemistry, Ankara University, Ankara, Türkiye P. Karpagavinayagam Department of Chemistry, V.O. Chidambaram College, Thoothukudi, Tamil Nadu, India B. Kavitha Department of Chemistry, Sri Ranganathar Institute of Engineering and Technology, Athipalayam, Coimbatore, Tamil Nadu, India M. Kavitha Department of Chemistry, V.O. Chidambaram, Thoothukudi, Tamil Nadu, India Nur Melis Kilic Faculty of Science, Department of Biochemistry, Ege University, Bornova-Izmir, Türkiye Nagaraju Kottam Department of Chemistry, MS Ramaiah Institute of Technology (Autonomous Institute Affiliated to Visvesvaraya Technological University, Belgaum), Bangalore, Karnataka, India; Center for Advanced Materials Technology, MS Ramaiah Institute of Technology (Autonomous Institute Affiliated to Visvesvaraya Technological University, Belgaum), Bangalore, Karnataka, India Ipek Kucuk Faculty of Pharmacy, Department of Analytical Chemistry, Ankara University, Ankara, Türkiye; The Graduate School of Health Sciences, Ankara University, Ankara, Türkiye Sevinc Kurbanoglu Faculty of Pharmacy, Department of Analytical Chemistry, Ankara University, Ankara, Türkiye Kevser Kubra Kırboga Faculty of Engineering, Department of Bioengineering, Bilecik Seyh Edebali University, Bilecik, Türkiye Anil Madesh Inflammation Research Laboratory, Department of Studies & Research in Biochemistry, Mangalore University, Jnana Kaveri Post Graduate Campus, Kodagu, Karnataka, India

List of contributors

xv

Karrar Mahmood Inflammation Research Laboratory, Department of Studies & Research in Biochemistry, Mangalore University, Jnana Kaveri Post Graduate Campus, Kodagu, Karnataka, India Dipak Maity Department of Chemical Engineering, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India; Department of School of Health Sciences & Technology, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India; School of Engineering and Technology, The Assam Kaziranga University, Jorhat, Assam, India Gajiram Murmu Materials Chemistry Department, CSIR-Institute of Minerals & Materials Technology, Bhubaneswar, Odisha, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, India B.P. Nandeshwarappa Department of Studies in Chemistry, Shivagangothri, Davangere University, Davangere, Karnataka, India K. Narasimha Murthy Department of Microbiology and Biotechnology, Jnana Bharathi Campus, Bangalore University, Bangalore, Karnataka, India Raghu Ningegowda Department of Chemistry, Jyoti Nivas College Autonomous, Bangalore, Karnataka, India Dilek Odaci Faculty of Science, Department of Biochemistry, Ege University, Bornova-Izmir, Türkiye Muharrem Olcer Faculty of Pharmacy, Department of Pharmaceutical Technology, Afyonkarahisar Health Sciences University, Afyonkarahisar, Türkiye Tamanna Harihar Panigrahi Department of Chemistry, National Institute of Technology, Rourkela, Odisha, India V. Prasad Department of Physics, Indian Institute of Science, Bangalore, Karnataka, India S. Pratibha Department of Basic Science, Sri Venkateshwara College of Engineering, Affiliated to Visvesvaraya Technological University, Belagavi, Karnataka, India; Department of Physics, Sri Venkateshwara College of Engineering, Bengaluru, Affiliated to Visvesvaraya Technological University, Belagavi, Karnataka, India J. Antony Rajam Department of Chemistry, St. Mary’s College (Autonomous), Thoothukudi, Tamil Nadu, India Shashanka Rajendrachari Department of Metallurgical and Materials Engineering, Bartin University, Bartin, Türkiye R. Rajkumar Department of Chemistry, Kamaraj College, Thoothukudi, Tamil Nadu, India

xvi

List of contributors

Gnanesh Rao Department of Biochemistry, Bangalore University, Bangalore, Karnataka, India Sumit Saha Materials Chemistry Department, CSIR-Institute of Minerals & Materials Technology, Bhubaneswar, Odisha, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, India Elen Romão Sartori Laboratory of Electroanalytical and Sensors, Department of Chemistry, Center of Exact Sciences, State University of Londrina, Londrina, Parana, Brazil N. Senthilkumar PG & Research Department of Chemistry, Arignar Anna Government Arts College, Tiruvannamalai, Tamil Nadu, India M.B. Siddesh Department of Chemistry, KLE’s S. K. Arts College and H. S. K. Science Institute, Hubballi, Karnataka, India Hülya Silah Faculty of Science, Department of Chemistry, Bilecik Seyh Edebali University, Bilecik, Türkiye K. Soumya Department of Microbiology, Field Marshal K.M. Cariappa College, A Constituent College of Mangalore University, Madikeri, Karnataka, India Saniye Soylemez Faculty of Engineering, Department of Biomedical Engineering, Necmettin Erbakan University, Konya, Türkiye A. Sreeharsha Department of Pharmaceutical Sciences, College of Clinical Pharmacy, King Faisal University, Hofuf, Al-Ahsa, Saudi Arabia; Department of Pharmaceutics, Vidya Siri College of Pharmacy, Bengaluru, Karnataka, India Nagaraja Sreeharsha Department of Pharmaceutics, Vidya Siri College of Pharmacy, Bengaluru, Karnataka, India; Department of Pharmaceutical Sciences, College of Clinical Pharmacy, King Faisal University, Al Ahsa, Saudi Arabia C. Srinivas Department of Microbiology and Biotechnology, Jnana Bharathi Campus, Bangalore University, Bangalore, Karnataka, India K.H. Sudheer Kumar Department of Chemistry, B.M.S. Institute of Technology and Management, Affiliated to Visvesvaraya Technological University, Belagavi, Karnataka, India Gopavaram Sumanth Department of Medicinal Chemistry, National Institute of Pharmaceutical Education and Research (NIPER-R), Raebareli Transit Campus, Lucknow, Uttar Pradesh, India

List of contributors

xvii

A. Sunilkumar Department of Physics, Ballari Institute of Technology and Management, Ballari, Karnataka, India S. Thomas International and Inter University Centre for Nanoscience and Nanotechnology, Mahatma Gandhi University, Kottayam, Kerala, India Didem Nur Unal Faculty of Pharmacy, Department of Analytical Chemistry, Ankara University, Ankara, Türkiye; The Graduate School of Health Sciences, Ankara University, Ankara, Türkiye Deepadarshan Urs Inflammation Research Laboratory, Department of Studies & Research in Biochemistry, Mangalore University, Jnana Kaveri Post Graduate Campus, Kodagu, Karnataka, India Bengi Uslu Faculty of Pharmacy, Department of Analytical Chemistry, Ankara University, Ankara, Türkiye C. Vedhi Department of Chemistry, V.O. Chidambaram, Thoothukudi, Tamil Nadu, India P.V. Vijayarani Department of Chemistry, V.O. Chidambaram College, Thoothukudi, Tamil Nadu, India Y.B. Vinay Kumar Department of Computer Science and Engineering, R.L. Jalappa Institute of Technology and Management, Affiliated to Visvesvaraya Technological University, Belagavi, Karnataka, India Adimule Vinayak Department of Chemistry, Angadi Institute of Technology and Management, Belagavi, Karnataka, India Yashaswini Department of Physics, B.M.S. Institute of Technology and Management, Affiliated to Visvesvaraya Technological University, Belagavi, Karnataka, India

About the editor Jamballi G. Manjunatha is working as an assistant professor in chemistry at FMKMC College, a constituent college of Mangalore University, Madikeri, India. He received his PhD degree in chemistry from Kuvempu University and postdoctoral degree from the University of Kebangsaan Malaysia. He has received various awards and published more than 160 research articles in reputed international journals. He is an editor of 13 books (RSC, ACS, IOP, Elsevier, and Bentham Science Publishers) and special issues (IOP Science Publisher, Frontiers in Sensors, and MDPI). He is also an editorial board member for many reputed journals and editor-in-chief of Sensing Technology journal (Taylor and Francis).

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Preface This edited book describes the “novel nanostructured materials for biosensing applications.” At present, biosensors are the most useful device for biomedical, industrial, food, agricultural, and environmental monitoring. The chapters cover comprehensive information of new nanostructured material
based biosensors, from basic to real-time utilization. It gives a complete account of nanostructured material
based biosensors, recent innovations, practical applicability, and so on, which will be helpful for industrial sector, researchers, professors, and engineers. This book includes the modification of electrochemical biosensors with improved analytical properties and its real-world utilization has been a hot topic today. The technology of developing the biosensor devices has been increased in various fields including clinical diagnosis, food quality control, and environmental monitoring. Nanostructured materials have provided great impact as an electrode material as they hold features such as rich surface chemistry, strong absorption capacity, rapidity of response, selectivity, and robustness. The nanostructured materials provided the opportunities in creating the new innovations. Hence, they are widely used as the electrode material in various sensors. Nanostructured materials include inorganic, organic, carbon, and biomass-derived materials and composite nanostructures. As there are numerous applications, the potential of bulk and surface modification is significant in the area of modern analytical chemistry. Chemically modified biosensors have enthralled by applying different modified materials due to their characteristics of getting fast response times, amplified output, high sensitivity, and feasibility of miniaturization. Jamballi G. Manjunatha

xxi

Acknowledgments I gratefully acknowledge my sincere gratitude to my mother Sharadamma Jamballi and Professor GMH.

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PART 1

Fundamentals, current advancements in nanostructured electrochemical biosensors

CHAPTER 1

Fundamentals of nanostructured materials and synthetic routes S. Pratibha1 and Yashaswini2 1

Department of Physics, Sri Venkateshwara College of Engineering, Bengaluru, Affiliated to Visvesvaraya Technological University, Belagavi, Karnataka, India 2 Department of Physics, B.M.S. Institute of Technology and Management, Bengaluru, Affiliated to Visvesvaraya Technological University, Belagavi, Karnataka, India

1.1 Introduction 1.1.1 Nanomaterials and nanotechnology Richard Feynman first explained the term nanotechnology in his classic talk “There are plenty of rooms at the bottom” in 1961 (Feynman, 1992). The Feynman vision projects the development of nanomaterials and nanomachines with atom-by-atom control. Norio Taniguchi’s first use of the word “nanotechnology” was at the International Conference on Precision Engineering (ICPE) in 1974. His description indicated “production technology to obtain extra high precision and ultrafine dimensions, that is, accuracy and fine length of 1029 m on the order of 1 nm (nanometer)” (Whatmore, 1999). The materials whose components dimension is less than 100 nm are called nanomaterials, and they exist in the form of zero-, one-, two- and three-dimensional forms. Quantum dots, thin films, nanowires, and nanotubes are the different forms of nanomaterials. In science, nanotechnology is an important branch which deals with designing, developing, producing, and applying nanomaterials in devices. Various research-specialized fields are established, namely, nanomedication, nanobiotechnology, nano-optics, nanoelectronics, and nanosensing. The list of applications of nanomaterials and nanotechnology varies from bucket to rocket science. Interestingly, various applications attracted the researchers, as the nanomaterials possess special properties which include dust-resistant paints, sensors for humidity stabilization, and toxic gas detection sensors (Pratibha & Chethan, 2022; Pratibha et al., 2020; Pratibha, Chethan, et al., 2020). The grain size plays a major contribution in the nanomaterials exhibiting some exotic and exciting material properties. The shape, size, and dispersal of the atoms in nanomaterials also have a greater impact on the material Novel Nanostructured Materials for Electrochemical Bio-sensing Applications DOI: https://doi.org/10.1016/B978-0-443-15334-1.00001-8

© 2024 Elsevier Inc. All rights reserved.

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Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

properties (Feynman, 1992; Mishra et al., 2007; Whatmore, 1999; Vollata, 2013). The surface area and volume of the atom change in proportion to the particle’s shrinking size. Therefore the ratio of surface to volume is high; as a result, a more number of atoms are accumulated on the surface of the material. Consequently, a greater number of atoms are directly exposed to the externally induced effects which greatly affect the chemical and physical properties of the nanomaterials (Salah, 2011). Appropriate regulation of the properties and the reaction of the nanomaterials lead to novel devices and technologies. The variation in physical, chemical, and optical properties with variation in size, shape, and distribution of particles has developed the keen interest of researchers in the field of nanomaterials and their applications (Pushpanjali et al., 2020; Raril & Manjunatha, 2018). For the last three to four decades, technologists are trying to apply these nanomaterials in the field of science, technology, medical, biological, and environmental applications due to their excellent physical and chemical properties such as electrical, magnetic, thermal, optical, and mechanical properties (Amrutha et al., 2019; Charithra & Manjunatha, 2019, 2021; Hareesha et al., 2021; Manjunatha, 2019). The day-to-day applications of nanomaterials are optical telecommunications, image processing, digital memory storage, photonics, logic circuits, bio-photonic, magnetic data storage, magneto-electronic devices, biotechnology, and medicine (Begum et al., 2022; Pratibha, Chethan, et al., 2020; Pratibha et al., 2022; Pratibha & Chethan, 2022; Pratibha & Dhananjaya, 2023; Yashaswini et al., 2021). Also, flat-panel displays with low-energy excitation sources, cathode ray tubes, bio-labeling, solar energy converters, optical amplifiers, as catalysts, thermoluminescence dosimeter (TLD), phosphors, sensors, coating materials and miniaturization of devices, limiting the emission of pollutants, cleaning up contaminants in soil and water, sunscreen lotions, automotive, etc., are some of the major appliactions of nanomaterials. (Ditcovski et al., 2010; Lakshminarasimhan & Varadaraju, 2008; Rodriguez-Viejo et al., 1997; Shea., 1998; Snyders et al., 2006; Yang et al., 1998). The inorganic nanomaterials, like semiconductors, insulators, polymers, composites, etc., exhibit fascinating size- and shape-dependent properties like high crystallinity, conductivity, structural constancy, prominent luminescence, lower melting, and boiling point because of their quantum confinement effect (McKittrick et al., 1999). Therefore the sizeand shape-dependent properties of the nanomaterials have made the researchers think about the development/preparation of the nanomaterials.

Fundamentals of nanostructured materials and synthetic routes

5

Nanomaterials possess two major properties: • Size impact: The bulk material has continuous energy levels (extended periodicity of lattice) that will get altered by a set of distinct energy levels (quantum confinement effect). • The surface/interface-generated effects: The ratio between surface and volume gets increased as the dimensions get reduced leading to the availability of a significant number of atoms on the surface with different chemical environments compared to the bulk material. The surface plasma resonance (SPR) phenomenon allows the metallic NPs to reveal the size-dependent optical properties same as that of semiconducting quantum dots (QDs). This effect is because of the mutual oscillations of the conduction band electrons and further protuberant in the case of noble metals Ag and Au NPs (Barnes et al., 2003). The incident light excites the electrons, and the related oscillations interact with the electromagnetic radiations producing an improved electromagnetic field leading to the scattering and absorption of light (Klabunde & Richards, 2009).

1.2 Classification of nanoparticles Nanomaterials are classified into various types based on their morphology, size, and chemical and physical properties. Carbon-based nanomaterials, polymeric nanomaterials, metal nanoparticles, semiconductor nanomaterials, ceramic nanomaterials, and others are just a handful of them. The inorganic solids that make up ceramic nanomaterials are oxides, carbonates, phosphates, carbides, and other compounds. These nanoparticles have high thermal resistance and chemical inertness (Prinith et al., 2019). The classification of nanoparticles based on their size, shape, composition, and surface properties, which can affect their properties and applications, is briefed as follows: 1. Size-based classification: Nanoparticles can be classified based on their size, typically into the following categories: • Ultrafine particles or nanoparticles (between 1 and 100 nm), • Nanocrystals (between 2 and 100 nm), and • Nanoclusters or quantum dots (between 2 and 10 nm). 2. Shape-based classification: Nanoparticles can be classified based on their shape, which can affect their properties and applications. Some common shapes include: • Triangular nanoparticles,

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Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

• • • • 3.

Octahedral nanoparticles, Rod-shaped nanoparticles, Spherical nanoparticles, and Cube-shaped nanoparticles. Composition-based classification: Nanoparticles can be classified based on their composition, which can affect their properties and applications. Some common types of nanoparticles include: • Carbon nanoparticles (e.g., fullerenes, carbon nanotubes), • Magnetic nanoparticles (e.g., iron oxide), • Semiconductor nanoparticles (e.g., quantum dots), and • Metal nanoparticles (e.g., gold, silver, platinum). 4. Surface-based classification: Nanoparticles can also be classified based on their surface properties, such as their charge or functional groups. This can affect their interaction with biological systems and their ability to bind to specific molecules. Some examples include: • Anionic nanoparticles (negatively charged), • Cationic nanoparticles (positively charged), • Functionalized nanoparticles (with specific functional groups), and • Neutral nanoparticles.

1.3 Synthesis of nanoparticles As discussed earlier, nanoparticles are extremely small particles, measured in nanometers (nm). One nanometer (1 nm 5 1029 m) is one billionth of a meter. They can be found in both natural and artificial forms. They are bigger than atoms but smaller than solid particles. As a result, they exhibit Brownian motion rather than following quantum theory. They have uses in a variety of fields, including pharmaceuticals, catalysis, engineering, environmental remediation, industrial manufacture, etc. (Hasan, 2015; Khan et al., 2019; Liu, 2006; Manjunatha, Nagabhushana, Adarsha, et al., 2019; Manjunatha, Nagabhushana, Raghu, et al., 2019; Saravanan et al., 2021), due to their small size and huge surface area. Nanoparticles are complex in nature and are mainly constituted of three layers: • The core layer: This is the most important and fundamental component of the nanoparticle and exhibits all of its exceptional characteristics. • The shell layer: This sandwiched layer, unlike the core, is composed of separate chemical constituents.

Fundamentals of nanostructured materials and synthetic routes

7

•

The surface layer: This is the top layer, can function in the presence of polymers, metal ions, and tiny molecules, and is the layer that is most exposed. The primary factor determining a nanomaterials’ physical characteristics and potential uses is its fabrication process. So picking the appropriate synthetic pathway for designing nanomaterials is what motivates many of the recently developing methodologies. This sparked the creation of numerous adaptable and effective techniques for making nanomaterials. When using different techniques to create nanoparticles, there are two basic strategies that are used. Fig. 1.1 explains the two synthesis techniques.

1.4 Top-down approach Top-down approaches involve the reduction of bulk materials into nanoparticles using mechanical, chemical, or thermal methods. The mechanical-physical particle manufacturing process is another name for this technique. In this technique, a large particle is crushed into smaller particles that can be used as nanoparticles by applying a lot of force. These top-down methods often produce nanoparticles with a wide size distribution and limited control over particle shape. For example, ball milling, crushing, grinding, milling, lithographic cutting methods, chemical vapor deposition, and physical vapor deposition can all be used to achieve this. The creation of ceramic and metal-based nanoparticles is accomplished using this method.

Figure 1.1 Approaches involved in nanoparticle synthesis. Strategies used in different techniques of nanoparticle synthesis.

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1.5 Bottom-up approach The building-up process is another name for this approach. This process involves creating larger particles from smaller particles, such as atoms, molecules, and nanoparticles. This is based on the creation of a complex particle through the assembly of a number of tiny particles. This approach often involves the use of chemical or physical methods to control the size, shape, and composition of the nanoparticles. Common bottom-up methods including spinning, chemical vapor deposition, sol
gel synthesis, electrochemical synthesis, and biological synthesis can all be used to accomplish this. Nanoparticles produced using green and biological processes are economical and environmentally beneficial. Metal oxide nanoparticles and metal nanospheres are made using this method. Table 1.1 briefs about different examples of nanoparticles prepared using different methods. According to the literature, metal ion interaction kinetics and adsorption processes have a significant impact on various morphological features, such as size, shape, and stability. In order to build or scale up a new synthesis method, it is now important to do so by manipulating the physicochemical parameters. There are numerous approaches to creating nanoparticles. A few of the numerous synthesis techniques which are most preferred by the researchers are discussed as shown in Fig. 1.2. Also, the synthesis of nanoparticles is classified into two types based on the medium used while preparing nanoparticles. Table 1.1 Classes of the nanoparticles synthesized from the several procedures. Approach

Technique

Nanoparticles

Bottomup

Sol
gel

Carbon, metal, and metal oxide based Organic polymers Carbon and metal based

Spinning Chemical vapor deposition (CVD) Pyrolysis Biosynthesis Topdown

Mechanical milling Nanolithography Laser ablation Sputtering Thermal decomposition

Carbon and metal oxide based Organic polymers and metal based Metal, oxide, and polymer based Metal based Carbon and metal oxide based Metal based Carbon and metal oxide based

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Figure 1.2 Nanoparticle synthesis methods. Different methods of synthesis.

1.5.1 Wet chemical methods Wet chemical methods are a common and widely used approach for synthesizing nanoparticles. These methods involve the use of a liquid medium, typically water or an organic solvent, to dissolve or disperse the precursor materials and induce nucleation and growth of nanoparticles. Here are some examples of wet chemical methods. 1.5.1.1 Sol
gel process A bottom-up strategy is employed in the sol
gel process, a technique for creating colloidal nanoparticles. This method involves the preparation of a solution of metal salts, which is then hydrolyzed to form a gel. The gel is then heated to form nanoparticles. This method is versatile and can be used for various materials. The sol
gel method involves the preparation of a sol (a colloidal suspension of nanoparticles in a liquid) followed by gelation to form a three-dimensional network. The gel is then dried and calcined to form nanoparticles. Alkoxides and alkoxysilanes must be used as metal ion precursors in order to do this. Tetramethoxysilane (TMOS) and tetraethoxysilane (TEOS) are the two precursors that are utilized the most frequently. This method is particularly useful for producing ceramics, glasses, and metal oxides. It has many uses, including the manufacturing of injectable nanocomposites like plasminogen activator entrapped in alumina, protective nanoparticle coatings, optical and refractory ceramic fiber fabrication, nanoscale powders, and sintered ceramic nanomaterials (Bokov et al., 2021).

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1.5.1.2 Solution combustion synthesis Solution combustion synthesis (SCS) is an important technique for the synthesis and processing of nanomaterials. It is an exothermic reduction and oxidation reaction involving an oxidizer and a fuel in a controlled way. At a very high temperature, the reaction occurs by ejecting huge heat making the reaction system self-sustained (Pratibha et al., 2023). It is the more economical, easy, and relatively fast phenomenon of preparing highly phase pure nanopowders involving comparatively simple instruments than other methods. The stoichiometry, structural composition, and homogeneity of the end products are controllable. Also, it is easy to scale up the yield. The limitations of the SCS method include the agglomerated end products, the enormous release of toxic gases during the usage of organic fuels, and the poor control over the exothermic reaction the explosion may occur. Different parameters, such as water content, fuel, the release of gaseous products, and flame temperature during the combustion process influence the SCS reaction (Pratibha et al., n.d.; Pratibha, Chethan, et al., 2020; Pratibha et al., 2020a, 2020b; Pratibha et al., 2019, 2020a, 2022). 1.5.1.3 Green and biological synthesis Emerging methods for more efficient nanoparticle production should be less expensive, easier to make, and environmentally benign. Therefore biosynthesis and green synthesis are the preferable manufacturing methods for them. Plants and plant extracts appear to be a decent alternative among all the biological options because they are readily available, needless upkeep, and are less expensive to produce. This method of synthesis involves the use of natural resources such as plant extracts, microorganisms, enzymes, microbes, protists, and algae as biological agents that can be exploited to synthesize nanoparticles. The size and shape of the nanoparticles can be controlled by adjusting the reaction conditions, such as pH and temperature. This method is eco-friendly, cost-effective, and does not require toxic chemicals. This process involves mixing a metal salt with plant extract and letting it sit for a few hours at room temperature. This causes the metal salt to dissolve into the appropriate nanoparticles. Green synthesis can produce nanoparticles with a wide range of sizes and shapes, and the properties of the nanoparticles can be tailored by selecting different natural resources with lower purity or control over size and shape (Begum et al., 2022; Kumar et al., 2022; Pratibha et al., 2020).

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1.5.1.4 Solvothermal/hydrothermal method This method involves heating a precursor solution in a sealed vessel at high temperature and pressure, inducing rapid nucleation and growth of nanoparticles. The size and shape of the nanoparticles can be controlled by adjusting the reaction conditions, such as solvent type, temperature, and pressure. The solvent’s boiling point is raised by the pressure that is created in the vessel as a result of solvent vapors. Solvents including ethanol, toluene, water, and other substances are frequently used in solvothermal processes. Water pressure, temperature, reaction time, precursors, and other variables can be changed during the synthesis of nanocrystals to maintain a high nucleation rate that results in the creation of particles with a homogeneous size distribution. The high temperature, high pressure created during the reaction, and lack of flexibility for managing the nucleation and growth processes are the key drawbacks of this approach. This method can produce nanoparticles with high purity and controlled size but may require specialized equipment (Liu et al., 2022). 1.5.1.5 Chemical reduction In this method, metal ions are reduced to form nanoparticles using a reducing agent. This method is simple, but it may require toxic chemicals. Chemical reduction is one of the most commonly used methods for synthesizing metal nanoparticles. In this method, a reducing agent is added to a solution of metal ions to reduce them to form nanoparticles. The size and shape of the nanoparticles can be controlled by adjusting the concentration of the reducing agent, the pH of the solution, and the reaction time (Daruich De Souza et al., 2019). 1.5.1.6 Electrochemical synthesis In this method, metal ions are reduced at the surface of an electrode to form nanoparticles. This method is simple and can produce a large quantity of nanoparticles. Electrochemical synthesis involves the use of an electric current to reduce metal ions at the surface of an electrode to form nanoparticles. The size and shape of the nanoparticles can be controlled by adjusting the potential, current, and pH of the electrolyte (Yan et al., 2021). 1.5.1.7 Microemulsion method In this method, a microemulsion of water, oil, and surfactant is used to form nanoparticles. This method is useful for producing nanoparticles with a narrow size distribution. The microemulsion method involves the

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use of a microemulsion, which is a stable, transparent, and isotropic liquid system consisting of water, oil, and surfactant. The microemulsion acts as a reaction medium for the synthesis of nanoparticles. This method can produce nanoparticles with narrow size distribution and high stability (Rodríguez-Rodríguez et al., 2019). 1.5.1.8 Microwave-assisted synthesis This method involves using microwave radiation to heat a reaction mixture and induce rapid nucleation and growth of nanoparticles. The size and shape of the nanoparticles can be controlled by adjusting the microwave power and reaction time. This method is relatively fast and efficient but may require specialized equipment (Kheradmandfard et al., 2021). 1.5.1.9 Emulsion polymerization This method involves dispersing monomer droplets in an aqueous medium containing a surfactant and initiator, which are then polymerized to form nanoparticles. The size and shape of the nanoparticles can be controlled by adjusting the monomer concentration and reaction conditions. This method can produce nanoparticles with high purity and controlled size but may require specialized equipment (Jenjob et al., 2019).

1.5.2 Dry chemical methods Dry methods are another group of techniques for synthesizing nanoparticles. These methods do not involve a liquid medium and instead rely on gas-phase reactions or solid-state reactions to form nanoparticles. Here are some examples of dry methods. 1.5.2.1 Mechanical grinding/ball milling The mechanical milling method is a top-down strategy where large structural particles are broken down into coarse particles using grinders. It involves milling a mixture of precursor powders in a ball mill to induce solid-state reactions that form nanoparticles. The size and shape of the nanoparticles can be controlled by adjusting the milling parameters, such as ball size, milling speed, and reaction time. This method can produce nanoparticles with high purity and controlled size but may require long milling times. Mechanical, thermal, and centrifugal forces are all used in this process. This technique produces broad-sized nanoparticles with sizes between 10 and 1000 nm. They are used to create bulk materials with nanoscale grains and nanocomposites. For this procedure, a variety of mills

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are available, including vibrating ball mills, attrition mills, planetary ball mills, high-energy mills, and mills that use low levels of energy (Krishna. & Patel, 2019). 1.5.2.2 Laser ablation A high-beam laser is used in the laser ablation process to remove layers of solid metals. The metal surface is exposed to radiation by the laser beam, which irradiates it. It also employs the top-down method, which entails utilizing a laser beam to vaporize the metal’s surface. The wavelength, intensity, and pulse length of the laser beam all affect how things break down (Rafique et al., 2019). 1.5.2.3 Electro-explosion Another top-down strategy is electro-explosion, which involves passing a strong pulsed current over a thin metal wire, which causes the metal ions in the wire to explode. Using a pulsed discharge mechanism, a significant quantity of heat is transferred into the wire, melting the metal ions and ionizing them. Basically, this process is utilized to make metallic nanopowders. Electrochemical synthesis involves the reduction of metal ions at the surface of an electrode to form nanoparticles (Hashemzadeh et al., 2020). 1.5.2.4 Chemical vapor deposition Solid metal is deposited on another hot metal surface utilizing a separate chemical reaction in the vapor or gas phase in a process known as chemical vapor deposition (CVD), which is a bottom-up method. CVD involves the decomposition of a precursor gas to form nanoparticles on a substrate. This process needs extra activation energy to start the chemical reaction, which a high temperature (1000°C) can deliver. A gas supply system, a deposition chamber, and an exhaust system make up the bulk of the CVD device. In the creation of nanocomposites, CVD is useful (Saeed et al., 2020). 1.5.2.5 Physical vapor deposition Physical vapor deposition (PVD) involves the evaporation of metal atoms in a vacuum, which then condenses on a substrate to form nanoparticles. This method is useful for producing nanoparticles with controlled size and shape. PVD involves the use of high-energy physical processes such as thermal evaporation, sputtering, or laser ablation to deposit metal atoms onto a substrate to form nanoparticles. This method can produce

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nanoparticles with a narrow size distribution and precise control over the shape and composition of the nanoparticles (Jamkhande et al., 2019). 1.5.2.6 Solvent-free synthesis This method involves mixing dry precursor powders and inducing solidstate reactions to form nanoparticles. The size and shape of the nanoparticles can be controlled by adjusting the reaction conditions, such as temperature and pressure. This method can be used to synthesize a wide range of materials, including metals, oxides, and sulfides. The process typically involves mixing dry precursor powders and heating the mixture to induce solid-state reactions. The temperature, pressure, and duration of the reaction can be controlled to produce nanoparticles of different sizes and shapes. Solvent-free synthesis can be a cost-effective method for large-scale nanoparticle production (Landge et al., 2018). 1.5.2.7 Photochemical synthesis This method involves using light to induce chemical reactions that form nanoparticles. The size and shape of the nanoparticles can be controlled by adjusting the light intensity and wavelength, as well as the reaction conditions. This method can produce nanoparticles with high purity and controlled size but may require expensive light sources (Jara et al., 2021). 1.5.2.8 Ion implantation This method involves using ion beams to implant atoms or ions into a substrate material, forming nanoparticles in the substrate. The size and shape of the nanoparticles can be controlled by adjusting the ion energy and implantation dose. This method can produce nanoparticles with unique properties but may require specialized equipment (Stepanov, 2010). 1.5.2.9 Flame spray synthesis This method involves spraying a precursor solution into a hightemperature flame, causing rapid nucleation and growth of nanoparticles. The size and shape of the nanoparticles can be controlled by adjusting the spray conditions, precursor concentration, furnace, and flame temperature. This method can produce nanoparticles with high purity and controlled size but may require specialized equipment (De Iuliis et al., 2019).

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1.5.2.10 Electrospinning This method involves spinning a polymer solution through an electric field to form nanofibers, which can then be processed into nanoparticles. The size and shape of the nanoparticles can be controlled by adjusting the spinning parameters, such as solution concentration and electric field strength. This method can produce nanoparticles with unique properties but may require specialized equipment. Dry methods offer several advantages over wet chemical methods, including higher purity and control over nanoparticle morphology. However, they may require specialized equipment and may be limited in the types of materials that can be synthesized. Additionally, dry methods are often more expensive than wet methods due to the cost of equipment and energy consumption (Zhang & Yu, 2014).

1.6 Conclusion In summary, there are many methods for synthesizing nanoparticles, each with its advantages and disadvantages which involves a combination of topdown and bottom-up approaches to control the size, shape, and composition of nanoparticles. The choice of method depends on the desired properties such as surface chemistry and stability of the nanoparticles, as well as practical considerations like cost, scalability, and environmental impact.

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1603. Available from https://doi.org/10.1016/j.jeurceramsoc.2005.03.237. Stepanov, A. L. (2010). Synthesis of silver nanoparticles in dielectric matrix by ion implantation: A review. Reviews on Advanced Materials Science, 26(1
2), 1
29. Available from: http://www.ipme.ru/e-journals/RAMS/no_12610/stepanov.pdf. Vollata, D. (2013). Nanomaterials: An introduction to synthesis, properties and applications (2nd Ed). Wiley-VCH Verlag GmbH & Co. KGaA. Whatmore, R. W. (1999). Ferroelectrics, microsystems and nanotechnology. Ferroelectrics, 225(1), 179
192. Yan, K., Xu, F., Wei, W., Yang, C., Wang, D., & Shi, X. (2021). Electrochemical synthesis of chitosan/silver nanoparticles multilayer hydrogel coating with pH-dependent controlled release capability and antibacterial property. Colloids and Surfaces B: Biointerfaces, 202111711. Available from https://doi.org/10.1016/j.colsurfb.2021.111711. Yang, S., Stoffers, C., Zhang, F., Jacobsen, S. M., Wagner, B. K., Summers, C. J., & Yocom, N. (1998). Green phosphor for low-voltage cathodoluminescent applications: SrGa2S4:Eu2. Applied Physics Letters, 72(2), 158
160. Available from https://doi.org/ 10.1063/1.120674. Yashaswini, D. K., Pratibha, S., Lokesh, R., Dhananjaya, N., & Pandurangappa, C. (2021). Disaccharide assisted LaAlO3: Ce3 1 perovskite: Structural and optical studies suitable for display devices. Inorganic Chemistry Communications, 123. Zhang, C.-L., & Yu, S.-H. (2014). Nanoparticles meet electrospinning: Recent advances and future prospects. Chemical Society Reviews, 43(13), 4423. Available from https:// doi.org/10.1039/c3cs60426h.

CHAPTER 2

Modern trends in carbon nanostructured material-based electrochemical biosensing systems Puneetha J.1, Nagaraju Kottam2,3 and Shashanka Rajendrachari4 1

Department of Chemistry, JSS Academy of Technical Education (Affiliated to Visvesvaraya Technological University, Belgaum), Bangalore, Karnataka, India 2 Department of Chemistry, MS Ramaiah Institute of Technology (Autonomous Institute Affiliated to Visvesvaraya Technological University, Belgaum), Bangalore, Karnataka, India 3 Center for Advanced Materials Technology, MS Ramaiah Institute of Technology (Autonomous Institute Affiliated to Visvesvaraya Technological University, Belgaum), Bangalore, Karnataka, India 4 Department of Metallurgical and Materials Engineering, Bartin University, Bartin, Türkiye

2.1 Introduction Electrochemical analysis, in comparison with other disclosure approaches such as chromatography, luminescence, and spectroscopy, is a simple and profitable approach with advantages in terms of usability, precision, and steadiness for determining the amounts of electroactive species in a solution, both quantitatively and qualitatively. Analytical methods engaged include cyclic voltammetry, differential pulse voltammetry, chronoamperometry, linear sweep voltammetry, and stripping voltammetry. They are completely useful electroanalytical procedures when they have been refined for the best electrochemical response. The type of the analyte held down examination, the kind of electrode utilized, and the electrolyte employed can all influence these processes. The area and structure of the electrode, as well as the method of fabricating, can affect the system’s voltammetric response. Electroanalysis processes take into account the chemical-physical properties of electrode surfaces, as well as the consequence of the exerted potential, adsorption, and coverings utilized to the electrode surface to improve sensing. Carbon compounds are often accustomed to electroanalytical inspection due to their chemical passivity, comparatively vast potential window, poor background current, and adaptability for diverse modes of evaluation. Other electrode constituents, such Novel Nanostructured Materials for Electrochemical Bio-sensing Applications DOI: https://doi.org/10.1016/B978-0-443-15334-1.00002-X

© 2024 Elsevier Inc. All rights reserved.

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Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

as sprayed metal electrodes, have shorter potential windows and lifetimes than carbon electrodes (Chauhan et al., 2017; Baranwal & Chandra, 2018).

2.2 Neurotransmitters, neurochemicals as biomolecules Biological beings are made up of a variety of macromolecules and small molecules. Micromolecules include metabolites, fatty acids, neurotransmitters, amino acids, vitamins, and hormones, while supermolecules include proteins, carbohydrates, nucleic acids, and enzymes. Biomolecule research contributes to a better understanding of their basic physiological functions in the human body’s healthy growth and development. Endogenous and exogenous biomolecules are involved in a wide range of biological practices, including loading and diffusing genomic evidence, controlling biological/neurological activity, conveying lesser molecules/hormones, and catalyzing biochemical reactions. Neurotransmitters are endogenous chemical messengers that operate as signal transducers between neurons and nonneuronal somatic cells, allowing information to travel all over the brain and body via chemical synapses. These vital substances are generated by several secretors, including the pituitary, pineal, and adrenal glands. Before clumping together at neuronal terminals, NTs are naturally maintained in vesicles. NTs are released from synapses and proceed over the festering gap, where they join to acceptors on the surface of neighboring neurons or cells, activating them. As a result, the neurite end of the other neuron is activated, similarly releasing NTs in order to form a connection with the following neuron. As a result, neurons respond biologically, setting off a complex cascade of events (Mele et al., 2010). The first neurotransmitter was discovered in 1921, and myriads of chemical transporters involved in colligation communication were discovered after that. Among the several NTs, biogenic amines such as dopamine, epinephrine, norepinephrine, and serotonin, as well as amino acids such as tyrosine and acetylcholine, may play a role. Essential nervous system functions such as behavior and cognition were mediated by NTs. They control and regulate muscle tone, heart rate, slumbering, understanding, cognizance, rumination, appetite, and temperament (Baranwal & Chandra, 2018). Changes in NTs amounts in the central nervous system (CNS) have been linked to Alzheimer’s, Huntington’s, and Parkinson’s disorders, as well

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as schizophrenia, epilepsy, arrhythmias, congestive heart failure, glaucoma, thyroid hormone deficiency, sudden infant death syndrome (SIDS), anxiety, and depression. Because extracellular quantities of neurotransmitters are low and concentrations can change quickly, in vivo measurements are difficult (Kurian et al., 2011). Many other electroactive neurochemicals, in addition to neurotransponders, exist in the brain and can intrude with neurotransmitter investigation. As a result, quantifying NTs concentrations in human fluids is crucial for diagnosis, disease monitoring, and therapeutic interventions. Some of the most common methods for determining the NT concentrations include fluorimetry, chemiluminescence, chromatography, mass spectrometry (MS), and capillary electrophoresis (CE). The majority of the treatments discussed have been demonstrated to be time-consuming and exorbitant, with complex pretreatment steps; yet, they have strong sensibility and specificity, as well as low limit of detection (LOD). Furthermore, for on-site monitoring studies, these solutions are ineffective. Electrochemical detectors are propitious for surveilling neurotransmitters or neurochemicals because they provide great selectivity and fast responsiveness, as well as high precision and reproducibility. They also provide a broad array of linear reactions, little sensing limitations, and apparent time assessment that produce data quickly, as well as the ability to detect two or more chemicals at the same time. Furthermore, in therapeutic and diagnostic research, this type of sensor can be used for on-spot determination and can be incorporated with powerful, handy, or microscopic tools. Beyond CNTs, the latest study gained concentration on employing a variety of novel forms of carbon nanostructured materials. Reduced graphene oxide, carbon nanohorns, graphene nanofoams, graphene nanorods, and graphene nanoflowers, as well as crystalline diamond and diamondlike carbon, are nowadays progressively popular for sensors. Carbon nanostructures, including graphene, have outstanding electrochemical properties, leading to their widespread use. The unique carbon-derived nanostructures have features not present in bulk materials; therefore, their potential in sensing applications is clear. As a result, they can operate with greater sensitivity and selectivity across a larger temperature and dynamic range, not just in harsh environments. Previously, a range of materials, including platinum, gold, and several types of metals, have been utilized as electrode materials for electrochemical sensing (Dresselhaus et al., 2004; Wang & Liu, 2012). In the recent years, carbon polymorphs including graphene, carbon nanotube, and diamond have become popular as

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Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

electrode materials for electrochemical sensing. The analytes in this chapter included neurotransmitters and neurochemicals including dopamine, ascorbic acid, and serotonin, as well as hydrogen peroxide, proteins like biomarkers, and DNA.

2.2.1 Carbon nanotubes Formerly, Sumio Iijima has discovered carbon nanotubes (CNTs) in 1991 (Ko et al., 2006; Brian, 1991). CNTs are graphene cylinders that have been folded up. The number of cylinders stacked into each other, as well as the specific sp2 hybridized carbon lattice, governs their properties (Mele et al., 2010). Single-walled carbon nanotubes (SWNTs) and multiwalled carbon nanotubes (MWNTs) are two structural types of CNTs that have usages in a variety of areas, including composite materials, nanoelectronics, energy research, and biomedicine. CNTs have photosensitive and electrical features that make them ideal for detecting biomolecules. SWNTs exhibit semiconducting properties and resonant Raman scattering, creating them ideal for application as biosensor nanoprobes. SWNTs can operate as transistors; in this scenario, the particles that fix to the nanotubes’ surfaces act as gating molecules, changing the conductance of semiconducting SWNTs. As an amperometric biosensor, MWNTs grown on a platinum substrate were employed. CNTs are an intriguing class of 1D NMs that have been intensively studied in biosensors, prognosis, tissue technology, cell tracing, and labeling, delivering a drug, and natural molecules. Manjunatha et al., reported that, through an electrochemical oxidation process, a novel modified multiwall carbon nanotube paste electrode with sodium dodecyl sulfate as a surfactant (SDS) was created. Using cyclic voltammetry (CV) and differential voltammetry (DPV), this electrode was used to electrochemically detect dopamine (DA), ascorbic acid (AA), uric acid (UA), and their mixture (Manjunatha et al., 2014). Motsaathebe and Fayemi stated that detection of serotonin (5-HT) in tomatoes was made using MWCNT-AONP nanocomposite on screenprinted carbon electrodes (SPCEs) to detect. When compared to other electrodes investigated, the SPCE-MWCNT-AONP-modified electrodes demonstrated superior electronic conductivity and improved current approach whenever it pertained to detect 5-HT. SPCE-MWCNTAONP (84.13μA) . SPCE-fMWCNTs (33.49 μA) . SPCE-AONPs (24.40 μA) . SPCE-bare (2.89 μA) was the current response. Employing SWV, the sensitivity, limit of detection (LOD), and limit of quantification

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(LoQ) for the SPCE-MWCNT-AONP-modified electrode toward 5-HT detection were 0.2863 μA μM21, 24.6, and 74 nM, respectively, with linearity from 0.016 to 0.166 μM (R2 5 0.9851). The observed LOD value for the envisaged sensor was superior to that of other chemically altered electrodes reported in the literature. Additionally, the proposed sensor showed an excellent consistency and anti-interference performance. The average RSD (percent) value of 2.57 (n 5 3) was found in real-sample analysis of 5-HT in tomatoes, with recoveries ranging from 91.32% to 108.28%. The studies clearly indicate that the suggested new sensor can be used to diagnose and treat diseases at the point of care (Motsaathebe & Fayemi, 2021). The very first carbon nanotube paste electrode for cyclic voltammetric dopamine detection was developed by Britto et al., (1996). Carbon nanotube (CNT) yarn electrodes have also been developed for in vivo neurochemical detection. A CNT yarn is a CNT macrostructure made up of several parallel CNT filaments. Carbon nanotube filaments and yarns have also been made via electrospinning. Carbon nanotube filaments and yarns have also been made via electrospinning (Ko et al., 2006). Schmidt et al. employed FSCV to create CNT yarn disk-shaped (CNTy-D) electrodes for electroactive neurotransmitter detection (Schmidt et al., 2013). Tigari & Manjunatha reported a novel sensor fabrication using anionic surfactant sodium lauryl sulfate-modified carbon nanotube and pencil graphite composite paste electrode (SLSMCNTPGCPE shows a linear current response to a diverse concentration of RF in 0.2
0.8 and 1
5 μM with a low detection limit of 1.16 3 10
8 M by applying differential pulse voltammetry (DPV)) (Tigari & Manjunatha, 2020). The EPPGE-SWCNT composite was manufactured by Adekunle et al., and the EPPGE-SWCNT-Fe electrode was created by electrochemical deposition of Fe NPs. The DA detection response of EPPGESWCNT-Fe2O3 was sevenfold higher than that of bare EPPGE and twofold higher than that of EPPGE-SWCNT. DA had a sensitivity of 3.44 μA μM21 and a LOD of 0.36 μM21. Bala et al., looked into the electrocatalytic properties of Fe3O4, ZnO NPs doped with phthalocyanine (PC) and 2,3-naphthalocyanine (Nc) functionalized MWCNTs placed on GCE. MWCNT/Fe3O4/2,3-Nc-, MWCNT/Fe3O4/29 H,31HPc-, MWCNT/ZnO/2,3-Nc-, and MWCNT/ZnO/29 H,31H-Pc-modified electrodes had corresponding LODs of 1.77, 1.35, 2.34, and 0.75 μM, respectively. The MWCNT/ZnO/29 H, 31H-Pc-modified electrode has the lowest LOD for DA, as can be observed from the results. The better

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Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

electron accepting capacity of 29 H, 31H-PC than 2,3-Nc in facilitating electrochemical oxidation of DA could be related to its higher vulnerability and lower unfilled energy level (Bala et al., 2019). The effectiveness of high density carbon nanotube fiber (HD-CNTf) transverse sections called rods (diameter B69 μm and length B40 μm) as an extremely sensitive substrate for the screening of typical neurotransmitters was reported by Gupta et al., The open-end CNTs of HD-CNTf rods microelectrodes are accessible at the interface with electrolytes and cells, and they have a low resistance value of 1050 Ω. Dry-spun CNT fibers were wrapped in an insulated polymer to retain inherent morphology and orientation during the manufacturing process. Employing square wave voltammetry (SWV) and cyclic voltammetry, the researchers used the clusters of HD-CNTf rod microelectrode to detect neurotransmitters such as dopamine (DA), serotonin (5-HT), epinephrine (Epn), and norepinephrine (Nor-epn) (CV). They display strong linearity across a wide linear range (1 nM to 100 M) and have a high limit of detection (32, 31, 64, and 9 pM for DA, 5-HT, Epn, and Nor-epn, respectively) (Gupta et al., 2020). They exhibit positive linearity over a wide linear range (1 nM to 100 μM) and have a high limit of detection (32, 31, 64, and 9 pM, respectively) for DA, 5HT, Epn, and Nor-epn. The detection of DA in human bodily fluids and real-time tracking of dopamine release via living pheochromocytoma (PC12) cells were performed to illustrate the practicability of HD-CNTf rod arrays (Gupta et al., 2020). Kruss et al., reported that application of a new technique, corona phase molecular recognition (CoPhMoRe), to identify adsorbed polymer phases on fluorescent single-walled carbon nanotubes (SWCNTs) that allow for the selective detection of specific neurotransmitters, including dopamine. They functionalized and suspended SWCNTs with a library of different polymers (n 5 30) containing phospholipids, nucleic acids, and amphiphilic polymers to study how neurotransmitters modulate the resulting band gap, near-infrared (nIR) fluorescence of the SWCNT. We identified several corona phases that enable the selective detection of neurotransmitters. Catecholamines such as dopamine increased the fluorescence of specific single-stranded DNA- and RNA-wrapped SWCNTs by 58% 2 80% upon addition of 100 μM dopamine depending on the SWCNT chirality (n,m). In solution, the limit of detection was 11 nM [Kd 5 433 nM for (GT)15 DNA-wrapped SWCNTs] (Kruss et al., 2014). Chang et al., created composite electrodes with a portion of carbon nanotubes (CNTs) exposed to the sample and the rest encapsulated in

Material-based electrochemical biosensing systems

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polymer micropillars and the sensor base. In a 7-day impedance test, the partial implantation arrangement, in combination with the microchannel array design, offers the electrodes with a persistent coating and minimal conductivity loss. After a 2-hour fouling experiment, cyclic voltammetric investigations demonstrated that dopamine behaves in a quasireversible manner, with a signal retention of 93%. It has a detection limit of 0.77 nM, a quantitative limit of 2.34 nM, and a sensitivity of 0.453 nA nM21 when measuring dopamine using differential pulse voltammetry (DPV). When detecting dopamine with and without extra uric acid, ascorbic acid, or glucose, all of which are frequent interfering bioactive substances, clearly differentiated DPV peaks were found (Chang et al., 2021). For the first time, Yang et al., produced carbon nanotubes on niobium substrates. Instead of using a flat metal surface, metal wires with a width of only 25 μm were employed as CNT substrates, which have the potential to be used in tissue applications due to their little tissue damage and good spatial resolution. After chemical vapor deposition, aligned CNTs are produced on metal wires, as seen by scanning electron microscopy. CNT-coated niobium (CNT-Nb) microelectrodes have a higher precision and lesser ΔEp value than CNTs grown on carbon fibers or other metal wires, according to fast-scan cyclic voltammetry. CNT-Nb microelectrodes have a detection range for dopamine of 11 6 1 nM, which is about two times lower than naked CFMEs. Adsorption processes were simulated using a Langmuir isotherm, and other neurochemicals such as ascorbic acid, DOPAC, serotonin, adenosine, and histamine were observed. With great sensitivity, CNT-Nb microelectrodes were performed to analyze induced dopamine release in anaesthetized rats. This research shows that CNT-grown metal microelectrodes, particularly CNTs grown on Nb microelectrodes, are beneficial for neurotransmitter monitoring (Yang et al., 2016). The increased current responsiveness of the modified electrode to DA and AP was attributed to its significant adsorptive ability, high aspect ratio, and unique structure of the MWCNT (125 mV peak difference). The MWCNT-modified GCE yielded LODs of 0.8 and 0.6 μM for DA and AP, respectively, while also ensuring adequate sensibility against DA in the presence of elevated concentration of AP and vice versa (Elugoke et al., 2020). Swamy and Venton explored the codetection of dopamine and serotonin in vivo using carbon-fiber microelectrodes made with single-walled

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carbon nanotubes. S/N ratios for neurotransmitters significantly elevated after nanotube coating, according to fast-scan cyclic voltammetry. Fastscan rates did not reveal the electrocatalytic activity of nanotubes, whereas delayed scanning revealed quicker kinetics. After being exposed to serotonin, nanotube-modified microelectrodes showed much less fouling than naked electrodes. After administering a serotonin artificial precursor to a sedated rat, the nanotube-modified electrodes were applied to measure stimulated dopamine and serotonin levels simultaneously in the striatum. Because of their heightened susceptibility and resistance to fouling, nanotube-coated microelectrodes can be employed with the rapid imaging modalities and are ideal for in vivo evaluation of neuromessengers (Swamy & Venton, 2007). The organic phase (DNA sequence) encircling SWCNTs was modified to construct detectors with variable sensing properties for catecholamine transporters, according to Florian et al. Although the majority of DNA-functionalized SWCNTs responded to catecholamine neurotransmitters, the dissociation constants (Kd) and detection limits were strongly reliant on functionalization (sequence). Kd value varies from 2.3 μM (SWCNT-(GC)15 1 norepinephrine) to 9.4 μM (SWCNT-(AT)15 1 dopamine), with high sensitivity often in the single-digit nM range. Interestingly, various SWCNT symmetric sensors display distinct fluorescence increases. Furthermore, at low concentrations, certain sensors (e.g., SWCNT-(GT)10) may discriminate between distinct catecholamines, such as dopamine and norepinephrine (50 μM) (Mann et al., 2017).

2.2.2 Carbon-based quantum dots and graphene-based QD’s QDs are a type of semiconductor NP with a diameter of 1
10 nm with the elements from the periodic groups II
VI or III
V. In reality, QDs have been classified as quasizero dimensional nanomaterials, with three dimensions measuring less than ten nanometers in each direction, limiting internal electron transport to nanoscale size in each direction. Because of their improved quantum efficiency and good optical properties, semiconductor QDs (SQDs) and tiny organic fluorescent dyes (OFDs) are gaining popularity in biomedical and biotomography. However, they have significant drawbacks that have restricted their use, including increased lethality, poor bioactivity, cost, and chemical inertness. In a water-based environment, these materials have a limited dissolution rate/bioavailability. Several ways for improving QD solubility have been proposed, including

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placing them in a shell such as silica, using a persistent surfactant layer, and substituting polar functional groups on the OFDs surface; however, most modifications are made in organic solvents. Carbon-based QDs, such as GQDs and CQDs, are typically classified as zero-dimensional compounds with fluorescence properties. However, after the discovery of CQDs, GQDs, it has been discovered that they are significantly more efficient than semiconductor QDs due to lesser toxic effects, better bioactivity, tolerable chemical resistance, and dispersion. According to the study, graphene QDs were discovered to be modified versions of graphene or graphite and other graphitic threedimensional materials utilizing upper edge synthetic approaches. Multilayer topologies with lateral diameters of up to 100 nm are common in G-QDs. Carbon dots, on the other hand, are decided to make utilizing bottom-up synthetic methods and also have a spherical morphology with a radius of up to 10 nm. Carbogenic dots or carbon nanodots are other names for these particles. In addition, the GQDs have physicochemical properties that are identical to graphene. The GQDs were assumed to be small graphene layers with transverse sizes less than 10 nm that contributed up the final particle in terms of size. Due to the prevalence of edge interactions with CQDs, quantum size effect, tiny sizes, and bioactivity, a number of CQD characteristics branched from graphene characteristics, enabling them to be acknowledged as effective drug carriers, permitting simultaneous observation of the releasing kinetics. They can be used in a number of biomedical field due to its special physicochemical and catalytic features (Liu et al., 2020; Lim et al., 2015). Huang et al., designed a simplified, responsive, and credible system (CDs
CS/GCE) using CDs and chitosan (CS) hybrid sheet altered glassy carbon electrode (GCE). In addition, when contrasted to GCE responses, this CDs
CS/GCE displayed appropriate electrochemical replies for sensing DA under ideal conditions. As a result, at dosages ranging from 0.1 to 30.0 mM, the DA oxidation peak current (Ipa) was linear, with a LOD of 11.2 nM (3 S/N). This has also been claimed that this CDs
CS/GCE has been successfully employed to identify DA levels in an injectable DA solution (Huang et al., 2013). Cernat et al., used a GCE modified by Au@CDs(Au@CDs)
chitosan (CS), Au@CDs
CS/GCE, to identify DA in another study published in 2013. The Au@CDs
CS/GCE showed a greater catalytic activity in opposition to DA oxidation than the bare GCE, CDs
CS/GCE, and CS/GCE. In optimum conditions, a LOD of 0.001 M (3 S/N) was

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Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

recorded for DA critical determination within the linearity range of concentrations of 0.01
100.0 M (Cernat et al., 2020). In 2014, Hu et al. developed and characterized a novel DA biosensor on a reduced graphene oxide (rGO)-CD composite film with improved specificity, stability, and sensitivity. The rGO-CDs (GCE) had more adequate electrochemical responses for detecting DA than the plain GCE, CDs/GCE, and GO/GCE. Furthermore, with a LOD of 1.5 nM (3 S/ N), a continuous relation was established between the DA oxidation peak current and its dosage in the areas of 0.01000
450.0 M. Eventually, it was discovered that the rGO-CDs/GCE were fairly effective in suppressing ambient current induced by large uric acid (UA) and ascorbic acid (AA) (Hu et al., 2014). Cui and Zhang’s GR/Au nanocomposite-modified glassy carbon electrode (GR/Au/GCE) demonstrated high selectivity in the sensing of epinephrine (EP). On this modified electrode, EP oxidation occurred at lower positive potentials than on bare GCE. EP concentrations between 5.0
108 and 8.0
106 mol L21 (L.O.D. 5 7.0
109 mol L21) were shown to be proportional to anodic peak current. Furthermore, EP and ascorbic acid (AA) oxidation peaks were separated by around 180 mV. As a result, the GR/Au nanocomposite-modified electrode successfully differentiates between the signals of the two analytes. GR/Au nanocomposite-modified glassy carbon electrode (GR/Au/GCE) produced by Cui and Zhang showed a remarkable sensitivity in the detection of epinephrine (EP). It was discovered that oxidation of EP occurred at lower positive potentials on this modified electrode than on bare GCE. The anodic peak current was found to be proportional to EP concentrations between 5.0 10 8 and 8.0 10 6 mol L21 (L.O.D. 5 7.0 109 mol L21). Furthermore, the oxidation peaks of EP and ascorbic acid (AA) were separated by roughly 180 mV. As a result, the GR/Au nanocomposite-modified electrode satisfactorily distinguishes between the two analytes’ signals. GR/Au nanocomposites also showed the outstanding electrocatalytic properties toward a range of many microbiomolecules (including dopamine, b-nicotinamide adenine dinucleotide, and uric acid), hinting that they may be used to construct biosensors (Cui & Zhang, 2012). In order to conduct an electrochemical examination of riboflavin (RF) in a 0.2 M phosphate buffer solution with a pH of 7.0 and the presence of ascorbic acid, Varun et al. reported the development of a functionalized carbon nanofiber and carbon nanotube composite paste electrode (Varun et al., 2021).

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Jiang et al., created an NCQDs that they adjusted on the GCE and utilized to voltammetrically quantify DA. According to the study, NCQDs were created utilizing a hydrothermal process. NCQD-modified electrodes demonstrated an improved electrochemical sensitivity to DA. With linear ranges spanning from 0 to 1.0
103 M and a lower LOD of 1.0
109 M at a signal-to-noise ratio of 3, the NCQDs displayed a good electrochemical behavior for the detection of DA. On the other hand, the NCQDs augmented electrode had known for its anti-incumbrance for perceiving DA in the environment of UA and/or AA. Finally, inorganic ions were reported to have no effect on the tracking of DA (Jiang et al., 2015). Sodium dodecyl sulfate (SDS) surfactant was used to create and apply a novel carbon nanotube (CNT)-graphite mixture paste electrode (SDSMCNTGMPE) for sensitive electrochemical detection of resorcinol (RS), according to the study of Manjunatha (2017). Manjunath et al., reported that using cyclic voltammetry (CV) and differential voltammetry, a modified graphene paste electrode (SDSMGPE) prepared by electrochemically immobilizing sodium dodecyl sulfate surfactant (SDS) on a graphene paste electrode was used to simultaneously determine dopamine (DA) in the presence of ascorbic acid (AA) and uric acid (UA) (DPV). Using the CV method, the modified electrode exhibits a high electrocatalytic activity for the oxidation of DA, AA, and UA as well as three clearly defined voltammetric peaks at approximately 167, 12, and 303 mV (Shankar et al., 2009).

2.2.3 Nanodiamond Nanodiamond (ND) is a type of carbon nanomaterial with a core of covalently bonded sp3 carbon molecules and a surface decorated with sp2hybridized carbon atoms through boundary defects or loading. In the last decade, new type of carbon nanomaterial called nanodiamonds (NDs) has demonstrated the sufficient contact area and electrocatalytic activity toward NTs. Merely very few electrochemical ND-based NT sensors are now developed, which is interesting. In a solution of 0.1 mol L21 phosphate buffer pH 7.4 on B/C 4000 ppm follicular electrodes with increasing BDD growth period, Simona produced boron-doped diamond exhibited the minimum detection limit of 2107 mol L21, except any stimulation done between the various surveys. Furthermore, increased specificity for dopamine detection over common interfering chemicals such as uric acid, ascorbic acid, and

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Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

paracetamol was achieved for chosen porous electrodes (Baluchová et al., 2019). Recent electrochemical tests revealed that the transference rate in the [Fe3 (CN)6]32/42 redox system rises as the film thickens. The specificity and susceptibility results for DA blended with AA analysis demonstrate that the 8h-BDD and 12h-BDD electrodes have well-separated oxidizing maxima of DA and AA, and the 12h-BDD electrode has ideal sensibility until the DA concentration drops to 1 μM (Qi et al., 2016). Shahrokhian and Khafaji have announced the fabrication of a unique customized pyrolytic graphite electrode containing nanodiamond/graphite. In the presence of ascorbic acid, the produced modified electrode works as a very precise sensor for collateral investigation of EN and UA (AA). The electrode has a catalytic expression for analyzing EN and UA peaks, and it fully suppresses the AA interfering effect. The electrical behavior of the electrode was found to be linear with EN and UA levels in the ranges of 0.01
10 and 0.01
60 μM, correspondingly. Both compounds have a detection range of 3 nM as a consequence of these experiments. For the detection of EN in human serum samples, urine, and the equivalent injection samples, this sensor demonstrated an excellent repeatability, consistency, and specificity (Shahrokhian & Khafaji, 2010). Ramos et al., presented a biofilm of graphite, nanodiamonds, and gold nanoparticles tethered in casein as a minimal cost electrode susceptible to serotonin measurement. The conductive nanoparticles were anchored to the GCE using a casein biofilm. Differential pulse voltammetry was used to make the observations, which revealed a linear relation with an LDR of 0.3
3.0 μmol L21, a LOD of 0.1 μmol L21, and a tolerance of 0.18 mA L mol21. The sensor was used to measure serotonin in artificial urine samples that had a high recovery rate (91.4%
103%). As a result, the suggested electrode used a moderate rate biofilm to enhance the permittivity and electron transfer rate of the pristine electrode, which may be used in electrochemical biosensor applications (Ramos et al., 2020). Shahrokhian and Bayat have created a pyrolytic graphite electrode (PGE) with a thin film of graphite/diamond nanomixture on the surface (NGD). The electrode has been demonstrated to be competent in electrochemically sensing TRP and 5-hydroxytryptophan (HTRP). The inclusion of the NGD film caused a significant increase in pulse duration and wave quality, enabling nanomolar TRP and HTRP levels to be detected. Using cyclic voltammetry, the potential scan speeds, solution pH, aggregation conditions, and modifying quantity were all optimized. TRP and

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HTRP were determined using direct sweep voltammetry with detection limits (S/N 5 3) of 30 nM (TRP) and 6 nM (HTRP) with optimal accumulation time and open circuit operation (HTRP). The electrode is simple to manufacture, has greater precision, sharp peaks, sustained stability, and excellent voltammetric consistency and repeatability, and is easy to use. The sensor’s features make it ideal for detecting TRP and HTRP in pharmaceutical and therapeutic formulations (Shahrokhian & Bayat, 2011).

2.3 Conclusion The recent progress in the material design and synthesis, particularly nanomaterials, has resulted in very reliable electrochemical sensing devices with better analytical performance. Carbon nanoparticles are one among them and exhibit extraordinary sensitivity and surface conductivity. Carbon nanomaterial-based modified electrodes have also proven their capacity to serve as anchors for various neurotransmitters. As a result, carbon nanoparticles are attracting a lot of attention of electrochemists. The researchers are using different varieties of carbon materials such as CNTs, graphene, carbon dots, and carbon diamond as a modifier to determine dopamine, ascorbic acid, epinephrine, and norepinephrine. These types of electrodes show high chemical inertness, biocompatibility, and antifouling characteristics.

References Bala, K., Sharma, D., & Gupta, N. (2019). Carbon-nanotube-based materials for electrochemical sensing of the neurotransmitter dopamine. ChemElectroChem, 6(2), 274
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652. Available from https://doi.org/10.1021/acs. analchem.5b01257.

CHAPTER 3

Developments in inorganic and organic based nanostructured materials for electrochemical biosensing applications Adimule Vinayak Department of Chemistry, Angadi Institute of Technology and Management, Belagavi, Karnataka, India

3.1 Introduction Nanostructured materials exist in 1D, 2D, and 3D configurations having average size between 1 to 100 nm (Cheng, 2014; Kreyling et al., 2010). Combining different hybrid metal oxide nanomaterials and their use in engineering, physics, biology, chemistry and bionanotechnology for the development novel devices like biosensors, nanomedicines, etc. (Adimule et al., 2021; Bellah et al., 2012). For the conversion of accurate biological transformation into useful signals, an analytical device (Hareesha & Manjunatha, 2020; Manjunatha, 2018) in biosensor makes recognition of elements in direct contact with the transduction element (Nasrollahzadeh et al., 2019). On the other hand, nanostructured (NS) materials with a hybrid combination of inorganic and organic metal nanonetworks (Adimule et al., 2021; Adimule, Nandi, et al., 2021; Adimule et al., 2021) showed extraordinarily physiochemical properties such as thermal and electrical properties, optical scattering, and significantly greater performance as compared with their bulk counterparts (Huang et al., 2006; Noah, 2019). The combination of oxide metal inorganic and organic structures in hybrid nanomaterials (Adimule et al., 2021; Adimule et al., 2021) enabled its enhanced performance in energy storage devices (Adimule et al., 2021, 2022; Reddy et al., 2012), structural strength, and antimicrobial applications as well as sensor properties (Jain & El-Sayed, 2007). A wide range of different dimensions of NS exists such as 1D NS like nanorods and nanowires, 2D NS like nanosheets, and 3D NS like polymorphic crystals (Jain et al., 2008). The diversified features of the Novel Nanostructured Materials for Electrochemical Bio-sensing Applications DOI: https://doi.org/10.1016/B978-0-443-15334-1.00003-1

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nanomaterials depend on their size, and most of the metallic NPs show tunable properties like optical scattering and PL (Shashanka, Chaira, & Kumara Swamy, 2015; Shashanka, Kumara Swamy, 2020a,b). These properties are directly dependent on their aspect ratio (Logeswari et al., 2013) and the nature of the oxides in coatings (Makarov et al., 2014). Further, C-nanomaterials attracted much attention from the researcher due to their exceptional properties like thermal, mechanical, electrical, electronics, etc., in developing applications in the area of energy storage (Manjunatha, 2018b, 2020), sensors, FETs, and nanoscale electronic components (Noah, 2019; Verma & Mehata, 2019). Different physical and chemical methods have been developed for the fabrication of the NS (Muhammed, 2003; Yu et al., 2013). In addition, the use of metal oxide inorganic and organic hybrid NS improvises the biosensing properties and addresses the key challenges in the development of biosensors such as sensitivity, selectivity, interaction of the analyte with biosensor surface, and reduced response time (Stern et al., 2007, Shashanka et al., 2015, 2016). In the present investigation, the synthesis of metal oxide hybrid NS by simple precipitation method, various NS fabrication procedures, classification and varieties of biosensors, their types, possible fabrication or immobilization, and applications are discussed in detail.

3.2 Experiment 3.2.1 Typical synthesis of inorganic and organic nanomaterials In a typical process, metal nitrate (Mx (NO3)2) was dissolved in requisite quantity of demineralized water (DM), added with pinch of cetyl trimethyl ammonium bromide (CTAB) or triethanol amine (TEA) and heated to reflux; after completion of the reaction, reaction mixture was cooled to room temperature (RT); NH4OH/NaOH solution was added dropwise; and precipitate formed was filtered, washed with cold water and ethanol/acetone, dried at 100°C
200°C, and calcinated at 750°C
800°C.

3.2.2 Fabrication of the inorganic/organic nanostructures 3.2.2.1 Lithography In order to fabricate the NS, in lithography, photons, electrons, and ions are employed (Venkatesan & Bashir, 2011). During the lithography process, it transfers the patterns on the mask to the substrate surface and is

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Figure 3.1 A schematic representation of optical lithography using negative and positive photoresist.

widely used technique in the microelectronics industries (Biswas et al., 2012; Baglin, 2012). In photolithography, ultraviolet radiation was used to transfer the substrate on a photosensitive layer on the semiconductor surface (Kawata et al., 2001). Upon exposure to the radiation of a specific wavelength, the substrate undergoes changes in its composition and is subsequently transferred by the etching process (Qiao et al., 2007). Maskless approaches include ion-beam lithography and laser ablation methods (Fabre et al., 2013; Yu et al., 2013) which generate high-energy ions and multiphoton for adsorption in the photochemical process (Fig. 3.1). 3.2.2.2 Chemical vapor deposition process In chemical vapor deposition (CVD) process, the substrate is exposed to the volatile precursor, gets deposited on the substrate, and is obtained as thin-film coatings (Prasad Yadav et al., 2012). Wide varieties of NS with different physical and chemical properties were produced by changing the experimental conditions such as nature of the substrate, composition of the gas mixture, temperature, etc. (Asmatulu, 2012). CVD involves

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Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

Figure 3.2 A schematic representation of the CVD process of MoS2 shell growth on Au nanoparticles.

number of processes such as the generation of active reactants in gaseous form, delivering the precursors, adsorption, decomposition, migration, and nucleation of the atoms. CVD process is used to develop dielectrics, conductors, epitaxial layers, microelectronics, 2D nanosheets, metal oxides, and borophenes (Oliveira & Machado, 2013; de Oliveira Sousa Neto et al., 2019; Lu et al., 2019) (Fig. 3.2). 3.2.2.3 Sol
gel nanofabrication Sol
gel fabrication process involves the production of gelation network by inorganic nanomaterials and the existence of a colloidal liquid form to produce 3D NS (Prasad et al., 2018). Sol
gel involves metal precursors in solution deposited over the substrate, and then, heat is transferred to form final products. The technique has been widely used in the fabrication of metal oxide NS due to the superiority of chemical reaction and improves the chemical homogeneity of the final products (Praveena et al., 2016). Suitable capping agents provide easy chemical modification during the synthesis of hybrid nanomaterials. Nanocomposites of SiO2 and octadecyl amine with polypropylene were achieved by sol
gel techniques (Fig. 3.3) (Ayinde et al., n.d). 3.2.2.4 Green synthesis The process of green synthesis involves reducing agent obtained from the plant products to reduce the metal ions in the solution. The plant-obtained reducing agents provide greener pathways for the reduction of metal ions and their chemical composition. Ag and Mg NPs exhibit antimicrobial

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Figure 3.3 A schematic representation of sol
gel synthesis.

properties (Sani et al., 2017). For example, reduction of Ag1 from AgNO3 involves plant extract Clitoria ternatea. Some of the other substrates that support the synthesis of Ag NPs include cellulose fillers, ceramic fillers, chitosan, etc. (Turner, 2013; Bandara & Weerasinghe, 2005).

3.3 Results and discussion 3.3.1 Characterization Special techniques are required for the characterization of the NS as they have small size, shape, and morphology (Rahman et al., 2010). Various imaging techniques were employed for the characterization of the NS. Crystallite size, phase, and particle size are determined by X-ray diffractometer (XRD) spectral investigation. The size modulation of the NPs is directly dependent of the concentration of the dopant, temperature, and synthetic parameters. Changes in the synthesis of NS, doping concentration, and its effect can be studied by Raman spectral investigation. The microstructural orientation and size of the NPs were confirmed by scanning electron microscopy (SEM) and transmission electron microscopy (TEM) techniques (Fig. 3.4). The atomic composition of the elements and inner architecture of the NS were examined by X-ray photoelectron spectroscopy (XPS). The NS pore size, pore volume, and the available specific areas were studied by BET studies. The presence of various functional groups and their characteristics such as stretching and bending vibrations were confirmed by FT-IR spectroscopic investigation.

3.3.2 Characteristics of biosensors The commercial utility of the biosensors depends on the specific static and dynamic requirement which is effective in modulating the

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Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

Figure 3.4 (A) Typical TEM image of ZnO quantum dots (QDs) obtained through a wet synthesis method. (B) SEM images of ZnO nanorods. (C) SEM image of ZnO nanosheets formed through a simple mixed hydrothermal synthesis method. (D) SEM images of acid-washed porous SnO2 microcubes after calcination at 900°C for 2 h. Inset: TEM image of the as-prepared porous SnO2 microcubes. (E) ZnO ultraporous film made by flame spray pyrolysis.

biosensor devices. The following are the few characteristics of biosensor systems. 1. Selectivity and sensitivity: Particular target molecule can be identified and detected by bioreceptors in the analyte, and the minimum amount of analyte in low concentration is responsible for the effective detection of the molecules. 2. Linearity and response time: Time taken for obtaining 95% of the results which also comprises high degree of linearity. 3. Stability and reproducibility: The precision and accuracy of the biosensor depend on the effectiveness of the detection in low concentration (Manjunatha, 2020; Manjunatha, 2020) of the analyte. Stability determines the extent of vulnerability inside and outside the environment in the detection of the molecules (Manjunatha et al., 2015, 2013).

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Figure 3.5 A schematic representation of the top-down and bottom-up approaches for the fabrication of nanostructures.

3.3.3 Classification of biosensors The construction of biosensor device depends on the bioreceptors. Various criteria are taken into consideration while classifying the biosensors. Biosensor classification is a diverse and multidisciplinary field. The flowchart of the classification of the biosensors is displayed in Fig. 3.5.

3.4 Nanomaterials-based biosensors Advancement in nanotechnology enables exploring various types of nanomaterials such as metal oxide nanostructures, carbon nanotubes, quantum dots, nanowires, etc., which provides improved detection by controlling the size and morphology.

3.4.1 Electrochemical biosensing of inorganic nanomaterials Various metal oxides are widely employed in the field of electrochemistry, catalysis, and sensors because of their diversified physical, chemical, and biological properties. Most of the NPs possess high electrocatalytic performance (Raril et al., 2020; Tigari & Manjunatha, 2020), low cost, can attract the organic molecules, and are therefore used widely in the

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Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

effective detection of bioreceptor and biosensor device fabrications (Muhammed, 2003). Some examples of oxide-based biosensors and their typical characteristic features are enlisted below. 1. P-type semiconductors with superparamagnetic and superantiferromagnetic NiO NPs find applications in the field of electrocatalysis, sensors, thermistors, etc. (Naresh & Lee, 2021). 2. Ni/Cu metal oxide biosensors are effective in the detection of glucose biosensors in 0.1 M phosphate buffer solution (Purohit et al., 2020). 3. Co3O4 NPs possess diversified properties such as optical, sensor, lithium-ion batteries, supercapacitors, chemical sensors, etc. (Malhotra & Ali, 2017). 4. Fe2O3 NPs are the best-known NMs because of their bioanalytical and faster electron transfer rates. Properties of the electrochemical biosensors, especially for the metal oxides, are directly dependent on the electrochemical properties (Manjunatha et al., 2012; Raril & Manjunatha, 2018) of the analyte and transducers. Metal oxides which are inorganic in nature when used in biosensor device fabrication exhibit high sensitivity, selectivity, and capability for the detection. The biosensors are responsible for the generation of detectable signals on the surface of transducers in terms of voltage, current, and capacitance (Grieshaber et al., 2008; Shanker et al., 2014). Based on the transduction nature of the analyte, electrochemical sensors are classified into: 1. Potentiometric, 2. Amperometric, 3. Impedimetric, 4. Conductometric, and 5. Voltammetric. The inorganic metal oxide NS, especially metal oxides like Y2O3, ZnO, Co3O4, Gd2O3, CuO, Mn2O3, etc., can detect the biological specimen effectively by either potentiometric or voltammetric determinations.

3.4.2 Potentiometric biosensors The potentiometric biosensors work on the principle of the amount of charge accumulated on the surface of the transduction materials. The inorganic oxide possesses a commonly dopant element which makes the conduction of current/voltage either by electrons or hole transportation inside the NS (Rajesh et al., 2009). The oxygen vacancies created in the

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NS are responsible for the migration of charge density, thus enhancing the electrochemical efficiencies. The analyte and receptor develop effective interaction at the working electrode as compared with the reference electrode whose initial current is set to zero. In common, in order to transform the biochemical reaction signal into potential output, ionselective electrodes and ion-selective field-effect transistors are used (Chaubey & Malhotra, 2002; Pisoschi, 2016). The pictorial representation of the electrochemical biosensors is shown in Fig. 3.6A.

3.4.3 Voltammetric determinations Organic metal oxides when placed in the aqueous solution show a large change in the current gain as the applied voltage is increased. The voltammetric biosensor detects the analyte by measuring the current when increasing the large applied voltage. The detection of the analyte in small concentration, high accuracy, and simultaneous detection of multiple analyte samples are possible in voltammetric determination (Hangarter et al., 2010).

3.4.4 Electrochemical biosensing of organic nanomaterials Organic nanomaterials used for the biosensing device fabrication work on the mode of field-effect transistor (FET) transduction. A large number of organic molecules are used for the effective biosensing of various biomolecules such as CNTs (SWCNTs and MWCNTs), graphene, various conducting polymers, and other heterocyclic molecules largely used in the biosensing applications. Future transistor technology involves “nanoelectronics” in which the active surface of the device probe consists of nanometersized molecules. The integration of especially 1D NMs into functional electronic devices has received considerable attention due to their diversified biological applications as effective sensitive tools. High-throughput engineered probes are created by using NS with compatible, suitable bioenzymes like antibodies, transport proteins, enzymes, etc. The dimension of the molecules shrinks to nanoscale, thus enhancing the effect of biochemical changes at the surface of the receptor. Organic NMs containing biosensor devices provide a unique facility by changing the local chemical environment, changes in the sensitizing layer, and transducer actions. Conducting polymeric NS provides an attractive alternative to the rest other class of organic NS due to their low cost (Xia et al., 2010), lightweight, and easy processing (Rajesh et al., 2009). The crucial factor responsible for the development of conducting polymeric NS biosensor

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Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

device fabrication is to provide a selectively sensitive surface over the NS to provide contact resistance variation in the liquid phase containing analyte and receptor molecules. In common, functional monomers contained in the polymeric molecules integrate into the co-polymeric scheme and provide the site for effective interaction between the analyte and the bioreceptor molecules (Yoon et al., 2008, 2009) (Fig. 3.6).

Figure 3.6 (A) Schematic representation of a peptide-modified thin-film transistor. (B) Assembly in water produces no ions to pair with the peptide termini. (C) When assembled in an HCl solution, the N-termini pair with chloride ions. (D) When assembled in a KOH solution, the C-termini pair with potassium ions to produce a dipole pointing toward the substrate surface. The source
drain current versus source
drain bias (E) and the square root of the source
drain current versus the gatesource voltage (F) for pentacene OTFTs assembled on SiO2 under basic, neutral, and acidic conditions, as well as with and without peptide.

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47

3.4.5 Electrochemical biosensing of hybrid (inorganic and organic) nanomaterials Hybrid NMs containing inorganic and organic structures appropriately doped into the nanomatrix provide effective interaction sites in the liquid phase containing analyte and bioreceptor molecules in biosensing. In the case of fabrication of the organic and inorganic molecules, flexible electrochemical sensors are produced as a result of sandwitching 0D, 1D, 2D, and 3D NS over the surface of the organic molecules. The organic molecules provide effective interaction sites and establish a strong bond between the dispersed analyte and the bioreceptor molecules. Usually, acid functional groups present in the organic polymeric NS provide effective interaction sites between the dispersed 1D and 2D NMs and form stable contact between the electrode materials (Yoon et al., 2009). Thrombin, glucose (Tolani et al., 2009), and human serum albumin (Lee et al., 2015) are used as organic bioreceptor molecules for the device fabrication process (Yoon et al., 2008) (Fig. 3.7). Inorganic
organic hybrid nanoflowers were synthesized by using Cu (II) ions from copper(II) sulfate solution and bovine serum albumin (BSA) in phosphate buffer saline (PBS) solution. The synthesis was performed by adding BSA into the PBS solution, and Cu(SO4)2 solutions were added and incubated at room temperature for 3 days. A micrometer-sized NM having blue color was obtained. Different protein components as shown in Fig. 3.8 are used such as carbonic anhydrase, trypsin, alpha-amylase, glucose oxidase, etc. The flower-shaped hybrid NMs show significantly enhanced electrochemical performance higher than the other counterparts and significantly high possessing stability (Cui et al., 2016). Mass transfer rate becomes insignificant as a result of flower-shaped morphology and effective confinement of enzyme molecules (Lee et al., 2017). Similar to the Cu(II) ions, Ca(II) ions from CaSO4 incorporated into the alpha-analyze enzyme showed significantly enhanced sensitivity and stability as compared with free enzymes due to the strong interaction between alpha-amylase and Ca21 ions in PBS solution. Ca21 ions are also incorporated for differentiating enzymes such as lipase, chloroperoxidase, etc. (Fig. 3.9). The strategy for developing multiple enzyme molecules is incorporated with metal ions for the development of multifunctional organic
inorganic hybrid NS.

Figure 3.7 (A) A schematic illustration of a human olfactory receptor (hOR)-conjugated polypyrrole NT-FET. (B
C) Real-time changes of normalized ISD upon addition of target odorant (amyl butyrate, AB) and nontarget odorants (butyl butyrate, BB; propyl butyrate, PB; hexyl butyrate, HB), measured at VSD 5 50 mV.

Figure 3.8 (A) Schematic illustration of carbon nanotubes immobilized on a sensor surface for enhanced electrochemical detection of cancer cells. (B) Schematic representation of gold nanoparticles/aligned CNTs immobilized for an electrochemical DNA biosensor for cancer detection.

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Figure 3.9 Illustration of the synthetic process for conc. AGOx-calcium organic
inorganic hybrid nanoflowers and the corresponding scheme for immunoassay of Escherichia coli O157:H7.

Figure 3.10 Schematic illustration of the fluorometric immunoassay based on fluorescent hybrid nanoflowers and immunomagnetic separation.

For example, Cu(II) ions are incorporated with glucose oxidase and horseradish peroxidase (HRP) for the effective detection of glucose molecules (Yoon et al., 2008). The schematic representation of the fluorescent hybrid nanoflowers entrapping of the inorganic and organic hybrid NS is displayed in Fig. 3.10.

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3.5 Conclusion In summary, in the present context, various inorganic metal oxides, organic molecules, and hybrid NS biosensor requirements and their characterization and classification were discussed in detail. Further, the importance of inorganic, organic, and hybrid NS electrochemical biosensing mechanisms, their characteristics and properties like electrical conductivity, transduction, sensor performances, and comparison of the effectiveness of the biosensor performances of various inorganic, organic, and hybrid NS were presented in detail. The inorganic, and organic, based nanostructures are the promising pathway for the development of efficient biosensors which can detect biomolecules in very low concentration and in shorter time intervals. The hybrid structures thus develops strong interaction between analyte and transducers with high rate of reproducibility of the results.

Acknowledgments All the authors are thankful to M.S. Ramaiah University of Applied Sciences (MSRUAS), Bangalore, Karnataka, India, and Centre for Nano and Material Sciences (CNMS), Bangalore, Karnataka, India for constant support and encouragement.

Author contributions Dr. Vinayak Adimule was involved in the design, characterization, conceptualization, manuscript preparation, and revision.

Conflict of interest All the authors declare that they do not have any conflict of interest.

Data availability Data obtained from the present study are enclosed in the manuscript, and more data can be obtained from the corresponding author by request email.

Funding The authors did not receive any funding from any source, institution, or organization.

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CHAPTER 4

Organometallic and biomassderived nanostructured materials for biosensing applications Gopavaram Sumanth and Sandeep Chandrashekharappa Department of Medicinal Chemistry, National Institute of Pharmaceutical Education and Research (NIPER-R), Raebareli Transit Campus, Lucknow, Uttar Pradesh, India

4.1 Introduction By producing signals proportional to the concentration of an analyte in the reaction, a biosensor is a device that detects biological or chemical processes (Bhalla et al., 2016). Since Lel and Clark created the first oxygen biosensor in1962, researchers from a variety of disciplines have created a number of biosensors for use in food, drink, environmental and agricultural applications, medicine, biotechnology, and protection against bioterrorism (Malhotra et al., 2005). A growing field of multidisciplinary study is biosensors. In order to detect different kinds of targeted biomolecules, several biosensor types are combined with various transducers, each of which has its benefits and limits. In nanobiotechnology, aptamers, DNAzymes, aptazymes, and PNA are common examples of nucleic acid components (Kim et al., 2008; Singh et al. 2009, 2010). In organic chemistry, various reagents and metals are used to construct different scaffolds for biological applications (Chandrashekharappa et al., 2018; Khedr et al., 2018; Sandeep et al., 2016; Uppar et al., 2020; Venugopala et al., 2020). For a variety of reasons, nanostructures are utilized in the construction of biosensors today, and this has produced important advancements in this field (Abedini & Zhang, 2021; Zhang et al., 2021; Zhao et al., 2020). The goal of incorporating nanomaterials into biosensor structures is to raise the level necessary to stabilize biomaterials, which will increase sensitivity, catalyze the reaction, enable reactions to occur at low potentials, and speed up the transfer of electrons from the active reaction center to the electrode surface (in electrochemical nanosensors) (Alam et al., 2020a, 2020b; Zhang et al., 2020; Zhu et al., 2020). The Novel Nanostructured Materials for Electrochemical Bio-sensing Applications DOI: https://doi.org/10.1016/B978-0-443-15334-1.00004-3

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development of third-generation biosensors depends heavily on the elimination of chemical intermediates of electron transfer, which may be accomplished by using nanomaterials in the construction of biosensors (Guo et al., 2014; Sun et al., 2019; Wang et al., 2013; Zhang & Wang, 2019). Nanoparticles have a significant role in the surface adsorption of biomolecules due to their high free surface energy and large specific surface area (Freeman et al., 2013; Li et al., 2013; Wang et al., 2014). An essential class of chemical sensors called electrochemical biosensors uses electrodes as transducers to transform biological data into electrical signals (Zhang et al., 2019a). Electrochemical sensors have been the subject of in-depth research up to this point, and in some cases, the sensors produced by these studies have even been commercialized and found wide use in a variety of clinical, industrial, environmental, and agricultural domains (Gholipour et al., 2019; Sun et al., 2018; Zhang & Ou, 2015).

4.2 Principle of biosensor The transducer transforms the information from this contact into a quantifiable impact whereas the biological layer is in charge of the specific interaction with the analyte (Wang et al., 2020; Xu et al., 2020). For instance, mechanical transducers translate the analyte
bioreceptor interaction into changes in bending or resonant frequency; optical transducers typically translate this occurrence into changes in light frequency or intensity; electrochemical transducers translate it into changes in current, potential, and so on. Finally, the reading system counts the amount of these changes. Fig. 4.1 shows the biosensor process schematically. The reading system counts the effects of the encounter on the physical world (Jiang et al., 2017; Öhlén et al., 2016). A good reading system can monitor resonant frequency changes, bending changes, changes in electrochemical parameters like current and potential, and changes in optical characteristics, among other physical events (Feng et al., 2020; Pan et al., 2020; Wang et al., 2020).

4.3 Nanotechnology Due to the rising demand for controlling desirable molecules found in the human body and environment, nanomaterials have lately attracted a lot of attention (Long-Term, 2008). A nanomaterial is made up of nanoparticles (NPs) that are at least 100 nm in one dimension smaller than that. When referring to materials that are sub-nanometers or several hundred

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Figure 4.1 Biosensor principle.

nanometers in size, the term “nanotechnology” is used (Balzani, 2006; Tansil & Gao, 2006). Higher electrical conductivity, nanoscale size, the ability to amplify desired signals, and compatibility with biological molecules are all features of the designed nanomaterials (Colvin, 2003). Carbon materials, for instance, can be used to conjugate biomolecules (enzymes, antibodies, DNA, cell, etc.). According to research, the inclusion of nanomaterials may improve the performance of biosensors, particularly their sensitivity, and lower limit of detection by many orders of magnitude.

4.3.1 Classification of nanoparticles Nanomaterials were divided by size and dimensions. There are four types of nanomaterials as shown below. 4.3.1.1 Zero-dimensional nanomaterials In these zero-dimensional nanomaterials, materials with all three dimensions exist in the nanoscale, for example, NPs such as gold, platinum, silver, palladium, or quantum dots. The shape of NPs is spherical and size with a diameter of 1
50 nm. It has been found that some polygon and cube shapes constitute zero-dimensional nanomaterials. 4.3.1.2 One-dimensional nanomaterials These one-dimensional nanomaterials have one dimension in the range of 1
100 nm, and the other two dimensions can be in the macroscale. Nanotubes, nanofibers, nanowires, and nanorods are examples of one-

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Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

dimensional nanomaterials. Some metals (Au, Ag, Si, etc.), metal oxides (ZnO, TiO2, CeO2, etc.), quantum dots, and others can provide onedimensional nanostructures. 4.3.1.3 Two-dimensional nanomaterials In this class of nanomaterials, two dimensions are in the nanoscale and one dimension is in the macroscale. Nano-thin films, thin-film multilayers, nanosheets, or nanowalls are two-dimensional nanomaterials. The area of these nanomaterials can be several square micrometers keeping the width always in the nanoscale range. 4.3.1.4 Three-dimensional nanomaterials In three-dimensional nanomaterials, all dimensions are in the macroscale, and there are no dimensions in the nanoscale. Bulk materials are threedimensional nanomaterials that are fixed with individual blocks which may be in nanometer scale (1
100 nm) or more.

4.4 Gold nanoparticles Due to their biocompatibility, optical, and electrical characteristics, as well as their comparatively simple manufacture and modification (Biju, 2014), gold nanoparticles are the most commonly utilized noble metal nanoparticles for biosensor applications (Zhu, 2016). Au may quickly shed its unpaired electron from the s-subshell and reach a stable state because of a fully occupied d-subshell. A direct and unrestricted electronic transition between the electrode materials and electroactive substances is made possible by this activity of Au. Small-scale, highly active Au NPs enable stable immobilization of large biomolecules without impairing their structure or function. The Turkevich procedure, a straightforward and repeatable chemical method, is the method used the most frequently to create Au NPs (Kimling et al., 2006). Sodium tri-citrate is used as a reducing agent to reduce gold from a mono-salt precursor (HAuCl4) to its zerovalent form (Au 1 ). NPs with different optical responses may be created in a variety of sizes and forms depending on the stoichiometry between HAuCl4 and sodium tri-citrate. Based on the aggregation state, size, and shape of Au NPs, red-to-yellow color changes are suggested to represent different interaction regimes with distinctive molecular geometries (Aldewachi et al., 2018). Au nanostructures are also frequently employed as signal amplification linkers in a

Organometallic and biomass-derived nanostructured materials for biosensing applications

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variety of biosensors due to their excellent biocompatibility, catalytic, conducting, and light scattering capabilities. As a result, these varied properties of Au NPs serve as effective instruments for identifying a variety of biomarkers, such as DNA/RNA, proteins, amino acids, pathogens, and others (Chaicham et al., 2018; De La Escosura-Muñiz et al., 2016; Lee et al., 2015). For improved detection signal and analyte response, Au NPs have been used in several publications, either alone or in conjugated form with other materials. Shan and colleagues revealed amino phenylboronic acid-modified Au NPs for detecting T cell biomarkers of lymphoblastic leukemia (CCRF-CEM) in one such investigation (Shan et al., 2014). Using surface plasmon resonance (SPR) transduction, gold nanoparticles have shown their benefits in bioanalysis. The detection of the analyte can be recorded in several ways, such as changes to the angle, intensity, or phase of the reflected light, and is often predicated on a change in the dielectric constant of the propagating surface plasmons’ surroundings of gold films (Guo, 2012; Wijaya et al., 2011). A clear SPR signal amplification may be produced when using gold films and gold nanoparticles in the same configuration, in addition to the usage of a pure gold nanoparticle-based SPR transduction substituting the gold film (Pedersen & Duncan, 2005). In reality, in addition to the immobilized bioreceptor unit and the recognized analyte, the surface plasmons on gold nanoparticles cause a disruption of the gold film’s evanescent field. Gold nanoparticles offer exceptional visual qualities in addition to the capacity to transmit electrons between a variety of electroactive biological entities and the electrode. In redox enzyme biosensing, where the bioreceptor unit catalyzes the oxidation or reduction of the analyte, this approach is mostly employed. The generated species are oxidized or reduced by the electrode in traditional electrochemical enzyme biosensor setups, producing the electrochemical signal. This method’s drawback is that observable molecules must diffuse to the electrode, where a sizeable portion of the solution is wasted. In order to regenerate this biocatalyst, gold nanoparticles can contact the enzyme’s redox center by transporting the electrons engaged in the redox reaction to the electrode. This is known as acting as electron shuttles. An obvious enhancement in the electrochemical signal is anticipated since such wiring of enzymes eliminates the requirement of enzymatically generated redox species that have to reach the electrode surface. Using enzymes when metal ions are involved in the catalytic redox process, as they are for horseradish peroxidase (HRP), might result in very efficient wiring (Xu et al., 2006).

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Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

4.5 Magnetic nanoparticles Magnetic nanoparticles (MNPs), which can have a metallic or nonmetallic background, have lately garnered a lot of attention for biological sensing in relation to pathogens and nanoscale resolution bio-interactive stimuli via altered ligand
receptor proximities. MNPs set themselves apart from their bulk counterparts due to their significantly different magnetic sensitivity (with a high residual magnetism). MNPs might be categorized as paramagnetic, ferromagnetic, or supra-magnetic depending on their alignment in or without an external magnetic field and their 3d-subshell unpaired electrons (Kolhatkar et al., 2013). In biosensor devices, magnetic nanoparticles are a viable replacement for fluorescent labels. Because there are fewer magnetic domains (regions of parallel-oriented magnetic moments created by interacting unpaired electrons of an atom) in nanosized magnetic nanoparticles than in their bulk material, these particles exhibit unusual magnetic behaviors, known as superparamagnetic behavior. In the absence of an external magnetic field, magnetization appears to be zero on average and can randomly change direction within a very short period of time (Neel’s relaxation time). By using an external magnetic field to align the magnetic moments, these temperature-dependent phenomena were eliminated. The magnetic susceptibility of superparamagnets is substantially greater, even though this effect seems to be identical to that of conventional paramagnetic materials (Bishop et al., 2009). Therefore, as long as there is no external magnetic field applied, this superparamagnetic property inhibits attractive or repulsive interactions between the magnetic nanoparticles. Magnetic nanoparticles used for various applications are shown in Fig. 4.2.

4.6 Metal oxide nanoparticles Metal oxide nanoparticles (MO NPs) are considered suitable as engineering biosensors due to their improved biocompatibility, robust absorption, electronic, catalytic, optical properties, electron transfer kinetics, chemical stability, and cost-effective preparation (Hahn et al., 2012). Similar to their metallic counterparts, the form, size, and surface modification of MO NPs have a significant impact on how effective they are as biosensors (Yi et al., 2017). The nano-dimensions of metal oxides give a high sensitivity and selectivity with equivalent metal sensitivity through improved biochemical interactions with biomedical devices. Significant opportunities for binding

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Tumour cell Normal cell

Diagnosis NP

MNPs

Therapy

Hyperthermia Therapy

Targeting Magnet

Figure 4.2 Magnetic NPs for biosensing application.

the various disease-specific antigens and infection-promoting chemicals are indicated by the MO NPs’ size-dependent tunneling response. MO NP sensors have quick signal transduction and analyte sensing tuning time. Through electrochemical, optical, magnetic, and electrical processes, a number of MO NPs, including ZnO, TiO2, CeO2, SiO2, NiO, and Fe3O4, are employed for biological sensing (Yuan et al., 2019). For screening their unique signaling responses, their size-dependent physicochemical characteristics with regulated effects of capping gents are essential (Ahmad et al., 2018; Luqman et al., 2019; Tripathy et al., 2016). A stronger biological response compared with bare ZnO NPs was made possible by further modifying their surfaces with dendrimer cages (Gupta et al., 2019). For improved performance and increased detection specificity in the biosensing setups, several applications combine numerous MO NPs (Cai et al., 2015; Tripathy et al., 2016).

4.7 Carbon nanoparticles Due to the beneficial inherent properties, such as but not limited to high electrical and thermal conductivity, chemical stability, optical properties,

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Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

large specific surface, biocompatibility, and simple functionalization, carbon-based nanomaterials have become more and more prevalent in the design of sensors and biosensors (Manjunatha et al., 2021; Manjunatha, 2020; Pushpanjali &, Manjunatha, 2020). The unifying strategy used by the various described approaches for optimizing the (bio)sensor design is modifying the (bio)sensor surface (Morais, 2021). Because of their advantageous characteristics, nanostructured carbons like carbon nanotubes (CNTs) (Hareesha et al., 2021; Manjunatha Charithra & Manjunatha, 2020; Tigari & Manjunatha, 2020a; 2020b) and graphene are frequently utilized as electrical or electrochemical transducers in biosensor devices (Valentini et al., 2013; Vamvakaki & Chaniotakis, 2007). In particular, carbon nanotubes have an exceptional fusion of electrical (Manjunatha et al., 2010), biocompatible, and nanowire morphological features (Battigelli et al., 2013). As a result, CNT interfaces provide obviously expanded capabilities, such as the ability to approach a redox enzyme’s active regions and connect it to the bulk electrode. Additionally, their simple and well-documented organic functionalization (Ménard-Moyon et al., 2010) gives nanostructured electrodes novel features like specialized biomolecule docking sites or redox mediation of bioelectrochemical interactions. Additionally, CNT films have high electroactive surface areas as a result of naturally occurring, extremely porous, three-dimensional networks that are excellent for anchoring a large number of bioreceptor units, producing high sensitivities (Le Goff et al., 2011; Wang, 2005). Due to their distinctive mechanical, electrical, and magnetic characteristics, CNTs are one of the most common 1D nanomaterials and have been employed in the past to create a variety of high-performance sensors and biosensors (Barsan et al., 2015; Meyyappan, 2016). Additionally, CNTs are excellent candidates to be used in the construction of chemical and biological sensors with great sensitivity and selectivity because of their high surface area and strong adsorption capacity toward diverse molecules/biomolecules (Tables 4.1 and 4.2). According to reports, a number of CNT-based biosensors can screen the glucose index by immobilizing glucose oxidase through a variety of ways. These glucose sensors work on the basis that glucose oxidase produces H2O2 when glucose is present. HRP, which is coupled to an electrode to provide an electrical signal, then reduces the peroxide species. A glucose oxidase-modified biosensor with hydroquinone acting as a redox mediator was created in a 2016 study by immobilizing cytochrome C on the surface of multi-walled carbon nanotubes (MWCNTs) (Eguílaz et al.,

Table 4.1 Different nanoparticles for biosensing applications. Sl. no.

Principal aspects

Biosensing application

References

1

Modified collagen with Au NPs

Biosensing of glucose and heparin

2

Au NPs fabrication on carbon screen-printed electrode, 2.5% Nafion as enzyme-free sensor probe Modified Au NPs with horseradish peroxidase-labeled polyclonal antibody and neutravidin as two discrete probes Three DNA fragments that were hybridized to H37Rv aptamer as recognition probe which are fabricated with Au NPs Au NPs with glucose oxidase as sensor probe coated on tapered fiber Au NPs with cholesterol oxidase as sensor probe coated on thiolated fiber

Biosensing of uric acid

Unser et al. (2017) Stozhko et al. (2018)

3

4

5

6

Biosensing DNA and Salmonella typhimurium antibody

Savas et al. (2018)

Biosensing Mycobacterium H37Rv strain

Zhang et al. (2019b)

Biosensing of glucose

Yang et al. (2020) Kumar et al. (2019)

Biosensing of cholesterol

Table 4.2 Different metal oxide and metal nanoparticles for biosensing applications. Sl. no.

Principal aspects

Biosensing application

References

1

Ag-ZnO

Biosensing of Escherichia coli

2

ZnO/Fe2O3

Biosensing of glucose

3

Ni(OH)2/ZnO

Biosensing of glucose

4

Co3O4/C

Biosensing ascorbic acid

5

Fe3O4

6

Mn3O4

Biosensing of antimigraine drug (rizatriptan benzoate) Biosensing of rifampicin

7

Polydopamineconjugated Fe3O4

Roy et al. (2017) Apelgren et al. (2019) Fawzi and Authors (2018) Haldorai et al. (2018) Madrakian et al. (2016) Gan et al. (2015) Wu et al. (2017)

Biosensing of troponin-1

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Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

2016). For this sensor, a minimum glucose detection limit of 8 M was reported; nevertheless, efficiency was thought to be compromised by the bound protein on the VTs surface. It was suggested that a lesser degree of protein immobilization would negatively impair repeatability; as a result, signal amplification might be provided by crosslinking additional enzymes on the surface of CNTs. When graphene oxidase was first covalently connected to single-walled carbon nanotubes (SWCNTs) in the work by Kwon and colleagues, additional glucose oxidase was then crosslinked over the covalently attached molecules using glutaraldehyde as a crosslinker (Kwon et al., 2010; Sun et al., 2012). Although graphene-based biosensors are demonstrably more advanced than CNT-based biosensors (Yang et al., 2010), interest in this two-dimensional material for bioanalytical applications is steadily rising. A large variety of graphite-based bulk materials are also referred to as graphene, in addition to the fabrication of real monolayer graphene sheets from highly oriented pyrolytic graphite (HOPG) by mechanical cleavage using a scotch tape to exfoliate one sheet, by CVD on metal foils, or using epitaxy techniques where the graphene layer is formed out of silicon carbide (Bonaccorso et al., 2012). According to the Hummers and Offeman approach, these compounds are often produced by mechanical exfoliation (Coleman, 2013; Paton et al., 2014) or chemical oxidation of graphite (Hummers & Offeman, 1958). This initially called graphitic oxide is now generally known as graphene oxide and allows obtaining soluble carbon oxide sheets of undefined layer composition and sizes. The electric conductivity of this isolating material can be reestablished by chemical, thermal, or electrochemical reduction (Kuila et al., 2011). Even when the exceptional conductivity of real monolayer graphene cannot be obtained, reduced graphene oxide has other beneficial properties in high-performance biosensor devices. As for CNTs, graphene-based materials are mostly used in electrochemical biosensors (Kuila et al., 2011; Ratinac et al., 2011) where graphene is principally used as electrode material with enhanced specific surface. In optical or colorimetric biosensor configurations, graphene materials can potentially function as the transduction component itself. For DNA, aptamer, immuno, or protein sensors (Ma et al., 2012), very effective graphene-based fluorescence resonance energy transfer (FRET) biosensors were created in conjunction with modified receptor units for organic dye (Li et al., 2010) or quantum dots (Dong et al., 2010).

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4.8 Conclusion Nanomaterials have enhanced biological moiety sensing capabilities, which can be linked to improvements in electron microscopy and quantum mechanics as well as their increased sensitivity. The current state of better sensing using nanomaterials is quite positive, reducing time, resources, people, and energy requirements. Without a question, the healthcare industry continues to be a valuable source of resources, but the careful monitoring of evolving pathogenic components in infections and diseases calls for the referral of databases and standardized replies. Researchers have thoroughly investigated the usage of nanomaterials in point-of-care applications for biosensor technology. The use of nanoparticles in biosensors significantly enhances their sensitivity, selectivity, quick response, and low-cost capabilities.

Future perspectives The goal of biosensor research is to combine electrical and biological systems to create devices that are quicker, smaller, more affordable, and more effective. The combination of biosensors with cutting-edge integrated circuits with downsizing, cost-effectiveness, and wireless technology may be the future trend. Prior to making a decision to start a new research development, greater consideration should be given to analytical chemistry, interactions between biomolecules and nanomaterials, and technology viability. A new generation of biosensor technologies may be created by combining nanostructured materials with biosensor transducers in a number of creative ways. The development of nanomaterials-based biosensors in recent years has the potential to advance the disciplines of biosensor research and technology due to their superior mechanical, optical, magnetic, and electrochemical capabilities. There are, however, a lot of obstacles to be overcome.

Summary • •

We have presented a comprehensive account of different NMs capable to function as robust and efficient biosensing applications in native and functionalized forms. Nanomaterials have a major impact on recent advances in biosensing techniques.

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• •

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Organometals have remarkable progress; without these, it is impossible to move in organic chemistry. Mainly organometals are used in research and industry as a catalyst. In order to facilitate the design of better biosensing techniques, the ultimate goal of this special issue is to give new information on the creative exploitation techniques of these nanomaterials.

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116.

PART 2

Fabrication of nanostructured materials based biosensing platforms

CHAPTER 5

Fabrication routes for metallic nanostructured electrochemical biosensors Thiago C. Canevari LabNaHm: Multifunctional Hybrid Nanomaterials Laboratory, Engineering School, Universidade Presbiteriana MAckenzie, São Paulo, Brazil

5.1 Introduction Biosensors belong to the class of electrochemical sensors that can be obtained by immobilization of different biological species such as proteins, antigens, antibodies, genetic materials, and amino acids onto or inside other (nano)materials as goals to provide specific electroactive characteristics to determine specific biological species (Anusha et al., 2022; Krishnan et al., 2022). However, it is essential to emphasize that another class of electrochemical biosensors can also be formed only by nanostructures, formed by the combination of different (nano)materials, called nonenzymatic biosensors, for also being able to determine biological species in real samples. These electrochemical biosensors are highly sensitive and specific, have fast response, easy to operate, have miniaturization possibility, and can be used for real-time monitoring in different media and point-of-care devices development (Trojanowicz, 2016). Nanotechnology is a branch of science that makes it possible to obtain nanomaterials, materials with at least one dimension with a diameter of less than 100 nm (1029m) with applications in different areas such as electronics, catalysis, nanofiber, medicine, cosmetics, battery, environmental, and biosensors, among others (Ali, 2020; Bhushan, 2017; Christian et al., 2008; Titus et al., 2019), in addition to allowing the development of tools that will enable the understanding of the structural properties and physicochemical of these nanomaterials (Toma, 2016). Nanomaterials are a lot reactive because they have many surface atoms which can form 0D, 1D, 2D, and 3D structures in the function of atoms arranged. Zero-dimensional (0D) nanomaterials Novel Nanostructured Materials for Electrochemical Bio-sensing Applications DOI: https://doi.org/10.1016/B978-0-443-15334-1.00005-5

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present all their dimensions on the nanometer scale. Therefore “0D” means that no size is outside the nanometer scale. They are part of this classification group, for example, the quantum dots (QDs), nanoparticles, core
shell, and nanospheres. One-dimensional (1D) nanomaterials have two dimensions on the nanometer scale and a one-dimensional geometric shape. Therefore “1D” means that only one size is outside the nanometer scale. They are part of this classification group, for example, nanotubes, nanowires, nanorods, and nanoribbons. Two-dimensional (2D) nanomaterials have only one of their dimensions at the nanometer scale. Therefore “2D” means that two of its dimensions are outside the nanometer scale. They are part of this classification group, for example, graphene and thin films. Three-dimensional (3D) nanomaterials do not have any of their dimensions on the nanometer scale. Therefore they are called bulk (Thanh et al., 2014; Tielas et al., 2014). Each nanometric dimension has energies as a function of the state density that has an energy related to the mobility capacity of the confinement effects that give rise to each of the above classifications. From 3D to 2D material, one of its axes is confined, increasing the mobility of the particle since the possibility of locomotion of space that was previously threedimensional and is now two-dimensional is reduced. The same happens between 2D
1D material and 1D
0D (Jayawardhana & Gamalath, 2017). Through nanotechnology, hybrid nanomaterials and nanostructures can be obtained. Hybrid nanomaterials can be obtained by the intrinsic combination (covalent or van de Waals forces) of different nanomaterials resulting in a single nanomaterial with physical
chemical properties superior to start materials that can be applied in other areas, mainly in developing electrochemical sensors (Canevari, 2022). Nanostructures can be defined by combining different structures with at least one dimension between 1 and 100 nm favoring the applications in other areas, mainly in electrochemistry, due to improving mass transport besides the high number of active sites on the surface (Centi & Perathoner, 2009). The electrochemical biosensors based on metallic nanostructures have multifunctionalities and various applications compared to isolated nanomaterials and other materials with high dimensions (1026 m) and in bulk form. The main route to producing metallic nanostructures can be used in the electrochemical

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biosensors construction which is classified into two approaches, designated top-down and bottom-up (Abid et al., 2021). Top-down (from top to bottom) produces nanomaterials from structures of larger scales, that is, macro-scales, usually through physical processes. Force is applied until smaller particles are obtained, carrying out a method of material fragmentation. A counterpoint is that the material obtained generally has low granulometric homogeneity due to the demand for high control of the process variables to refine the particles. Some examples of processes are evaporation techniques, milling, lithography, high-pressure homogenization, ultrasound emulsification, and membrane emulsification. Bottom-up is a synthesis approach in which atoms and molecules form nanostructures by controlling chemical reactions under thermodynamic control based on molecular properties of self-organization. In other words, the nanostructure is formed by joining atom by atom or molecule by molecule. Some examples of processes are supramolecular formation, nanoparticle formation, monolayer autoaggregation, direct autoaggregation, and probe lithography, among others. According to Table 5.1, some of the main methods employed for synthesizing nanoparticles and nanostructure can be divided into bottom-up and top-down processes. It is essential to say that supramolecular chemistry contributes significantly to the formation of nanostructured material (Atwood, 2017; Richard, 2018; RSC & Goddard, 2007) obtained by the bottom-up synthetic route. Supramolecular chemistry is based on forming van der Waals bonds, mainly hydrogen bonding, favoring the formation of large nanostructures functionalized with excellent electrocatalytic properties that are constantly employed in the construction of biosensors (Cao et al., 2021; Khalil-Cruz et al., 2021; Liu et al., 2022; Qian et al., 2022).

Table 5.1 Some of the main methods employed for synthesizing nanoparticles and nanostructure can be divided into bottom-up and top-down processes. Bottom-up

Top-down

Sol
gel Electrochemical Hydrothermal Chemical vapor deposition (CVD) Wet route

Plasma sputtering Milling Laser ablation Electrochemical Solid route

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The methods encompass solid, gaseous, or liquid processes and can form different types of metallic nanostructure (MN) with different shapes, sizes, and stabilities. These different synthetic routes can be employed to obtain metallic nanostructures used by electrochemical biosensors construction by modifying the surface of glassy carbon and screen-printed electrode with each other (Hareesha et al., 2021; Manjunatha et al., 2013; Manjunatha, 2018; Manjunatha et al., 2018; Nambudumada et al., 2020; Raril & Jamballi, 2020; Tigari & Manjunatha, 2020). The metallic nanostructured electrochemical biosensors have been employed for the electrochemical determination of different biological species in real samples.

5.2 Bottom-up process 5.2.1 Sol
gel method The sol
gel method is commonly used to obtain different nanostructures which are used in other areas (Sanchez et al., 2010), mainly in the construction of electrochemical (bio)sensors (Walcarius, 2001; Yang et al., 2006). The main advantage of the sol
gel method is its versatility. Through the variation of reaction parameters, such as type of metallic precursor, pH value, type of solvents, and use or not of structural drivers, they directly impact the morphology: structure, porosity, active sites on the surface, and mass transport of metallic nanostructures. The sol
gel process consists of three steps: hydrolysis of molecular precursors, condensation, and polymerization (Dunn & Zink, 2007), with the condensation and polymerization steps co-occurring. Yang et al. (2006) synthesized a Pt-CNT-silicate metallic nanostructured-based electrochemical biosensor by sol
gel method. HRTEM has probed Pt-CNT-silicate metallic nanostructured formation, and this nanostructure has been used to incorporate glucose oxidase enzyme. A Pt-CNT paste-based biosensor has been constructed. The glucose biosensor has shown good electrocatalytic response, in pH 6.98 phosphate buffer, with a sensitivity of 0.98 μAm M21 cm22 and a linear range from 1 to 25 mM. Canevari et al. (2011) prepared a SiO2/SnO2/Sb2O5 metallic nanostructured ceramic material, by sol
gel method, that had been used as a matrix for immobilization of Meldola’s blue (MB) cationic dye. The XPS technique and N2 isotherms have characterized the formation of metallic nanostructured material. This nanostructured material presented porous

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with a diameter of less than 20 nm and has been employed in constructing an electrochemical biosensor to determine the cofactor NADH. The working electrode has been formed through a homogeneous mixture of the SiO2/SnO2/Sb2O5/MB with graphite (99.99%) and pressed in disk format. The biosensor presented a good response in the NADH determination, in the potential of 20.05 V in 1 mol L21 KCl aqueous solution at pH 7.3. The detection limit calculated was 1.5 3 1027 mol L21. Dopamine and ascorbic acid have not shown significant interference in detecting NADH on this biosensor. Cincotto et al. (2015) prepared the reduced graphene oxide-Sb2O5, a metallic nanostructured material, by sol
gel method, that had been used as a matrix for the immobilization of laccase enzyme. The XPS technique and HR-TEM have characterized the formation of metallic nanostructured material. An electrochemical biosensor for estriol has been constructed on a glassy carbon electrode by immobilizing laccase onto reduced graphene oxide-Sb2O5, a metallic nanostructured material. The biosensor has shown an excellent response at estriol determination with high sensitivity (275 mA/M) and a limit of detection of 11 nM. The estriol determination by biosensor has been performed using thionine as mediator (1 mM) in 0.1 M sodium phosphate buffer at pH 7.

5.2.2 Chemical vapor deposition The chemical vapor deposition (CVD) technique is widely used in constructing metallic nanostructures for developing biosensors because it can form thin films of metals and inorganic solids. Good results are achieved through the choice of suitable molecular precursors. This technique involves introducing the volatile molecular precursor into a reactor containing the metallic nanostructures onto a metallic substrate in which they will be electrically heated. In this way, after cooling, a thin film will be formed on the nanostructure, which may include a thin layer or multiple layers (Housecroft & Sharpe, 2013). Gunes et al. (2022), by CVD technique on the nickel metallic surface, prepared the metallic graphene foam/hematite (GF/α-Fe2O3) nanostructure. The graphene foam/hematite (GF/α-Fe2O3) nanostructure was used to build a glucose biosensor by modifying an ITO electrode. SEM, XPS, Raman, and electrochemical techniques characterized the metallic nanostructure. Measurements employing the biosensor were performed in PBS buffer, with pH 7.4. The biosensor showed an excellent response for

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glucose determination using the chronoamperometry technique with a detection limit of 71.6 μM. An interference study was performed by introducing ascorbic acid (B0.1 mM), mannose (B0.055 mM), and galactose (B0.032 mM). The ITO/HNC/CS/GOx enzyme electrode shown to be highly specific to glucose can be employed for glucose determination in real samples such as human blood, food, and other biological samples. Kim et al. (2020) developed a polyallylamine (PI)-based metallic nanostructured MoS2 2 Au 2 PI through the CVD plasma technique used to construct a biosensor to determine endocrine hormones: PTH, T3, and T4. The formation of MoS2 was proven through the XPS technique in which the binding energies of the Mo41 3d obtained were 229.2 and 233.0 eV, which correspond to Mo 3d5/2 and Mo 3d3/2, and the binding energies of the S2 2 2p peaks showed 163.1 and 164.2 eV. The electrochemical biosensor has been fabricated using the ELISA procedure that is a lot used to produce biosensors taking into account basic immunology concepts (antigen binding to its specific antibody), allowing the detection of tiny quantities of antigens, such as antibodies, hormones, proteins, and peptides, in a real sample. The biosensor showed an excellent response for PTH, T3, and T4 determination of hormones with a detection limit of pg mL21.

5.2.3 Wet route: solvothermal and hydrothermal processes The wet route is one of the most used synthesis methods to obtain metallic nanostructures in solution because it allows a specific synthesis control (Tan & Zhang, 2015). Many solvents are used (Liang et al., 2021) in which various reducing agents are added to form metallic nanoparticles, such as ascorbic acid, hydrazine, citric acid, ethylene glycol, N,Ndimethylformamide, borohydride, hydrogen peroxide, and carbon dots, among others (Lu et al., 2015; Rodrigues et al., 2018). The solvent greatly influences obtaining metallic nanoparticles, mainly in size and stabilization. The use of particle directing agents, ionic or neutral, directly influenced the crystalline form of the nanoparticle (nanostructure) formed (Chen et al., 2018), in which the nanostructures that show a more excellent symmetry present the more minor the energy split of the confined energy levels. The hydrothermal and solvothermal methods are part of the wet route, in which the solvents used are, respectively, water and a solvent

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other than water. In this route, metallic nanoparticles are obtained by employing high pressure and high temperature using an autoclave (Abid et al., 2021), favoring homogeneous metallic nanoparticles. Thus the wet route, including the solvothermal and hydrothermal route, is widely used to obtain metallic nanostructures in developing (bio)sensors (Cesana et al., 2020; Han et al., 2016; Povedano et al., 2017). Povodeno et al. (2017) developed an RhNPs/rGO/Sb2O5 metallic nanostructure in which rhodium nanoparticles were obtained in situ in the matrix through the wet route. RhNPs were reduced by adding sodium borohydride in a rhodium chloride solution. The metallic nanostructure RhNPs/rGO/Sb2O5 has been used as a matrix for developing a biosensor to determine endocrine interference estriol by laccase immobilization enzyme cross-linking of the enzyme laccase with glutaraldehyde (Fig. 5.1). The formation of RhNPs was confirmed by HR-TEM (Fig. 5.1B), with an interplanar spacing of 0.234 nm in agreement with rGO and 0.613 nm referring to the RhNPs. The glassy carbon modified with nanostructure metállica Lac-RhNPs/ rGO/Sb2O5 showed an excellent response of the 17β-estradiol with high sensitivity of 25.7 Am M21 cm21 and a low detection limit of 0.54 ppm (Fig. 5.2). The measurements have been performed with 17β-estradiol

Figure 5.1 Schematic display of the steps involved in preparing the rGO/Sb2O5 nanohybrid and the Lac-RhNPs/rGO/Sb2O5/GCE enzyme electrode and HR-TEM RhNPs/rGO/Sb2O5. Reprinted with permission from ref 39 Copyright (2017), with permission from Elsevier. From Povedano, E., Cincotto, F. H., Parrado, C., Díez, P., Sánchez, A., Canevari, T. C., Machado, S. A. S., Pingarrón, J. M. & Villalonga, R. (2017). Decoration of reduced graphene oxide with rhodium nanoparticles for the design of a sensitive electrochemical enzyme biosensor for 17β-estradiol. Biosensors and Bioelectronics, 89, 343
351. https://doi.org/10.1016/j.bios.2016.07.018.

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Figure 5.2 Differential pulse voltammograms recorded Lac-RhNPs/rGO/Sb2O5/GCE for 17β-estradiol determination with concentrations ranging from 0 to 11 pM at PBS pH 7. From Povedano, E., Cincotto, F. H., Parrado, C., Díez, P., Sánchez, A., Canevari, T. C., Machado, S. A. S., Pingarrón, J. M., & Villalonga, R. (2017). Decoration of reduced graphene oxide with rhodium nanoparticles for the design of a sensitive electrochemical enzyme biosensor for 17β-estradiol. Biosensors and Bioelectronics, 89, 343
351. https://doi.org/10.1016/j.bios.2016.07.018.

concentrations ranging from 0 to 11 pM at PBS pH 7. The biosensor has been used to determine the hormone in real human urine samples. Yang et al. (2022) prepared a metallic nanostructure containing reduced graphene oxide/CdS using the hydrothermal method which was used as a matrix to build a biosensor for hydrogen peroxide by modifying the surface of the glassy carbon electrode. The metallic nanostructure was characterized by UV-vis spectroscopy, field emission scanning electron microscopy (FE-SEM), transmission electron microscopy (TEM), and Xray diffraction (XRD). The biosensor was formed by immobilizing hemoglobin in the reduced graphene oxide/CdS metallic nanostructure. Lcysteine was used as a facilitator of hemoglobin anchoring in the matrix, giving rise to the rGO/Hb/CdS biocomposite. The biosensor showed good electrocatalytic activity for hydrogen peroxide determination with a detection limit of 6 3 1027 M. Tarlani et al. (2015) prepared a metallic nanostructure of ZnO/ MWCNTS through a solvothermal process, in which a solution of Llysine, L-cysteine (cysteine), and L-arginine (arginine) dissolved in water
ethanol (1:1 v/v) was used as guides of ZnO nanostructures. SEM and XRD confirmed that different morphologies had employed this synthetic route, such as cube, sphere, rod, powder, particle, and candy-like rock.

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The biosensor was formed by the immobilization of glucose oxidase on the ZnO/MWCNT nanostructure supported on a glassy carbon electrode, in which spherical ZnO showed a better response in the determination of glucose, in PBS, pH 7, and potential of 0.12 V, in comparison with the other structures with a detection limit of 0.82 mM and sensitivity of 64.29μA cm22 mM21. This biosensor was used for glucose determination in real samples.

5.2.4 Electrochemical process The electrochemical method is widely used to obtain nanomaterials because it is a versatile method, in addition to allowing control of the size of the nanomaterials obtained as a function of the distance between the electrodes, reaction time, and applied potential (Deng et al., 2014). The electrochemical method is the bottom-up process when solvents are used as precursors (Ramimoghadam et al., 2014). The top-down is used when an electrode containing the material is obtained from the nanoparticles (Ming et al., 2012). Thus carbon nanoparticles, also known as carbon dots, commonly obtained by electrochemical means and other methods, have been used as catalysts and reducing agents for the construction of metallic nanostructures that are used as a matrix in the construction of electrochemical biosensors (Wang et al., 2021). Canevari et al. (2017) prepared a metallic nanostructure based on magnetite/carbon quantum dots (MagNP/C-dots), in which carbon dots were previously prepared through the bottom-up electrochemical route. As shown in Fig. 5.3, the MagNP/C-dots metallic nanostructure was characterized by X-ray photoelectron spectroscopy (XPS) and highresolution transmission electron microscopy (HR-TEM) techniques. The metallic nanostructure based on magnetite/carbon quantum dots (MagNP/C-dots) was kept on the surface of a printed carbon electrode with a magnet connected to the outside, allowing for better dispersion of MagNP/C-dots on the surface. The glassy carbon electrode modified with MagNP/C-dots was used to determine the coenzyme NADH, which showed an excellent response at pH 7.0, with a detection limit of 20 nM as shown in Fig. 5.4. Another essential piece of information is related to the electrode’s ability to determine NADH in serum and not suffer significant interference from other species, such as dopamine, ascorbic acid, and uric acid.

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Figure 5.3 X-ray photoelectron spectroscopy (XPS) and high-resolution transmission electron microscopy (HR-TEM) of metallic nanostructure based on magnetite/carbon quantum dots (MagNP/C-dots). From Canevari, T. C., Cincotto, F. H., Gomes, D., Landers, R., & Toma, H. E. (2017). Magnetite Nanoparticles Bonded Carbon Quantum DotsMagnetically Confined onto Screen Printed Carbon Electrodes and their Performance as Electrochemical Sensor for NADH. Electroanalysis, 29, 1968. https://doi. org/10.1002/elan.201700167.

5.3 Top-down process 5.3.1 Plasma sputtering The plasma sputtering method is widely used in the formation of nanostructured thin films of different compositions, which are applied in the production of catalysts, coating of automotive parts, and the construction of support for the development of electrochemical (bio)sensors. The plasma sputtering method is widely used in constructing nanostructured films because it is a nonthermal vaporization process performed under low pressures (Abegunde et al., 2019). Generally, the plasma equipment used to form nanostructured films consists of a sputtering source, gas supply, substrate holder, evacuated chamber, and electrode. The eject particles of elements that will form the nanostructure are formed by discharge sources by applying an electric potential in the electrode, in a gas phase, and in a low-pressure environment. The electrons accelerated will collide with gas particles, emerging called plasma. These plasma-containing ions are the source of sputtering (Maqbool et al., 2007; Nguyen & Yonezawa, 2018). Ogurcovs et al. (2022) developed a biosensor by modifying the metallic nanostructured film obtained through the plasma sputtering technique. The Al:ZnO thin film of nanostructured material was prepared on the polyimide substrate surface. The chemical composition and morphology

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Figure 5.4 Electrochemical determination of NADH coenzyme in PBS, pH7, by glassy carbon electrode modified with metallic nanostructure based on magnetite/carbon quantum dots (MagNP/C-dots). From Canevari, T. C., Cincotto, F. H., Gomes, D., Landers, R. & Toma, H. E. (2017). Magnetite Nanoparticles Bonded Carbon Quantum DotsMagnetically Confined onto Screen Printed Carbon Electrodes and their Performance as Electrochemical Sensor for NADH. Electroanalysis, 29, 1968. https://doi. org/10.1002/elan.201700167.

of the thin film were characterized, respectively, using X-ray photoelectron spectroscopy and scanning electron and atomic force microscopies. Then, the biosensor was formed by immobilizing single-stranded OPE-01 DNA primers onto a polyimide substrate modified with Al:ZnO thin film of nanostructured material. The biosensor showed an excellent response in DNA determination. Tang et al. (2022) developed the metallic nanostructure NiCoLDH@Cu hetero-nanosheet array by plasma magnetron sputtering that served as a nonenzymatic biosensor for glucose determination in human serum. The NiCo-LDH@Cu nanofilm was characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), transmission electron microscopy (TEM), highresolution transmission electron microscopy (HR-TEM), and atomic force microscopy (AFM). The biosensor showed a detection limit (LOD) of 157 nmol L21.

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5.3.2 Milling The milling process is a mechanical method that produces nanoparticles or metallic nanostructures through friction, mainly through direct contact between the bead mining and the sample. The nanostructure mill and ball size are highly influenced by ball mass, mass size and magnitude, sample quantity, and sample shape. It is a technique widely used to complement the different metallic nanostructures (Caicedo et al., 2020; Lobo et al., 2019; Moghaddam, et al., 2018; Otis et al., 2021; Wei et al., 2020). In this sense, Li et al. (2021) prepared a two-dimensional Mo2C/ Mo2N nanostructure by ball milling at high temperature (800°C under an H2 1 N2 gas atmosphere) that has been used as a support for the construction of the chlorpyrifos aptasensor (CPF). The glassy carbon electrode modified with the nanostructure was decorated with gold nanoparticles (AuNPs) and then was modified with a ferrocene (Fc) probe via Au
S bonds. The aptasensor constructed with oligonucleotide DNA showed an excellent limit of detection of 0.036 ng mL21 being applied to determine CPF in real samples. Zhang et al. (2015) prepared a metallic nanostructure by combining graphene nanosheets, chitosan, and Fe3O4 nanoparticles. The graphene/ chitosan nanostructure was obtained using a ball mill and then decorated with Fe3O4 nanoparticles. AFM confirmed the formation of the metallic nanostructure, and XPS confirmed the presence of functional groups such as N-carboxylic acid. The biosensor was obtained through the immobilization of glucose oxidase (GOx) via covalent linkage due to the presence of carboxylic groups from chitosan. The biosensor showed a good glucose detection response with a detection limit of 16 μM and sensitivity of 5.658 mA cm22 M21.

5.3.3 Laser ablation The laser ablation method is widely used in the production of metallic nanostructures because it takes into account the incidence of highintensity lasers on the surface of different solid materials, most commonly metals, immersed in other solvents, ripping off molecules and atoms, which will form the nanostructures (Huang et al., 2019; Mintcheva et al., 2018; Ravi-Kumar et al., 2019). In this sense, Kalita et al. (2012) developed a metallic nickel nanostructure by applying the laser ablation technique, which was used to modify the surface of the ITO electrode. The NiNPs/ITO electrode was

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modified with dimethylsulfoxide (DMSO) and ethylene carbodiimide (EDC) to create functional groups for covalent immobilization of antiaflatoxin (a-AfB1) monoclonal antibodies. The formation of NiNPs was confirmed by HR-TEM. This biosensor AfB1/DMSO/RnNi-film/ITO was used to determine toxins in food showing good electrocatalytic response with a detection limit of 32.7 ng dL21 and sensitivity of 0.59 LA ng21 dL21. Electrochemical measurements were performed in phosphate buffer, pH 7.

5.4 Conclusions This work has demonstrated different synthetic routes to obtain metallic nanostructures that will serve as a substrate for developing other electrochemical biosensors used to determine other species in real samples. As can be seen, each synthetic route, bottom-up and top-down, confers different physicochemical properties that allow the constructed biosensors to present excellent electrocatalytic responses due to the improvement in the electron transfer process. This allows other biosensors containing metallic nanostructures to be built through different routes, making electrochemical biosensors increasingly present in medical centers and self-analysis because they are easy to use, have quick response, and can be used without the need for advanced training.

Websites Orcid: Available from https://orcid.org/0000
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4336
8097?lang 5 en Researchgate: Available from https://www.researchgate.net/profile/Thiago_ Canevari

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CHAPTER 6

Design of nanostructured biosensors based on organic and other composite materials B. Chethan1, V. Prasad1, A. Sunilkumar2, S. Thomas3 and A. Sreeharsha4,5 1

Department of Physics, Indian Institute of Science, Bangalore, Karnataka, India Department of Physics, Ballari Institute of Technology and Management, Ballari, Karnataka, India International and Inter University Centre for Nanoscience and Nanotechnology, Mahatma Gandhi University, Kottayam, Kerala, India 4 Department of Pharmaceutical Sciences, College of Clinical Pharmacy, King Faisal University, Hofuf, Al-Ahsa, Saudi Arabia 5 Department of Pharmaceutics, Vidya Siri College of Pharmacy, Bengaluru, Karnataka, India 2 3

6.1 Introduction to sensors A receptor
transducer sensor device is used to convert a biological response into an electrical signal. The design and development of biosensors have attained a greater interest nowadays because biosensors find widespread applications in the medical field, diagnosis of the disease, ecology monitoring, and maintaining the quality of food, drug, and water. The biosensing devices attained a greater demand and face many challenges to fabricate the sensing device with better sensitivity, a lower limit of detection, good stability, quick response time, reduced device size, and simple operation. These challenges can be fulfilled by the interphase of chemical and morphological properties of the nanomaterials with the sensor technology. The nanomaterials from zero to three dimensions are having advantageous properties like high surface area, enhanced conductivity, and tunable electrical and mechanical properties making these nanomaterials potential candidates to fabricate biosensors. Among the nanomaterials, nanoparticles, nanowires, and nanorods find advantageous properties because of their high stability, high carrier capacity, high detection limit, large surface area, active sites, and more thermal conductivity. The ferrites, polymers, metal, metal oxides, carbon-based materials, and their composites are widely used in the fabrication of biosensors. In this chapter, the evolution of the sensors, types of sensors, and biosensor types are discussed deliberately. This chapter provides Novel Nanostructured Materials for Electrochemical Bio-sensing Applications DOI: https://doi.org/10.1016/B978-0-443-15334-1.00006-7

© 2024 Elsevier Inc. All rights reserved.

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different methods which have been used in the synthesis and fabrication of biosensors using nanomaterials. In this modern world, as awareness of man increased to lead a sophisticated life, the need for science and technology has gained momentum (Amrutha et al., 2021; Chethan et al., 2019; Gleiter, 2000; Hareesha & Manjunatha, 2021; Hareesha et al., 2021; 2021; Manjunatha et al., 2014; Pal et al., 2011; Pushpanjali et al., 2021; Tigari & Manjunatha, 2019; Manjunatha, 2020). Nowadays civilized people depend more on the gadgets like computers, Xerox machines, air conditioning, cell phones, television, smoke detectors, and refrigerators. Many of these gadgets work with the help of sensors. The term sensor refers to a device or module that assists in detecting changes in physical quantities, such as pressure, heat, humidity, movement, force, and an electrical quantity like current, and then turns these physical quantities into signals that can be monitored and analyzed. Sensors are the brains of measuring systems. An ideal sensor should have the following qualities: high resolution, reproducibility, repeatability, range, drift, calibration, sensitivity, selectivity, and linearity (Chethan et al. 2022, 2023; Chethan et al., 2018; Chethan Ramana et al., 2019; El-Denglawey et al., 2021; El-Denglawey Manjunath et al., 2021; Manjunatha et al., 2019; Pratibha & Chethan, 2022; Pratibha et al., 2020; Ravikiran & Chethan, 2022; Rupashree et al., 2021; Shanawad Chethan et al., 2023; Shanawad et al., 2023; Sunilkumar et al., 2023). Today, we benefit from science and technological advancements that make our lives run more smoothly. We frequently rely on various devices that help us to interact with the physical environment, such as television remote controls, smoke detectors, infrared (IR) thermometers, lamp switches, and fans. Due to numerous applications, including environmental and food quality monitoring, medical diagnostics and health care, automotive and industrial manufacture, as well as space, defense, and security, the advancement of sensor technology has assumed increasing significance (Dincer et al., 2019; Ensafi et al., 2011; Ensafi, 2019; Theavenot et al., 2001).

6.1.1 Classification of sensors Depending on the physical quantity and analyte to be measured, sensors can be broadly categorized into a number of categories, which include: (1) energy source, (2) physical contact, (3) comparability, (4) analog and digital sensors, and (5) signal detection. Based on these quantities, sensors are broadly classified as follows (Khanna, 2012; White, 1987).

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Energy source: Two types of sensors are employed based on energy sources: 1. Active and passive sensors: Active sensors, such as microphones, thermistors, strain gauges, and capacitive and inductive sensors, require an external energy source. These kinds of sensors are known as parametric sensors (the output depends on the parameter). Thermocouples, piezoelectric sensors, and photodiodes are examples of passive sensors that produce signals without requiring external energy. These sensors are referred to as self-generating sensors. 2. Physical contact: Based on physical contact, sensors can be classified as contact or noncontact. 3. Contact and noncontact sensors: Contact sensors, like temperature sensors, need to make physical touch with their stimulus, whereas noncontact sensors include optical, magnetic, and infrared (IR) thermometers. 4. Comparability sensors can be either absolute or relative. 5. Absolute and relative sensors: Thermistors and strain gauges are examples of absolute sensors. Relative sensors, such as a thermocouple that measures temperature differences and a pressure gauge that measures pressure, relative to atmospheric pressure, perceive the stimulus in relation to a fixed or changing reference. 6. Analog and digital sensors: Sensors come in two varieties: analog and digital. An analog sensor converts a measured physical quantity into an analog form (continuous in time). This group of analog sensors includes thermocouples, strain gauges, and resistance temperature detectors (RTDs). Pulses are the output that a digital sensor produces. Encoders fall under the category of digital sensors. 7. Signal detection: The basic classification of sensors based on signal detection and transformation of information is as follows: a. Physical sensors: A physical quantity is measured by a physical sensor, which then transforms into a signal that the user can recognize. The force, acceleration, rate of flow, mass, volume, density, and pressure are just a few of the environmental changes that these sensors can identify. The use of physical sensors has increased significantly in the biomedical industry, especially with the development of novel measurement technologies and the improvement of microelectromechanical system technology for the creation of more precise and smaller sensors.

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b. Thermal sensors: A thermal sensor is a device that measures the temperature of an environment and converts the measured data into electronic data for recording or monitoring temperature change signals. Thermistors, RTDs, and thermocouples are a few types of temperature sensors. c. Biological sensors: Biological sensors keep an eye on biomolecular interactions like those involving antibodies and antigens, DNA and enzymatic reactions, or cellular communication. The abbreviated form of the term “biosensors” refers to biological sensors. d. Chemical sensors: The International Union of Pure and Applied Chemistry defines a chemical sensor as a device that converts chemical information into an analytically useful signal ranging from the concentration of a particular sample component to total composition analysis. Chemical sensors are used to keep an eye on the quantity or activity of the relevant chemical species in the gaseous or liquid phase. In addition, they are used to monitor assays for organophosphorus chemicals, food and drug analyses, and environmental pollution. They can be utilized for clinical diagnostic applications as well.

6.1.2 Biosensor A biosensor is a tool or probe that combines an electronic component with a biological element, like an enzyme or antibody, to produce a quantifiable signal. Information about a physiological change or the presence of different chemical or biological components in the environment is detected, recorded, and transmitted by the electronic component. Biosensors are available in a variety of sizes and designs, and they have the ability to measure and detect even very low quantities of certain diseases, harmful chemicals, and pH values. Certain static and dynamic requirements are required to develop a highly effective and capable biosensor system. These requirements allow for the optimization of the biosensors’ performance for commercial applications. 6.1.2.1 Constituents of biosensors The main constituents of biological sensors comprise of: 1. Analyte: A material of interest whose components are being determined or detected is an analyte. The biological constituents may be in the form of glucose, lactose, ammonia, and glucose (Bhalla et al., 2016). 2. Transducer: One crucial component of a biosensor is the transducer which is a device that converts energy from one form to another.

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It transforms the biorecognition event into an electrical signal that is quantifiable and connected to the quantity or the presence of a chemical or biological target. 3. Bioreceptor: Bioreceptors are biological components such as enzymes, cells, aptamers, deoxyribonucleic acid (DNA or RNA), and antibodies that are capable of recognizing the target substrate. Biorecognition is the process of producing a signal when a bioreceptor and an analyte interact. 4. Electronics: To get the signal ready for the display, it is processed. Amplification and digitalization take place on the electrical signals collected from the transducer. The display unit quantifies the signals that have been processed. 5. Display: The display unit is made up of a user interpretation system, such as a computer or a printer, that provides the output so that the user can read and understand the appropriate response according to the end-user requirement. 6.1.2.2 Evolution of biosensors Leland Charles Clark Jr., the father of the biosensors, reported about the components of the biosensors in this work in the year 1956. He fabricated the electrode which is possible to determine the oxygen content in the blood. Later in 1962, Clark reported about the amperometric enzyme electrode for glucose detection. In the upcoming year 1967, Updike and Hicks modified the Clarks work and find out the first functional enzyme electrode for oxygen sensor. After, in 1969 Guilbault and Montalvo depicted the first urea detection sensor based on potentiometric enzyme electrode. In the year 1973, Guilbault and Lubrano fabricated the hydrogen peroxide detection sensor based on the lactate enzyme sensor. In this way, many researchers have fabricated many biosensors in these years. 6.1.2.3 Characteristics of biosensors There are some static and dynamic conditions that must be met to create a highly effective and powerful biosensor system. These requirements allow for the performance of the biosensors to be enhanced for commercial applications which are as follows. Selectivity: When choosing a bioreceptor for a biosensor, selectivity is an important attribute to be taken into account. A bioreceptor may identify a specific target analyte molecule in a sample that contains undesired pollutants and admixture compounds.

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Sensitivity: It is defined as the smallest amount of analyte that can be accurately detected or recognized in the fewest steps at low concentrations (ng mL21 or fg mL21) to confirm the presence of analyte traces in the sample. Linearity: Linearity helps ensure that the findings of measurements are accurate. The substrate concentration can be detected at higher levels when linearity (straight line) is increased. Reproducibility: Reproducibility is defined by precision (similar output when the sample is measured multiple times) and accuracy (the ability of a sensor to generate a mean value that is more closely related to the actual value when the sample is sampled multiple times). When the same sample is analyzed more than once, the biosensor’s ability to produce the same results is what matters. Stability: One essential quality in biosensor applications where ongoing monitoring is necessary is stability. Stability is the degree to which the biosensing equipment is vulnerable to environmental perturbations both inside and outside. The affinity of the bioreceptor (the degree of analyte binding to the bioreceptor) and bioreceptor degradation with time are the variables that determine stability. Response period: It is playing a very crucial role in selecting the best sensor which is having short response time and recovery time factors which implies its effectiveness.

6.1.3 Classification of biosensors based on bioreceptors Bioreceptors are regarded as the key element in the development of biosensors, as it was previously discussed. Enzymatic biosensors are the most prevalent type of biosensor. Other types include immunosensors, which have high specificity and sensitivity and are particularly useful in diagnosis, aptamer- or nucleic acid-based biosensors, which have high specificity for microbial strains and nucleic acid-containing analytes, and microbial or whole-cell biosensors. The second division is based on the transducer, and the sensors are divided into the following groups: electrochemical (which is further divided into potentiometric, amperometric, impedance, and conductometric groups), electronic biosensor, thermal biosensor, optical, and massbased or gravimetric. Bioreceptor
analyte combinations fall under a different group and are few. Various classifications are made based on the technology (nano, surface plasmon resonance [SPR], biosensors-on-chip

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[lab-on-chip], electrometers, and deployable) and the detection sensor systems (optical, electrical, electronic, thermal, mechanical, and magnetic). According to the quantity of interactions between analyte and bioreceptor, transducers produce visual or electrical signals. The working principle divides transducers into the following major categories: electrochemical, optical, thermal, electronic, and gravimetric transducers. Depending on the input, the output may take the form of a figure, numerical, graphic, or tabular result. Catalytic and affinity/noncatalytic biosensors are two categories of biosensors that fall under the biorecognition principle. Analyte
bioreceptor interaction leads to the creation of a novel biochemical reaction product in a catalytic biosensor. Enzymes, microbes, tissues, and entire cells are all a part of this biosensor. An irreversible binding between the analyte and the receptor occurs in the case of affinity (noncatalytic) biosensors, and no new biochemical reaction product is produced as a result of the contact. The detection targets for this sort of sensor include antibodies, cell receptors, and nucleic acids. 6.1.3.1 Enzyme-based biosensors Enzymes are typical biocatalysts that are effective at accelerating the rate of biological reaction. An enzyme-based biosensor’s operation is based on the catalytic reaction and binding properties for detecting the target analyte. The process of recognizing analytes involves a number of potential mechanisms: analyte concentration is correlated with decreased enzymatic product formation because 1 The analyte is metabolized by the enzyme. 2 The analyte activates the enzyme. 3 The enzyme concentration is tracked by monitoring the change in enzyme characteristics. Because enzyme-based biosensors have a long history, different biosensors can be created based on the specificity of the enzyme. Improving the sensitivity, stability, and flexibility of the enzyme structure is costly and difficult due to the exceedingly sensitive nature of the enzyme structure. For enzyme-based biosensors, electrochemical transducers are most frequently employed. Glucose and urea biosensors are the most used enzyme-based biosensors. Due to the long history of enzyme-based biosensors, many biosensors can be developed depending on the specificity of the enzyme (Schroeder & Cavacini, 2010).

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6.1.3.2 Antibody-based biosensors Affinity biorecognition elements like antibodies have been in use for more than 20 years due to their broad variety of applications and potent antigen
antibody interactions. Immunoglobulins (Ig) have a “Y” shape with two heavy and two light polypeptide chains joined by disulfide bonds, and antibodies have this structure as well. Immunosensors are biosensors that rely on the interaction between an antibody and an antigen or that incorporate antibodies as ligands. There are two types of immunosensors: 1 Nonlabeled and 2 Labeled. To precisely identify the antigen
antibody complex, nonlabeled immunosensors are built by calculating the physical alterations brought on by the formation of the complex. An easily detectable label is added in the case of labeled immunosensors (Bhardwaj et al., 2021). 6.1.3.3 Aptamer-based biosensors The synthetic single-stranded nucleic acids known as aptamers can fold into two-dimensional (2D) and three-dimensional (3D) structures and can bind to target molecules in a selective manner. Because there is less spatial blocking and more surface area on the targets in 2D or 3D structures, their binding efficiency is high. Aptamers are nucleic acid molecules, which makes them physically and functionally stable throughout a wide variety of temperatures and storage conditions. Aptamers may be chemically synthesized, are stable in the pH range of 2
12, and have some thermal refolding properties, in contrast to antibodies, which must be produced by biological systems. Aptamers also have the advantage of being chemically altered to meet the detection requirements for the target molecule. Fluorescent nanoparticles, like QDs, offer significant advantages over conventional fluorescent dyes for tracking biological systems in real time. Aptamer
QD conjugates were employed to pinpoint targets, including cancer cells, bacterial spores, and proteins (He et al., 2021). 6.1.3.4 Whole-cell-based biosensors Since microbes (bacteria, fungi, algae, protozoa, and viruses) have the potential to serve as biorecognition components, they are used in the construction of whole-cell-based biosensors. They can manufacture recognition components, such as antibodies, on their own and without the need

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of extraction and purification. Whole-cell-based biosensors are simple to use and are developing quickly compared to animal or plant cells. The whole-cell-based biosensor principle states that the cells may interact with a wide range of analytes, display the electrochemical response that a transducer can detect, and communicate. These biosensors were effectively used in environmental monitoring, food analysis, pharmacology, heavy metals, pesticides, detection of organic pollutants, and drug screening due to their high selectivity, good sensitivity, and capability of detection (Riangrungroj et al., 2019). 6.1.3.5 Nanoparticle-based biosensors A new class of bioreceptor nanomaterials have recently been proposed in addition to the ones mentioned above. Numerous nanomaterials have been used as bioreceptors as a result of advances in nanotechnology and nanoscience. In terms of biosensing applications, nanoparticles offer a wider variety in both transducers and bioreceptors. For instance, nanomaterials based on cerium oxide show catalytic activity that is bioreceptorfriendly and mimics biological processes. Many inorganic materials, including graphene- and CNT-based nanomaterials, noble metal nanoparticles, and quantum dots, have been successfully used as transducers because of their effective transduction capabilities.

6.1.4 Emerging nanomaterials used in the fabrication of biosensors Through specific self-assembly techniques nanomaterials are synthesized. These nanomaterials have many distinct properties including electrical, mechanical, optical, and magnetic. Nowadays, many nanomaterials are used in drug delivery, bloodless surgery, multifunctional device fabrication, and the fabrication of biosensors. Nanomaterial-based biosensors have attained advanced properties compared to conventional biosensors. These nanobiosensors got epitome sensitivity, stability, and selectivity for the detection of various biomolecules. Advanced nanomaterials are broadly classified into two types: 2D transition metals and 2D organic polymers. 6.1.4.1 Two-dimensional transition metals Transition metals are those elements in groups 4
11 in the periodic table. Due to its intriguing characteristics, including a significant surface area and an ultrathin planar structure, transition metal nanomaterials can be used to create biosensors.

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6.1.4.1.1 Transition metal chalcogenides The transition metal dichalcogenides (TMDCs) are a class of 2D graphene cognate/nanosheets that are considered to be advanced. They are typically represented by the formula MX2, which stands for a hexagonal layer of a transition metal (M) and two layers of chalcogen (X). They can be made using a variety of techniques, such as mechanical cleavage, epitaxial growth, and chemical vapor deposition (CVD). Recently, a hybrid structure of blue phosphorene (BlueP)/TMDCs, graphene, and Ag
Au bimetallic sheets was used to create a surface plasmon resonance (SPR)-based biosensor. The study’s findings showed that compared to traditional biosensors, the monolayer BlueP/MoS2 and graphene structure significantly increase the biosensor’s sensitivity by 19.73%. A photoelectrochemical immunosensor for the detection of carcinoembryonic antigen was made using tungsten disulfide (WS2) nanosheets in a different investigation. According to the performed investigation, the photoelectrochemical responses of WS2 combined with GNPs were improved (Singh et al., 2020). To achieve photoelectrical immune sensing of the antigen in clinical samples, the nanocomposite was coated onto a glass surface, and then, antibodies specific to carcinoembryonic antigens were immobilized. Additionally, 2D TMDC-derived quantum dots have demonstrated their value in the optical detection of neurotransmitters without the use of antibodies. 6.1.4.1.2 Advanced transition metal oxides Comparable to TMDCs, transition metal oxide displays a variety of distinctive qualities, such as electrocatalytic and magnetic capabilities, which make them a fantastic choice for use in the construction of biosensors. Due to their distinctive electrical, optical, and chemical properties in comparison to other transition metal oxides (TMOs), manganese oxides are the most widely employed advanced materials in sensing applications. TMOs and 2D transition metal carbides were combined in a recent work to create a biosensor. For the separation and purification of proteins, a biosensor based on molecularly imprinted polymers has been developed. In this study, the surface of tubular carbon fibers with carboxyl modifications was grown with MnO2 nanosheets. The outcomes demonstrated that the development of MnO2 shells increases the quantity of protein-imprinting sites. An electrochemical biosensor was created to detect hydrogen peroxide using a MnO2
graphene nanosheet nanocomposite on a glassy

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electrode. The findings of this study showed that TMOs’ electrocatalytic activity is beneficial in the oxidation of H2O2, which results in the catalytic activity of the biosensor at extremely low concentrations. Metal
organic gels were utilized to create copper oxide nanoparticles, another TMO that can mimic peroxidase activity and be used to detect cholesterol and glucose. To create diverse nanostructures for drug delivery, therapy, and the monitoring of various diseases, 2D organic polymers are utilized. These polymers have the ability to mimic a wide range of biomolecules. These sensors have promising applications in clinical medicine, food analysis, environmental analysis, and other fields. 6.1.4.2 Two-dimensional organic polymers Due to their exceptional qualities, including great flexibility and tunability, ultrathin structure, and adaptability, organic polymers have been employed extensively which are still in demand. Modified metal
organic frameworks and polypeptides are the two organic polymers in this group that are most frequently employed, and they have become the preferred materials for making biosensors. 6.1.4.2.1 Metal
organic frameworks Inorganic and organic crystalline porous hybrid materials are arranged in metal
organic frameworks (MOFs) to form a cage-like structure. Typically, positively charged metal ions are surrounded by organic linker molecules. A MOF’s hollow structure provides an incredibly large internal surface area which greatly increases its utility. Photodynamic treatment for tumors can be performed with organic polymer-based MOFs. By using platinum nanoparticles to magnify the signals, a MOF-based biosensing device has also been created for the detection of neurotransmitters. A MOF containing 2D palladium nanosheets, doxorubicin, and polydopamine was used to create a theranostic nanoplatform to improve biocompatibility. The application of this mixture as a medication delivery component resulted from its impressive photothermal conversion and optoacoustic properties. As a result, these nanoparticles can be used successfully in applications for sensing, imaging, and drug delivery when combined with other materials. They can also be employed for both treatment and bacterial eradication. A biosensor for augmented antiinfective therapy has been created using 2D carbon nanosheets generated from MOFs.

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6.1.4.2.2 Black phosphorous The most thermodynamically stable form of phosphorus is called black phosphorous (BP). Phosphorene, also known as BP, offers important characteristics as a nanomaterial, including strong electroconductivity, an ambipolar field effect, high carrier mobility, and an adjustable bandgap. For the purpose of creating biosensors for the diagnosis and treatment of various diseases in recent years, numerous researchers have employed BP. The application of a 3D BP nanoscaffold for recovering neurogenesis was the subject of a revolutionary work which is presented in the year 2020. For instance, cellulose hydrogels were used in the construction of 2D BP nanosheets (BPNSs) for photothermal therapy against cancer. These hydrogels and BPNS 3D networks have improved stability, strong photothermal responsiveness, and flexibility. The clinical study demonstrates the unique applications of this nanoplatform which is also 100% safe and biocompatible. In another fascinating study, BP was used to construct a 3Dprinted scaffold that participates in bone regeneration and is intended to be used in the photothermal ablation therapy of osteosarcoma. As a result, researchers frequently use BP to create nanodevices for the treatment of diseases due to their photothermal characteristics. A 2D fingerprint nanoprobe based on BP has been used to demonstrate an enhanced fabrication method for biological surface-enhanced Raman scattering (SERS) characterization. This work created flake-shaped BP
gold nanoparticle nanohybrid theranostic nanoplatforms for phototherapy, bioimaging, and drug delivery. Genome editing, antibacterial effectiveness, photodynamic anticancer therapy, imaging, and cancer theranostics have all utilized BPcontaining biosensors.

6.1.5 Distinct platforms in the fabrication of advanced biosensor devices In these decades, more advanced biosensing devices are fabricated using different device fabrication techniques. These biosensors are fabricated by many more techniques, viz., ion beams, microfluidics, near-field electrospinning, lab-on-a-chip, and chip calorimetry. Fabrication of the integrated biosensing device for local and real-time sensing applications got epitome scope. Micro- and nanoscale patterning on the surface of the sensor enhances the sensing performances by getting over the surface-based limitations. Miniaturization in device fabrication has helped to get remarkable sensing performances in biosensors. Several types of biosensors based

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on the different fabrication techniques are made, and they depicted better sensitivity and little limit of detection. Nowadays, versatile biosensors are being fabricated to detect various biomarkers or diseases, namely, cancer, cholesterol, bacterial infection, and exosomes. 6.1.5.1 Focused ion beam technique This technique is usually used for the deposition of nanomaterials. These days, this technique has got widened the scope for the fabrication of the biosensing device. The probe attached to the ion beam is used for the fabrication of the biosensing devices. This technique is the more consistent way of preparing biosensing devices. Many more modifications are applied to the focused ion beam (FIB) technique to fabricate more reliable nanobiosensor devices. The FIB-made biosensors are compact, less costly, and can be used as a refractive index for various chemical and biological sensing applications (Erdman et al., 2019). Principle: High- and low-gallium ion-beam focusing is used for sitespecific sputtering in this technique. Advantages: Multiple specimens are formed in a small area and are time efficient, and beam strength can be adjusted. Disadvantages: The use of gallium may contaminate the samples, and physical and electrical properties can be affected. 6.1.5.2 Electrospinning This is the oldest technique used by researchers for many decades. According to their convenience, the researchers have made many modifications to this technique for the fabrication of biosensors. By decreasing the electrode gap distance, one can successfully deposit the nanomaterials on the sensing device. Through the electrospray technique, this technique has evolved. M13 bacteriophage microfabrication has been achieved with this technique (He et al., 2017). Principle: By decreasing the spinning gap, controllable deposition can be achieved. Advantages: This method is simple and cost-effective, and large-scale processing is possible. All polymers (high molecular weight) can be easily processed by this method. Disadvantages: This method is not suitable for 3D structures, and synergistic porosity for achieving good biosensing is unable to be achieved by this method.

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6.1.5.3 Paper-based microfluidics This technique is based on the principle of fluid action. The paper-based devices are easy to fabricate and of less cost. Usually, cellulose paper is used for the fabrication of the device followed by computer-based printing. The printing can be performed through different methods, namely, wax printing, laser printing, and conducting inkjet printing. Among these printing techniques, wax printing is widely used because it is effective, easier, and cost-effective. These paper-based microfluid devices will perform better sensitivity than other techniques. The paper-based CMOS photodiode biosensor is used to detect and diagnose sepsis (Hu et al., 2020). By using this paper-based sensing device, biomarkers are formed to detect glucose and lactate in human serum. A 3D paper-based sensing device with glucose detection has been developed to detect silver ions (Xiao et al., 2019). Principle: This method is mainly based on fluidic actuation. Advantages: This method is of low cost, easily desirable, simple, possibility of rapid detection, flexible substrate, easily degradable, and ecofriendly. Disadvantages: This method is limited to multiple detections, it is not operable at room temperature, and extra heating is very much necessary for proper sensing. 6.1.5.4 Microelectromechanical systems Microelectromechanical systems (MEMSs), nanoelectromechanical systems (NEMSs), and bio-nano-electromechanical systems (bio-NEMS) are the major biosensing fabrication techniques used for micro- and nanoscale device fabrication. For the detection of biochemical components, MEMS fabrication techniques are widely used (Bryzek, 2005). Bio-NEMS technique is majorly used to detect highly complex biochemical components. Moreover, the MEMS techniques are used in biosensors for diagnosis of diseases, therapeutics, and monitoring ecosystem and human health. To detect genome bacteria and viruses, a miniaturized silicon-chip biosensor has been fabricated by the MEMS technique (Battaglia et al., 2019). Principle: This method is mainly based on capacitive piezoresistive resonant thermoelectric principle. Advantages: Industrial production is possible, cost-effective, and low power consumption is possible for device fabrication. Disadvantages: For the production of a single unit, it is too expensive, especially during the initial developmental stage.

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6.1.5.5 Surface plasmon resonance-based biosensor Using incident light to stimulate the electrons at the interfaces of the material is the basic technique of the SPR technique. An SPR biosensor is used to detect the gluten in the urine samples of people to detect celiac disease. A highly sensitive biosensor to detect microRNA was developed (Wei et al., 2020). Principle: The incident polarized light falls on the metal film at the interface of the media with varying refractive index (RI). Advantages: Miniaturized devices can be prepared with this method, and the devices prepared through this method are highly sensitive. Disadvantages: Calibration has to be done for a long time. 6.1.5.6 Whispering-gallery-mode biosensors Whispering-gallery-mode (WGM) biosensing devices are very much sensitive to biomolecules and chemical ions. Usually, this technique is used for the examination of the modifications occurring on the surface of the material. For the ultrasensitive detection of the biomolecules, this method is preferable. For the detection of the grapevine virus, an optical immunosensor device was fabricated using the WGM resonator technique (Fu et al., 2020; Tereshchenko et al., 2020). Principle: It works on the principle of the wave that travels on the concave surface. Advantages: Q-factor is high, low mode volumes, small size, easy to integrate with the chip, and high tenability. Disadvantages: Bending loss and evanescent coupling loss are observed.

6.2 Conclusion In these decades, tremendous improvements happened in the fabrication of biosensor devices for better management of health. These days, many more opportunities are opening for the development, implementation, and acquisition of versatile properties of nanomaterials in the fabrication of biosensors. The use of advanced 2D transitional materials and organic polymers has attained better sensitivity, selectivity, and stability in biosensors. The biocompatible nature, enhanced conductivity, and good sensing response of the nanomaterials and their composites made it easier to develop biosensing devices. Using nanomaterial composites leads to fabricating the sensing devices with less detection limit. These types of

Table 6.1 Timeline of the biosensors developed in these years. Sl. no.

Researchers name

Year

Biosensor

References

1. 2.

M. Cramer Soren Sorensen

1906 1909

Electric potential arising between parts of the fluid Concept of pH and pH scale

3.

Griffin and Nelson

1909
22

4. 5. 6.

W.S. Hughes Leland C. Clark Leland C. Clark et al

1922 1956 1962

7.

Updike and Hicks

1967

8.

Guilbault and Montalvo Bergveld Guilbault and Lubrano K. Mosbach and B. Danielsson D.W. Lubbers and N. Opitz Suzuki et al. Clemens et al.

1969

First to demonstrate the immobilization of the enzyme invertase on aluminum hydroxide and charcoal Discovered a pH measurement electrode Invented the first oxygen electrode Experimentally demonstrated an amperometric enzyme electrode for detecting glucose First functional enzyme electrode based on glucose oxidase immobilized onto an oxygen sensor Reported the first potentiometric enzyme electrodebased sensor for detecting urea Discovery of ion-sensitive field-effect transistor Defined glucose and a lactate enzyme sensor based on hydrogen peroxide detection at a platinum electrode Developed enzyme thermistor

Cremer (1906) Sörensen and Mitteilung (1909) Griffin and Nelson (1916) Hughes (1922) Heineman et al. (2006) Clark and Lyons (1962) Updike and Hicks (1967) Guilbault and Montalvo (1969) Bergveld (1970) Bergveld (1970)

9. 10. 11. 12. 13. 14.

1970 1973 1974 1975 1975 1976

Demonstrated fiber-optic biosensor for carbon dioxide and oxygen detection First demonstrated microbe-based immunosensor First bedside artificial pancreas

Mosbach and Danielsson (1974) Lübbers and Opitz (1975) Suzuki et al. (1975) Clemens et al. (1976)

15.

Peterson

1980

16. 17. 18.

1982 1983 1983

19. 20.

Schultz Liedberg et al. Roederer and Bastiaans Cass. A. E Pharmacia Biacore

1984 1990

21. 22.

Poncharal et al. S. Girbi et al.

1999 2018

Demonstrated the first fiber-optic pH sensor for in vivo blood gases Fiber-optic biosensor for glucose detection Surface plasmon resonance (SPR) immunosensor Developed the first immunosensor based on piezoelectric detection First mediated amperometric biosensor SPR-based biosensor First nanobiosensor Nerve-on-chip-type biosensor for assessment of nerve impulse conduction

Yoo and Lee (2010) Schultz (1982) Liedberg et al. (1983) Roederer and Bastiaans (1983) Cass et al. (1984) Mun’delanji and Tamiya. (2015) Poncharal et al. (1999) Gribi et al. (2018)

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quick-responding, lower-LOD biosensing devices are used for health monitoring applications. The recently flourished SERS and WGM techniques have remarkable advantages for device fabrication, miniaturization, and possible easy handling. With the use of the new fabrication technology, using advanced nanomaterials finds a way to develop versatile devices for biosensing (Table 6.1).

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4576.

CHAPTER 7

Current electrochemical biosensors in market, trends, and future reliability: a case study S. Kalaiarasi1, P. Karpagavinayagam2 and C. Vedhi2 1

PG and Research Department of Chemistry, A.P.C. Mahalaxmi College for Women, Thoothukudi, Tamil Nadu, India 2 Department of Chemistry, V.O. Chidambaram College, Thoothukudi, Tamil Nadu, India

7.1 Introduction Electrochemical sensors create an electrical signal that is proportional to the concentration of the analyte. A sensing electrode (also known as the working electrode) and a reference electrode are typically found inside an electrochemical sensor. Electrochemical biosensors’ relative simplicity is among their main advantages. Simple circuits and cheap electrodes could be combined to quickly perform tests in portable systems that are easy to use and are miniature systems. For diagnosing diseases, condition monitoring, and environmental monitoring (Bakker & Telting-Diaz, 2002), trying to decide the analyte within a complicated specimen at the juncture and close to living time is very appealing (Zhu et al., 2008). For minimal, easily-to-use, tiny gadgets for a variety of applications, including pollution management and clinical issue, biosensors hold out a lot of potential (Guth et al., 2009). As a result of their extensive use in diabetes management, potentiometric instruments have taken the lead among the many biosensing approaches. Due to the need for diabetic patients to check their blood sugar levels many times per day, sugar biosensing actually accounts for around 70% points of the biomarker industry, making it an interesting market for businesses (Privett et al., 2008, 2010). Due mostly to sugar tracking, electrochemical biosensors represent some of the most popular biosensors on the market. Electrochemical biosensors are perfect for point-of-care uses because they can be readily reduced, were naturally cheap, and only necessitate basic electronics for conditioning and readout. Amperometric biosensors, which frequently Novel Nanostructured Materials for Electrochemical Bio-sensing Applications DOI: https://doi.org/10.1016/B978-0-443-15334-1.00021-3

© 2024 Elsevier Inc. All rights reserved.

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include mediators to improve electron transport, measure currents caused by electroactive species. Some of the most promising electrochemical sensors for systems with clearly defined charges, such as DNA, are based on electrochemical impedance spectroscopy (Merkoçi, 2007). Due to the exceptional characteristics of nanoparticles like carbon nanotubes and graphite, electrical nanobiosensors with incredibly low detection limits are currently being produced (Wang et al., 2008; Wei et al., 2009). Since the introduction of nanoscale and nanostructure techniques, the latter has expanded quickly, turning even a basic cellphone into a potent and full electrochemical base for (bio)sensing activities (Kang et al., 2010).

7.2 Biosensors The word “biosensor” is short for “biological sensor.” It is made up primarily of a transducer and an identifying component such as genetic code, antibodies, enzymes, or other physiological body (Maduraiveeran et al., 2018). The basic idea of the biological sensor is to identify analytes using a transduction system and recognition element, and it helps in identification via multiple techniques such as visual, electrochemical, and mechanical mechanisms. The biorecognition component communicates with the substance under test (Hareesha et al., 2021; Manjunatha Charithra & Manjunatha, 2020; Manjunatha, 2020a). The initial biological sensor was developed more than a century ago— a device that shows the presence of blood elements employing electrochemical processes—and is currently developing the need for an hour—a lightweight, simple-to-operate rapid evaluation kit for biosensors detection. Our journey has truly traveled a long distance (Manjunatha et al., 2020; Manjunatha, 2020b; Manjunatha & Hussain, 2022; Prinith et al., 2021; Pushpanjali & Manjunatha, 2020; Pushpanjali, Manjunatha, & Srinivas, 2020). As previously stated, biological sensors are versatile tools that can be applied to any field of application, but this was not the case a decade ago. When choosing an enzyme receptor for a biosensor, selection is a significant consideration to think about. A bioreceptor may identify a particular analyte component of an object that contains a variety of species as well as foreign substances. It will only yield beneficial outcomes when the target molecule interacts with the bioreceptor. In biological sensors have a high rate of false-positive results and poor selectivity because biological specimens are complicated and contain a variety of components.

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7.2.1 Types of biosensors While this involves identification, biological sensors protect a wide range of uses. Beginning with blood sugar identification, biological sensors have advanced significantly, creating new avenues for researchers to capitalize on their many benefits. Biosensors have been a boon to avoid major harm through their effective detection capacity, if in medical care, water quality monitoring, or agriculture (Arlett et al., 2011; Raril & Manjunatha, 2020; Raril, Manjunatha, Ravishankar, et al., 2020). In the market, many types of biosensors are available, and usage is highly required for daily life as listed given below (Bahadır & Sezgintürk, 2015). • Electrochemical biosensor (Abe et al., 2014). • Nanoparticles-based electrochemical biosensor (Graditi et al., 2016). • Graphene-based electrochemical biosensor (Grabowska et al., 2014). • Aptamer-based electrochemical biosensor (Citartan et al., 2013). • Dendrimer-based electrochemical biosensor (Clark & Clark, 1973). • Carbon-nanotube-based electrochemical biosensors (Guo, 2013). • Graphene-based electrochemical biosensors (Kunzelmann et al., 2014). • Hydrogel-based electrochemical biosensors (Harris et al., 2013).

7.3 Recent trends in biosensors From recent studies, oxidoreductase-related applications have traditionally used dendrimer-based electrochemical biosensors most. This is perhaps because dendrimers naturally have the ability to have a more advantageous orientation, superior biocompatibility, and a high density of active sites for the immobilization of enzymes. Additionally, it can be seen that the hybrids created by combining dendrimers with metallic nanoparticles, redox probes, and carbon materials have a range of uses in electrochemical biosensors (Lee et al., 2017). Biosensors are expected to have used in food evaluation, protection of the environment, medical identification, pharmaceutical, and growing crops sectors, among others, due to their accuracy, flexibility, straightforwardness, high level of sensitivity, ability to perform a real-time and onsite examination, speed, and inexpensive cost (Li et al., 2011). Furthermore, biosensors provide exciting possibilities for a wide range of decentralized clinical applications, including emergency room screening, home self-testing, and alternative site testing, as well as continuous and real-time in vivo monitoring. A new generation of biosensors is emerging,

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bringing together new biological receptors with an ever-increasing number of transducers (Lu et al., 2008). Biofabrication of mechanical components improves the performance of mass-based biosensors. In fact, both electrical and optical biosensors use this type of technology to create better biosensors. Major advancements in micro- and nanofabrication technologies allow for the creation of mechanical gadgets with tiny components that move (Erden & Kılıç, 2013; Fracchiolla et al., 2013; Lu et al., 2008). The capacity to create these types of structures using semiconductor manufacturing processes connected biological physics and biological engineering principles, allowing for the development of practical micro- and nano-electromechanical biosensors that can be mass-produced. Plenty of obstacles stay in weightbased detectors because of capturing agents for manufacturing at the nanoscale by using microelectronic production for high quantities evaluation. In this regard, it is important to highlight the enormous usage possibilities of semiconductor components and quantum dot technology. However, no biosensor technology can perform simultaneous, real-time quantitative assays on large arrays, but the fabrication of micro- and nanoscale cantilevers may make it possible (Tigari & Manjunatha, 2020; Tigari & Manjunatha, 2020).

7.4 Future reliability We are certain that nanomaterials, downsizing, and the construction of multimodal arrays for evaluation in biomedical activities are the driving forces behind the advancement of electrochemical biosensors. Although the research listed above can explore the use of electrochemical biosensors, there are still few research articles that have used these approaches in miniature systems. A number of different approaches involving several domains, from chemical analysis and semiconductors to molecular genetics, are apparently required to enhance the application of tiny electrochemical biosensors. It is also crucial to emphasize that there are still difficulties in examining new protocols and approaches for these applications. More substrates and electrochemical methods should be used in these systems, and this will enable the development of electrochemical biosensors for use in devices (Kumar & Rani, 2013). The advancement of biosensing for usage in technologies would be made possible by the use of additional materials or electrochemical techniques in such systems. Electrochemical sensors have garnered a lot of

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attention in recent years as among the most key techniques, with considerable potential for use in a variety of fields, including healthcare and environmental monitoring (Khimji et al., 2013). Quick patient monitoring techniques have become a key problem in the modern era, and as we have seen in this chapter, biosensors play a significant part in their development by offering high specificity, mobility, and quick analysis. To improve the use of nanoscale electrochemical biosensors, a variety of strategies involving multiple fields, such as chemical analysis (Liu et al., 2014), semiconductor, and cell biology, appear to be necessary. It is also essential to emphasize that testing new protocols and methods for all these applications often presents challenges. Graphene and nanoparticles, which seem to be popular types used in electrochemical sensors and biosensors, are relevant in this situation for use in care assessment, particularly when combined with biological molecules and other equipment that have complementary properties to increase sensitivity, specificity, and stability. Therefore, in addition to the detection approach used, which must have been accepted for evaluation, one of the essential factors that determine the effectiveness of biosensing instruments seems to be the combination of material with biomolecules for a given application (Su et al., 2016). An electrochemical sensor that is being tested with developments with high-throughput techniques focusing on identification limit, evaluation time, and accessibility enabled massive consumer demand for cheap sugar and pregnancies using known to inhibit human chorionic gonadotropin immobilization removal with oblique flow technological advances (Lai & Haile, 2005). Optic-based biological sensors are the next major biological sensing technological advances including fiber-optic chemistry. Because of its high capacity for load and hydrophobic nature, nanogel-based linkage is ideal for just one molecule recognition, such as DNA or peptide. Recent advances in molecular optoelectronics have even enabled the development of optical biometric recognition systems (Bailera et al., 2017). Contemporary approaches to biosensor discovery include combined approaches that use various methods such as electrochemical, electromechanical, and fluorescence-cum-optical-based biosensors, as well as genetically engineered microbes. As the demand and need for using biosensors for rapid analysis at a low-cost increase, biofabrication will pave the way for identifying cellular to whole animal activity with a detection limit of high accuracy for single molecules. The biosensors should then be

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designed to operate under multiplex conditions. In that case, both 2D and 3D detection with sophisticated transducers is required for targeting and calculating smaller analytes of fascination.

7.5 Conclusion Biosensors have demonstrated their effectiveness, performance, and exceptional recognition for different substances in biomedical, agricultural, food safety, and water surveillance applications. Glucometer, as the first-ever biosensor, offers a wealth of concepts regarding future scientific research and the use of biosensors in our daily lives. Wearable technology may identify the existence of small bacteria and diagnose the individual’s medical limitations. Additionally, the development of artificial biological science that uses bacteria as sensors will be crucial for detecting the environment and meeting energy demand. The writers of the paper emphasized the significance of using bacterial fuel cells in the development of a water treatment technique and sources of energy for sensors that monitor the environment. In general, we emphasized the type of biosensors, which has possible uses and features such as identifying analyte capacity, evaluation time, mobility, expenses, and modification.

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CHAPTER 8

An overview of stability and lifetime of electrochemical biosensors Ersin Demir1, Kevser Kubra Kırboga2 and Mesut I¸sık2 1

Faculty of Pharmacy, Department of Analytical Chemistry, Afyonkarahisar Health Sciences University, Afyonkarahisar, Türkiye 2 Faculty of Engineering, Department of Bioengineering, Bilecik Seyh Edebali University, Bilecik, Türkiye

8.1 Introduction The introduction of biosensors into the literature is not far from today but coincides with the middle of the 19th century (Heineman et al., 2006). Leland L. Clark and Lyons developed an oxygen electrode in 1950, and the first amperometric enzyme sensor was developed for glucose determination in 1962, thus introducing the term biosensor to the scientific world (Clark & Lyons, 1962; Heineman et al., 2006). In 1975, such biosensors were introduced to the market as “Model 23 A YSI analyzer” (Yoo & Lee, 2010). A biosensor is a self-contained integrated device that can provide quantitative or semiquantitative analytical information, directly using a biochemical receptor (Lee, 2005). It is most simply defined as an analytical device capable of converting a biological response into a signal (Bollella & Katz, 2020). From the time of its discovery to the present, endless biosensors have been developed in the fields of biology, chemistry, and materials science. Moreover, due to the biosensors’ extraordinary specific and selective properties, they can be used in medicine, agriculture, and pharmacy. Studies have gained momentum in the last two decades due to the great advantages of biosensors, such as low detection limits, short analysis times, low cost, no preprocessing, portability, and miniaturization potential. Especially nanomaterials such as metals, conductive polymers, biopolymers, composites, molecularly imprinted polymers (MIPs), antibody
aptamer, and deoxyribonucleic acid (DNA) carbonaceous materials and metal
organic framework (MOF) contributed significantly to the development of biosensors. Indeed, scientists are looking for new analytical methods that are on-site, online, and portable that can get quick answers. There is a need for a Novel Nanostructured Materials for Electrochemical Bio-sensing Applications DOI: https://doi.org/10.1016/B978-0-443-15334-1.00022-5

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sensitive and selective analyzer set that will provide very fast results, especially in the detection of defense and health problems. Not only these problems but also the analysis of these samples is extremely important, as food analyses and environmental analyses directly or indirectly affect human health. Contrary to traditional methods, electrochemical biosensors have been and are an inspiration to the scientific world in this sense. Moreover, all factors such as widespread use of electrochemical methods, increase in sensor diversity, and development of new and unique materials enable the production of biosensors with extremely excellent properties. It is understood from the great acceleration in the sensor studies conducted in the last 5 years that these developments do not mean that new sensors will not be produced. Moreover, specific, selective, and sensitive electrochemical sensors for analyte determinations are increasing day by day. In particular, the discovery of new materials means new horizons in the world of sensors for the analysis of all analytes defined as substances. The development of biosensors, their analysis in samples such as medicine, food, and the environment, and the development of portable, body-integrating sensors are not considered impossible. The weak points of biosensors such as stability and shelf life are being improved day by day. For this, hybrid materials are built from different materials. Moreover, scientific studies are continuing at full speed for biosensors to take place in our daily lives. The main reason here is that the events on the sensor surface are not fully and clearly understood. It is the full elucidation of electrochemical processes with new, superconducting, and catalytic materials produced in parallel with the developing technology today. Biosensor manufacturing baselines are well established, and material development and analytical method improvement are intensively researched by scientists.

8.2 Design and principle of biosensors The world of biosensors has not been too far from the present but has become important in the last two decades. The main reason here is that the events on the sensor surface are not fully and clearly understood. It is the full elucidation of electrochemical processes on the surface of biosensors with new, superconducting, and catalytic materials produced in parallel with the developing technology today. Biosensor manufacturing baselines are well established, and material development and analytical method improvement are intensively researched by scientists. A typical biosensor includes (a) an analyte, (b) a bioreceptor, (c) a transducer, (d) electronics, and (e) a display (Fig. 8.1) (Bhalla et al., 2016),

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Figure 8.1 Basic components of biosensors.

where analyte: the relevant substance to be determined in the samples (e.g., the amount of glucose in the blood or the determination of lactose in milk); bioreceptor: a biological element and substance that can sense or recognize an analyte, for example, enzymes, aptamers, and antibodies. Biorecognition expresses chemical changes such as light, heat, pH, charge, or mass during the interaction between the bioreceptor and the analyte. Converter is the part of the biosensor that converts energy from one form to another. This process transforms the change of a chemical or biological target as a result of bioreceptor interaction into a measurable signal (electrical). They are classified as electrochemical, optical, electronic, thermal, and gravimetric converters according to their working principle. Electronics: The converted signal is processed to prepare the image. The electrical signals obtained from the converter are amplified and converted into digital images. Imaging: The imaging unit consists of a computer or printer-connected system that produces output so that the corresponding response can be interpreted. The output can be in the form of numerical data, graphical, or table containing data. A biosensor is a system that detects physical or chemical changes that occur between the analyte and the bioreceptor as a result of

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biorecognition procedures. It is possible to classify biosensors according to the bioreceptor layer in the biorecognition process. According to this classification, the enzyme is divided into cell-based, affinity biomoleculebased, aptamers, and molecularly imprinted polymer (MIP) biosensors. Biosensors are classified according to the bioreceptor layer [Najeeb MA, Ahmad Z, Shakoor RA, Mohamed AMA, Kahraman R. A novel classification of prostate-specific antigen (PSA) biosensors based on transducing elements] (Najeeb et al., 2017; Phumlani et al., 2021). Transducers are needed to make the changes between the analyte and the bioreceptor measurable. Sometimes this change is in terms of current, and sometimes it happens based on the mass. It is possible to separate different types of biosensors depending on the transducer elements. Biosensors can be grouped under the main heading of electrochemical, optical, electronic, thermal, and gravimetric.

8.3 Electrochemical biosensors In recent years, the development of electrochemical methods due to their stability, superior selectivity, portability, and miniaturization has led to the opening of new horizons for the scientific world. In this respect, due to the unique properties of biosensors, the development and applications of electrochemical biosensors have gained great importance, and studies have increased rapidly in the last two decades. The basic working principle of electrochemical biosensors is that the electrical potential difference between the analyte and the bioreceptor is proportional to the active concentration of the substance. Biomaterials such as enzymes, molecularly imprinted polymers (MIPs), antibody
aptamer, and deoxyribonucleic acid (DNA) are used as receptors in electrochemical biosensors (Gui et al., 2018). In addition, metal-modified composite electrodes on carbonaceous material surfaces are preferred. In this system, the current or potential difference from the system as a result of the redox behavior of the analyte is used for the quantitative analysis of the target analyte in the sample. Conductimetric-, amperometric-, voltammetric-, potentiometric-, and impedimetric-based biosensors are used for measurement depending on the analyte and bioreceptor process.

8.3.1 Interface of biosensor Creating the interface to interact with the analyte is the most challenging process in biosensor design. This interface structure, which will provide

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extraordinary selectivity, must be unique to the target analyte even in a complex matrix environment. In addition, the biomolecule located in the bioreceptor must be in an immobile structure on its surface. Highly active biomolecules such as enzymes should be the interface layer between the denatured bioreceptors and the surface of the electrodes (Song et al., 2021). Sometimes a solid surface such as silicon is used as this interface, while sometimes a series of substrates such as glass, paper, and polymer are made of different materials. The interface, also called biocompatible surface, directly affects the stability, shelf life, selectivity, and sensitivity of the biosensor. Therefore one of the most important steps in biosensor development is to build a high-stability interface. In addition, the coupling enthalpies, entropies, and thermodynamics of the interface can be said as other parameters that affect the stability of the biosensor (Visalakshan et al., 2019).

8.3.2 Materials of biosensor interfaces Due to both the application area and sensitivity of biosensors, they have been successfully used in qualitative and quantitative analyses of numerous pesticides, drugs, and organic substances with superior selectivity. The most basic factor here is that it is formed from different materials seen in the bioreceptor. It is possible to classify these materials as metallic nanomaterials, carbon-based nanomaterials, polymer, and metal
organic frameworks. 8.3.2.1 Metal-based nanomaterials In recent years, advances in nanomaterials due to technology have made a positive contribution to the production of biosensors (Song et al., 2021). These nanomaterials, which have particularly large surface areas and catalytic properties, contribute positively to the development of the bioreceptor. Moreover, by increasing the stability of the biosensor, sensors with longer life and high repeatability have been developed. In particular, nanomaterials are ideal immobilization materials in bioreceptors due to their excellent conductivity, large surface area, outstanding catalytic activity, and excellent biocompatibility. The metal-based interface used in the production of biosensors varies widely. These nanomaterials are nanoparticles such as Au and ZnO, Fe3O4, MnO2 and TiO2, MoS2 semiconductor, bimetallic nanocrystals Ni/ZrO2, microporous structure, and microrod structures. In addition, noble metal- and alloy-based nanomaterials are widely used in biosensor production due to their catalytic and biocompatible properties.

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Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

8.3.2.2 Carbon-based nanomaterials Carbonaceous materials come to the fore in the use of electrochemical sensors due to their large surface area and unique properties such as excellent conductivity, stability, and durability (Inagaki & Kang, 2016). Nanostructures such as single- or multi-walled carbon nanotubes, nanoporous carbons, graphene-based nanomaterials, and carbon nanofibers are important materials as bioreceptors. They are the most applied materials due to their large surface areas, stability, stability between biomolecules and the surface, unmatched conductivity, and catalytic effects. It also has superior properties such as film-forming ability, modification with nanomaterials, and biocompatibility. Treatment with nanoparticles, polymers, and heteroatoms such as nitrogen, sulfur, and phosphorus improves the electrocatalytic activity, stability, and resistivity of carbonaceous materials. Considering all these features, it can be said that carbon sensors are the most important material in the production of biosensors. 8.3.2.3 Polymer Polymers are extremely sensitive materials used in making bioreceptors in biosensors. It is frequently preferred as an interface, especially because it is easy to process and its chemical and physical properties can be adjusted as necessary. It develops polymers specific to the analyte target and has gained an important position in the production of biosensors. The polymers used in the construction of bioreceptors can be divided into conductive polymers and nonconductive polymers. Conducting polymers are coated on the electrode surface, increasing the sensitivity of the sensors which use to detect numerous analytes in real samples. Nonconductive polymers, on the other hand, are preferred to immobilize certain receptors in the sensor device. Until now, a large number of polymer-based biosensors have been produced for the determination of various target substances. Various polymers such as chitosan, polyethylene glycol, agarose, and hydrogel have been widely used in these sensors. 8.3.2.4 Metal
organic framework In the last decade, the new and porous metal
organic framework (MOF) is an interesting hybrid material in the production of electrochemical sensors. Metal ions and organic ligands are formed, which are bound together by strong coordination bonds. Unlike inorganic nanomaterials, MOFs are biocompatible compounds with a natural degradability process. Therefore MOF-type sensors have been applied for the determination of several

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biological agents such as DNA, RNA, and enzymes. MOFs with porosity show both outstanding catalytic activity and excellent affinity as bioreceptor. MOF constitutes an important class in electrochemical biosensors due to its advantages such as unique lattice structure, large surface area, and different metal central atoms.

8.4 Reproducibility and lifetime The repeatability of electrochemical biosensors is a measurement of scattering and drift in observations and findings, such as the repeatability of analytical equipment. When assessing sensitivity under storage or operational circumstances, biosensor stability may also be calculated as a deviation. Drift detection is particularly important for biosensors that have been studied over a relatively short period and are slow to evolve. Repeatability is determined for analyte concentration within a usable range. For example, in studies on some biosensors, it has been reported that the biosensors can be used for more than 1 year in laboratory conditions, but their practical life is either unknown or may be limited to days or weeks when incorporated into biological tissue, like industrial processes or in vivo implanted glucose biosensors (Turner, 1993). The procedures for evaluating biosensors’ behavior for several days after entering industrial reactors are much more involved and challenging to handle, even though it is relatively simple to determine the laboratory stability of biosensors while they are operating, both in storage and in the presence of the analyte (Thévenot et al., 2001). Storage state, like dry or wet, atmospheric composition, such as air or nitrogen, pH, buffer composition, and the presence of additives are crucial factors in determining storage stability. The operational stability of a biosensor response can vary significantly depending on sensor geometry, preparation method, and applied receptor and transducer. Additionally, the limiting factor, such as a substrate’s internal or exterior diffusion or biorecognition reaction, has a significant impact on the response rate. Finally, depending on the operating environment, it might vary greatly. We advise taking into account the analyte concentration, continuous or sequential interaction of the biosensor with the analyte solution, temperature, pH, buffer composition, presence of organic solvents, and sample matrix composition when determining operational stability (Section 3.3). In bench or industrial, whether the useful life is storage (shelf) or working (use) life is determined by storage, operating conditions, and

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Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

substrate concentrations. Biosensor rate-limiting step or factor information is particularly important for understanding its stability characteristics. The lifetime evaluation mode, i.e., initial precision and calibration curve, should be specified relative to the upper limit of the linear concentration range for accuracy or repeatability. For accuracy in the linear concentration range, the definition of life in tL is recommended as the required storage or operating time for a 10% (tL10) or 50% (tL50) reduction. To determine the storage life, the sensitivities of different biosensors derived from the same production batch with different storage times under the same conditions should also be compared (Thévenot et al., 2001). Both shelf stability and operational stability are significant factors; however, shelf stability is more critical in some circumstances than operational stability, such as when producing disposable biosensors for glucose (Hill et al., 1997). In some circumstances, both types of stability may be required, particularly with multipurpose carbon paste biosensors. The majority of the paste, however, is not in direct contact with the analyte solution, necessitating shelf stability. However, if the instrument is to be used repeatedly, the tip, where the measurement takes place, needs to be operationally stable.

8.4.1 Definition of stability The degree to which sensor qualities hold true over time is referred to as stability. Aging of components, a decline in sensitivity of components, and changes in signal-to-noise ratio can all lead to changes in stability, also known as drift (Gibson, 1999). Therefore it is crucial to establish the various categories of stability right away. When enzymes are immobilized in solution, as a dehydrated powder (e.g., lyophilized), or on a substrate such as the surface of a biosensor, they can be stabilized to increase shelf life or operational stability.

8.4.2 Shelf stability When an enzyme, protein, diagnostics, or gadget is maintained under certain circumstances after creation, its shelf stability may be described as an increase or improvement in the activity retention of the product. The commercialization of unstable materials that deteriorate over time depends on this characteristic. In the food business, where products are stamped with expiration dates on the packaging, shelf stability is demonstrated frequently. Pharmaceuticals use a similar technique, and producers of

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enzymes frequently include an expiration date on their protein goods. One of the key determinants of a biosensor device’s commercial success is frequently the stability of the labile biomaterial used in it.

8.4.3 Operational stability One of the most important aspects of the functioning of a biosensor is operational stability. Operational stability is the capacity of a protein or enzyme to maintain its activity while being used. This factor, which has to do with a device’s usability and operating longevity, is the most frequently referenced one in biosensor literature. When analyte monitoring is frequently necessary or reusable sensors are used in the measurement process by an analytical instrument, the lifespan of a sensor can sometimes be important. The signal at a certain concentration of the measured analyte degrades as a result of biosensor aging. Temperature, processing or usage, and time all affect how something ages. According to the Arrhenius theory, increasing the latter speeds up aging (McAteer et al., 1999). These experiments are adequate for disposable sensors and do not provide anything about aging characteristics for long-term usage. Because there are many different types, labeling, and manufacturing procedures for biosensors, the data reported here may not be applicable to all biosensors. However, different enzyme biosensors and biosensing approaches can be used with the suggested methodology, processes, and models to assess sensor deterioration utilizing high temperatures accelerating aging (Panjan et al., 2017) (Fig. 8.1). Various biosensor-based wearable devices are being developed that require high operational stability of biosensors. The development of wearable sensors has led to significant growth and change across a wide range of sectors, including healthcare, informatics, communications, and biological sciences. This revolution is primarily being driven by the newly discovered capability to continually observe and evaluate patients’ physiology in their natural surroundings. Most of the technologies available on the market are focused on electrophysiological, electromechanical, or acoustic measurements. Traditional challenges in biochemical sensing, such as reliability, repeatability, stability, and slippage, have an important place in wearable sensing systems due to variations in the operating environment, sample/sensor usage, and motion artifacts (Sonawane et al., 2017) (Figs. 8.2 and 8.3).

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Enzyme

MIP

Cell-Based

Bioreceptor

Affinity Biomolecule

Aptamers

Figure 8.2 Commonly preferred bioreceptors.

Transducer elements

Electrochemistry

Opc

Elektronic

Thermal

Gravimetric

Acusc

Amperometric

Chromogenic

Piezoelectric

Voltammetric

Luminogenic

Magnetoelasc

Potenometric

Opcal fiber

Impedometric

chemiluminesce nce

conductometric

SRP

Figure 8.3 Types of biosensors by transducer class.

Table 8.1 Materials of various interfaces used in biosensor construction. Analytes

Biosensor

Technique

Linear range (μM)

LOD (nM)

LOQ (nM)

Interference

Sample

Ref

Cefepime

Penicillinase@CHIT/ PtNPs-ZnO/ ZnHCF/FTO electrode

CV

0.1
750

100

-

Gastric lavage

Chauhan et al. (2021)

Acetaminophen

Chitosan/TiNPsDNA/CPE

DPV

0.5
300

140

-

Serum and pill

Jazini et al. (2020)

Carbamazepine

Fe3O4/PANI
Cu (II)/CILE

DPV

0.05
30

32

-

Blood serum and urine

Fatahi et al. (2020)

Chlorambucil

MnO2@NiFe2O4/ GCE

DPV

0.025
150

4.68

-

Amphetamine, ketamine, ephedrine, thebaine, metham phetamine, codeine Ca21, Mg21, Na1, Al31, Cl 2 , uric acid, folic acid, ascorbic acid, dopamine NaCl, KNO3, tryptophan, cysteine, uric acid, ascorbic acid. Dopamine, uric acid, glucose, mercury, dipheny lamine, sodium, potassium, nitrite, diuron

Tablet, human urine, drinking water

Sakthivel et al. (2019)

(Continued)

Table 8.1 (Continued) Analytes

Biosensor

Technique

Linear range (μM)

LOD (nM)

LOQ (nM)

Interference

Sample

Ref

Chloroquine

rGO@WS2/GCE

DPV

0.5
82.4

40

-

Human blood serum, pharma ceutical formulation

Srivastava et al. (2019)

Didanosine

PPy/rGO/PGE

DPV

0.02
50.0

8

-

Tablet and urine

Karimi-Maleh et al. (2018)

Ethambutol

HRP/ZnONPs/ rGO/GCE

DPV

2
32

21.4

671.3

Pharmaceutical form

Chokkareddy et al. (2018)

Etoposide

DNA/GO/ CoFe2O4/ZnAlLDH/FTO bioelectrode

DPV

0.2
10

1.0

-

D-glucose, creatine hydrate, Lascorbic acid, uric acid, Lcysteine, urea K1, Cl 2 , Na1, Br 2 , glucose, sucrose, uric acid, methionine Ca21, K1, Cl 2 , Ag1, Br 2 , Na1, SO32 2 , glucose, ascorbic acid, sucrose Na1, K1, Ca21, Mg21, Fe21, uric acid, glucose, ascorbic acid, citric acid, methionine, valine, caffeine, ibuprofen, aceta minophen

Human blood plasma, serum, and urine

Vajedi and Dehghani (2020)

Indomethacin

ZnFe2O4/ MWCNTs/CPE

DPV

5.0
200

500

Metoclopramide

ZnFe2O4/ MWCNTs/CPE

DPV

0.6
90

130

Nilutamide

Co-Ni-Cu-MOF/ NF

DPV

0.5
900.0

0.48

Streptomycin

Cyt c/ZnONPs/ MWCNTs/GCE

DPV

0.02
2.22.8

56.2

-

-

-

-

Cu21, K1, Na1, SO422, NO32, Cl2, glucose, glutamine, lysine, citric acid, ascorbic acid, uric acid, dopamine NO3-, SO42-, CO32-, glucose, sucrose, fructose, ascorbic acid, urea, dopamine, citric acid NaCl, AgNO3, CaCl2, NaSO4, sucrose, glucose, urea, ascorbic acid, dopamine, citric acid

Human serum, urine, pharma ceutical products

Hassannezhad et al. (2019) Hassannezhad et al. (2019)

Tablet, human serum

Akhter et al. (2021)

Pharmaceutical form

Chokkareddy et al. (2021)

(Continued)

Table 8.1 (Continued) Analytes

Biosensor

Technique

Linear range (μM)

LOD (nM)

LOQ (nM)

Interference 21

1

2

Temozolomide

ds-DNA/Au-NPs/ PGE

DPV

0.005
45.0

1.0

-

Mg , Li , Br , glucose, alanine, uric acid

Tetracycline

MCS@UiO-66NH2/Lac/ABTS/ CHIT/GCE

DPV

1.0
60

894

-

Atropine

SWCNT/Chit/GCE

SWV

0.1
150

16.5

54.9

Carbamazepine

MIPEDOT-GCE

SWV

1.0 3 102
2.0 3 103

0.980 3 106

2.97 3 106

Oxytetracycline, tetracycline, streptomycin, sulfate Glucose, uric acid, ascorbic acid, paracetamol, xanthine, hypoxanthine -

RR-ethambutol

CD/CuMOF/CNF/ GCE

SWV

0.1
100

31

-

-

5-

TiO2 sol
gel film/ PGE

Amperometry

0.1
1

3300

10000

Nafion-OMC/GCE

Amperometry

0.1
370

83.5

-

Aminosalicylic acid Isoniazid

Uric acid, ascorbic acid, dopamine, glucose

Sample

Ref

Blood serum, urine and pharma ceutical dosage form Milk and honey

Jahandari et al. (2019)

Datura stramonium, pharma ceutical form

Mane et al. (2018)

-

Hammoud et al. (2021) Upadhyay et al. (2020)

Racemic mixture, blood, urine and pharma ceutical dosage form Pharmaceutical formulations Human urine and blood serum

Zhong et al. (2021)

Rocha et al. (2021) Yan et al. (2011)

Guaifenesin

Ni-SiO2/MLG/ SPCE

Amperometry

0.1
317.5

5.7

-

Metronidazole

DNA/GCE

Potentiometry

300
1500

8050

-

Dasatinib

Au-NPs/rGO/dsDNA/GC

EIS

0.03
5.5

9.0

-

Tetracycline

Aptamer/AuNPs/ rGO/PGE

EIS

1.0 3 10210
1.0

3.05 3 1028

-

Triclosan

NA-DNA/IrO2 NPs/MWCNTsGr/GCE

EIS

0.01
10.0

1.2

3.7

Na1, K1, Cl2, NO32, SO422, uric acid, ascorbic acid, dopamine, catechol, resorcinol, hydro quinone, 4aminophenol, nitrophenol, flutamide, chlora mphenicol Ca21, Na1, F 2 , niclosamide, sulfonamide, amoxicillin, ascorbic acid, glucose, phenylalanine Streptomycin, sulfadiazine penicillin G

Pharmaceutical forms

Huang et al. (2021)

-

Rafique et al. (2022) TahernejadJavazmi et al. (2018)

Tablet, urine

Milk

Toothpaste, hand washing

MohammadRazdari et al. (2020) Jalalvand (2022)

(Continued)

Table 8.1 (Continued) Analytes

Promethazine

Biosensor

AuNP-GrNP/GCE

Technique

AdSV

Linear range (μM)

0.0010
1.0;1.0
10

LOD (nM)

0.40

LOQ (nM)

1.4

Interference 1

1

21

K , Na , Mg , Fe21, Zn21, I2, Cl2, NO32, CO322, SO422. glucose, urea, sucrose, uric acid, ascorbic acid, dopamine

Sample

Ref

Biological fluid and forensic samples

Promsuwan et al. (2020)

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147

differences. GC/CNT/HRP-GOx/Nafion composite electrode has the lowest detection limit of 0.5 μM, and its stability was determined as 97% after 1 week. CoPc
MWNTs/GC composite electrode shows approximately 93% stability after 90 days, while PtNW
CNT
CHIT has 85% stability (Table 8.1). The linear range, detection performance, and stability of the composite electrodes differ depending on the choice of materials used to form composites with CNT. These results emphasize the importance of choosing the composite material to be used in electrode design with suitable and ideal performance (Table 8.2). An important goal of analytical chemistry is to create fast, easy, and small analytical systems for the detection of potent toxic nerve agents. The studies present the results of developing a high shelf life and functionally stable cholinesterase biosensor for nerve gas detection (Arduini & Palleschi, 2012). Acetylcholinesterase (AChE) recovered from electric eels in various forms and butyrylcholinesterase (BChE) derived from horse serum were immobilized on screen-printed electrodes chemically modified with electrochemical medium Prussian blue (PB) to evaluate various types of immobilization (PB-SPEs). In order to measure the quantity of the enzymatic product thiocholine, PB-SPEs exploited the enzymatic activity of immobilized enzymes at 1200 mV in amperometric mode against the substrates acetylthiocholine and butyrylthiocholine. The glutaraldehyde, bovine serum albumin, and Nafion-immobilized BChE biosensor demonstrated a shelf life of more than 6 months and operational stability of up to 10 hours under dry circumstances at room temperature (Arduini & Palleschi, 2012). In another study, they reported using a new porous activated carbon (Vamvakaki & Chaniotakis, 1996) to immobilize polyelectrolyte-stabilized enzymes for the construction of biosensors with high operational and storage lifetimes. This is done by physically adsorbing the combination of enzyme and polyelectrolyte into the electrode pores without the need for chemical coupling agents, which prevents unneeded denaturation. The acquired stability of glucose and hydrogen peroxidase biosensors is shown using the polyelectrolyte diethylaminoethyl-dextran (DEAE-dextran) as an enzyme-stabilizing polyelectrolyte. The use of positively charged polyelectrolytes in conjunction with porous activated carbon has great promise for the development of diverse biosensors with long operating stability, high repeatability, and quick reaction times (Gavalas et al., 1998). The good operational stabilities can be attributed to the fact that there are strong interactions between polyphenol oxidases and tissues, which

Table 8.2 An overview stability and performance of CNT-based glucose biosensors. Electrode material

Detection limit (μM)

Linear range (mM)

Stability

Reference

(Au-Pt)NPs/CNT/Au/GOx GCE/PB/MWNT/GOx PDDA/GOx/PDDA/CNT/GCE GC/CNT/HRP-GOx/Nafion PtNW
CNT
CHIT CoPc
MWNTs/GC GOx
Pt
SG/CNT Au/CNT
GOx Gox/Pt/CNT/graphite Au/SWNT/GOD-HRP/PPy

400 12.7 7.0 0.5 3 1 N/A less than 10 50 90

0.5 to 17.5 0.0 to 8.0 1.5 3 1022 to 6.0 0.025 to 0.4 5 3 1023 to 15 1.0 3 1022 to 2.6 1 to 25 0.05 to 13 0.2 to 20 0.030 to 2.43

75% (25 days) 85% (14 days) 90% (30days) 97% (7 days) 85% (30days) 93.4% (30 days) 1 month 3 months 3 weeks 67% (14 days)

Chu et al. (2007) Zhu et al. (2006) Liu & Lin (2006) Yao & Shiu (2008) Qu et al. (2007) Zuo et al. (2012) Yang et al. (2006) Wang & Musameh (2003) Salimi et al. (2007) Zhu et al. (2007)

Au, gold; PtNPs, platinum nanoparticles; CNT, carbon nanotubes; GOx, glucose oxidase; GCE, glassy carbon electrode; MWNTs, multiwalled carbon nanotubes; PB, Prussian blue; PDDA, polydiallyldimethylammonium chloride; PtNWs, platinum nanowires; SWNTs, single-walled carbon nanotubes; CHIT, chitosan; HRP, horseradish peroxidase; CoPc
MWNTs/GC, Cobalt (II) phthalocyanine
multiwalled carbon nanotubes
modified glassy carbon; SG, sol
gel; PPy, polypyrrole; N/ A, not available.

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can be firmly immobilized on crosslinked gelatin films, providing better stability and performance to biosensors (Sarioglu et al., 2009). Another recent study demonstrated the use of very stable single-molecule enzyme nanocapsules (SMENs) as a biorecognition component in enzyme-based biosensors in place of the conventional natural enzyme. This study’s primary goal is to address the biggest obstacle and problems in the field of biosensors, such as thermal stability, organic solvent tolerance, long-term operational stability, etc., in order to overcome the inadequate stability of enzyme-based biosensors. Additionally, it describes research using nGOx SMENs as extremely reliable nano(bio)sensors for point-of-care diagnostic uses. The development and use of biosensors in point-of-care diagnostics, biomedical sensing, wearable technology, implantable equipment, and biofuel cells may be aided by the proposed SMEN-based nano(bio)sensors, which have strong stability in the changeable operating environment (Dhanjai et al., 2020). Alkane thiol self-assembled monolayers (SAMs) continue to see widespread use in electrochemical biosensors. But their usefulness reflects a potentially important compromise. Although effective electron transport is favored by shorter SAMs, they are poorly packed and relatively unstable. Although longer SAMs are more stable, their electron transfer efficiency suffers, which impairs sensor performance. In their study, Phares et al. compared the signaling and stability of biosensors made with a short, six-carbon monothiol with those made using one of two commercially available trihexylthiol anchors using the electrochemical DNA (E-DNA) sensor platform. They claim that despite the gain, specificity, and selectivity of all three anchors are practically identical, they all successfully enhance effective electron transfer and E-DNA signaling. The three anchors’ stabilities, however, differ greatly from one another. The flexible trithiol-fixed sensors exhibit enhanced stability, preserving 75% of their original signal and maintaining excellent signal properties after 50 days of storage in the buffer. Likewise, these sensors exhibit excellent temperature stability and robustness against electrochemical interrogation. The stability of sensors made using rigid trithiol fixation is comparable to that of monothiol, although both exhibit significant ( . 60%) signal loss upon wet storage or thermal cycling. When making SAM-based electrochemical biosensors, it may be possible to use a flexible trithiol anchor to increase sensor robustness without reducing electron transfer efficiency and adversely affecting sensor performance (Phares et al., 2009). The maximum repeatability, consistency, and stability in contemporary biosensors are now shown by label-free affinity electrochemical biosensors-

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Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

built electrodes made using semiconductor manufacturing technology (SMT) and a streptavidin biomediator. The point-of-care (POC) requirements are still not met by such biosensors in terms of these three factors, though. The goal of this study was to find a solution to the repeatability and accuracy restrictions brought on by issues with biosensor manufacturing in order to create a platform that can create products that go above and beyond POC requirements. A biosensor with remarkable repeatability, impressive precision, and great stability was created utilizing optimized SMT manufacturing parameters and an innovative, beyond-example binder. This shows that biosensors may be validated for POC development (Chen et al., 2020). One of the most crucial elements in the development of electrochemical immunosensors is the great stability of the redox signal. Redox-active species, on the other hand, typically exhibit low stability and weak conductivity, which prevents their use in electrochemical immunosensors. The conductive polymer poly(indole-5-carboxylic acid) (PIn-5-COOH) possesses ultrahigh redox stability, according to a study on stability. In contrast to earlier reports, where the redox signals only remained above 90% after 50 cyclic voltammetric cycles (CV), the redox signal of PIn-5COOH may remain 96.03% after 500 CV cycles in pH 6.2 buffer solution. The ultrahigh redox stability of PIn-5-COOH should be due to its stable nature, according to mechanism studies. For the detection of alphafetoprotein, electrochemical immunosensors made with the PIN-5COOH/MWCNTs-COOH nanocomposite demonstrated a broad linear range from 0.001 to 100 ng mL21 and a low detection limit of 0.33 pg mL 2 1. The development of electrochemical immunosensors with incredibly stable redox signals is now possible because of this study (Yang et al., 2019). The PIn-5-COOH/MWCNTs-COOH nanocomposite demonstrated good selectivity, wide linear range, low detection limit, ultra-stable redox signal, long-term stability, and reproducibility in electrochemical immunosensors (Yang et al., 2019). Due to their high potential for preserving the stability of the biosensor, enzyme immobilization, physical adsorption, capture technique, covalent bond method, chemical crosslinking method, electrochemical polymerization, and capture method are all of considerable interest (Lee et al., 2020). The polymers used to maintain the enzyme’s activity can provide a biocompatible microenvironment that helps increase the stability of biosensors. More importantly, it is possible to further increase the efficiency of developed biosensors by trapping negatively charged enzymes in positively charged polymers. This is due to the unique interaction between

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151

Figure 8.4 Used glucose oxidase SPE biosensors as seen via a microscope (10 and 60 times magnification). Aging biosensors: (A) a brand-new, unaltered blank electrode with screen printing. (B) A recently made glucose biosensor. (C) Research on the glucose sensor after prolonged usage. (D) The glucose biosensor following reusable research (Panjan et al., 2017).

positively charged polymers and negatively charged enzymes, resulting in stronger binding to increase stability (Lee et al., 2020) (Fig. 8.4). In a recent study, polymeric ionic liquids (PILs) were used to develop and create an AChE@PILs@AuNPs composite with a core
shell structure. PILs served as both enzyme immobilizers and modifiers in this build, resulting in the first amperometric AChE electrochemical biosensors. PILs served as the intermediate layer, while fused AuNPs served as the outside layer. AChE was kept in PILs to serve as the inner core. The developed electrochemical detection platform AChE@PILs@AuNPs/GCE has shown remarkable sensitivity for the detection of carbaryl and dichlorvos due to the charge property of PILs and the electron transport channel of AuNPs (DDVP). AChE@PILs@AuNPs/GCE further showed good stability, including thermal and long-term stability (Wan et al., 2022) (Fig. 8.5A). A delicate, reproducible, interference-free, inexpensive “off-the-shelf” H2O2 detection device was created by combining a financial carbon ink of an SPE with a sample of glassy carbon particles modified with Prussian blue (PB). Studies on these probes’ storage stability have also demonstrated that the PB modification process can offer long-term stability for PB activity and probe robustness. It has already been shown how to create PB, bulk-modified screen-printed electrodes utilizing activated PB microparticles (,38 μm) combined with carbon ink in a recent paper (O’Halloran et al., 2001). Results show a significant increase in stability over this study’s findings when compared to SPEs, which exhibited a 50% decline in H2O2 signal after 4 hours (Fig. 8.5B). Due to their promising

152

Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

Figure 8.5 (A) AChE biosensor construction and operation as shown schematically in relation to ATCl (Wan et al., 2022). (B) An analysis of the PB bulk-modified SPE’s operational stability (Ricci et al., 2003).

qualities, the sensors were later employed as supports for the immobilization of enzymes like glucose and lysine oxidase, producing a lysine and glucose biosensor. Furthermore, sensitivity, LOD, linearity range, storage stability, and operating stability all exhibited remarkable results. Recovery experiments on the probes’ usage to assess the amount of glucose in drinking samples produced positive outcomes. The sensors are an easy-touse, affordable, and mass-producible probe for glucose detection due to the lack of any enzyme immobilization or agent modification, following the cheap cost and the printing process of the sensors. Additionally, the excellent stability shown throughout a complete day qualifies these probes for “in situ” continuous investigation. Additionally, the fact that no high temperatures were present throughout the printing process is encouraging for the use of different oxidase enzymes (Ricci et al., 2003; O’Halloran et al., 2001).

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8.5 Conclusion Indeed, biosensors will be the most remarkable analysis kits of the near future. The main reason for this can be shown as factors such as fast analysis time, preprocessing required, high accuracy and sensitivity, outstanding selectivity, portability, and on-site analysis. In addition to these factors, biosensors have gained vital importance with the addition of extremely important factors such as stability and shelf life. Due to the incredible and unique properties they exhibit, the usage areas of biosensors are expanding day by day. It has application in a wide spectrum of areas such as health, food, defense, and engineering. The commercialization processes of biosensors, patents, and articles are increasing with a huge trend. In this chapter, the stability and shelf life of biosensors were discussed. The shortcomings and advantages of biosensors were examined in detail. It was understood that the stability and shelf life of biosensors were improved with advanced nanomaterials. However, although this issue remained in the background of scientific studies, it was understood that scientists should concentrate on the stability and shelf life of biosensors. It has been determined that these two factors are effective in taking place more in our daily lives. It was understood that this required the correct use of technology and the discovery of new materials. As a result, in this chapter, it is understood that in addition to factors such as the development of numerous biosensors and the determination of analytes, the stability and shelf life of biosensors, which are a little weak, should be further improved for them to be commercialized, included in routine analyses and to be more involved in our daily life.

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PART 3

Applications of nanostructured electrochemical biosensors

CHAPTER 9

Nanostructured materials-based electrochemical biosensor devices for quantification of antioxidants Bruna Coldibeli and Elen Romão Sartori Laboratory of Electroanalytical and Sensors, Department of Chemistry, Center of Exact Sciences, State University of Londrina, Londrina, Parana, Brazil

9.1 Introduction Antioxidants play a valuable role in human health in the diet. Present in various types of beverages such as wines, juices, teas, and coffee drinks, the antioxidants can occur naturally or are intentionally added to delay or inhibit the onset of oxidation reactions, keeping their sensory characteristics unaltered (Karadag et al., 2009). Their daily consumption contributes to numerous benefits to the human body: They boost immunity, reduce the risk of cancer and cardiovascular disease, provide defense against many diseases, and combat cellular aging due to the action of excess free radicals. In the broadest sense, an antioxidant molecule can be defined as a substance capable of preventing or delaying the action of free radicals and other molecules that can induce oxidation in molecules with reactive properties (Karadag et al., 2009; San Miguel-Chávez, 2017). Free radicals are constantly produced by the human body. They are products formed during the conversion of food nutrients into energy. Although they are essential for health, in excess, free radicals begin to oxidize healthy cells such as proteins and lipids (Zhong & Shahidi, 2015). These species have a single electron, are free to bond with any other electron, and are therefore highly reactive. Consumption of foods rich in antioxidants helps to delay, control, or prevent oxidative processes caused by excess free radicals in the body that lead to the development and propagation of degenerative diseases. In this context, recent advances in medicine and nutritional science have emphasized lifestyle changes and approaches based on diet and nutrition. As a result, the consumption of Novel Nanostructured Materials for Electrochemical Bio-sensing Applications DOI: https://doi.org/10.1016/B978-0-443-15334-1.00007-9

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foods and beverages with antioxidant properties that contribute to maintaining human health has increased significantly. The human antioxidant defense system consists of enzymatic (endogenous) and nonenzymatic (exogenous) systems. The enzymatic system is formed by a series of enzymes that the human body produces naturally. However, the efficiency that stimulates the production of this system decreases over the years. Therefore it is important to maintain the quality of the nonenzymatic defense system by taking antioxidants, which include a variety of substances of dietary origin, such as carotenoids, flavonoids, other phenolic compounds, vitamin A (retinol), vitamin C (ascorbic acid), vitamin E (tocopherol), and minerals (copper, selenium, and zinc) (Gulcin, 2020; Kumar et al., 2017; San Miguel-Chávez, 2017). Beverages such as wines, juices, teas, and brewed coffee drinks are sources of antioxidants. These compounds not only have beneficial effects on human health but can also influence the nutritional and physicochemical properties of each beverage. Therefore it is of paramount importance to control the quality of beverages containing natural antioxidants. Enzyme biosensors offer simple, fast (real-time analysis), and costeffective analytical approaches for this purpose. Moreover, biosensors developed by coupling enzyme recognition with electrochemical transducers based on nanostructured materials play an important role in the detection and determination of antioxidant compounds in beverages due to their sensitivity, stability, and selectivity (Pohanka & Skládal, 2008; Turner, 2013). Generally, the antioxidant compounds in beverages occur at low concentrations, and the enzymatic biosensors can detect or determine them due to their high sensitivity. Furthermore, these analytical devices have high selectivity and stability for more than 200 measurements (Gomes et al., 2020; Salamanca-Neto et al., 2020). This useful lifetime and reusability are due to the numerous efforts made in the search for suitable microenvironments that help to maintain the biological activity of the enzyme, either using nanostructured materials (Liu & Ju, 2003) or polysaccharides (Coelho et al., 2019; Mattos et al., 2019). In industry, electrochemical enzymatic biosensors are valuable for beverage quality control because these devices are selective, sensitive, have a low cost of construction and storage, and also offer the potential for miniaturization/ automation and rapid continuous monitoring (Freire et al., 2002; Rotariu et al., 2016). In this brief review, we present the electrochemical enzymatic biosensors developed with nanostructured materials for the determination of a

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specific antioxidant or total antioxidant content in real beverage samples (wines, juices, teas, blueberry syrup, and brewed coffee beverages) containing these compounds. The data collection was conducted for the last decade (2012
22) and considered scientific papers in which the application was specifically in beverages, with carbon- and metal-based electrodes made/modified from nanostructured materials, and that use the electrochemical reduction process to quantify or estimate antioxidant capacity. A total of 19 scientific articles presenting these specifications were used in this review.

9.2 Reference analytical methods employed for the determination of antioxidants in beverages Antioxidant capacity or total reducing power is defined as the ability of certain molecules to act as electron donors or proton receptors in oxidation
reduction reactions. All antioxidants present in the sample represent the antioxidant capacity, while the total phenolic content refers to the phenolic compounds, which are a group of antioxidants (Karadag et al., 2009; San Miguel-Chávez, 2017). It is a fact that a variety of methods are available today for the evaluation of antioxidant capacity and total phenolic content in beverages. However, a single technique does not guarantee the determination of the different types of antioxidant compounds present in a complex sample. The most commonly used analytical methods for determining antioxidant capacity in beverages are based on colorimetric methods monitored by UV-vis spectrophotometry, including 2,2-diphenyl-1-picrylhydrazyl (DPPH) and Trolox equivalent antioxidant capacity (TEAC), which use the 2,2-azino-bis-3-ethylbenzothiazoline-6-sulfonic acid reagent (ABTS). Total phenolic content (total phenols and polyphenols) is another important parameter of total antioxidant capacity, and the Folin
Ciocalteu assay is the well-known method for this purpose (Munteanu & Apetrei, 2021; San Miguel-Chávez, 2017). These colorimetric methods, on the other hand, are time-consuming, have low sensitivity, require a large number of samples, and use reagents that are not environmentally friendly. Determination of total antioxidant activity by DPPH is based on electron donation by the antioxidants to neutralize the DPPH radical, which is accompanied by decolorization of the purple color measured at 515 nm. This method is based on the assumption that the antioxidant activity is equal to the electron-donating capacity or so-called reducing

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power (Zhong & Shahidi, 2015). DPPH is a radical and an oxidizing agent at the same time. Methanol must be used for this test because DPPH is soluble only in this medium. In addition, several antioxidants react very slowly or not at all with DPPH due to steric hindrances, and there may be interference from other molecules that have absorption in the same wavelength range as DPPH, such as the anthocyanins (500
550 nm), which may interfere with the results and make them difficult to interpret (San Miguel-Chávez, 2017; Zhong & Shahidi, 2015). The ABTS assay measures the ability of antioxidants to scavenge the highly stable chromophore cation radical ABTS, either by direct reduction via electron donation or by radical quenching via hydrogen atom donation, and the balance of these two mechanisms is generally determined by the structure of the antioxidant and the pH of the medium. Thus, in the presence of an antioxidant, there is a discoloration of the blue
green color of the cation radical ABTS, tending to be colorless, which is quantified as a decrease in absorbance at 734 nm (San Miguel-Chávez, 2017; Zhong & Shahidi, 2015). Trolox (6-hydroxy-2,5,7,8-tetramethylchroman-2-carboxylic acid) is used as an antioxidant standard. A disadvantage of the ABTS method is that the radical must be generated before the test is carried out and the reaction is only completed after 16 hours (Amarowicz & Pegg, 2019). The Folin
Ciocalteu method is based on the reduction of the Folin
Ciocalteu reagent by phenolic compounds under alkaline conditions. This reagent consists of a mixture of phosphomolybdic acid (H3PMo12O40) and phosphotungstic acid (H3PW12O40). In the presence of phenolic compounds, these two acids are reduced to molybdenum oxide (Mo8O23) and tungsten oxide (W8O23), respectively, resulting in a bluish color that absorbs in the visible range with a maximum wavelength at 725 nm (Zhong & Shahidi, 2015). This reduction occurs in an alkaline medium, and the most suitable reagent is sodium carbonate. The result of the total phenolic content in the sample is expressed in gallic acid equivalents using an analytical curve. Ferulic acid, catechin, tannic acid, and sinapic acid were also used as standard compounds (Amarowicz & Pegg, 2019). The disadvantage of this method is that the Folin
Ciocalteu reagent may also react with other nonphenolic substances present in complex samples, especially with any readily reducible components present in the test mixture, such as ascorbic acid (Amarowicz & Pegg, 2019). Other compounds that may interfere are ascorbic acid, sugars, organic acids, aromatic amines, proteins, and also some inorganic substances such as iron

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sulfate, potassium nitrite, sodium phosphate, and manganese sulfate, leading to an overestimation of the total phenolic compounds. Despite these considerations, the use of enzymatic biosensors to evaluate a specific antioxidant or its total content in beverages makes sample preparation simpler, can be miniaturized, is time-saving, requires minimal sample pretreatment, and reduces costs (Hoyos-Arbeláez et al., 2017; Rotariu et al., 2016). In addition, they provide high sensitivity with very good detection limits and selectivity for electrochemical measurements of antioxidants in complex samples. Their use avoids the interference in the analysis by the presence of some compounds such as ascorbic acid, which can mask the presence of other organic acids at lower concentrations, or the high content of anthocyanins, which can interfere with direct spectrophotometric measurements (Lino et al., 2014; Sousa et al., 2004).

9.3 Oxidoreductase enzymes used in the development of electrochemical biosensors for the determination of phenolic compounds (antioxidants) An enzymatic biosensor can be defined as an analytical device consisting of an immobilized enzyme in close contact with a suitable transducer (Fatibello-Filho & Capelato, 1992; Thévenot et al., 2001; Turner, 2013). Generally, oxidoreductase enzymes are used for the determination of phenolic compounds (antioxidants) in beverages (Rotariu et al., 2016), with tyrosinase, laccase, and peroxidase being the most widely used in the last decade because of their ability to catalyze a wide range of redox reactions. Antioxidants can be determined directly on the surface of electrochemical sensors by exploring their oxidation process. However, this determination is associated with a high overvoltage, the contribution of interfering species, and parallel reactions with the formation of polymeric products that can passivate the sensor surface, whereas electrochemical biosensors containing an oxidoreductase enzyme can overcome these inconveniences (Rosatto et al., 2001; Siraj et al., 2021). The use of the biosensor assembled with this class of enzymes leads to the formation of species that can be electrochemically reduced in an electrode surface to detect/determine the phenolic compounds at a convenient low potential (at potentials close to 0.0 V vs SCE) (Rosatto et al., 2001). The measured reduction current is proportional to the concentration of the antioxidant (phenolic compound) in the solution. The stage of catalysis of the phenolic compound by the enzyme oxidoreductase

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(catalytic oxidation) leads to high concentrations of the oxidized species in the solution, which consequently leads to a larger signal of the current intensity resulting from the electrochemical reduction (Rosatto et al., 2001). For this reason, the reduction signal of the oxidized species is used to quantify the phenolic compound. In addition, there are other ways to monitor the concentration of phenolic compounds, such as detecting the consumption of O2 or the consumption of H2O2. Tyrosinase (monophenol monooxygenase; EC 1.14.18.1) and laccase (benzenediol: oxygen oxidoreductases, EC 1.10.3.2) belong to the enzyme family of multicopper oxidases because they have copper atoms distributed between the bonding sites (Rosatto et al., 2001). They are widely distributed in some plants, animals, and microorganisms and exhibit different substrate selectivity and mechanisms. Although laccase and tyrosinase are copper proteins that catalyze the oxidation of phenolic compounds, their specificities and mechanisms are different. Tyrosinase enzymes catalyze reactions of mono- (except ferulic acid) and diphenols, such as p-cresol, catechol, and levodopa, which are first hydroxylated to the ortho position to form o-diphenols and further oxidized to o-quinones, while the enzyme is oxidized back to its native form by reduction of molecular oxygen (Rosatto et al., 2001). This enzyme shows no significant activity in the oxidation of p- and m-benzenediols and their substituted derivatives (Bucur et al., 2021). Eqs. (9.1) and (9.2) represent the two successive phases of the action of the enzyme tyrosinase in the catalysis of phenolic compounds involving molecular oxygen. Hydroxylase activity: tyrosinase

phenol 1 1/2O2
! catecholðdi-phenolÞ 1 O2

(9.1)

Diphenolase activity: tyrosinase

catechol 1 1/2 O2
! o-quinone 1 H2 O

(9.2)

Laccases catalyze the oxidation of a variety of substrates such as phenol, ortho-, para- and meta-benzenediols and their substituted derivatives, aromatic amines, and heterocyclic compounds with the concomitant fourelectron reduction of oxygen to water [Eq. (9.3)], without the intermediate formation of hydrogen peroxide (Arregui et al., 2019; Brugnari et al., 2021; Rodríguez-Delgado et al., 2015; Rosatto et al., 2001). laccase

o-diphenol 1 O2
! o-quinone 1 2 H2 O

(9.3)

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Another oxidoreductase enzyme used for the determination of phenolic compounds and, consequently, the antioxidant capacity related to them is the peroxidases (hydrogen peroxide oxidoreductase; EC 1.11.1.7). These enzymes are hemeproteins (cofactor: Fe31 protoporphyrin), and horseradish peroxidase (HRP) is the most commonly used peroxidase enzyme, mainly because of its high stability over long periods at room temperature and because it is commercially available. Its response to phenolic compounds is based on the mechanism of double displacement by two substrates, H2O2 and the electron-donating phenolic compounds. The enzyme is oxidized by hydrogen peroxide to form a first intermediate [HRP-I; Eq. (9.4)]. The enzyme is then reduced to its native form (HRP [Fe31]) in two steps, with the phenolic compound being oxidized in each step [Eqs. (9.5) and (9.6)]. AH2 and AH are the reducing substrate and its oxidized radical species, respectively. The oxidized form of the phenolic compound can be reduced on the electrode surface [Eq. (9.7)] and used for its quantification in a real sample. Another way to quantify the phenolic compound is to correlate H2O2 with phenolic compound content (Hu et al., 2008; Krainer & Glieder, 2015; Rosatto et al., 2001; Veitch, 2004).
HRP Fe31 1 H2 O2 ðsubstrateÞ - HRP-I 1 H2 O (9.4) HRP-I 1 AH2 -HRP-II 1 AH

(9.5)


HRP-II 1 AH2 -HRP Fe31 1 AH 1 H2 O

(9.6)

AH 1 2H1 1 2e2 -AH2

(9.7)

The enzymatic biosensors developed for the determination of antioxidants can be set up in two different main configurations: the addition of the enzyme to a carbon paste modified with nanostructured materials by procedures similar to those used to prepare the solid graphite electrode or immobilization of the enzyme by physical or chemical means on the surface of a solid electrode modified with nanostructured materials (Munteanu & Apetrei, 2022). This one was most commonly used because of its better sensitivity, and the enzyme does not leach into the solution during analysis. On the other hand, it is easy to prepare, versatile and offers the possibility to immobilize cofactors and mediators when necessary.

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9.4 General aspects of the construction of electrochemical enzymatic biosensors When designing a biosensor, it is very important to have a sensor (transducer) that has high redox currents and lower redox overpotential relative to the target analyte, as this ensures better biosensor performance, such as sensitivity, stability, and selectivity (Abdulbari & Basheer, 2017; Malhotra & Ali, 2018; Turner, 2013). This is achieved by preparing the sensor that is to receive the enzyme with nanostructured materials, either carbonbased or metal nanoparticles. The shape and size of the nanomaterials provide an increase in electrochemical activity compared to that of the corresponding raw material (Luo et al., 2006). Carbonaceous structures, present on a nanoscale of 1
100 nm, show new properties due to their dimension, which are completely different from those of the bulk material and improve the sensitivity of the sensor (Bezzon et al., 2019), and for this reason, it has been widely used in the development of different sensors (Hareesha et al., 2021; Manjunatha, 2020; Prinith et al., 2021; Raril & Manjunatha, 2020; Scremin et al. 2021, 2022; Tigari & Manjunatha, 2020). In addition, the high reactivity of various carbon structures allows functionalization, which can increase the selectivity for the desired analysis or enable the immobilization of enzymes on their surface to obtain biosensors (Bezzon et al., 2019). Metal nanoparticles are structures of pure metal (e.g., gold, platinum, and titanium) or their compounds (oxides, sulfides, and hydroxides) with dimensions (length, width, and thickness) in the size range of 1
100 nm. At such small sizes, many metals have improved the analytical performance (sensitivity and selectivity) of the bare electrode used for surface modification (Barsan & Brett, 2016). This is due to their large surfacearea-to-volume ratio, which immensely increases the contact area (Campbell & Compton, 2010; Jamkhande et al., 2019; Kumar et al., 2018; Mody et al., 2010). In the last decade, carbon nanotubes, fullerenes, graphene, and metallic nanoparticles have been used as nanostructured materials for the development of biosensors to detect/determine antioxidants. By exploring the properties of nanomaterials and their dimensions at the nanoscale, biosensors can detect low concentrations of the analyte of interest (Malhotra & Ali, 2018). In addition, some metallic nanoparticles can allow proteins to maintain their biological activity upon adsorption by providing a microenvironment similar to that of redox proteins in native systems (Barsan &

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Brett, 2016; Liu & Ju, 2003; Luo et al., 2006). Thus enzymes can be conveniently immobilized on existing functional groups on these nanomaterials used to modify the surface of electrodes commonly used in electroanalysis (glassy carbon, graphite, metallic) and still retain their bioactivity efficiently. Immobilization of the enzyme on the surface of the sensor must be considered to obtain a stable device with a long useful life (several measurements without surface renewal or loss of enzyme activity). Different methods are used for the immobilization of the enzyme on the surface of electrodes modified with nanostructured materials. Physical adsorption, entrapment, and crosslinking have been the main methods used in the development of biosensors for the determination of antioxidants (Fernández-Fernández et al., 2013; Sassolas et al., 2012). Physical adsorption is a simple and inexpensive immobilization method in which the enzyme is attached to the electrode surface by hydrophobic and ionic interactions, hydrogen bonds, and van der Waals forces, by amino acid groups of the enzyme and the groups present on the surface of the electrochemical sensor (Sassolas et al., 2012). Entrapment is another method of enzyme immobilization in which the enzyme can be entrapped in a porous matrix (polyacrylamide, collagen, alginate, or gelatin), retaining the enzyme in a physical form and allowing the passage of the substrate and products. In the crosslinking method, the enzyme is immobilized on the surface of the electrochemical sensor with a chemical bi- or multifunctional reagent; that is, the chemical molecule has at least two reactive ends that bind to specific groups of amino acids on the enzyme surface via chemical bonding. Glutaraldehyde, epichlorohydrin, and 1-ethyl-3-(3-[dimethylamino] propyl) carbodiimide hydrochloride (EDC) are commonly used as chemical agents for protein crosslinking. Although this method is more difficult and expensive than adsorption, it can provide a more stable immobilized enzyme. In this method, the immobilized enzyme is better protected from the environment and is not easily leached into the solution during measurements because the strength of the chemical bond is greater than in the physical adsorption or entrapment methods (Fernández-Fernández et al., 2013; Sassolas et al., 2012). Fig. 9.1 shows a schematic representation of a carbon- or metal-based electrode modified with nanostructured materials to enhance the analytical signal. After this modification, an oxidoreductase enzyme is physically or chemically immobilized on the surface of the nanomaterial to detect and identify antioxidants in beverages. This figure also shows the

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Figure 9.1 Schematic presentation of (A) electrochemical cell employed in the voltammetric/amperometric analysis, which consists of reference, working (biosensor), and auxiliary electrodes immersed in a supporting electrolyte (buffer solution); (B) a carbon- or metal-based electrode modified with nanostructured materials (carbon nanostructured material, metal nanoparticle, and both nanostructured materials in the same modification) employed for the immobilization of an oxidoreductase enzyme.

electrochemical cell used in the measurements, which consists of three electrodes: reference, working (biosensor), and auxiliary, all inserted into a supporting electrolyte. The potential signal applied to the surface of the working electrode is measured in relation to the fixed potential of the reference electrode and the current flow between the working electrode and the auxiliary electrode. In amperometry, the current generated by the chemical reaction of the oxidized species (which occurs during enzymatic oxidation) on the surface of the transducer is measured while a constant potential is applied. In contrast, in voltammetry, the potential is varied during the measurement of the reduction current (Haddad & Haddad, 1990).

9.5 Application of enzymatic biosensor for the determination of a specific antioxidant or its total content in beverages In the last decade, polyphenols such as chlorogenic acid, caffeic acid, and gallic acid were the exogenous antioxidants that emerged as targets determined in beverages using electrochemical enzymatic biosensors. Catechol, guaiacol, and Trolox were used as antioxidant molecules to measure the total content of the antioxidant in beverages employing enzymatic biosensors. Other exogenous antioxidants that were determined using biosensors were tyrosol, rutin, catechin, and quercetin.

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Next, the analytical methods described in the literature for the determination of antioxidants in different types of beverages using electrochemical enzymatic biosensors are presented. These were distinguished according to the type of nanostructured material used in the modification of the sensor for the immobilization of the enzyme, namely carbon-based nanomaterial (single-walled carbon nanotubes [SWCNTs], multi-walled carbon nanotubes [MWCNTs], reduced graphene oxide [rGO], and carbon black), metal nanoparticle (AuNPs, Pt
Pd bimetallic alloy NPs, PtNPs, and PdNPs), carbon-based nanomaterial/metal nanoparticle (CNTs/AuNPs, fullerene/AuNPs, rGO/PtNPs, graphene nanoplatelets/ AuNPs, and graphene quantum dots [GQDs]/molybdenum disulfide [MoS2] nanoflakes).

9.5.1 Carbon-based nanomaterials Table 9.1 presents the enzymatic biosensors reported in the literature employing carbon-based nanomaterials. The antioxidant, the base electrode used to prepare the biosensor, and the nanostructured material used to modify the base sensor are presented. In addition, this table shows the potential used for the quantification of the antioxidant and also the LOD value. Polyphenol compounds were determined in green tea employing the tyrosinase biosensor developed using a carbon screen-printed electrode (CSPE) modified with SWCNTs and iron(II) phthalocyanine (FePc) (Apetrei et al., 2012). Tyrosinase was immobilized by glutaraldehyde crosslinking technique, and the analytical determination was based on the catechin reduction peak at about 10.15 V (vs Ag/AgCl) by amperometry. The FePc was used in the modification to provide an increase in the peak current, thereby increasing the sensitivity of the biosensor. Catechin was used in this study to relate the content of polyphenol compounds in green tea; however, a study of interferences possibly present in this type of samples or of other phenolic compounds was not realized. Catechin presented a linear response range for 5.0
250 μmol L21 in 0.01 mol L21 phosphate buffer solution (pH 7.0), with a limit of detection (LOD) of 0.89 μmol L21. Infusions of green tea were prepared and analyzed by the Tyr/SWCNTsFePc/C-SPE biosensor and the Folin
Ciocalteu method, showing a good relationship between the results of the total content of polyphenols. Tyrosinase biosensor based on nanostructured carbon materials was also developed for the determination of caffeic acid in beers (Wang et al.,

Table 9.1 Enzymatic biosensors reported in the literature employing carbon-based nanomaterials. Biosensor

Antioxidant

Base electrode

Nanostructured material

Enzyme (origin)

Potential

LOD (μmol L21)

Samples

Reference

Tyr/SWCNTsFePc/C-SPE

Polyphenol compounds (catechin) Caffeic acid

C-SPE

SWCNTs

Tyrosinase (mushroom)

10.15 Va

0.89

Green teas

Apetrei et al. (2012)

GCE

SWCNTs


0.1 Vb

0.06

Beers

CPE

MWCNTs

Tyrosinase (mushroom) Tyrosinase (mushroom Agaricus bisporus)


0.25 Vc

-

Red and white wines

Wang et al. (2013) Sýs et al. (2015)

GCE

MWCNT

Laccase (Trametes versicolor)


0.1 Vb

6.0

Red wine, white wine, and black tea

Zappi et al. (2018)

GCE

rGO and MWCNTs

0.0 Vb;
0.1 Vb

0.3; 0.5

Fruit juices

Vlamidis et al. (2017)

CGE

rGO

Laccase (Trametes versicolor); tyrosinase (mushroom) Laccase (Trametes versicolor)


0.15 Vc

0.076

CBPE

Carbon black

Laccase (Botryosphaeria rhodina MAMB05)

10.23 Vc

0.026

Red fruit, peppermint, and green lemon tea Red wine, apple juice, lemon juice, and green tea

Boujakhrout et al. (2016) Gomes et al. (2020)

PANI/TyrSWCNTs/GCE Tyr/Nafion/ MWCNTs/CPE

GCE/MWCNTs/ [Ch][Phe]/Lac

Lac/rGOMWCNTs/GCE Tyr/rGOMWCNTs/GCE Lac/GC-rGO/GCE

CBPE/CMB-Lac

a

vs Ag/AgCl. vs SCE. vs Ag/AgCl (3.0 mol L21 KCl).

b c

Trolox equivalent antioxidant capacity Total polyphenols content (gallic acid) Total polyphenols content (catechol) Total phenolic compounds (catechol) Quercetin

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2013). The GCE was modified with SWCNTs dispersed in chitosan. Then, tyrosinase was immobilized on the SWCNTs with the EDC reagent. After, polyaniline was dropped onto this surface to obtain the final biosensor, with tyrosinase enzyme embedded into SWCNTs and polyaniline (PANI/Tyr-SWCNTs/GCE). This material offered a porous microstructure with numerous cavities, promoting a highly accessible surface area for the reaction between enzyme and substrate. The developed biodevice was evaluated every 3 days, and after 24 days, its response was about 90% of the initial, showing relatively good stability, which the authors justified by the biocompatible microenvironment provided by polyaniline for the protection of the enzyme-specific ability. Amperometric measurements of caffeic acid at
0.1 V (vs SCE) were recorded in 0.1 mol L21 phosphate buffer solution (pH 6.5), and a linear concentration range was obtained between 0.25 and 470 μmol L21, with LOD of 0.06 μmol L21. The authors did not present studies of possible interfering compounds in the developed biosensor response. Before the analysis, beer samples were degasified by centrifugation and diluted five times in the supporting electrolyte. In this work, the authors did not use the spectrophotometric method to compare the results obtained. The analyses were carried out by the standard addition method and presented recovery percentages of 100.2%
102.2%. Another example of a nanostructured tyrosinase biosensor based on amperometric measurements of the Trolox molecule (a water-soluble derivative of vitamin E with antioxidant properties) was reported by Sýs et al. for the determination of the equivalent antioxidant capacity in red and white wines. To obtain this biosensor, the surface of a carbon paste electrode (CPE) was modified with MWCNTs dispersed in N,Ndimethylformamide (Sýs et al., 2015). Then, the tyrosinase enzyme was immobilized on this surface with Nafion, named Tyr/Nafion/ MWCNTs/CPE. Wine samples were directly transferred to the electrochemical cell containing 0.1 mol L21 phosphate buffer solution (pH 7.0), and the amperograms were registered by the reduction process of Trolox at
0.25 V versus Ag/AgCl (3.0 mol L21 KCl). The authors compared the results obtained using the biosensor with those obtained using the official spectrophotometric method based on DPPH, emphasizing that the use of the biosensor avoids the use of solutions with unstable radicals. Another biosensor for quantifying the total content of polyphenols in wines and black tea was constructed by modifying a GCE with activated MWCNT-COOHs dispersed in the choline-phenylalanine [Ch][Phe]

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ionic liquid (Zappi et al., 2018). Enzyme immobilization was performed by mixing laccase in MWCNTs-COOH/ionic liquid suspension and further crosslinking with glutaraldehyde. The biosensor response decreased by 10% after 10 days and 33% after 20 days. This stability was attributed to the antifouling properties of the ionic liquid and the high enzyme loading, which were effectively immobilized. The proposed biosensor was coupled with flow injection analysis (FIA) for the amperometric detection of gallic acid at
0.1 V (vs SCE). This antioxidant exhibited a linear behavior in the concentration range of 6.0
300 μmol L21, with LOD of 6.0 μmol L21 in 0.5 mol L21 acetate buffer solution (pH 5.0). Gallic acid was used to relate the amount of polyphenol compounds in red wine, white wine, and black tea. The analyses made by the GCE/MWCNTs/ [Ch][Phe]/Lac biosensor and the Folin
Ciocalteu method were compared, and the differences between the obtained results by both methods were justified by the lack of specificity from the spectrophotometric method. Additionally, according to the authors, the determination of polyphenols performed by the biosensor did not show interference from reducing sugars, and the low work potential prevented the interference of ascorbic acid and quercetin. Vlamidis et al. developed two biosensors, a laccase, and a tyrosinase biosensor, both based on the immobilization of the enzyme on the GCE surface modified with MWCNTs and reduced graphene oxide (rGO) dispersed in N,N-dimethylformamide (Vlamidis et al., 2017). The graphene oxide was electrochemically reduced after drop-casting onto the GCE surface. According to the authors, MWCNTs combined with rGO provided better electrode sensitivity than when used separately. The enzyme was immobilized immediately after the electrochemical reduction of graphene. The laccase biosensor was prepared by the immobilization with bovine serum albumin reticulated with glutaraldehyde (Lac/rGOMWCNTs/GCE) and operated in a 0.1 mol L21 acetate buffer solution (pH 4.5), whereas the tyrosinase was immobilized with chitosan (Tyr/ rGO-MWCNTs/GCE) and used in 0.05 mol L21 phosphate buffer solution (pH 6.5). Storing the biosensors in buffer solutions proved to be a better alternative when compared to storage under dry conditions. The biodevice composed of laccase maintained 93.3% of its original response after 1 month, whereas the tyrosinase biosensor showed less stability and lost its initial response at about 50% after 2 days of use. Chronoamperometric measurements at 0.0 V and
0.1 V (vs SCE) of various catechol concentrations showed linear responses in the range of

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1.0
300 and 1.0
340 μmol L21, with LOD values of 0.3 and 0.5 μmol L21, respectively, for the laccase and tyrosinase biosensors. The authors noted that the tyrosinase biosensor showed higher sensitivity compared to the laccase biosensor and that this increase in sensitivity was not related to the higher activity of the biomolecule, as the tyrosinase enzyme lost some of its activity even when it was very well immobilized. In addition, the tyrosinase biosensor also responded to gallic acid and rutin. Benzoic acid and 2,3-di-hydroxybenzoic acids act as inhibitors because they block electron transfer from the electrode to the Cu ions. The poor response of the tyrosinase biosensor to other analytes tested (pyrogallol, dopamine, epicatechin, catechin, caffeic acid, and chlorogenic acid) was attributed to the lower activity of the immobilized enzyme. Nevertheless, the two biosensors were used in the determination of total polyphenol content in commercial juices. The samples were centrifuged, filtered, diluted in the appropriate buffer solution, and immediately analyzed by the two biosensors. The results obtained for the antioxidant capacity of the samples using both biosensors were compared with the ABTS spectrophotometric method, showing differences between these results. In addition, two of the analyzed samples showed higher values of antioxidant capacity. The authors suggested that this is related to the known high content of carotenoids and ascorbic acid in these two samples. However, the analytical response of biosensors was not studied separately for these compounds. The total content of phenolic compounds was analyzed in herbal teas using an amperometric laccase biosensor (Boujakhrout et al., 2016). For this purpose, the CGE was modified with a nanohybrid material based on glycol chitosan (GC)-rGO, and the enzyme was immobilized on this modification by the crosslinking technique with glutaraldehyde. Through electrochemical impedance spectroscopy (EIS), the authors demonstrated the high conductivity of the nanohybrid material and the high enzyme loading on the biosensor surface. Better stability of the biosensor was achieved when stored under wet conditions (0.5 mol L21 phosphate buffer solution [pH 5.5]) at 4°C, which promoted the maintenance of the full performance of the biosensor. Catechol was used as a standard molecule to determine the total phenolic content in herbal teas. Its reduction process, measured at
0.15 V versus Ag/AgCl (3.0 mol L21 KCl), showed a linear behavior at concentrations of 0.2
15 μmol L21, with LOD of 0.076 μmol L21, in 0.1 mol L21 phosphate buffer solution (pH 5.5). An interference study was performed for D-glucose, fructose, Dgalactose, NO32, 17β-estradiol, 17α-ethinyl estradiol, bisphenol A, uric

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Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

acid, and ascorbic acid. With the exception of ascorbic acid, which caused an increase in the cathodic current of about 17%, the other compounds did not affect the catechol response. The samples were prepared by infusing red fruit tea, peppermint tea, and green lemon tea with boiling water. The total phenolic content was determined in the samples by the Lac/ GC-rGO/GCE biosensor and the Folin
Ciocalteu method, and the results correlated linearly. Carboxymethyl-botryosphaeran (CMB) was used to covalently immobilize laccase in an aqueous solution using EDC and Nhydroxysuccinimide (NHS) (Gomes et al., 2020). A sufficient aliquot of this solution was then layered on the surface of the carbon black paste electrode (CBPE). This solution containing laccase immobilized on CMB can be used to prepare various biosensors. The CBPE/CMB-Lac biosensor was evaluated in terms of its stability, and after 30 days of experiments, the RSD of its response was calculated at 3.24%. This result was justified by the effective immobilization of the enzyme in the CMB, which preserves the biocatalytic activity of the enzyme and ensures the long-term stability of the biosensor. The cathodic peak resulting from quercetin reduction at the electrode surface at 10.23 V (vs Ag/AgCl (3.0 mol L21 KCl) was monitored by SWV in 0.5 mol L21 phosphate buffer solution (pH 6.0) and showed a linear response in the concentration range of 0.0498
0.794 μmol L21, with LOD of 0.026 μmol L21. Other phenolic compounds such as epinephrine, dopamine, paracetamol, guaiacol, and catechol did not cause significant interference in the cathodic response. The constructed biosensor was used for the quantification of quercetin in red wine, apple juice, lemon juice, and green tea. Samples were transferred directly to the electrochemical cell without any sample treatment, and analyses were performed using the standard addition method. In this work, the authors used high-performance liquid chromatography (HPLC) to compare the results obtained. They found that the results obtained by both methods were statistically equivalent at a 95% confidence level.

9.5.2 Metal nanoparticles Table 9.2 presents the enzymatic biosensors reported in the literature employing metal nanoparticles. The antioxidant, the base electrode used to prepare the biosensor, and the nanostructured material used to modify the base sensor are presented. In addition, this table shows the potential used for the quantification of the antioxidant and the LOD value.

Table 9.2 Enzymatic biosensors reported in the literature employing metal nanoparticles. Biosensor

Antioxidant

Base electrode

Nanostructured material

Enzyme (origin)

Potential

LOD (μmol L21)

Samples

Reference

AuNPs/TTFTCNQ/PVC/Tyr

Phenolic compounds content (catechol) Catechin

AuNPs/ TTFTCNQ/ PVC Pt disk

AuNPs

Tyrosinase (mushroom)

0.0 Va

0.643

White, rosé, and red wines

Sánchez-Obrero et al. (2012)

AuNPs

10.14 Vb

0.0012

Apple juices

Total phenolic content (tyrosol) Polyphenol content (chlorogenic acid) Polyphenolic content (caffeic acid)

C-SPE

AuNPs

Tyrosinase (mushroom) Tyrosinase (mushroom)


0.2 Vc

1.7

Beers

Singh et al. (2013) Cerrato-Alvarez et al. (2019)

GCE

AuNPs

Horseradish peroxidase


0.2 Va

2.7

Green coffee and yerba mate

Tulli et al. (2018)

CPE

Pt
Pd bimetallic alloy NPs

10.22 Va

0.37

White wines

Pusch et al. (2013)

Chlorogenic acid

CPE

PtNPs

10.42 Va

0.18

Coffee

Rutin

GCE

PdNPs

Peroxidase (cauliflower Brassica oleracea L. var. botrytis) Laccase (Botryosphaeria rhodina MAMB-05) Laccase (Botryosphaeria rhodina MAMB-05)

10.33 Va

0.084

Green tea and red wine

Salamanca-Neto et al. (2020) Mattos et al. (2021)

Pt/AuNPs
PPy/Tyr Tyr/AuNPs/SPCE Lap/{[(VBT)(VBA)4]41}  25/ AuNPs/HRP/GCE PO/BMI.PF6Pt0.5-Pd0.5/ CPE

Lac/PtNPs/ BOT/CPE Lac/(αFe2O3.PdNPs)/ GCE

vs Ag/AgCl (3.0 mol L21 KCl). vs Ag/AgCl. c vs silver pseudo-reference electrode. a

b

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Sánchez-Obrero et al. used a tyrosinase enzyme-based biosensor for the determination of phenolic compound content in wines (SánchezObrero et al., 2012). The biosensor was prepared by immobilizing the tyrosinase enzyme in a colloidal gold nanoparticle (AuNPs)-tetrathiafulvalene-tetracyanoquinodimethane-PVC (AuNPs/TTF-TCNQ/PVC) composite electrode by the crosslinking technique. The enzyme was added to the composite by the drop-casting technique, and after drying, it was immersed in a glutaraldehyde solution for 40 min. The authors mention the good electrochemical properties of the biosensor but did not present studies about it. The analytical curve was obtained using FIA with amperometric detection at 0.0 V (vs Ag/AgCl [3.0 mol L21 KCl]) and showed a linear concentration range between 0.6 and 10 μmol L21 and a LOD of 0.643 μmol L21 in 0.05 mol L21 phosphate buffer solution (pH 7.4). The wine samples (white, rosé, and red) were properly diluted in the supporting electrolyte and analyzed in terms of the polyphenolic compound content by extrapolating the analytical curve, with the results expressed in catechol. The authors declared that the proposed biosensor has good stability for 2 weeks and recommend replacing it after 3
4 weeks. The results obtained using the biosensor were significantly different from those obtained by the Folin
Ciocalteu reference method. The methods are based on different principles. The reference method consists of a redox reaction of phenols, and the biosensor is based on an enzyme reaction, which depends on the applied potential. Using the biosensor, different fractions of total polyphenols are obtained by changing the reduction potential, obtaining with the biosensor results corresponding to the “antioxidant fraction.” This indicates that proper selection of method or a combination of methods is important for a valid evaluation of total antioxidant content in beverages. Tyrosinase was also used as a biorecognition element in the biosensor developed for the determination of catechin (Singh et al., 2013). The enzyme was entrapped in the matrix of the composite of AuNPs and polypyrrole (PPy) electrodeposited in a platinum disk electrode, resulting in the Pt/AuNPs
PPy/Tyr biosensor. EIS and cyclic voltammetry studies showed that the presence of the AuNPs in the composite matrix enhanced the electrochemical response and led to an increase in conductivity, current intensity, and diffusion coefficient. The voltammetric profile of catechin showed three electrochemical processes: the oxidation of the catechol moiety to o-quinone at 10.24 V, the reduction of o-quinone to catechin at 10.14 V, and a small peak at 10.62 V (vs Ag/AgCl) corresponding to

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179

the oxidation of the hydroxyl group present in the central ring of catechin. The current intensity of the reduction process was monitored by cyclic voltammetry in the presence of different concentrations of catechin, and a linear range was observed from 0.001 to 0.01 μmol L21 with LOD of 0.0012 μmol L21 in 0.05 mol L21 phosphate buffer solution (pH 7.0). The authors suggested that the better analytical features obtained in this study compared to other studies reported in the literature might be due to the incorporation of gold nanoparticles. Packed apple juice samples were analyzed using the Pt/AuNPs
PPy/Tyr biosensor and chromatography, and the catechin concentration was calculated by correlating the analytical signal with the respective analytical curve. For the chromatographic measurements, methanolic extracts of each sample (5%) were prepared from apple juices filtered twice through filter paper (0.2 μm), while no sample preparation was mentioned for the amperometric measurements. The obtained results differed from each other by up to 9.2%. Moreover, the long-term stability study of the biosensor showed 85% of its initial sensitivity in 70 days. Cerrato-Alvarez et al. developed a simple biosensor based on glutaraldehyde crosslinking immobilization of tyrosinase on a C-SPE modified with AuNPs (Tyr/AuNPs/C-SPE) and its application in the determination of total phenolic content in commercial beers (high fermented, low fermented, and nonalcoholic) (Cerrato-Alvarez et al., 2019). This content in beers was expressed as mg L21 of tyrosol since this is the main phenolic compound in this beverage type. The analytical curve was obtained by amperometry at
0.2 V (vs silver pseudo-reference electrode) in the range of 2.5
40 μmol L21 in 0.1 μmol L21 phosphate buffer solution (pH 7.0), with LOD of 1.7 μmol L21. Sample preparation was simple, the beers were degassed, and the pH was adjusted to 7.0 with 0.1 mol L21 phosphate buffer solution. This biosensor showed an RSD of 1.7% for 29 measurements. The analyses performed by the Folin
Ciocalteu method showed higher concentrations of phenolic content in the beer samples. The authors commented that this occurred because of the nonselectivity of this method compared with the biosensor, which has the advantage of being restricted to the detection of phenolic compounds that are substrates of tyrosinase. It should be noted that the authors did not perform a study of interferences for the developed biosensor in the sample types analyzed. In the construction of a biosensor for polyphenol quantification in green coffee and yerba mate beverages, the HRP enzyme was immobilized by electrostatic forces on nanohydrogels composed of laponite (Lap),

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AuNPs, and a vinylbenzyltriethylammonium polycation copolymerized with vinylbenzylthymine groups (Lap/{[(VBT)(VBA)4]41}  25/AuNPs/ HRP) (Tulli et al., 2018). The AuNPs incorporated into this matrix caused an improvement in conductivity, resulting in a reduction of the charge transfer resistance. This biosensor was air dried at 25°C and immersed in 0.1 mol L21 phosphate buffer solution (pH 7.0) for 45 minutes for the swelling step before use. The mechanism of this biosensor was to monitor the reduction process of the oxidized polyphenol by amperometry at
0.2 V versus Ag/AgCl (3.0 mol L21 KCl), which was previously formed from the enzymatic oxidation of the phenolic compound in the presence of H2O2. The assay for polyphenolic content was based on the use of chlorogenic acid, and the linear response was obtained up to 4.2 μmol L21 with LOD of 2.7 nmol L21, in 0.1 mol L21 phosphate buffer solution (pH 5.0), containing 600 μmol L21 H2O2. According to the authors, typical substances present in plant tissues, such as glucose, ascorbic acid, tartaric acid, and citric acid, were investigated as possible interfering compounds, and none of them caused a significant change in the chlorogenic acid response. Furthermore, this biosensor maintained 95% of its initial response after 7 days of storage in the buffer solution at 8°C. The samples of green coffee and yerba mate were prepared by adding an appropriate amount of each one in water at 80°C, shaking for 10 minutes, and then filtering. The results of the analyses using the biosensor and the Folin
Ciocalteu spectrophotometric method showed that the analytical methods were not statistically different at a 95% confidence level. Pusch et al. reported the development of a biosensor based on the modification of CPE with platinum (Pt)
palladium (Pd) bimetallic alloy nanoparticles dispersed in 1-butyl-3-methylimidazolium hexafluorophosphate ionic liquid (Pt-Pd-BMI.PF6) together with peroxidase (PO) enzyme immobilized on the nanoclay matrix (PO/BMI.PF6Pt0.5-Pd0.5/ CPE) by physical adsorption (Pusch et al., 2013). The nanostructured materials added to the graphite paste led to an improvement in the analytical response of the caffeic acid. The reduction process of this phenolic compound at 10.22 V (vs Ag/AgCl [3.0 mol L21 KCl]) was used for the determination of caffeic acid in white wines by SWV in 0.1 mol L21 acetate buffer solution (pH 5.0). Linearity was observed in the concentration range of 2.7
22 μmol L21, with a LOD of 0.37 μmol L21. Moreover, the biosensor showed 80% of its initial response after 80 days (over 600 measurements; renewed surface as necessary), demonstrating excellent

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stability. The authors observed that chlorogenic acid, gallic acid, quercetin, and catechin showed peaks at very close potential values, suggesting the lack of specificity of the PO/BMI.PF6Pt0.5-Pd0.5/CPE biosensor, but its selectivity for this group of phenolic compounds. An interference study showed that ascorbic acid, glucose, and sucrose did not cause significant changes in the biosensor response, even at 10-fold excess; nonetheless, sulfite and bisulfite (1:10 molar ratio) caused a change in the cathodic current of caffeic acid of about 50%. The wine samples were acidified with hydrochloric acid and bubbled with nitrogen to eliminate the interfering species before analysis. The proposed biosensor was used in the determination of polyphenols in white wines from five different grape varieties and showed good recovery percentages (95.5%
108.3%). Additionally, the samples were also analyzed by the Folin
Ciocalteu method, and despite the higher results, the methods showed good correlation (r 5 0.990). A laccase biosensor was constructed by Salamanca-Neto et al. for the determination of chlorogenic acid in coffee beverages. Employing a statistical mixture designer, the optimum ratio of the biosensor content was established as 1:6:1 of platinum nanoparticles (PtNPs), exopolysaccharide botryosphaeran (BOT), and laccase (Salamanca-Neto et al., 2020). The layers of each material were sequentially deposited on the CPE previously prepared with graphite oxide (Lac/PtNPs/BOT/CPE). The response of the biosensor decreased by 6.42% after 150 measurements were performed over 30 days. The analytical curve for chlorogenic acid was constructed based on the 5-o-caffeoylquinic acid response, the major constituent of the caffeic acid group in coffee, by SWV in 0.1 mol L21 phosphate buffer solution (pH 4.0) using the reduction process at about 10.42 V versus Ag/AgCl (3.0 mol L21 KCl). It increased linearly with concentrations in the range of 0.56
7.3 μmol L21, with a LOD of 0.18 μmol L21. An interference study was performed for species commonly present in coffee such as ferulic acid, p-coumaric acid, caffeic acid, caffeine, and glucose. Biosensor response variations were calculated to be up to 4.5% for an equal molar ratio and up to 6.3% for a 1:10 molar ratio. Traditional and specialty coffee beverages were analyzed by the biosensing method and by chromatography. The results showed relative errors lower than 6.42% and high correlation (r 5 0.975). The authors concluded that this laccase biosensor can serve as a selective method for the determination of chlorogenic acid for the quality control of brewed coffee beverages.

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Mattos et al. immobilized laccase on the photoactive material hematite (α-Fe2O3) decorated with palladium nanoparticles (PdNPs) to develop a biosensor for the highly sensitive determination of the flavonoid rutin in green tea and red wine (Mattos et al., 2021). Laccase was immobilized on PdNPs decorating α-Fe2O3-faceted microcubes by the physical adsorption technique. EIS demonstrated that the nanomaterial caused an increase in the electron transfer rate in the electrochemical system. The combination of the photoelectrochemical process with the biocatalytic oxidation by enzymes was explored to quantify this flavonoid based on the resulting cathodic signal at 10.33 V versus Ag/AgCl (3.0 mol L21 KCl) by SWV. The analytical curve showed linearity in the concentration range of 0.08
300 nmol L21, with a LOD of 0.084 nmol L21. Other phenolic compounds such as epinephrine, dopamine, paracetamol, guaiacol, catechol, hydroquinone, phenylamine, quercetin, chlorogenic acid, ferulic acid, gallic acid, coumaric acid, caffeic acid, and quinic acid were evaluated as potentially interfering species, but none of them caused a significant effect in the rutin response, even at 10-fold excess. Green tea and red wine were analyzed directly by the Lac/(αFe2O3.PdNPs)/GCE biosensor without prior sample treatment. The determined rutin concentrations were compared to those obtained by the HPLC method and showed no statistical difference at the 95% confidence level. The biosensor was used for 30 days with an RSD of the cathodic signal of 2.8%. These results demonstrate that the immobilization of the enzyme on the PdNPs, although performed by physical adsorption, proved to be efficient, indicating that the enzyme activity was maintained over several analyses without renewing the surface.

9.5.3 Carbon-based nanomaterial/metal nanoparticle Table 9.3 presents the enzymatic biosensors reported in the literature employing carbon-based nanomaterials and metal nanoparticles. The antioxidant, the base electrode used to prepare the biosensor, and the nanostructured material used to modify the base sensor are presented. In addition, this table shows the potential used for the quantification of the antioxidant and also the LOD value. Amatatongchai et al. reported a laccase biosensor for the determination of total phenolic content in tea infusions (Amatatongchai et al., 2013). For this purpose, the authors used a GCE modified with a nanocomposite of NH2-functionalized carbon nanotubes (CNT-NH2), AuNPs, and

Table 9.3 Enzymatic biosensors reported in the literature employing carbon-based nanomaterials and metal nanoparticles. Biosensor

Antioxidant

Base electrode

Nanostructured material

Enzyme (origin)

Potential

LOD (μmol L21)

Samples

Reference

GCE/CNTNH2/AuNPs/ Lac-BSA Au-SPE/AuNPsfullerenols/Lac

Total phenolic content (gallic acid) Polyphenol content (gallic acid)

GCE

CNT-NH2 and AuNPs


0.05 Va

0.71

Fullerene and AuNPs


0.1 Va

6.0

Jasmine and mulberry tree teas Red and white wines

Amatatongchai et al. (2013)

Au-SPE

Lac/AuNPs/ GNPl/C-SPE

Phenolic antioxidant capacity (hydroquinone) Total polyphenolic content (caffeic acid)

C-SPE

GNPl and AuNPs

Laccase (Trametes versicolor) Laccase (Trametes versicolor) Laccase (Rhus vernicifera)


0.05 Vb

1.5

Wine and blueberry syrup

Zrinsski et al. (2020)

C-SPE

rGO and PtNPs

Laccase (Trametes versicolor)


0.1 Va

0.09

Eremia et al. (2013)

Total polyphenolic content (caffeic acid)

C-SPE

GQDs and MoS2 nanoflakes

Laccase (Trametes versicolor)


0.05Vc

0.32

Blueberry, lime, forest fruits, and exotic fruit teas Red wine

C-SPE/Pt-NPs/ rGO/Lac/ Nafion C-SPE-MoS2GQDs-Lac a

vs Ag/AgCl. vs Ag/AgCl (3.0 mol L21 KCl). c vs silver pseudo-reference electrode. b

Lanzellotto et al. (2014)

Vasilescu et al. (2016)

184

Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

bovine serum albumin (BSA) as a matrix for immobilization of the enzyme with glutaraldehyde. An enzyme
BSA solution was applied to the electrode surface, and after 30 min, a glutaraldehyde solution was also added and dried at room temperature. Gallic acid was used as a standard for the electroanalytical studies of the GCE/CNT-NH2/AuNPs/Lac-BSA biosensor. The evaluation of total phenolic content was based on the reduction process of gallic acid at
0.05 V (vs Ag/AgCl) in 0.1 mol L21 citric buffer solution (pH 6.0). Using the FIA system with amperometric detection, the gallic acid concentrations showed a linear behavior in the range of 3.0
60 μmol L21 and LOD of 0.71 μmol L21. The infusions of jasmine and mulberry were analyzed by the proposed amperometric biosensor and the classical Folin
Ciocalteu spectrophotometric method, and the results showed that the methods significantly agreed with each other. Another nanostructured laccase-based electrochemical biosensor was developed by Lanzellato et al. (2014). These authors coupled two different nanomaterials (AuNPs and fullerenes); first, functionalized AuNPs were immobilized on a gold screen-printed electrode (Au-SPE) surface modified with a self-assembled monolayer of suitable thiols, and then, the polyhydroxy fullerene was linked to the AuNPs-modified electrode, where the laccase enzyme was finally immobilized by using EDC and NHS reagents (Au-SPE/AuNPs-fullerenols/Lac). Characterization studies showed that the nanostructured materials improved the electrochemical performance of the Au-SPE in terms of electroactive area and electron transfer kinetics. Using gallic acid as the polyphenol standard, the biosensor was operated in the FIA system with amperometric detection at
0.1 V (vs Ag/AgCl) and showed a linear concentration range of 30
300 μmol L21, with a LOD of 6.0 μmol L21 in 0.1 mol L21 acetate buffer solution (pH 4.5). The sensitivity of the biosensor was 87% after 120 days of preparation and about 53% after 240 days. The authors did not present a study of the biosensor response in the presence of other antioxidant compounds, since these compounds and others may be present in beverages. Samples of white and red wines were diluted 10 and 100 times, respectively, in the buffer solution before the analysis. The polyphenol content was determined by the described biosensor and Folin
Ciocalteu method, and the results agreed with each other. Zrinski et al. also reported the use of C-SPE to obtain a biosensor to evaluate the phenolic antioxidant capacity in wine and blueberry syrup samples (Zrinski et al., 2020). The surface of this electrode was modified with AuNPs and graphene nanoplatelets (GNPl), and the laccase enzyme

Electrochemical enzymatic biosensors

185

was immobilized on gold nanoparticles with Nafion (Lac/AuNPs/GNPl/ C-SPE). They observed that both nanomaterials improved the electrical conductivity of the biosensor. Furthermore, the presence of AuNPs caused a homogeneous distribution of the enzyme, due to the preferential adsorption of the enzyme to gold rather than to carbon, since in graphene nanoplatelets the authors reported that there was an agglomeration of the enzyme in small platelet-like structures. The biosensor showed stability over 5 days after preparation, with no significant decrease in the current response. The electrochemical reduction of the enzymatic oxidation product of hydroquinone was monitored by chronoamperometry at a fixed potential of
0.05 V (vs Ag/AgCl [3.0 mol L21 KCl]) in 0.1 mol L21 phosphate buffer solution and presented linear response in the range of 4.0
130 μmol L21, with a LOD of 1.5 μmol L21. The authors carried out a very detailed study on compounds that could interfere with the evaluation of phenolic antioxidant capacity. Ascorbic acid and other compounds that can be electrochemically oxidized at low potentials and glucose were tested as possible interferents. In the presence of these compounds, the biosensor showed low interference ( . 10%). On the other hand, in the presence of caffeine, caffeic acid, p-coumaric acid, sinapic acid, syringic acid, ferulic acid, p-hydroxybenzoic acid, and phenol, a response .23% was obtained. The total phenolic antioxidant capacity was determined in red wine and blueberry syrup by the proposed biosensor, and the results agreed with those obtained from the conventional spectrophotometric method using ABTS. Eremia et al. modified a C-SPE with PtNPs and rGO to immobilize laccase by the adsorption method and stabilized it on a Nafion membrane (Eremia et al., 2013). The authors highlighted that a better analytical response was obtained when the rGO and PtNPs were used together in the modification of C-SPE, due to the synergistic effects of both nanomaterials, which played an important role in facilitating electron transfer. The C-SPE/PtNPs/rGO/Lac/Nafion biosensor was stored on a silica gel layer at 4°C and preserved its initial response for 2 weeks, but after 6 weeks it showed a decrease of 12.6% in its response. Amperometric measurements at
0.1 V (vs Ag/AgCl) of different concentrations of caffeic acid revealed linear response in the range of 0.2
2 μmol L21, with a LOD of 0.09 μmol L21 in 0.1 mol L21 acetate buffer solution (pH 5.0). Infusions of the teas (blueberry, lime, forest fruits, and exotic fruits) were prepared in hot water (80°C) and diluted before the analysis. Total polyphenolic content, expressed as molar equivalents of caffeic acid, was

186

Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

determined in these samples by the developed biosensor and compared to the results from the Folin
Ciocalteu method. The higher values obtained in the spectrophotometric method were justified by this nonspecific reaction; consequently, the method is affected by chemical interferences from the other compounds present in the matrix. Additionally, they comment that some fruit infusions may have a high content of anthocyanins that contribute to the reduction of phosphomolybdate ions in the Folin
Ciocalteu reagent. A C-SPE was also used to fabricate another laccase biosensor (Vasilescu et al., 2016). The surface of this electrode was modified with a nanocomposite formed by molybdenum disulfide (MoS2) nanoflakes and graphene quantum dots (GQDs). The immobilization of the enzyme occurred through electrostatic interaction between the negatively charged laccase and the positively charged GQDs. The synergic interaction between GQDs and MoS2 sheets improved the electrochemical performance due to the increase in the electroactive area and conductivity caused by the nanocomposite. The C-SPE-MoS2-GQDs-Lac biosensor maintained 85% of its initial response after 4 weeks stored at 4°C. Caffeic acid was used as a standard for the total polyphenolic content assays, and its electrochemical reduction was detected by chronoamperometry at a work potential of
0.05 V (vs silver pseudo-reference electrode) in 0.1 mol L21 acetate buffer solution (pH 5.0). Linear responses were obtained in two concentration ranges: 0.38
10 and 10
100 μmol L21, with a LOD of 0.32 μmol L21. Ethanol was evaluated as an interfering agent due to its presence in the wine matrix, but it did not cause any change in the biosensor response. The red wine samples were properly diluted in acetate buffer solution (pH 5.0) and analyzed by the laccase biosensor and the Folin
Ciocalteu method. The total polyphenolic content in the red wine determined by both methods agreed, except for two samples, but the statistical test applied to these divergent results showed no significant difference. However, the authors did not carry out studies of other phenolic compounds with the biosensor, since they may be present in red wine samples, as well as sugars, vitamins, and flavonoids.

9.6 Conclusion In view of this, it can be concluded that the modification of the base electrode (transducer) with nanostructured materials is very important to improve the conductivity and consequently to obtain a better

Electrochemical enzymatic biosensors

187

performance (sensitivity) of the devices, as well as to support the immobilization of the enzyme. Furthermore, this brief review showed that it is important to investigate different phenolic compounds and other inorganic compounds or ions in the analytical response of the biosensor to evaluate the selectivity and effect of the concomitant and/or other antioxidant compounds in the sample. It may be that not all phenolic compounds show the same reduction potential value on the surface of a given biosensor. In addition, other inorganic compounds or ions may have an inhibitory effect on the enzyme used in the construction of the biosensor. It was also observed that some results obtained by classical methods for determining antioxidant activity or total antioxidant content differed from those observed when electrochemical enzymatic biosensors were used. In the classical spectrophotometric method, all antioxidant compounds are computed in the final result, introducing interference with the results and their interpretation. The biosensor is based on an enzyme reaction that depends on the applied potential and gives results corresponding to the “antioxidant fraction.” Therefore it is important and necessary to investigate concomitant compounds in the biosensor response, as well as other antioxidant compounds. Finally, the use of electrochemical enzymatic biosensors represents an alternative or complementary method for the determination of a specific antioxidant in beverages, which is very promising for use in industries, such as quality control, benefiting the general population. This trend in the use of biosensors is due to their selectivity, stability, and sensitivity in determining a wide range of antioxidants and other compounds in complex matrices. In addition, they present low cost, can be miniaturized/automated, and allow rapid continuous monitoring.

Acknowledgments The authors gratefully acknowledge financial support and scholarships from the Brazilian funding agencies CNPq (grant numbers 408591/2018-8, 305320/2019-0), Fundação Araucária do Paraná, and CAPES (grant number 88887.674846/2022-00).

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CHAPTER 10

Nanostructured electrochemical biosensors for pesticides and insecticides Yashaswini1, S. Pratibha2, Y.B. Vinay Kumar3 and K.H. Sudheer Kumar4 1

Department of Physics, B.M.S. Institute of Technology and Management, Affiliated to Visvesvaraya Technological University, Belagavi, Karnataka, India Department of Basic Science, Sri Venkateshwara College of Engineering, Affiliated to Visvesvaraya Technological University, Belagavi, Karnataka, India 3 Department of Computer Science and Engineering, R.L. Jalappa Institute of Technology and Management, Affiliated to Visvesvaraya Technological University, Belagavi, Karnataka, India 4 Department of Chemistry, B.M.S. Institute of Technology and Management, Affiliated to Visvesvaraya Technological University, Belagavi, Karnataka, India 2

10.1 Introduction Nanotechnology is the nanoscale phenomena applied in the field of science and engineering where materials at a nanoscale are utilized to design, characterize, and produce the desired structures for making devices and systems. Nanotechnology is the most promising technological field for the various research fields. Nanoparticles (NPs) are utilized as antioxidants and antireflectants cosmetics and sunscreens industries. NPs are engineered through physicochemical and biological routes to use for commercial applications. These NPs can attach firmly to the surface, so that causing health issues and the risk of detachment are lesser. NPs have found broad applications in commercial products right from personal care products to paints. The hazardous effects of other NPs present in consumer products are unknown and are still under research. Nanostructured materials (NMs) have a microstructure that is characterized in terms of length scale of the range of a few nanometers (1
10 nm) (Boverhof et al., 2015). The properties of NM change compared to single crystals/coarse-grained polycrystals with the same chemical composition. This deviation is due to the fact that there will be a reduced size/dimension of NM (Boverhof et al., 2015). The prominence of NM in the development of technology is due to their enhanced physicochemical and biological properties compared to that of bulk materials (Marques et al., 2021). The development Novel Nanostructured Materials for Electrochemical Bio-sensing Applications DOI: https://doi.org/10.1016/B978-0-443-15334-1.00010-9

© 2024 Elsevier Inc. All rights reserved.

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of biosensors through nanotechnology is useful in noticing the presence of minute amounts of toxins, pathogens, volatile compounds, and many organic compounds in body fluids and in various environmental samples, which are in turn use full in areas such as food processing, monitoring of diseases in humans, detection of bioterrorism agents, and assessing effectiveness of remediation process. In agriculture, using pesticides a variety of pests can be controlled to increase the crop production and its efficiency. Biosensors are used to estimate the pesticide contents in food samples to ensure the safety of food consumption (Rani et al., 2021). Though, the over dose of pesticides in agriculture will damage the environment as well as consumers’ health due to the high pesticide residues in food (Sikora et al., 2020). The harmful pesticide residues left out in the surrounding environment or the use of polluted food causes severe health issues especially irritation of eye or skin, problems on neurodegenerative diseases, and reproduction and even leads to cancer (Nahhal & El-Nahhal, 2021). For instance, in humans, most common pesticides are organophosphates and carbamates, which hinder the enzyme acetylcholinesterase, which is accountable for many biological and chemical reactions (Pope et al., 2005). The most common techniques used to detect these pollutants in the low concentration levels are high-performance liquid chromatography (HPLC) and gas chromatography coupled with mass spectrometry (Aquino et al., 2020, 2010). These conventional routes have several limitations such as requiring costly equipment, pretreatment operations, and highly skilled professionals. A sensor can be used as an alternative to find the presence of an analyte in a sample and estimate the amount of analyte. The sensor comprises a detection system called a receptor, a transducer, and a reader (Walcarius et al., 2013). The intention of utilizing nanomaterials in the biosensors is to enhance the stabilization of electrochemical biosensors, thereby augment the sensitivity, catalysis process, and required low potentials, and help to transfer the electrons rapidly from the active center to the surface of the electrode in nanostructured electrochemical biosensors (Zhu et al., 2020; Zhang et al., 2020; Alam et al., 2020; Zhang & Mousavi, 2020). In this framework, biosensors can be utilized as a possible alternative for sensing the amount of pesticides in the food contents which are lowcost and highly efficient devices (Zamora-Sequeira et al., 2019). Biosensor is a device composed of bioreceptor (biological component) and transducer (detector). The function of the bioreceptor is to identify the target analytes and the transducer detects the component and in turn converts into a measurable signal. The types of biosensors being used are tissuebased, DNA biosensors, enzyme-based, thermal biosensors, piezoelectric

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biosensors, and immunosensors. Electrochemical biosensors are defined as the type of biosensors that utilize an electrochemical transducer to carry out their functions. In today’s world, various electrochemical biosensors are developed for sensing the pesticide and insecticide levels. These electrochemical biosensors are extremely sensitive, quick, valid, and easy to employ. An overview of conventional methods developed for the diagnosis of pesticides has been discussed. The chapter describes the detection of some common pesticides present in food and environment samples such as malathion, chlorpyrifos, parathion, carbaryl, and paraoxon using electrochemical biosensors. An electrochemical biosensor is employed to detect the two most commonly used vegetable crop insecticides such as methyl parathion and chlorpyrifos, which are described in detail. High-performance electrochemical biosensors have been designed by using nanomaterials due to their large surface to volume ratio and excellent electrical properties. The importance of nanostructures in the electrochemical biosensors is to fill the gap between the converter and the bioreceptor, which is at the nanorange. The nanostructures have been employed to develop an electrochemical biosensor, which provides sealing between the converter and bioreceptor at the nanoscale dimension. The promising electrochemical biosensors have developed using carbon nanotubes (CNTs) as a base material due to their high resistance (Reta et al., 2018). In addition, CNTs reveal the excellent properties such as chemical stability and conductivity, high sensitivity, good biocompatibility, and easy function with any desired chemical samples (Gupta et al., 2018). Nanostructure metal oxide (Zn, Cu, Ni, Ti, and Fe)-based sensors are advantageous due to their low range of limit of detection, wide linearity, reproducibility, and stability. Copper oxide (CuO) nanomaterials are advantageous in terms of their accurate surface area, magnificent electrochemical activity, and the capacity to stimulate electron transfer reactions at low potential values (Pushpanjali et al., 2020; Prinith & Manjunatha, 2020; Raril & Manjunatha, 2018; Balliamada Monnappa et al., 2019). Zinc oxide (ZnO) nanostructured materials are attractive due to their high electrical conductivity, nontoxicity, cost-effectiveness, and chemical steadiness properties (Pushpanjali et al., 2020; Edwin et al., 2021). Electrochemical biosensors are classified as catalytic and propulsion types based on the nature of the biomaterial detection process. The general electrochemical sensor techniques are potentiometric analysis, chronometry measurement, voltammetry, impedance measurement, and field effect transistor (FET) (Hareesha et al., 2021).

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This chapter provides an extensive structure of the efficient NM electrochemical biosensors useful for pesticide identification and detection in food matrices and insecticide levels. The NM utilized to develop the electrochemical biosensors will be thoroughly deliberated. The shortcomings of the developed electrochemical biosensors to sense the pesticide and the future scope afford us with a broad route map for the probable future.

10.2 Properties of nanostructured electrochemical biosensors The properties of nanostructured electrochemical biosensors are as follows: • Rapid detection. • Accurate measurement. • Easy to operate. • Low response time. • High sensitivity and reliability. • Proper functional materials for the electrode.

10.3 Fabrication of nanostructured electrochemical biosensors Till now, remarkable studies have been carried out in the electrochemical sensor field and the sensors developed are extensively commercialized and found extensive applications in many industrial, clinical, and agricultural fields (Bukkitgar et al., 2020). Fig. 10.1 depicts the fabrication of

Figure 10.1 Nanostructured electrochemical biosensors.

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nanostructured electrochemical biosensors. The fabrication of electrochemical biosensors requires the essential elements, which are electrodes that serve various purposes such as aptamers and target recognition and binding. It also acts as a carrier to convert biological signals into electrical signals. The most used electrochemical biosensors among many electrodes are the disk electrodes (DE) and screen-printed carbon electrodes (SPCEs). The advancement in the field of NM, sensing electrodes are modified by increasing the number of nanocomposites such as multiwalled carbon nanotubes (MWCNTs), metal nanoparticles (MNPs), graphitized MWCNTs, Au nanoparticles, or glass carbon electrodes that are adopted to it (Kazemi & Khajeh, 2011). Also, the spongy carbon nanospheres, multifunctionalized composites of graphene (Naderi Asrami et al., 2018), nanoribbon-structured reduced graphene oxide with a covalent organic framework (Jiménez-Rodríguez et al., 2021), and carbon nanofiber-gold nanoparticles (CNFs-AuNPs) (Shetti et al., 2019) are used. These nanocomposites are useful to amplify the electrochemical signals and improve the sensing performance due to a larger surface to volume ratio, extremely good conductivity, and improvisation of the aptamer biocompatibility.

10.4 Nanostructured electrochemical biosensors fabricated for the detection of pesticides and insecticides Electrochemical biosensors fabricated using nanostructured materials are of much importance owing to their small size, transportability, quick measurements, and small sample size. The most commonly found insecticides are organophosphates (OPs), which are the esters of phosphoric acid, indicated by a general formula O

P(OR)3. They are called a class of synthesized chemicals that are developed to kill insects. These are widely utilized worldwide for agricultural fields and residential purposes including gardens (Huang et al., 2021). The OPPs are extremely toxic to insects and animals including amphibians, birds, and mammals. In agriculture, OPPs are well received ascribed to their broad-spectrum effect, high efficiency, and proper persistence. Generally, there will be meticulous inhalation and ingestion of OPPs seen when someone is exposed continuously to polluted soil, water, and food. Carbamates are known as esters of Nmethyl carbamic acid, which are normally employed as insecticides. Some derivatives of carbamic acid such as thiocarbamide acid and dithiocarbamic acid are used as herbicides. In agriculture, there exist more than fifty

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chemical compounds identified as carbamates that are used as insecticides (Gholipour et al., 2020). A major concern for many countries is the amount of pesticide residues in food and environmental samples. Accurate detection of pesticides in food samples and environment is very important to avoid viable hazards to organisms to prevent human health complications. The pesticides that are responsible for severe pollution in water and food are malathion, profenofos, phorate, isocarbophos, omethoate, etc. Biosensors have been developing as a latest area to detect and provide high-sensitive immunosensors, higher specificity, and reproducibility to the system. The basic structure of an electrochemical biosensor consists of a transducer, a biorecognition element, and a signal amplifier. The transducer converts the chemical information into an electrical signal, the biorecognition element selectively binds to the target analyte, and the signal amplifier amplifies the signal for detection. The requisites of these biosensors consist of systems with two or three electrodes (Yi et al., 2020). When target material interacts with the recognition element, there will be generation of the electrical signals (Jiao et al., 2017). These biosensors have been recognized as the most attractive sensors for the detection of pesticide. These are a widely used type of biosensors that make use of the surface of the electrochemical transducers for the detection of analytes in biological and nonbiological matrices. Some of the recent studies on the development of electrochemical biosensors for the detection of pesticides are tabulated in Table 10.1. In general, the principle of detection includes the generation or consumption of electrons in a biological reaction as reported in enzyme-catalyzed reactions (Yao et al., 2020). Electrochemical biosensors can be categorized into two types such as amperometric sensing, potentiometric sensing, and impedimetric sensing. In the case of amperometric sensing methods, the sensing will be performed based on the measurement of electrochemical oxidation and current reduction where the current depends directly on the density of electroactive species. Potentiometric sensing technique involves the measurement of difference in potential (generally pH electrode or ionselective electrode). Impedimetric detection method involves the impedance generation for measuring the resistance and capacitance values. Electrochemical biosensors are extremely attractive and persistent biosensors for many years and have continuously manifested substantial potentiality over the years by giving an extent of advantageous properties such as procedure involved in the measurement, short range of response time, adequate sensitivity, and selectivity (Feagin et al., 2018).

Table 10.1 Various nanostructured biosensors developed for the pesticides detection in food samples. Type of sample

Pesticide type

Nanostructured electrochemical sensor

Linear range

Limit of detection

Response time

References

Strawberry, Apple Cabbage, Apple, Orange juice Cabbage, Tomato

Methyl parathion Diuron

BSA/AChE-Glu-s-SWCNTs/GC Glove-MF/Printex

3.75 3 10211 M NR

15 min NR

Bala et al. (2018a) Bala et al. (2018b)

Paraoxon-Methyl

ZnO-G/GCE

1.6 ng mL21

NR

Nie et al. (2018)

Apple, Eggplant Wheat grains Orange, Grape Oranges, Tomatoes

Paraoxon Phosmet Fenitrothion Parathion

ZIF-8/MB composites AChE/WO3/g-C3N4/GCN/PGE IL@CoFe2O4NPs@MWCNTs@GCE UiO-66-NH2 Methyl

1 3 10210
5 3 1026 M 1
10 mol L21 9.2 3 1027 mol L21 0.002
0.04 μg mL21 and 0.06
1.0 μg mL21 20
4000 ng mL21 5
25 nM 0.02
160 μM 10
106 ng mL21

1.7 ng mL21 3.6 nM 0.0135 μM 10 ng mL21

60 min 15 min 60 sec 5 min

Onion, Paddy grains Apple, Orange, Cabbage Cabbage, Garland chrysanthemum, Leek, Pakchoi Apple

Paraoxon

Stearic acid/nanosilver/GCE

0.1
5 nM

0.1 nM

NR

Chlorpyrifos

SP-MCH-GE(DRAB 1 chlorpyrifos)

0.1 nM
0.5 μM

0.178 nM

50 min

Xu et al. (2018) Wang et al. (2019) Bala et al. (2018a) Kumar & Sundramoorthy (2019) Raymundo-Pereira et al. (2021) Parab et al. (2020)

Carbaryl

AChE/PDDA-MWCNTs-GR/GCE

0.8
50 ng mL21, 50
3000 ng mL21

0.13 ng mL21

12 min

Liu et al. (2020)

Monocrotophos

10210
102 6 mg mL21

0.05 pg mL21

15 min

Bilal et al. (2021)

Cabbage, spinach Cabbage Tomato

Carbaryl Carbaryl Carbaryl

AChE/CNTs-NH2/Ag NPs-NFMoS2/GCE AChE-e-pGON/GCE AChE
MWCNTs/GONRs/GCE GC/rGO/AChE

0.3
6.1 ng mL21 5
5000 nM 5.0
80.0 μg mL21

0.15 ng mL21 1.7 nM 1.9 nmol L21

12 min 3 min 5 min

Apple

Chlorpyrifo

AChE/CNTs-NH2/Ag NPs-NFMoS2/GCE

1 pg mL21

15 min

Cabbage, Rape, Lettuce

Methamidophos

AChE/OMC-CS/Fe3O4-CS/SPCE

5 3 1028
1027 mg mL21 and 1027
1024 mg mL21 0
600 μg L21

Kilele et al. (2021) Mehta et al. (2019) Kumaravel et al. (2020) Wang et al. (2020)

1 μg L21

12 min

Sun et al. (2013) (Continued)

Table 10.1 (Continued) Type of sample

Pesticide type

Nanostructured electrochemical sensor

Linear range

Limit of detection

Response time

References

Apple, Broccoli, Cabbage Apple, Broccoli, Cabbage Leek, Pakchoi Cabbage juice

Methomyl

GCE/MWCNT/PANI/AChE

0.4
8.0 μmol L21

0.95 μmol L21

3.5 min

Song et al. (2018)

Carbaryl

GCE/MWCNT/PANI/AChE

0.4
8.0 μmol L21

1.4 μmol L21

4 min

Li et al. (2017)

Chlorpyrifos Dichlorvos

CLDH-AChE/GN-AuNPs/GCE AChE/CS@TiO2-CS/rGO/GCE

0.05
150 μg L21 0.036
22.6 μM

0.05 μg L21 29 nM

10 min 10 min

Tap water, Well water, Chinese cabbage Soil and water

Malathion Methyl parathion Paraoxon

Amperometric Gold nanoparticle

1.0 3 1028
1.0 3 10212 g L21

-

Amperometric Graphene, Platinum

-

5.12 3 10213 5.85 3 10213 g L21 3 nM

Li et al. (2015) da Silva et al. (2018) Zhang et al. (2016)

Vegetables

Impedimetric graphene oxide, copper

Cabbage juice

Profenofos Phorate Isocarbophos Omethoate Dichlorvos

Tap water, Well water, Chinese cabbage Soil and water

Malathion Methyl parathion Paraoxon

0.01
100 nM 1
1000 nM 0.1
1000 nM 1
500 nM 0.036 μM (7.9 ppb) to 22.6 μM 1.0 3 10
8 to 1.0 3 10
12 g L21

Vegetables

Profenofos Phorate Isocarbophos Omethoate Dichlorvos

Cabbage juice

Amperometric chitosan-TiO2graphene nanocomposites Amperometric Gold nanoparticle

Amperometric Graphene, Platinum

-

Impedimetric graphene oxide, copper

0.01
100 nM 1
1000 nM 0.1
1000 nM 1
500 nM 0.036 μM (7.9 ppb) to 22.6 μM

Amperometric chitosan-TiO2graphene nanocomposites

-

0.003 nM 0.3 nM 0.03 nM 0.3 nM

-

Cesarino et al. (2012) Zhai et al. (2014)

29 nM (6.4 ppb)

-

Cui et al. (2018)

5.12 3 10
13 5.85 3 10
13 g L21 3 nM

-

Jiang et al. (2018)

-

0.003 nM 0.3 nM 0.03 nM 0.3 nM

-

Hondred et al. (2018) Fu et al. (2019)

29 nM (6.4 ppb)

-

Cui et al. (2019)

Nanostructured electrochemical biosensors for pesticides and insecticides

203

There are many nanomaterials that have been known for their significant applications in the detection of pesticides. Some of them are as follows: 1. Carbon nanotubes (CNTs): These materials have high surface area and very good electrical conductivity, which benefits them as a good sensing material. They can act as a functionalized material with specific molecules that bind to pesticides and enable the detection of pesticides. 2. Nanoparticles: There are numerous types of nanoparticles, which include Au, Ag, Mg, Fe, etc. used for pesticide detection. They can be functionalized with specific ligands to detect specific pesticides. 3. Graphene: The high surface area and excellent electrical conductivity of graphene useful for sensing applications can be bound well to pesticides and helpful to detect various pesticides. 4. Quantum dots (QDs): QDs are semiconducting nanomaterials that exhibit unique electrical and optical properties. The high sensitivity and specificity make them a good candidate for pesticide detection. 5. Nanowires: Nanowires display a high aspect ratio and extremely good electrical properties which are helpful in sensing applications. 6. Mesoporous silica: It has a higher surface to volume ratio and can have the ability to functionalize with specific molecules for pesticides detection. 7. Metal-organic frameworks (MOFs): These are suitable for pesticide detection applications, which have the ability to capture and detect the levels of pesticides due to the high surface area. The important element required for making electrochemical biosensors is the electrodes, which perform various purposes such as recognition of aptamers, aptamer binding, and targets and also employed as a carrier to convert signals of biological information into electrical information. Among all, disk electrodes (DEs) and screen-printed carbon electrodes (SPCEs) are the most useful electrodes in electrochemical biosensors. The development of nanomaterials made use of more and more nanocomposites, which are being considered to reconstruct the electrodes for sensing applications. They are metal nanoparticles, multiwalled carbon nanotubes, modified graphene multiwalled carbon nanotubes, AuNPs/glass carbon electrodes (Ehrich, 2005), porous carbon nanospheres, multifunctional graphene composites (Gupta et al., 2011), reduced graphene oxide nanoribbons with a covalent organic framework (Moon et al., 2018), and carbon nanofiber-gold nanoparticles (CNFs-AuNPs) (Uniyal & Sharma, 2018). These nanocomposites are being used to amplify electrochemical signals and improve the sensing performance due to a larger surface area.

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Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

This could also enhance conductivity and improve the biocompatibility of the aptamer. Electrochemical biosensors based on the inhibition of AChE (acetylcholinesterase) are attractive to detect pesticides. The AChE biosensor was fabricated by Cui et al. by doping Au nanorods on the composite material of mesoporous SiO2 and TiO2-chitosan gel which leads to the enhancement of the electrical conductivity. Using this electrochemical biosensor, the OPP was detected with the limit of detection of the two pesticides such as dichlorvos and fenthion which were 5.3 and 1.3 nM, respectively (Sassolas et al., 2012). AChE-based amperometric biosensor was developed by Zhang et al. to detect the amount of trichlorfon and malathion OPPs with the help of silver-rGO-NH2 nanocomposite. This is conjugated by polymer 4, 7-di (furan-2-yl) benzo thiadiazole electrochemically. The limit of detection was estimated for malathion and trichlorfon, respectively, as 0.032 and 0.001 μg L21. This biosensor exhibited higher conductivity, catalytic activity, good stability, and reproducibility to inspect OPPs (Verma & Bhardwaj, 2015). Hou et al. reported a SPE-based biosensor to detect OPPs in real samples that utilized nanocomposites to stimulate the transfer of electrons such as mesoporous carbon chitosan and antimony tin oxide-chitosan. Methamidophos and chlorpyrifos were utilized as model OP compounds and limits of detection were 0.01 and 1 μg L21, respectively (Yi et al., 2020). Furthermore, AChE-based biosensor was developed by incorporating smart nanomaterials, 3D graphene, and copper oxide nanoflowers to make available high aspect ratio and slow down AChE loading. It was observed that there was a remarkable pesticide detection displaying good stability and selectivity with a detection limit as less as 0.92 pM (Jiao et al., 2017). In order to detect malathion in the food matrix, an ultrasensitive fluorescent method was set up by Bala et al. by designing a nanoprobe consisting of quantum dots (QDs) to assemble FRET-based QD sensors, quencher (N-(3-guanidinopropyl) methacrylamide, PGPMA), and an aptamer as a recognition element (Yao et al., 2020). The presence of malathion revealed the quenching effect of fluorescence of the CdTe@CdS quantum dots by the target-aptamer complex. This method resulted in an excellent sensitivity and the successful malathion detection with a limit of detection as 4 pM, due to the remarkable properties of the QDs (Feagin et al., 2018). Furthermore, the existence of malathion level in food and soil was reported by the authors with a very low limit of detection 0.5 pM, which was significantly lower compared to the other methods, considering the malathion aptamer and silver nanoparticles as a

Nanostructured electrochemical biosensors for pesticides and insecticides

205

nanoprobe. In the presence of malathion, due to electrostatic interactions, the disengaged cationic hexapeptide caused the AgNPs to aggregate, making the system solution turn orange. Conversely, in the absence of malathion, the aptamers would interact with the peptide to remain yellow (Cui et al., 2019). One more sensor was developed for the analysis of malathion contents based on a label-free aptamer using SERS. Nie et al. customized Ag nanoparticles with positive spermine for the detection of malathion, which could bind with the targets by absorbing the aptamer considering the negative phosphate backbone. The results showed that the presence of malathion leading to the absorption of the malathionaptamer complex on the AgNPs@Spermine exhibited the increased peak intensity (Zhang et al., 2019). An electrochemical aptasensor was used to detect another type of organophosphate chlorpyrifos. In this method, electrode was fabricated by Xu et al. using copper oxide nanoflowers (CuO NFs) and carboxyl-functionalized single-walled carbon nanotube (c-SWCNT) nanocomposite to increase the surface area of the electrode to enhance the performance of sensing. The assessment was done by recording the reading of the change in the digital pulse voltammetry to estimate chlorpyrifos. It was reported that the maximum current of methylene blue was reduced with an increase in the amount of chlorpyrifos (Hou et al., 2019). For isocarbophos detection, Wang et al. developed a dual-modal aptasensor, which is based on the AuNPs (Au nanoparticles) including the effect of inner filtration between along with the inner filter effect between persistent luminescence nanorods (PLNRs) and AuNPs. If the isocarbophos is not present then inner filter effect between the conjugation of aptamer-AuNPs and PLNRs make to quench their phosphorescence and the presence of isocarbophos in the solution showed that the AuNPs get aggregated, leading to decrease in the phosphorescence. The developed sensor showed the superior sensor performance and selectivity detection of isocarbophos with a lower limit of detection of 7.1 and 0.54 μg L21 in colorimetry and phosphorescence mode (Bao et al., 2019). Some of the recently developed nanostructured electrochemical biosensors for pesticides detection have been provided in Table 10.1. Nanostructured electrochemical biosensors are known to be a promising candidate for the detection of pesticides and insecticides. These biosensors utilize nanostructured materials, such as carbon nanotubes, graphene, and metal nanoparticles, to enhance the sensitivity and selectivity of the sensor. In the case of pesticide and insecticide detection, the biorecognition element is typically an enzyme that is specific to the

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Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

target analyte. When the target analyte binds to the enzyme, an electrochemical signal is generated, which can be measured and quantified. There are many ways to improve the performance of the electrochemical biosensors using nanostructured materials. Surface area can be increased by using nanostructured materials which act as a good candidate for binding the biorecognition element to increase the sensor sensitivity. The kinetics of electron transfer can be increased between the biorecognition element and the transducer to enhance the selectivity and response time of the sensor. Finally, one can understand that the nanostructured electrochemical biosensors are a promising technology to detect pesticides and insecticides owing to their good selectivity, high sensitivity, specificity, and quick response time. These sensors are potential candidates for improving the food safety and environment monitoring by providing a quick and precise technique for the detection of harmful chemicals. Some of examples of the nanostructured electrochemical biosensors for the detection of pesticides are as follows: 1. Graphene-based electrochemical biosensors utilize graphene as a base material for detecting different pesticides. Organophosphate pesticides present in fruits and vegetables can be detected by using graphene and gold nanoparticle-based biosensors. 2. Carbon nanotube (CNT) electrochemical biosensors use CNT as a sensing element for pesticides detection. Multiwalled CNTs have been developed to detect pesticides carbamate present in the food samples. 3. Metal oxide electrochemical biosensors employ a sensing element as a metal oxide nanoparticle for detecting pesticides. ZnO nanoparticles based biosensors are useful in detecting organophosphate pesticides present in the food matrix. 4. Quantum dot (QD) electrochemical biosensors are used to detect pesticides using quantum nanodots as sensing material. CdS quantum dotbased biosensors are helpful to detect carbamate pesticides. 5. Magnetic nanoparticle electrochemical biosensors can be employed to detect pesticides utilizing magnetic nanoparticles as sensing elements. Iron oxide nanoparticles exhibit magnetic properties and have beneficial effects in detecting organophosphates present in food samples. 6. Apart from these, many nanostructured electrochemical biosensors have been fabricated to detect pesticides. Every biosensor has its unique properties, which are advantageous and limitations as well. The applications of these electrochemical biosensors depend on the specific application and the target pesticide.

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207

10.5 Applications of nanostructured electrochemical biosensors Nanostructured electrochemical biosensors are of interest to integrate physics, engineering sciences, chemistry, and biology. The performance of the sensors such as the sensitivity, efficiency, and response time can be increased by utilizing nanostructures in the development of electrochemical biosensors. Nanostructured materials are synthesized and applied in electrochemical biosensors for food safety, medical diagnostics, environment protection, and treatment of wastewater. These electrochemical biosensors are also utilized for monitoring various biological target species such as proteins, glucose, DNA bases, peptides, cell-based chips, and viruses.

10.6 Importance of electrochemical biosensors • • • •

The electrochemical biosensors signify a potential tool for measurement of real-time data which includes clinical diagnostics and food technology. Electrochemical biosensors are embedded with a high surface to volume ratio owing to smaller size of the nanoparticles, which can lead to high sensitivity. These sensors are known to exhibit excellent electrical or optical properties. These can be utilized as the extraordinarily sensitive transducers in biosensors. Other important aspects of electrochemical biosensors are their excellent limit of detection, strength, easy miniaturization, and capacity to be used in turbid biofluids with optical absorption and fluorescent compounds.

10.7 Challenges Nanostructured electrochemical biosensors are developed to enhance the selectivity, specificity, and rate of pesticide detection, although there are many challenges that need to be addressed for development and implementation of these biosensors for various applications. Achieving high specificity is one of the major challenges in pesticide detection. It is important that biosensors should be designed to detect specific pesticides without interfering with the other chemicals present in the sample. The complexity of the sample matrix and the probable crossreaction with other substrates makes it difficult. Sensitivity is another challenge to achieve for the target pesticide. The detection limit of the sensor must be smaller than the maximum reduction limit set by monitoring

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Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

agencies. Achieving high sensitivity would be challenging owing to lower pesticide concentrations in the environment. The biosensors that have been developed should maintain their stability and performance over time to make reliable and accurate measurements. Stability can get affected by certain factors such as sample matrix, electrode fouling, and environmental conditions. Reproducibility is one of the important challenges because the biosensors developed must give consistent results across various samples and users. The optimization of the biosensors is required in terms of designing and fabrication process. Biosensors must be integrated with material synthesis techniques and analysis of the data to furnish a complete analytical solution. This needs collaboration among the experts in chemistry, biology, and engineering. Ultimately, the developed biosensors must be cost-effective. There are many electrochemical biosensors available for the detection of pesticides such as Au Nps polypyrrole nanowires, ZrO NPs-modified screen-printed electrodes, MWCNT GCE, and Au-MWNT-modified GC electrodes, etc. The drawback of using these mentioned electrodes is the leakage of enzymes into the electrode and process of pretreatment. Overall, the nanostructured electrochemical biosensors developed for pesticide detection need a multidisciplinary approach and considering the specific challenges in the detection of pesticides.

10.8 Future scope This chapter describes the current advancement to design and apply electrochemical biosensors for pesticide and insecticide detection in the food matrix. Also, it emphasizes briefly the fundamental idea of different electrochemical biosensors, which have been developed to detect food contamination. Nanostructured electrochemical biosensor devices could be used for pesticide detection with more accuracy owing to their high aspect ratio, highly stable, and extremely good contact between the biocatalysts. Magnetically bioconjugated nanomaterials have also been used. CNT can be used for chemical and biological sensing applications. They are hollow graphitic tubes. They have a faster rate of electron transfer and also possess electrocatalytic effect. FeO are unique because of their magnetic and electric properties and can therefore be used in pesticide detection.

10.9 Conclusion Nanomaterials are of great interest due to their unique electrical, chemical, and physical properties. Initially, we have provided a broad overview

Nanostructured electrochemical biosensors for pesticides and insecticides

209

on organophosphate pesticides and its detection by using various nanostructured electrochemical biosensors. The method of detection affords a significant reference for monitoring food safety. We have discussed it successfully. The nanostructured electrochemical biosensors have been utilized significantly for pesticide detection in food samples owing to their fast response time, high sensitivity, and low cost. Furthermore, the applications of different nanomaterials with surface modifications have been reported for enhancing the sensitivity of the electrochemical biosensors for pesticide detection. In nanostructured electrochemical biosensors, various nanomaterials are used in different electrochemical techniques for the detection of pesticides and insecticides. The most commonly used electrochemical techniques in sensor technology are potentiometry, corona amperometry, voltammetry, impedance measurement, and FET. The designing/engineering of the electrode surface plays a vital role in sensor efficiency in terms of decomposition. In nanostructured electrochemical biosensors, metal nanoparticles improve the receptor surface area and thus enhance the sensor sensitivity. Furthermore, the electrocatalytic effect of metal nanoparticles aids the quick transfer of electrons. This rapid transfer of electrons minimizes the response time and maximizes the efficiency of the electrochemical sensor. AChE-based biosensors have been developed using carbon nanomaterials such as CNTs and graphene. Using these, one can observe that the biosensors have responded well for the detection of pesticides, primarily because two nanostructured electrode materials are used to transduce the signal to mediate current flow. Most of the existing limitations of the nanostructured electrochemical biosensors could be directly related to the selectivity in multicomposite mixtures and complex matrices and the inability of identifying a specific pesticide. Simultaneous use of the nanostructures and electrochemical techniques made it advantageous to develop the sensors with high sensitivity and decomposition power. Apart from the advantages of electrochemical biosensors, some of the issues to be considered about the detection of analytes, there will be a chance of leakage of the sample on the electrode surface.

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CHAPTER 11

Electrochemical biosensing for determination of toxic dyes Cem Erkmen1,2, Hülya Silah3 and Bengi Uslu1 1

Faculty of Pharmacy, Department of Analytical Chemistry, Ankara University, Ankara, Türkiye Faculty of Science, Department of Chemistry, Hacettepe University, Ankara, Türkiye 3 Faculty of Science, Department of Chemistry, Bilecik Seyh Edebali University, Bilecik, Türkiye 2

11.1 Introduction Since the recent century, with the continual improvement of dyeing and printing industrialization processing, huge amounts of dyes are discharged into the environment. Dyes and pigments are fundamental per diem chemical matters and are widely utilized in different industries to color their products like paper, leather, printing, textiles, rubber, plastics, printing, dye manufacturing, pulps, wood, food, cosmetic, pesticides, pharmaceuticals, etc. (Hareesha, Manjunatha, Amrutha, Pushpanjali, et al., 2021; Sriram et al., 2022; Zhou et al., 2019). Dye molecules and their metabolites in environmental matrix and food chain cause carcinogenicity, mutagenicity, and teratogenicity dysfunction of human beings’ liver, kidney, brain, central nervous, and reproductive systems (Zhou et al., 2019). Thus, there is a requirement to advance novel and selective analytical methodologies for the effective determination of toxic dyes (Manjunatha, 2019). Different analytical methods for the determination of toxic dyes have been noticed in the literature, particularly UV-vis spectrophotometry, liquid chromatography (LC), high-performance liquid chromatography (HPLC), gas chromatography (GC), thin-layer chromatography (TLC), capillary electrophoresis, surface-enhanced Raman spectroscopy (SERS), immunoassay techniques such as enzyme-linked immunosorbent assay (ELISA), and some methods based on mass spectrometry such as laser desorption/ionization (LDI)-Ms, real-time time-of-flight mass spectrometry (DART-TOF-Ms), matrix-assisted laser desorption/ionization (MALDI), liquid microjunction surface sampling probe mass spectrometry (LMJ-SSP Ms), and time-of-flight secondary ion mass spectrometry (TOF-SIMS) (Hareesha, Manjunatha, Amrutha, Sreeharsha, et al., 2021; Pushpanjali et al., 2020; Shahid et al., 2019). Among these techniques, Novel Nanostructured Materials for Electrochemical Bio-sensing Applications DOI: https://doi.org/10.1016/B978-0-443-15334-1.00009-2

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spectrophotometric groups have been generally employed for the routine quantitative detection of dyes. These techniques involve different spectrophotometric analytical methods such as the H - point standard addition method, derivative spectrophotometry, and cloud point extraction method (Vladislavi´c et al., 2018). In recent years, electroanalytical methods appear to be very encouraging due to their great simplicity, short response time, sensitivity, selectivity, low operating costs, and ability to simultaneously detect many different analytes at the same time (Prinith & Manjunatha, 2020). Biosensors and chemical sensors are recognized as trustworthy and generally transportable apparatus for quick and cost-effective detection of analyte species that have wide range from metal ions to inorganic and organic compounds, proteins, pollutants, antigens, viruses, fungi, bacteria, deoxyribonucleic acids, and others. So biosensors are utilized in different areas like pharmacy, medicine, drug development, food industry, crime detection, quality control, environmental analysis, etc., thanks to their unique properties. “Biosensors” are electroanalytical appliances similar to chemical sensors, nevertheless incorporating biological molecules for accurate and rapid determination of target species (Sanati et al., 2019; Zare-Shehneh et al., 2021). In this way, we have reviewed the recent studies in detecting toxic dyes using electrochemical biosensors by focusing on the biosensor architecture, selected electrochemical method, linearity range, selectivity, sensitivity, and their application areas.

11.2 Dyes and pigments Dyes and pigments are extensively utilized as colorant components in different industrial and production activities such as plastic, textile, leather, printing, paper, rubber, tannery, cosmetics, and food sectors (Ozturk & Silah, 2020). In some cases, the nonaqueous or aqueous solutions of dyes are eventually discharged into various water sources and generate undesirable colored and unpleasant odors in wastewater, causing environmental pollution. The colored wastewater has poor light absorption capability so these waters cause delayed photosynthesis in various herbs. In addition, these polluted waters are inconvenient and extremely disgusting for performing assorted human activities (Hassan et al., 2015). Taking into consideration both the volume of water discharged and the contaminant content, the wastewater composed by the textile industry is categorized as the most polluting among all industrial lines. Consequently, it is

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compulsory for scientists to discover ways for accomplishing the matters related to industrial water effluents loaded with dye pollutants (Hayat et al., 2022). Dyes are generally classified into two classes, such as synthetic and natural dyes. The natural dyes are pricey and are typically extracted from natural sources like plants, minerals, animals, fruits, and so on. Additionally, they are not deleterious to the environment. In comparison, synthetic dyes have taken more caution in many industries because of their ease and convenience of synthesis, low cost, and wide range of colors. But, synthetic dye molecules are extremely toxic (Sriram et al., 2022). Synthetic organic dyes and pigments are the major class of all coloring matters, and it is predicted that more than 100,000 synthetic organic dyes are existing commercially worldwide in a universal manufacturing volume of over 1,000,000 tons annually. The enormous amount of dyes manufactured and their extensive-ranging implementation areas form a great volume of colored wastewater and various kinds of postproduction contaminants and waste. Especially, the textile sectors are significant resource of water pollutants: throughout diverse dyeing operations, dye wastage is between 5% and 50%, depending on the kind of dye and fabric. Because of all these reasons, nearly 200 billion liters of colored effluents are created annually (Tkaczyk et al., 2020). Also, there are two primary dye classification systems in the literature where one is based on their chromogen groups involving diphenylmethane, acridine, azo, anthraquinone, azine, indigoid, oxazine, methine, nitroso, nitro, phthalocyanine, triphenylmethane, thiazine, and xanthene dyes and the others are based on their implementation objectives (including basic, acid, direct, fiber, disperse, reactive, mordan, and vat dyes) (Tkaczyk et al., 2020). Some synthetic azo dyes, particularly those coexisted with some other drugs or azo dyes, have mutagenic effects and may have important potential of genotoxicity. Azo dyes are more mutagenic after the breakage of the azo bonds by azoreductase enzymes, which are synthesized in the intestinal cells, which outcomes in colorless aromatic amine compounds (Rocha et al., 2016). So these dyes cause some health problems such as widespread digestive disorders involving gastroesophageal reflux disease, irritable bowel syndrome, cancer, hiatal hernia, lactose intolerance, urticaria, diarrhea, angioedema, and also some allergic symptoms such as nasal congestion, rhinitis, itching, bronchial asthma symptoms, dizziness, headaches, etc. (Vladislavi´c et al., 2018).

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Food colorants are separated into two groups, synthetic and natural. Natural colorants are ensured from colorful plants and animals in the nature. But since natural colorants are unstable to alterations in preservation situations such as pH, temperature, humidity, and light, they break down readily when subjugated to changes in preservation conditions (Tabanlıgil Calam & Ta¸skın Çakıcı, 2023). Synthetic dyes have been commonly applied, especially in the food sectors for nearly 40 years because of their expressive usefulness such as greater stability, bright color, lower cost, and an extensive range of tones compared with natural colorants. One of the most common synthetic colorants is the azo dye group which constitutes approximately 70% of synthetic colorants. Tartrazine, furthermore called as Food Yellow 4, Acid Yellow 23, and E102, is an azo dye in lemon yellow color utilized for color jams, confectionery, ice cream, jellies, alcoholic beverages, soft drinks, and other similar foods (George et al., 2023). Monitoring ultratrace or trace amounts of toxic dyes in various foods, natural, environmental, biological, clinical, and other real samples is very considerable, because the exposure of these dyes can cause toxicosis, affecting first the liver and then the central nervous system, eyes, kidneys, and skin (Manjunatha, 2018). Dye molecules are primarily formed of two key components. One of these is auxochromes that involve many functional groups like -OH, -SO3H, -COOH, and -NH3, which not only acquaint the chromophore group but also improves the fiber affinity for color and reduce the water solubility either by removing or donating electrons. The second is chromophores which occurred from atomic groups and involve diverse functional groups such as carbonyl (-C 5 O), nitro (-NO2), and azo (-N 5 N-), and these chromophore groups are principally accountable for dyeing the fabric (Sharma et al., 2021). So dyes and their metabolites are complicated organic matters with auxochromic and chromophore groups, which can be electrochemically reduced or/and oxidized; this causes the base of their electrochemical determination.

11.3 Electrochemical biosensors Electrochemistry is a considerable qualitative and quantitative analysis method for analyzing assorted biochemical molecules, like metabolites, proteins, neurotransmitters, electrolytes, drugs, pesticides, phenols, dyes, heavy metals, and so on, pointing spacious implementations in public health, personal health,

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food safety, clinical diagnosis, industrial applications, and environment analysis (He et al., 2023). Electrochemical biosensing systems submit myriad superiorities, involving straightforward fabrication, cost-effectiveness, sensitivity, selectivity, portability, low power necessities, and compatibility for in situ analysis (Prinith, n.d; Hara & Singh, 2021). Biosensors and chemical sensors based upon microelectromechanical system technologies have been improved to sit in for costly and complicated analytical appliances in various fields with compact and broadly employed sensors proposed for healthcare, environmental, and industrial applications (Arakawa et al., 2022). Biosensors have a purpose for robust and innovative analytical appliances, including biological sensing elements called bioreceptors, with an extensive range of implementations, like biomedicine, diagnosis, drug discovery, food processing and safety, environmental control and monitoring, defense industry, and security (Vigneshvar et al., 2016). Especially, environmental control and monitoring is one of the most significant applications wherein biosensor technologies are necessary for speedy recognition of contaminants and their residues to avoid health ventures (Vigneshvar et al., 2016). The term “sensor” has its origin from the Latin word “sentire” which primarily means “to identify” anything (Ali et al., 2017). Sensors are generally classified into diversified groups depending on the physical quantity (substance) or analyte to be survived, like (1) energy source (passive and active sensors), (2) physical contact (noncontact and contact), (3) comparability (relative or absolute sensors), (4) digital or analog sensors, and (5) signal determination (chemical, physical, biological, and thermal) (Naresh & Lee, 2021). Biosensors are electrical apparatus that measure biological or biochemical signals and transform them into electrical signals. A biosensor is an electroanalytical appliance that detects or determines the existence of an analyte species in the sample medium of interest (Chadha et al., 2022). Since biosensors were acquainted in 1962 by Leland C. Clark Jr., known as the father of biosensors, the improvement of electrochemical biosensors has taken much notice from investigators; therefore investigations on electroanalytical biosensors have incremented in the last three decades. The capability of electrochemical biosensors to grant a charming replacement for pricey and cumbersome analytical apparatus induced investigators to discover the area thanks to experimental and theoretical studies, involving other kinds of biosensors, such as magnetic, thermometric, optical, piezoelectric, and combinations of more than one kind. Electrochemical biosensors own other superiority over other kinds of

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biosensors. One of the most significant is the capability to actuate at ambient temperatures without an exterior heating system, which supposes very low to no power for totally self-powered electrochemical biosensors (Abdulbari & Basheer, 2017). The electronic supplementary determines, records, and transfers knowledge concerning a physiological alteration or the existence of assorted biological or chemical species in the environment. Biosensors are developed in various sizes and shapes and can determine and measure even low amounts of particular chemicals such as drugs, pesticides, food additives, dyes, phenols, microorganisms, bacteria, pathogens, and different toxic chemicals (Naresh & Lee, 2021). The main components of biosensors are their bioreceptor (bioelement), transducer, and electrical circuit, which are displayed in Fig. 11.1. A biological recognition element or bioreceptor is a biological asset such as enzymes, aptamers, hormone receptors, cells, tissues, antibodies, and deoxyribonucleic acid (DNA) that reacts peculiarly with the analyte species to generate a measurable signal. A transducer is an apparatus that transforms energy from one form to another (Chadha et al., 2022).

Figure 11.1 Schematic graph of classical biosensor comprising of bioreceptor, transducer, electronic circuit (processor and amplifier), and screen (PC or printer), and different kinds of bioreceptors and transducers used in the biosensors. Source: Reprinted with permission from Naresh, Varnakavi, & Lee, N. (2021). A review on biosensors and recent development of nanostructured materials-enabled biosensors. Sensors, 21(4), 1109. https://doi.org/10.3390/s21041109.

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An ideal biosensor must have some features such as: (1) the bioreceptor employed in the construction of the sensor must be devoted fully to the aimed analytical objective. (2) The selected biocatalyst has high stability at experimental conditions. (3) The biological reactions must be uncommitted of alterations in experimental conditions like temperature, pH, etc. (4) The response of the developed electrochemical sensor must be correct, accurate, repeatable, and also have a wide analytical concentration range. (5) The biosensor must ensure a fast and momentary response (ZareShehneh et al., 2021). The electrochemical biosensors are a private kind of biosensors where a biological species or biological reactions are determined by transforming the knowledge into the electrical signal, for example, current, voltage, impedance, conductivity, resistance, etc. (Singh et al., 2021). The electrode material is the most significant component of an electrochemical biosensor as it controls the flow of bioagents and electrons. Different electrochemical biosensor systems have been developed based on amperometry, voltammetry, impedimetry, and potentiometry (Singh et al., 2021). Conventional electroanalytical sensing systems are formed of electrochemical reaction cells, standard sensing electrodes, and bulky electrochemical workstations, which suppose specialized staff, restricting their convenient implementation, particularly in less advanced fields. Recently, with the refinement of integrated circuits, printed electronics, and intercommunication technologies, many wearable or transportable electrochemical sensing systems with cost-effectiveness, small size, and easy operation have evolved. Transportable electrochemical sensors generally are comprised of a reusable electronics apparatus and a portable electrode. The electrodes can be changed after the determination of analytes. Different analyte species could be determined by handling various electrodes with the same electronic apparatus. Miniaturized electrochemical potential and impedance detection analog front ends have been combined by utilizing D/A conversion chips, A/D conversion chips, impedance analysis chips, operational amplifiers, and other circuit moduli (He et al., 2023). To improve highly efficient and competent biosensor systems, specific static and dynamic requirements such as high sensitivity and selectivity, wide linearity range, short response time, high precision and accuracy, reproducibility, and stability are essential. The yield of the biosensor can be developed for various trading applications (Naresh & Lee, 2021). The primary approach in contravention of the electrochemical biosensors is to augment the conductivity of the electrode surface to achieving high

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electron transference between the analytes and the electrode surface. For this reason, it is indispensable to employ conductive materials in the construction of electrochemical biosensors (Khanmohammadi et al., 2020). In electrochemical biosensor systems, immobilization of molecular or ionic identification probes is the most important step to maintain the bioactivity and to control the inducement and conformation of biomolecules. The degree of holding biomolecules in their active forms will directly influence both the reproducibility and stability of the developed biosensor. Some molecules such as proteins and enzymes directly retained via adsorption on an unmodified (bare) electrode such as gold, platinum, or carbon are tended to denature, leading to fouling of the electrode surface. So a covalent attachment on various functional groups or a polymer matrix was generally exploited as the entrapment reagent. Different biological molecules (e.g., DNA, enzyme, cell, and antibody) can be immobilized on the active surface of the electrode via various immobilization methods such as direct adsorption, covalent attachment, layer-by-layer assembly, and intercalation (Li et al., 2011). Affinity-based biosensor systems are imitating a native biological occurrence, using the interactions of the target analyte species with a biological recognition element (bioreceptors) like antibodies, proteins, aptamers, and synthetic DNAs, or molecularly imprinted polymers (MIPs). The ensuing interaction will be carried to a signal by linking to a transducer. These sensors subscribe to a diversity of determination implementations involving especially diagnosis of noninfectious and infectious diseases, cancers, etc. (Sanati et al., 2019). Electrochemical investigation of DNA
small molecule interactions has lately taken great notice because of the utilization of simpler, lowcost, and smaller appliances with respect to spectroscopic techniques. Moreover, the explication of electrochemical information can subscribe to clarification of the mechanism by which DNA is interacted with small molecules like drugs and dyes in an approach to the real behavior that occurs in living cells in vivo (Heli et al., 2004). DNA is a concerning biomaterial that, has lately drawn much notice due to its ability to bind small ligand molecules with high specificity and affinity. The small molecules interact with DNA by covalent bonds (chemical modification of different DNA constituents) and reversible noncovalent bonds (groove binding, electrostatic, and intercalation) (Rezaei et al., 2016). Electrodes covered with a film of DNA polymers, which are called DNA-modified electrodes, generally in a solution/film/substrate layout,

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have been utilized in the researches on DNA
small molecule interactions, accumulation of trace analyte molecules involving dyes, drugs, pesticides, food additives, and potential contaminants (Heli et al., 2004). Among the diverse kinds of electrochemical sensors, impedimetric immunosensors present a group that merits private attention. These sensors can be highly sensitive and selective, because of the specificity of antibody
antigen interactions, and their application in integration with the electrochemical impedance spectroscopy (EIS) method makes possible the progress of labelfree assays. Genesis of the immunocomplex alters the impedance reply of the system, compared to the reply previous to the immunoaffinity reaction, ensuring the basis of the electroanalytical methodology and removing the usage of indirect measurements. This process provisions the electrochemical sensor as more straightforward and inexpensive because the assay requests fewer steps. Additionally, the EIS technique is a nondestructive method that consents to consecutive measurements to be made handling the same electrode (Rocha et al., 2016). Nucleic acids present analytical techniques as a vigorous tool in the identification and monitoring of many different considerable compounds and other species. Ions and molecules interact with DNA in three remarkably distinct ways involving groove binding, electrostatic, and intercalation. These interactions alter the structure of DNA and its base sequence, causing perturbation of DNA replication. Among them, electrostatic interactions are generally nonspecific and involve binding along the exterior of the double-stranded DNA (ds-DNA) helix. Groove-binding interactions include direct interaction of the molecule or ion with the edges of the base pairs in the minor or major channels of ds-DNA, expanding to fit over many base pairs. They have a very superior sequence specificity. In intercalation, another type of DNA
molecule interaction process includes attaching planar or almost planar aromatic ring systems between the base pairs, reasoning separation, and unwinding of base pairs. The structure of the electrochemical DNA biosensors is based on the immobilization of the nucleic identification layer over an electrochemical transducer. The alterations in the DNA structure in the course of intercalation with DNA-binding molecules are determined by nucleic acid identification (Ensafi et al., 2012). In genosensors, the bioreceptor (recognition element) is a group of nucleic acids, which are unbranched polymers that comprised four single units called nucleotides. These units include three components, that is, sugar, phosphate, and nitrogen-containing nucleobases. The nucleotide

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groups are different in the sequence of their bases. Usually, nucleic acids are classified into two primary categories, deoxyribonucleic acid (DNA) and ribonucleic acid (RNA). The difference between DNA and RNA monomers gets from the difference between their sugars where DNAs contain deoxyribose sugar and RNAs have ribose sugars. Also, DNA includes guanine (G), adenine (A), thymine (T), and cytosine (C), whereas, in RNA molecules, the uracil (U) base has been replaced by thymine base (Khanmohammadi et al., 2020). Enzyme-based biosensors, one of the most widely developed electrochemical sensors, employ enzymes as a biorecognition element (bioreceptors), and the analysis of the sample is based on the inhibition of enzymatic activity (Munteanu & Apetrei, 2022). Enzyme-based biosensors own different benefits, with the inclusion of high sensitivity, specificity, availability, selectivity, and diversification of functions, and are classified as either indirect or direct mode. In direct mode, the enzymatic biosensor analyzes target analyte concentration or product genesis during enzymatic reactions. But, in indirect mode, biosensors determine enzyme inhibition because of contact with the target analyte (Hara & Singh, 2021). In this process, after the enzyme inhibition molecule is exposed to a particular inhibitor for a definite duration of time, qualitative and quantitative determinations of the analyte species are carried out by analyzing the correlation between the enzyme inhibition rate and that of the inhibitor concentration (Munteanu & Apetrei, 2022). Enzyme-linked biosensor systems have some supremacies appertained to the nature of the enzyme used. Enzymes are highly selective for a specific substrate molecule, and for a large number of substrate molecules, biological reactions can be catalyzed by a solo enzyme molecule, ensuing in a magnification of the impact and an increment in sensitivity. The enzymes generally used in designing biosensors belong to the hydrolase, oxidoreductase, or lyase groups (Munteanu & Apetrei, 2022). Antibodies are protein molecules generated by the immune system and include antigen-recognition sites, which connect to their specific related antigens by noncovalent interactions with relatively high affinity. The interaction of antigen
antibody is the most considerable event in immunosensor systems. Among various kinds of immunosensors, electrochemical immunosensors are sensitive, specific, and can present realtime determination of plural targets in an automated sample platform (Sanati et al., 2019).

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11.4 Determination of toxic dyes based on electrochemical biosensors and their applications Electrochemical biosensors have been employed for toxic dyes due to their superiorities such as perfect sensitivity with very low detection limits, rapid analysis times, simultaneous detection of several analytes, etc. Selected determination methods of toxic dyes using electrochemical biosensors are given in Table 11.1. Recently, researchers have investigated the practicality of biological methods to determine the existence of several dyes in various sample matrices. Biological matters such as proteins and enzymes, in addition to several crosslinking reactions, have prosperously shown a meaningful and trustworthy detectability of dyes (Okeke et al., 2022). Among the several types of electrochemical sensors, impedimetric immunosensors stand out as highly selective methods due to the specificity of antigen
antibody interactions. Moreover, the use of these methods together with the EIS technique allows the development of more economical and simple label-free assay methods (Magar et al., 2021). In their study, Rocha and coworkers designed and characterized a labelfree impedimetric immunosensor for the detection of the textile azo dye Disperse Red 1 (Dr1) in treated water samples. As shown in Fig. 11.2, a glassy carbon electrode (GCE) was polished with alumina powder and washed with ethanol and water, respectively, and dried completely. Then, GCE was subjected to electrooxidation process (11.5 V for 15 s) in a solution containing nitric acid and potassium dichromate to form carboxylic groups on the GCE surface. Immediately after rinsing the electrode, the 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide/N-hydroxysuccinimide solution was incubated. In the next step, anti-Dr1 antibodies (Ab anti-Dr1) were incubated using Ab anti-Dr1 solution to the electrode surface and the electrode dipped in phosphatebuffered saline (PBS) to remove unbound weakly bound antibody molecules. The surface was incubated with ethanolamine and dipped in PBS so that the prepared immunosensor was ready to interact with the Dr1 dye. This process was carried out to block the activated carboxylic groups on the surface. As the immunosensor surface was incubated with increasing Dr1 concentration, a calibration curve was established according to the changing RCT values of Fe (CN)632/42 depending on the reaction between antigen and antibody. After characterization studies using cyclic voltammetry (CV) and EIS methods, a linear range of 8.40
100 nM with a limit of detection (LOD) of 2.52 nM was achieved with increasing Dr1 concentration under optimal conditions.

Table 11.1 Some reported electrochemical applications for the detection of toxic dyes. Analyte

Method

Sensor architecture

Electrolyte (pH)

Linear range

LOD

Application

Interferences

Ref.

Chrysoidine

DPV

DNA/MWCNTsPDDA/PGE

TE buffer (pH 7.0)

0.05
15.00 μg mL21

0.03 μg mL21

Cryptoxanthin, β-carotene, capsanthin, indigo carmine, capsaicin, tartrazine, saffron, and cryptoxanthin; Ca21, Fe31, Mg21, Al31, Cu21, Zn21, CO322, SO422, and NO32

Ensafi et al. (2014)

Disperse Orange 1

CV, EIS

Ab antiDO1/ DADD
DAH/ GCE

0.25 M PBS (pH 7.4)

5 nM
0.5 μM

7.56 nM

-

Yang et al. (2015)

Disperse Red 1

CV, EIS

Ethanolamine/Ab anti-Dr1/GCE

8.40
100 nM

2.52 nM

-

Rocha et al. (2016)

Indigo Carmine

CV

PGMCPE

2 3 1026
6 3 1025 M

11 3 1028 M

Manjunatha (2018)

CV

DNA-GCE

-

-

Commercial for mulation samples -

-

Neutral Red

0.1 M PBS (pH 7.4) 0.2 M PBS (pH 6.5) 0.02 M Tris
HCl buffer

Ketchup and chili sauce, tomato powder, fish, and textile effluent samples Tap water and mineral water samples Tap water samples

-

Heli et al. (2004)

Purpurin (C.I. 58 205)

DPV

DNA with GCE

Reactive Red 195

CV

Laccase-catalase/ CF

Rhodamine B

CV

Anti-Rh BmAB@CeO2/ SPE

Sudan I

CV, EIS

HNS/EDC/Sudan I-Mabs/BSA/ Au electrode

Sudan II

CV, EIS, SWV

DNA-PGE

Sudan II

ASDPV

Ds-DNAmodified PGE

0.02 M BRB (pH 7.0) 0.5 M PBS (pH 7.0) 0.01 M PBS (pH 7.4) 0.01 M PBS (pH 7.0) PBS (pH 8.0)

0.1 M PBS (pH 4.8)

0.66
9.9 μM

-

-

-

Wang et al. (2010)

10 μg L21
30 mg L21

-

Textile effluent samples

Glucose, ascorbic acid, urea

Rafaqat et al. (2022)

0.01
10000 ng mL21

0.89 pg mL21

Paprika and capsicol samples

-

Zhu et al. (2022)

0.05
50 ng mL21

0.03 ng mL21

Hot chili samples

-

Xiao et al. (2011)

1
20 nM, 20
5000 nM

0.3 nM

Sudan I, Sudan III, Sudan IV, and Red 7B

Rezaei et al. (2016)

0.5
6.0 μg mL21

0.43 μg mL21

Ketchup and chili sauce samples Ketchup and chili sauce samples

Capsaicin, capsanthin, cryptoxanthin, β-carotene, Ca21, Fe31, Mg21, Zn21, Al31, Cu21, CO322, SO422, and NO32

Ensafi et al. (2012)

(Continued)

Table 11.1 (Continued) Analyte

Method

Sensor architecture

Electrolyte (pH)

Linear range

LOD

Application

Interferences

Ref.

Sunset Yellow

DPV

0.02 μM

Soft drink samples

Tartrazine, glucose, citric acid, and ascorbic acid

Rozi et al. (2018)

DPV

0.05 M PBS (pH 5) 0.1 M PBS (pH 5.0)

0.08
10.00 μM

Tartrazine

Poly(AAm-coEMA)/Lac/ GCE Microsphereslaccase/AuNPs/ SPE

0.2
14.0 μM

0.04 μM

Candy coated with chocolate and commer cial mango juice samples

Glucose, ascorbic acid, sucrose, Sunset Yellow dye, and phenol

Mazlan et al. (2017)

Ab anti-Dr1: Anti-Dr1 antibodies, ASDPV: anodic stripping differential pulse voltammetry, BRB: Britton
Robinson buffer, BSA: bovine serum albumin, CF: carbon felt electrode, CV: cyclic voltammetry, DADD: 1,12-diaminododecane, DAH: 1,7-diaminoheptane, DO1: Disperse Orange 1, DPV: differential pulse voltammetry, Dr1: Disperse Red 1, EDC: 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide, EIS: electrochemical impedance spectroscopy, GCE: glassy carbon electrode, Lac: laccase, Mabs: monoclonal antibodies, NHS: N-hydroxysuccinimide, NPs: nanoparticles, PBS: phosphate-buffered solution, PDDA: poly(diallyldimethylammonium chloride), PGE: pencil graphite electrode, PGMCPE: polyglycine-modified carbon paste electrode, poly(AAm-co-EMA): poly(acrylamide-co-ethylmethacrylate), TE: Tris-EDTA, SAM: self-assembled monolayer, SPE: screen-printed electrode.

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Figure 11.2 Schematic illustration of the GCE modification procedure used to construct the impedimetric immunosensor. Source: Reprinted with permission from Rocha, C. G., Ferreira, A. A. P., & Yamanaka, H. (2016). Label-free impedimetric immunosensor for detection of the textile azo dye Disperse Red 1 in treated water. Sensors and Actuators, B: Chemical, 236, 52
59. https://doi.org/10.1016/j.snb.2016.05.040.

Moreover, using tap water spiked with Dr1, the immunosensor’s performance was assessed, and an acceptable recovery of 98.5% was obtained (Rocha et al., 2016). Carbon paste electrodes are widely used in electrode preparation and sensor applications in electrochemistry studies (Amrutha et al., 2019; Raril and Manjunath, 2018). In another study, Manjunatha prepared a biosensor based on a poly(glycine)-modified carbon paste electrode (CPE) and investigated the determination of indigo carmine (IC) by both CV and differential pulse voltammetry (DPV). In this study, the design of the biosensor was based on coating the bare CPE surface with a poly(glycine) film. For this purpose, the bare electrode surface was immersed in PBS (pH 5.7) containing glycine, and 10 cycles of CV were applied at a potential range of 500
1800 mV at 100 mV s21. The number of cycles for electropolymerization, the effect of different pH, scan rate, and concentration were optimized. The results demonstrated that, under optimum conditions, biosensor exhibited extraordinary electrocatalytic activity for the oxidation of IC. The developed sensor showed remarkable electroanalytical performance in the linear ranges (2 3 1026
1 3 1025 M) and (1.5 3 1025
6 3 1025 M) with a LOD of 11 3 1028 M. Moreover, real sample applications of the developed sensor using indigotindisulfonate injection demonstrated the applicability of the sensor with satisfactory recovery values (Manjunatha, 2018). In their study, Yang and coworkers developed a simple label-free impedimetric immunosensor design for the determination of the textile

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dye Disperse Orange 1. To form amino groups on the surface of the working electrode, the bare electrode was immersed in 1,12-diaminododecane (DADD) and 1,7-diaminoheptane (DAH) solutions, respectively, and the surface was modified by the CV technique. The obtained monolayer film layer by using these two diaminoalkanes of different lengths provided the appropriate surface for efficient immobilization of the antibody in the next step (Fig. 11.3). In this study, the effect of scan rate on modifying DADD and DAH on the electrode surface and the effect of the dilution of antibody and Disperse Orange 1 were both investigated to enhance the performance of the developed immunosensor. Under optimal conditions, the linear range for the Disperse Orange 1 was found to be linear in the range of 5.0 nmol L21 to 0.5 μmol L21 with LOD of 7.56 nmol L21. Moreover, thanks to the developed low-cost and simple immunosensor, the determination of Disperse Orange 1 in tap and mineral water samples could be done successfully (Yang et al., 2015). Modifying the electrode surfaces with functional nanomaterials to improve the performance of the sensing platforms gives special properties NH2

NH2

NH2

NH2

NH2

NH2

NH2

NH2

GCE

NH2

NH2 NH2

DADD DAH

NH2

NH2

GCE

NH2

NH2

NH2

NH2

GCE

GCE

H2N

NH2

NH2

GCE

H2N

NH2

NH2

Ab anti-DO1 DO1

Figure 11.3 Schematic representation of the preparation procedure and detection principle of the immunosensor. Source: Reprinted with permission from Yang, J., Gomes Da Rocha, C., Wang, S., Pupim Ferreira, A. A., & Yamanaka, H. (2015). A labelfree impedimetric immunosensor for direct determination of the textile dye Disperse Orange 1. Talanta, 142, 183
189. https://doi.org/10.1016/j.talanta.2015.04.042.

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such as large specific surface area and high conductivity. In recent studies, nanomaterials have been generally utilized as modifiers for constructing electrochemical sensors and biosensor systems employed for environmental, clinical, industrial, and pharmaceutical analyzes (Uslu, n.d.). In particular, metal-based nanomaterials are frequently preferred materials to improve the catalytic performance of sensors (Bozal-Palabiyik et al., 2021). In their study, Zhu and coworkers developed a sensitive immunosensor based on cobalt hydroxide and gold nanoparticles (Co(OH)2
Au NPs)-modified electrode for the determination of rhodamine B. When the surface of the bare electrode was coated with Co(OH)2
Au NPs, the impedance value of the modified electrode increased compared to the bare electrode. While this increase was due to the fact that Co(OH)2 is a poorly conductive material, it can significantly increase the specific surface area of the electrode. Moreover, when Co(OH)2 and Au NPs were used combined, the conductivity increased significantly. These increases indicated that in the next step, antigen and antibody molecules can be successfully immobilized on the electrode surface. After the nanomaterial-modified electrode was immobilized with blocking reagent, antibody and rhodamine B, respectively, antigen concentration, dilution factor for antibody, the interaction rate of cerium oxide used as signal amplification with the antibody, and the reaction time of antibody and rhodamine B were optimized. Under optimal conditions, the developed immunosensor exhibited a linear range of 0.01
10000 ng mL21 with LOD of 0.89 pg mL21. In addition, the developed immunosensor was successfully used for the determination of rhodamine B in red pepper and capsicol samples (Zhu et al., 2022). One of the most important factors in the preparation of biosensors is the choice of biorecognition elements that directly affect the selectivity of the biosensor. As protein catalysts that accelerate biochemical reactions, enzymes are of great interest due to their superior catalytic properties (Kurbanoglu et al., 2020). In 2017, for the first time, a biosensor developed for the determination of azo dye tartrazine in the study of Mazlan and coworkers utilized the laccase enzyme, which is frequently used in the design of biosensors for the determination of various phenolic substances. In this study, the immobilization of enzyme on functionalized methacrylateacrylate microspheres and Au nanoparticles (Au NPs)-modified electrode served as the design for the developed biosensor. The interaction reaction between tartrazine and laccase can be catalyzed by the laccase, and the DPV method was used to detect the current change. The obtained results showed that the methacrylate-acrylate microspheres and Au NPs-modified

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Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

electrode increased the efficiency of the electrode surface reaction for tartrazine detection. After optimizing the experimental conditions, the anodic peak current showed linearity in the range of 0.2
14 μM with LOD of 0.04 μM versus increasing tartrazine concentration. In addition, tartrazine content in candy coated with chocolate and mango juice samples was successfully determined using the developed biosensor (Mazlan et al., 2017). In another study, the laccase-based electrochemical enzyme biosensor was developed by Rozi and coworkers for the determination of Sunset Yellow. In this study, first of all, the surface of the working electrode was modified with a poly(acrylamide-co-ethyl methacrylate) (poly(AAm-co-EMA)) membrane using a one-step photopolymerization technique to enable more efficient immobilization of laccase. For the electrochemical behavior of the developed biosensor, the bare working electrode, poly(AAm-co-EMA)-modified electrode, and laccase-modified electrodes were investigated by the CV method. While there were no oxidation or reduction peaks in the bare and poly(AAm-co-EMA)modified electrodes in the buffer solution containing Sunset Yellow, both oxidation and reduction peak currents were observed in the laccase-modified electrode. These results showed that the developed biosensor showed significantly improved performance for Sunset Yellow determination. In order to determine the optimum conditions for the developed biosensor, different pH values, laccase enzyme loading, accumulation time, and stability were evaluated. When the DPV responses were examined, with increasing Sunset Yellow concentration, the current responses of the developed biosensor showed linearity between 0.08 and 10.00 μM with a LOD of 0.02 μM. In addition, the amount of Sunset Yellow in soft drink samples was successfully determined using the developed biosensor (Rozi et al., 2018). Biosensors, in which nucleic acids are used as biorecognition elements, provide high stability, easy preparation, and the formation of surfaces suitable for reuse. Unlike antibodies and enzymes, biosensors modified with DNA sequences shorten the detection time and simplify the detection method (S. Kurbanoglu et al., 2016). In their study, Ensafi and coworkers prepared a ds-DNA-based biosensor and evaluated the determination of chrysoidine in food and textile wastes based on the interaction between chrysoidine and ds-DNA. In this study, the interaction mechanism between chrysoidine and ds-DNA was investigated by monitoring the oxidation currents of both DNA’s electroactive bases guanine and adenine and chrysoidine in DPV. First, the surface of the activated bare pencil graphite electrode (PGE) was modified using multi-walled carbon nanotubes (MWCNTs)-poly(diallyldimethylammonium chloride) (PDDA) for more efficient immobilization of

Electrochemical biosensing for determination of toxic dyes

233

Figure 11.4 (A) Diagram for the preparation of DNA/MWCNTs-PDDA, (B) SEM image of (a) bare PGE, (b) MWCNTs-PDDA/PGE, and (c) DNA/MWCNTs-PDDA/PGE, (C) impedance spectra of (a) bare PGE; (b) MWCNTs-PDDA/PGE; and (c) DNA/MWCNTsPDDA/PGE in 5.0 mmol L21 Fe(CN) 632/42 containing 0.10 mol L21 KCl. Source: Reprinted with permission from Ensafi, A. A., Jamei, H. R., Heydari-Bafrooei, E., & Rezaei, B. (2014). Development of a voltammetric procedure based on DNA interaction for sensitive monitoring of chrysoidine, a banned dye, in foods and textile effluents. Sensors and Actuators, B: Chemical, 202, 224
231. https://doi.org/10.1016/j.snb.2014.05.001.

ds-DNA molecules to the surface. Next, the modified surface was incubated with ds-DNA for use in the detection of the chrysoidine as shown in Fig. 11.4A. Morphological examination of the prepared electrode surfaces was examined by scanning electron microscopy (SEM). In Fig. 11.4B, the graphite layers of the bare working electrode are clearly visible, while SEM images of the MWCNTs-PDDA (Fig. 11.4B)-modified surface showed a homogeneous coating. The obtained changed SEM image after incubation of the modified surface with ds-DNA also confirmed the immobilization of dsDNAs to the surface. In addition, electrochemical characterization results using EIS also showed the accuracy of the preparation steps of the biosensor (Fig. 11.4C). In general, the surface impedance decreased as a result of the modification of the bare electrode with nanomaterials, while the impedance value increased as expected as a result of incubation of the surface with dsDNA. After the optimum experimental conditions were determined, a linear range of 0.05
15.00 μg mL21 with LOD of 0.03 μg mL21 was obtained by using the developed DNA-based biosensor for the determination of chrysoidine. Moreover, using this biosensor, the chrysoidine content of ketchup tomato sauce, chili tomato sauce, fish, and industrial waste samples could be accurately determined (Ensafi et al., 2014). The integration of biorecognition elements with synthetically prepared MIP enables the preparation of more selective and sensitive bioimprinted polymer-based sensors. In their study, Rezaei and coworkers developed a DNA- and MIP-based bioimprinted sensor for Sudan II determination using a one-step electropolymerization method. In this

234

Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

Figure 11.5 (A) Schematic representation of the proposed bioimprinted sensor, (B) three-dimensional AFM image of treated PGE, and (C) three-dimensional AFM image of bioimprinted sensor. Source: Reprinted with permission from Rezaei, B., Boroujeni, M. K., & Ensafi, A. A. (2016). Development of Sudan II sensor based on modified treated pencil graphite electrode with DNA, o-phenylenediamine, and gold nanoparticle bioimprinted polymer. Sensors and Actuators, B: Chemical, 222, 849
856. https://doi.org/ 10.1016/j.snb.2015.09.017.

study, a poly-(o-phenylenediamine)-based surface was obtained on the electrode surface by CV technique using a mixture containing ds-DNA, Au NPs, o-phenylenediamine, and Sudan II (Fig. 11.5A). While the surface characterization of the bioimprinted polymer was successfully performed by CV and EIS methods, the surface morphology was also investigated using atomic force microscopy (AFM). As shown in Fig. 11.5B and C, the roughness changes of AFM images of the treated PGE and the bioimprinted polymer confirmed that the surface was successfully coated. For the successful determination of Sudan II, the number of scan cycles for electropolymerization, the composition of MIP, concentration of Sudan II, pH, incubation time, and removal time were optimized. Linear ranges in the range of 1.0
20.0 nM and 20.0
500.0 nM with LOD of 0.3 nM were obtained using square wave voltammetry (SWV) under optimum experimental conditions. Furthermore, the developed sensor has been successfully applied to the determination of Sudan II in hot pepper and ketchup sauces with satisfactory recovery values (90%
107%) (Rezaei et al., 2016). Aptamers, which have come to the fore as biorecognition elements in recent years, are single-stranded oligonucleotide molecules (either DNAor RNA-based) that can bind to target molecules with high specificity and affinity. Aptamers are simple to make and flexible enough to be modified with various chemical tags without losing their affinity. Due to their

Electrochemical biosensing for determination of toxic dyes

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several binding characteristics, aptamers provide a novel, quick, and efficient platform for the detection of a broad range of target compounds such as heavy metal ions, proteins, peptides, drugs, and small molecules (Ravalli et al., 2016). In 2019, Wang and coworkers designed a label-free electrochemical aptasensor for the sensitive and selective determination of malachite green. This aptasensor design was based on modifying the bare GCE surface with Au NPs, graphene quantum dots (GQDs), and tungsten disulfide nanosheets (WS2). As shown in Fig. 11.6A, first, the GCE surface

Figure 11.6 (A) Fabrication process of the aptasensor for malachite green detection, (B) EIS spectra of the designed aptasensor at different modification stages, (C) CV responses of different modified electrode. (a) Bare GCE, (b) AuNPs/GQDs-WS2/GCE, (c) aptamer/AuNPs/GQDs-WS2/GCE, (d) MCH/aptamer/AuNPs/GQDs-WS2/GCE, and (e) malachite green/MCH/aptamer/AuNPs/GQDs-WS2/GCE. The CV measurements were performed in 0.1 M KCl solution containing 5 mM K3 [Fe(CN)6] at a scan rate of 50 mV s21 A. Source: From Wang, Q., Qin, X., Geng, L., & Wang, Y. (2019). Label-free electrochemical aptasensor for sensitive detection of malachite green based on au nanoparticle/graphene quantum dots/tungsten disulfide nanocomposites. Nanomaterials, 9 (2). https://doi.org/10.3390/nano9020229.

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was modified with GQDs-WS2 and Au NPs, respectively. The modified surface is then modified with aptamer and 6-mercapto-1-hexanol (MCH) to prevent specific binding. In the last step, the aptasensor surface was incubated with increasing concentrations of malachite green, and DPV signals were followed. The prepared GQDs-WS2 surface exhibited superior electrocatalytic properties for more efficient modification of Au NPs, while the aptamers were more efficiently immobilized on the surface covalently via Au
S bonding when the surface was modified with Au NPs. Results from EIS (Fig. 11.6B) and CV (Fig. 11.6C), which were found in agreement with one another, showed that the developed aptasensor can be used successfully in the determination of malachite green. Using this developed label-free electrochemical aptasensor, linearity was achieved between increasing malachite green concentrations in the range of 0.01
10 μM and DPV responses. Also, the LOD value was found as 3.38 nM in fish samples (Wang et al., 2019).

11.5 Conclusion and future perspectives It is a significant topic to determine dyes, pigments, and their metabolites directly and accurately in environmental monitoring, food control, public, and health all the time. But a deficiency of appropriate and efficient determination techniques makes it arduous to apply rapid in situ determination of dyes in the sample matrix. Electrochemical sensors have extensive implementation probabilities in environmental monitoring and other areas. Despite remarkable improvement being made, there are certain limitations and difficulties in the design of electrochemical sensors. • Although electroanalytical biosensors are extremely sensitive, selective, and low cost, there is yet a requirement to advance their electrochemical performance. It is probable that search will proceed into the modification of electrode surfaces with assorted nanoparticles, quantum dots, conducting polymers, nanomaterials, etc., with regard to the development of selectivity, sensitivity, and the response of electrochemical biosensors. • The sensitivity, selectivity, and stability of electrochemical sensors will be cultivated by designing novel nanoelectrode compounds and materials. The use of new advanced conductor and semiconductor nanomaterials demonstrates well the electrochemical efficiency and high performance, displaying encouraging potential for electrochemical sensors. So, recently, investigators in the field of biosensors are studying the improvement of

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•

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novel nanostructured nanocomposites, which ensure an appropriate material for binding of biological sensing layers. Since the electrochemical biosensor systems have readily fabricated designs for the detection of toxic dyes in the environmental, industrial, and food matrices, commercializing them with low-cost methods is a significant topic that must be taken into notice. Also, the implementation of the electrochemical biosensor systems in real sample areas such as textile wastewater ponds for the determination of toxic dyes should be improved. Another significance that charms lots of researchers concerning the exploitation of this special area for discovery is its versatility. Biosensor technology is a multidisciplinary technology and includes the collaborative endeavors of chemistry, engineering, biology, physics, microbiology, biotechnology, electrical, electronics, and so on. As a result, future developments in biosensors will be possible with the cooperation of these branches of science.

Acknowledgment Cem Erkmen thanks The Scientific and Technological Research Council of Türkiye (TÜB˙ITAK) through the 2218-National Postdoctoral Research Fellowship Programme (Project number: 122C252).

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CHAPTER 12

Electrochemical detection of pathogens in water and food samples K. Soumya1, P.A. Geethanjali1, C. Srinivas2, K.V. Jagannath3 and K. Narasimha Murthy2 1

Department of Microbiology, Field Marshal K.M. Cariappa College, A Constituent College of Mangalore University, Madikeri, Karnataka, India Department of Microbiology and Biotechnology, Jnana Bharathi Campus, Bangalore University, Bangalore, Karnataka, India 3 Department of Studies in Chemistry, Central College Campus, Bengaluru City University, Bangalore, Karnataka, India 2

12.1 Introduction Food and water cleanliness are significant factors for the food industry. Pathogenic microbes in water and food have the potential to cause serious illnesses with both public health and economic consequences (World Health Organization [WHO], 2019). With an increase in the eating of fresh produce, ready-to-eat products, and fruits that have not been subjected to an important bacteria-kill step, such as cooking, the risk of consuming foods containing infection pathogens has increased. Many diseasecausing microbes, such as fungi, bacteria, and viruses, present in water and food endanger animal production and the supply of food, resulting in severe economic inferences. Ingestion of insecure food products contaminated by viruses, bacteria, chemicals, or parasites causes foodborne illnesses and is one of the main problems in public health worldwide, hindering socioeconomic progress. According to the World Health Organization, contaminated water and food containing destructive parasites, bacteria, chemical substances, or viruses cause over 200 infections ranging from diarrhea to cancer. Each year, a predictable 600 million people fall ill after consuming contaminated food, and 420,000 deaths occur, resulting in a loss of 33 million infirmity-adjusted life years (DALYs). Foodborne microbes are extremely varied in nature and continue to cause the main public health issues worldwide. As a result, food security is a critical problem for both Novel Nanostructured Materials for Electrochemical Bio-sensing Applications DOI: https://doi.org/10.1016/B978-0-443-15334-1.00032-8

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consumers and food production (Sankarankutty, 2014). Foodborne illnesses are particularly problematic in the twenty-first century. Science and technological advancements, as well as economic development, have been incapable of efficiently controlling the spread of foodborne illnesses, which are on the rise (Lawrence, 2018). Pathogen-caused foodborne illnesses are known to cause periodic intestinal swelling, joint problems, mental retardation, impaired vision, chronic kidney infections, and even death (Hoffmann et al., 2015). Diseases caused by foodborne pathogens are classified into four types. The first type is food poisoning, which refers to acute or subacute illnesses that happen after consumption of food contaminated with toxic ingredients (Inoue et al., 2018); the second type is hypersensitive illnesses related to food (Hose et al., 2018); and the third type comprises infective illnesses (dysentery) (Berhe et al., 2019). Without a doubt, foodborne illnesses have become a worldwide public health issue that affects everybody. Numerous water-based toxins can be fatal to fauna if inhaled. Waterborne disorders, such as diarrhea, systemic illnesses, and gastrointestinal, are worldwide problems that kill millions of people each year (WHO, 2015). The most common waterborne pathogens are Vibrio cholerae, Staphylococcus aureus, Bacillus cereus, Clostridium perfringens, and Escherichia coli (Huang, Hsu et al., 2016; Huang, Liu et al., 2016). Pathogens in food and water can pass through contaminated water and food. As a result, it is critical to identify pathogens in water and food before they enter the body and cause a severe outbreak (Chattaway et al., 2011). Such organisms mainly include Acinetobacter spp., C. perfringens, Clostridium difficile, Bacillus subtilis, Klebsiella oxytoca, Citrobacter koseri, Citrobacter freundii, B. cereus, Enterobacter sakazakii, Listeria monocytogenes, Salmonella, Enterobacter cloacae, E. coli, Campylobacter jejuni, and Klebsiella pneumoniae (Khan et al., 2010). Viruses are also accountable for a wide range of infections that kill thousands of people every year (WHO, 2015), including influenza (Bitton, 2014), Ebola (Zhao et al., 2014), Middle East respiratory syndrome (MERS) (Rhoden et al., 2021), HIV/AIDS (Alhamlan et al., 2015), and more recently, coronavirus disease, 2019 (COVID-19). Recently, the global health and economic impact of the SARS-CoV-2 pandemic (severe acute respiratory syndrome coronavirus 2) has intensified focus on the essentials for low-cost viral disease finding and preparedness for future outbreaks. Foodborne diseases caused by fungi, parasites, viruses, or bacteria are spread through the consumption of contaminated water or

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food. Norovirus (58%), C. perfringens (10%), Campylobacter spp. (9%), S. aureus (3%), and nontyphoidal Salmonella spp. (11%) cause the majority of illnesses. Nontyphoidal Salmonella spp. (35%), Norovirus (26%), Campylobacter spp. (15%), Toxoplasma gondii (8%), and E. coli (STEC) O157 (4%) were the important reasons for hospitalization. Campylobacter spp. (6%), T. gondii (24%), norovirus (11%), nontyphoidal Salmonella spp. (28%), and L. monocytogenes (19%) were the leading causes of death (Scallan et al., 2011). Nontyphoidal Salmonella spp. accounted for 90% of the total economic loss (Hoffmann et al., 2015). Conventional and official techniques for the detection and identification of disease-causing pathogens mainly rely on particular molecular and cultural approaches. Using traditional microbiology and molecular biology methods such as staining or microscopy, cell culture, PCR, membrane filtration, Enzyme Linked Immuno Sorbent Assay (ELISA), and microarray (Pashazadeh et al., 2017) increases the efficiency of pathogen detection in food and water. Cultural methods are very effective and sensitive, but they are expensive and time-consuming. Most of these techniques still necessitate steps such as bacterial culture purification and enrichment. The methods described above are considered reliable, but they have several drawbacks, particularly in the bacterial context, such as the need to concentrate the bacteria through membrane filtration of huge amounts of water, long lag times for progress (up to 72 hours), and the necessity for skilled staff. There are currently some disadvantages to immunological methods, such as time consumption process complications (5
6 days) and incomplete information, specifically the inability to differentiate species (Inbaraj & Chen, 2016). The conventional method is incapable of meeting the demands of food safety management and rapid pathogen detection (Cam & Oktem, 2019). As a result, there is still an essential need for fast, low-cost discovery and identification methods with high sensitivity and selectivity (Vidic et al., 2019). As a result of their high specificity and sensitivity, nucleic acid-related methods based on deoxyribonucleic acid (DNA) probes have become extensively established. Demand for faster detection of food and waterborne pathogens continues to rise to prevent infectious diseases, ensure food safety, and protect public health. Conjugated nanomaterials, integrating biological sensing elements, and electronic signal transducers on a single platform have acceptable diagnostic device advancements (Liu et al., 2019). In recent years, investigators have made significant advances in pathogen detection using chromatography, mass spectrometry, fluorescence,

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and electrochemical approaches. Electrochemical methods, for example, are among the most promising methods for detecting pathogens in a highly sensitive, low-cost, and selective way (Hasan et al., 2018). Electrochemical approaches have increased in popularity due to their ease of fabrication, suitability for miniaturization and biomolecule incorporation, and, most importantly, their appropriateness for infield use by unskilled operators. Electrochemical biosensors can operate as standalone units that can be reduced in size, permitting direct measurement of liquid media (Singh et al., 2016). Because of the direct transduction of definite binding of targets to electrons without the requirement for photons, the sensitivity of the electrochemical assessment is integrally greater than that of most detection approaches (Grieshaber et al., 2008). Electrochemical biosensors are at the forefront of analytical devices due to their specificity, high sensitivity, and low manufacturing cost, and emerging devices for observing microbes and pathogens in drinking water are extremely needed (Wu & Ju, 2012). As a result, recent research has concentrated on the alteration of electrodes, the use of nanomaterials, and the incorporation of other approaches to increase detection sensitivity. Electrochemical sensors are made up of two major components: a transducer and a receptor. Many biological elements, such as enzymes, phages, aptamers, whole cells, antibodies, DNA, and receptors, are used in biosensors (Kurbanoglu et al., 2020). Molecularly imprinted polymers (MIPs) placed on the electrode surface, on the other hand, serve as selective recognition units (Leibl et al., 2021). Electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV), differential pulse voltammetry (DPV), linear sweep voltammetry, square wave voltammetry (SWV), amperometry, alternating current voltammetry, polarography, and conductometry are among the electrochemical biosensor schemes used to detect pathogens. Electrochemical sensing is typically carried out with two electrodes (reference and working electrodes) or three electrodes (reference, working electrodes, and auxiliary) (Michael Immanuel Jesse et al., 2015). Numerous working electrodes, including laser-induced graphene, screen-printed carbon electrodes (SPCE), and microarray electrodes, have been used to identify foodborne pathogens (Soares et al., 2020). Moreover, the use of DNA and amplification reactions may increase the sensor's sensitivity (Cai et al., 2021). Unlike voltammetric measurement, amperometric detection includes measuring current at a constant voltage and recording the current as a function of time (Amine & Mohammadi, 2019).

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In a two-electrode system, potentiometry sensors measure the possible difference between the indicators and counter electrodes (Aragay & Merkoçi, 2012). Voltammetric techniques can be altered to include a step that preconcentrates the target on the electrode surface (Manjunatha et al., 2010; Manjunatha, 2020c). The preconcentrated target is then stripped from the surface using an electrical potential. A negative potential is used in anodic stripping voltammetry (ASV) to preconcentrate metal ions onto the electrode surface. Numerous electrode types used in electrochemical biosensors are described below. Gold's unique properties (such as conductivity, stability, and biocompatibility) have encouraged its use as an electrode in electrochemistry. The sensitivity and functionality of gold electrodes can be improved by altering their surface with appropriate molecules and polymers (Manjunatha, 2018). Furthermore, gold nanoparticles (NPs) were used in the electrochemical biosensing field not only because of their high conductivity and compatibility but also because of their high surface-tovolume ratio (Xiao et al., 2020). Carbon has been identified as one of the most widely used electrode materials in electrochemical biosensing. Carbon paste, carbon nanotubes, glassy carbon, and graphene electrodes are the most common forms of carbon used as electrodic materials; all of these carbon materials are less expensive than noble metals. Carbon-based electrodes have numerous advantages, including low background current, low cost, regenerability, and a wide range of operating potentials. Nevertheless, apart from their high price, glassy carbon electrodes require a perfect pretreatment process, which constrains their use in many electrochemical uses (Curulli, 2021). Carbon nanotubes (CNTs) exhibit a variety of properties related to their functionality, structure, morphology, and flexibility. They are categorized as single-walled nanotubes, double-walled nanotubes, and multiwalled nanotubes based on the number of graphite layers (Charithra et al., 2020; Manjunatha et al., 2020). Functionalized CNTs have been used in a variety of applications (Hareesha et al., 2021; Manjunatha Charithra & Manjunatha, 2020; Manjunatha, 2020b; Prinith et al., 2021; Pushpanjali & Manjunatha, 2020; Tigari & Manjunatha, 2020a,b). Chemical functionalities for biosensing applications can be easily considered and altered by modifying the tubular structure. Graphene is a widely used nanomaterial in the sensing field. Many procedures have been used to create various graphene-based materials (for example, electrochemically

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and chemically modified graphene) (Manjunatha, 2020b; Pumera, 2010; Raril & Manjunatha, 2020). Graphene has properties like high conductivity, which speeds up electron transfer, and a large surface area, which are much related to the corresponding properties of CNTS, so it is a good applicant for collecting sensors to detect multiple target particles. Screen printing technology provides numerous benefits for electrochemical biosensor assembly, comprising an extensive variety of geometries, disposability, portability, and mass production (Smart et al., 2020). These characteristics are critical for commercializing biosensors by analyzing the choice of support material, ink composition, and methods of surface alteration or functionalization (Hughes et al., 2016).

12.2 Label-based electrochemical detection Enzymes and NPs are commonly used as labels for electrochemical detection (Siangproh et al., 2011). Enzymes are typically used to catalyze a reaction that results in the formation of an electroactive product or the deposition of particles on an electrode surface, resulting in variations in electrical parameters. The ability to amplify the signal is one of the most significant benefits of using labels in electrochemical findings. When very low concentrations of bacterial cells are bound to the electrode surface, a signal amplification step is usually required. By conjugating nanomaterials to antibodies, they can be used as labels to bind target bacteria on the electrode surface. The acceleration in electrical resistance that results can then be calculated. Enzyme labels for electrochemical discovery were usually added to a sample's intercellular matrix. Label-free electrochemical methods depend on the direct detection of electrical property variations caused by a biochemical response on an electrode surface (Daniels & Pourmand, 2007). The immobilization of mediators and conductive materials on the electrode surface is required for electrochemical detection. Because bio-recognition elements such as phages and antibodies are frequently essential to be fixed onto an electrode surface, the protein immobilization process is critical to the progress of both label-based and label-free electrochemical biosensors. Adsorption, covalent binding, entrapment, and molecular linkers can all be used to immobilize proteins on a sensor surface (Kim & Herr, 2013). When developing enzyme-based detection, the number of proteins that can be immobilized on electrodes

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must be considered. Immobilization techniques should be stable and maintain enzyme activity after the procedure. A common method for providing the most stable immobilization is the development of covalent bonds among the functional groups of protein and the electrode surface (Wong et al., 2009). Redox cycling is an important signal amplification technique in the improvement of electrochemical discovery to attain ultrasensitive findings. Enzyme labels can help with signal amplification, but they are not continuous enough to detect low concentrations of bacteria. To overcome this issue, numerous methods of signal enhancement, such as enzymatic amplification and redox cycling, may be required. Likewise, electrochemical biosensors (potentiometric, amperometric, impedimetric, and conductometric) use voltage, current, capacitance, or impedance measurements to detect receptor target binding, which changes the biochemical response into a determinate electrical signal. Impedance biosensors use biomolecule connections with a conductive or semiconducting transducer surface to measure the resultant current (Knopf & Bassi, 2018). Electrochemical, optical (UV, fluorescence, bioluminescence, etc.), micromechanical transducers, thermometric, piezoelectric, and magnetic are the most commonly used signals. Potentiometry, conductometry, and EIS are used by electrochemical sensors to detect the analyte of interest. Electrochemical sensing has become popular due to its incorporation into point-of-care testing (Kaushik et al., 2021). Furthermore, the incorporation of various nanomaterials with rapid sensitivity, specific detection response, miniaturization, and integration capabilities, such as CNTs, metal oxide, silica NPs, and metallic NPs, into point-of-care testing (Mahari & Gandhi, 2022). Furthermore, when compared to CNTs, silica NPs, metallic NPs, and metal oxide sensors with only molecular probes, antibodies, or peptides, the use of different NPs, such as organic NPs, increases the discovery limit (Naresh & Lee, 2021).

12.3 Electrochemical detection of microorganisms Pathogens are disease-causing microbes that play an important role in the health of animals, humans, and plants, food safety, and ecological toxicity. Early findings of these microbes can save lives and resources, as well as pave the way for better disease control policies in a variety of industries (Sun et al., 2021). Biological water contamination is caused by living

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microbes such as fungi, bacteria, viruses, protozoa, and algae and is typically caused by contaminated water and poor hygiene practices. Throughout their growth, these microbes can release toxins and other harmful materials into their extracellular surroundings (Razmi et al., 2020), contaminating food and water materials and leading to a diversity of foodborne and waterborne infections. Foodborne pathogens not only endanger people's lives and health, but they also cause enormous financial losses (Bosch et al., 2018). As a result, food safety has become an increasingly important issue (Zhang, Zhou, Du, 2019; Zhang, Zhu, He et al., 2019). Food poisoning, allergic diseases, and infectious diseases are some of the health issues caused by foodborne pathogens (Sun et al., 2021). Bacteria are single-cell prokaryotic organisms with a wide range of shapes. Soil, air, water, and other biological species are among their habitats. They reproduce asexually through binary division, which explains their rapid propagation in infections (Gupta, 2000). Bacterial infections are one of the foremost causes of death worldwide; nevertheless, developing fast, cost-effective, and reliable pathogen detection approaches remains difficult. Due to their increasing competitive sensitivity, electrochemical sensing techniques have improved care in recent years for the discovery of pathogenic bacteria.

12.3.1 Electrochemical detection of Escherichia coli In most cases, the contagion is developed through the fecal-oral route by consuming contaminated and raw food, such as various leaf vegetables, unpasteurized milk, beef, and water. It should be noted that E. coli-related food/waterborne diseases are among the leading causes of illness in many developing countries (Kim et al., 2013), causing gastroenteritis and other diseases with dire consequences (Kaper et al., 2004). Humans are more likely to become infected with E. coli after drinking contaminated water or eating underripe fruits and vegetables. Furthermore, a person with poor cleanliness may become diseased through human transmission or by consuming feces-contaminated food (Guo et al., 2019). As a result, detecting E. coli in our diet is critical for our health. E. coli is one of the most common bacteria related to foodborne and waterborne illnesses. The need to deal with outbreaks, such as a spinachactivating event, prompted scientists to create analytical tools (Linman et al., 2010). The approaches have concentrated on identifying elements of the bacterial surface. Aptamers and antibodies were used in the

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methods to achieve immobilization on NPs. Microfluidic device with a coplanar waveguide for discriminating between live and heat-killed E. coli cells in culture media using microwave signals with frequencies ranging from 0.5 to 20 GHz. Researchers have developed a centrifugal microfluidic automatic wireless endpoint-finding method combined with LAMP that can perform 30 reactions at the same time (Sayad et al., 2018). Similar studies have used the LAMP method to evaluate microfluidic devices (Trinh et al., 2019). Using gram-positive B. subtilis and E. coli as reference pathogens, Yeung et al. (2006) defined the design and implementation of a multipathogen microdevice for microorganism monitoring. Cesewski and Johnson (2020) evaluated some biosensors based on EAT for the discovery of E. coli and other pathogens. Amperometry with a graphene-based FET was used to identify E. coli in nutrient broth diluted with phosphate-buffered saline solution (Wu et al., 2016). Pandey et al. (2017) created an immune electrode using graphene-wrapped copper (II)assisted cysteine hierarchical structure (rGO-CysCu), which established that E. coli O157:H7 cells could be distinguished from nonpathogenic E. coli and other bacterial cells. Huang, Liu et al. (2016) and Huang, Hsu et al. (2016) established a simple, label-free, and low-cost electrochemical biosensor based on rolling circle amplification (RCA) and peroxidase mimicking DNA enzyme amplification for extremely sensitive findings of E. coli. Xu and colleagues studied the progress in developing electrochemical biosensors for the fast detection of E. coli, explaining the several biosensor configurations and sensing methods (Xu et al., 2017). One of the most capable approaches for the quick and dependable finding of pathogenic bacteria is the electrochemical genosensor (Abdalhai et al., 2014). A gold electrode was used to immobilize complementary DNA on a SAM, which was then hybridized with an exact fragment of the pathogen gene to form a sandwich structure. The MWCNT embedded in chitosan with a bismuth layer adapted a GCE for sensor performance discovery. Chen et al. (2014) discovered E. coli at a LOD of 13 CFU mL21 using stripping voltammetry with a polymer-CNT composite-based electrode. There are several reports of electrochemical biosensors for finding E. coli in foodborne pathogens (Zhang et al., 2018). He et al. (2012) established that by using Pt and Ag/AgCl gate electrodes, FETs based on PEDOT:PSS organic electrochemical transistor electrodes enabled the finding of E. coli in KCl solutions. In DPV detection, the biocomposite was used to capture E. coli O157:H7 and methylene blue (MB) as electrochemical indicators

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(Zhang, Zhou, Du, 2019; Zhang, Zhu, He et al., 2019). Arora et al. (2007) reported an electrochemical DNA biosensor for E. coli detection. Arreguin-Campos et al. (2021) proposed using MIP/(diamine functionalized polyurethane-urea)/aluminum chip a stimulating label-free E. coli determination with EIS and the heat transfer method, a developing food examination technique. Huang, Liu et al. (2016) and Huang, Hsu et al. (2016) created a label-free electrochemical biosensor based on a novel 3D Ag nanoflower. When E. coli O157:H7 was taken by the biosensor, the Fe (CN)632/42 was used as a redox probe to notice resistance changes.

12.3.2 Electrochemical detection of Salmonella spp Salmonella is a gram-negative, rod-shaped bacterium with over 2650 serotypes (Kipper et al., 2019), the most dangerous of which are Salmonella typhimurium and Salmonella paratyphi A. The most common Salmonella serotype that can cause systemic infection is S. typhimurium (Pandey et al., 2014). Salmonella spp. is one of the most common causes of foodborne illness and a public health concern. Salmonella infection can be fatal in young children (especially those below the age of 5), the elderly, and people with compromised immune systems (Scallan et al., 2011). The two most common causes of human contagions are Salmonella enteritidis and S. typhimurium. Although the definitive culture media method is the gold standard testing technique, it is time-consuming and requires 2
5 days to confirm an analysis. Numerous researchers have focused on meat, dairy, vegetable, and beverage cultures. Efforts were made to develop a combined microfluidic sensor that produced detailed results through image examination using a smartphone application (Zhang, Zhou, Du, 2019; Zhang, Zhu, He et al., 2019). In milk, a micronanotechnology technique was used (Papadakis et al., 2018). After a preenrichment stage, this acoustic biosensor captured cells using magnetic beads and antibodies. For the finding of S. enteritidis, a pathogen assessment system based on microfluidics and a simple film was obtainable (Park, 2018). Dong et al. (2013) reported an electrochemical impedance immunosensor for the detection of S. typhimurium in milk samples. The fluorescence could be quantified using a smartphone app. The biosensor had a revealing limit of 58 CFU mL21 and a dynamic range of 1.4 3 102 to 1.4 3 106 CFU mL21. Antibodies immobilized on magnetic beads were used in another method of findings (Vinayaka et al., 2019). A detection limit of 2 CFU mL21 was

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found in a range of samples comprising egg yolk, vegetable salad, minced pork meat egg white, and whole egg. Wang et al. (2019) reported an online Salmonella detection process. To increase specificity, the device concentrated bacteria with immune magnetic NPs. The immune fluorescent microspheres were used to label the magnetic bacteria, resulting fluorescence emission. Muhammad-Tahir and Alocilja (2003) identified an electrochemical sandwich immunoassay as well as a reader for signal measurement. Kuang et al. (2013) described a fluorescent probe based on QDs antibodies for Salmonella detection with a sensitivity of 500 CFU mL21. Using two monoclonal antibodies that recognize Salmonella surface epitopes, they created antibody-coated magnetic NPs and QDs-antibody conjugates.

12.3.3 Electrochemical detection of Listeria monocytogenes L. monocytogenes, an opportunistic foodborne pathogen, is commonly found in ready-to-eat foods like milk, seafood, and heat-treated meat products (Vizzini et al., 2019). One of the most common food pathogens is L. monocytogenes. Pregnant women, the elderly, immunocompromised people, and neonates are more likely to contract the infection. L. monocytogenes has the potential to cause septicemia, abortion, stillbirth, meningoencephalitis, and meningitis, placing human health in danger (Liu et al., 2018). For the first time, Saini et al. (2020) described an electrochemical DNA biosensor based on the plcA gene (a virulent gene) for L. monocytogenes discovery using CV and EIS. Long et al. (2011) recommended a technique for identifying the hly gene in L. monocytogenes that combined HRCA (hyper 260 branching RCA) with a magnetic bead-based electrochemical method. Chemburu et al. (2005) suggested biosensors out of greatly detached carbon particles that could detect L. monocytogenes using antibodies immobilized on stimulated carbon particles labeled with HRPconjugated antibodies. Colorimetric biosensor strips made of peptides immobilized on a gold chip were also described to detect L. monocytogenes in milk and meat samples with an LOD of 2.17 3 102 CFU mL21 (Alhogail et al., 2016). The immobilizing HRP antibody against L. monocytogenes onto the surface carbon nanotube fibers created an amperometric immunosensor with a LOD of 1.07 3 102 CFU mL21 (Lu et al., 2016). The Gomes group established an advanced Listeria aptasensor using platinuminterdigitated microelectrodes (Sidhu et al., 2020). Chiriacò et al. (2018)

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created a miniaturized biochip with an array of interdigitated antibodies and functionalized electrodes for L. monocytogenes detection in medical and on-site settings. Wang et al. (2017) used urease-modified AuNPs to amplify the signal of impedance biosensors applied with magnetic NPs for the finding of L. monocytogenes in microfluidic impedance sensors made of different IDAM materials. Sun et al. (2012) defined electrochemical DNA biosensors made from GR and nanogold using electrodeposition methods to create Au/GR nanocomposite film-modified CILE. Gao et al. (2010) defined the electrochemical indicator toluidine blue for DNA electrochemical biosensors with diverse redox behavior on dsDNA and ssDNAaltered electrodes. Yang et al. (2017) tested magnetic beads to detect L. monocytogenes using the ECL detection technique in 269 other latest descriptions. Zhu et al. (2015) suggested a magnetic nanocarrier made of Fe3O4/Vancomycin (Van)/PEG for effective sample enrichment and in situ nucleic acid preparation of pathogenic L. monocytogenes for following gene sensing. Sitkov et al. (2022) used the microfluidic impedance of ITO interdigitated array microelectrodes to detect Listeria. Wu et al. (2010) described a new hybridization biosensor for the electrochemical discovery of LLO toxin gene PCR amplification products in food and the pathogen without labeling the target DNA.

12.3.4 Electrochemical detection of Vibrio spp Vibrio spp. is a genus of gram-negative bacteria found in numerous aquacultures and marine habitations; these are the most common and severe pathogens in shellfish and fish aquaculture around the world (Chatterjee & Haldar, 2012). Around 12 species of Vibrio spp. cause human contagions, which can be separated into cholera (by V. cholerae) and noncholera Vibrio infections (by V. parahaemolyticus, V. alginolyticus, and V. vulnificus) (Baker-Austin et al., 2018). Numerous species, including V. vulnificus, Vibrio harveyi, Vibrio anguillarum, V. alginolyticus, V. parahaemolyticus, and Vibrio salmonicida, affect mass death and vibriosis (contagion of skin and other organs) in cultured fishes (Ina-Salwany et al., 2019). V. cholerae is the pathogen accountable for human cholera, which is an older and more prevalent epidemic infection. Numerous epidemics around the world have been caused by V. cholerae, which is characterized by diarrhea, water loss, severe vomiting, and high death rates (Huang et al., 2013). As a result, it is included in international quarantine classifications of communicable illnesses. Cholera is accountable for 21,000
143,000 deaths and

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1.3
4.0 million cases globally each year (Ali et al., 2015). The techniques were tested on seafood, meat, dairy products, and bacterial cultures. Sharma et al. (2006) described the first V. cholerae electrochemical biosensor based on disposable SPE to adsorb V. cholerae polyclonal antibodies (PAb). To capture the targets, a one-step label-free biosensor for V. cholerae finding was established by means of antibodies covalently immobilized on a CeO2 nanowire-modified microelectrode. Zhao et al. (2007) developed a screen-printed graphite-based electrode for electrochemical detection of V. parahaemolyticus. Teng et al. (2017) reported an electrochemical sensor based on an antibody aptamer for the ultrasensitive discovery of V. parahaemolyticus. Laczka et al. (2014) described an analogous amperometric biosensor for the discovery of V. cholerae using a biotinylated PAb immobilized on a neutral vidine-altered surface of SPE. Park et al. (2017) developed a collective system that included a rotary microfluidic method suitable for the extraction of DNA, LAMP, and a colorimetric lateral flow strip.

12.3.5 Electrochemical detection of Streptococcus spp Streptococcus spp., compared to other bacteria, is a main cause of human and veterinary illness and death worldwide. Streptococcus detection using biosensors has been suggested for water and milk samples. Magnetically labeled specific peptides and antibodies improved specificity (Duarte et al., 2016). The detection encompassed SPR (Bouguelia et al., 2013), an impedance array (Lillehoj et al., 2014), a cytometer, and an electrical sensor. Streptococcus mutans electrochemical detection was achieved using printed circuit board (PCB) electrodes (Dutta et al., 2019). The thiolated primary antibody was immobilized to the electrode surface in this novel PCB-based electrochemical biosensor, and bacteria detection was accomplished using EIS. Ferreira et al. (2018) used electro polymerization to modify the graphite electrode surface. DPV analysis was used to track the current responses of EB in the presence of Streptococcus pneumoniae (Ferreira et al., 2018). Khan et al. (2018) used to optimize the detection limit and response time for the finding of bacterial species within a single sensor chip.

12.3.6 Electrochemical detection of Bacillus spp Bacillus species come into contact with humans and can cause food poisoning (Nwaru & Virtanen, 2017). Many foods, particularly improperly

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refrigerated left-overs, can cause this type of diarrhea (Xie & Zhou, 2018). B. cereus causes vomiting, abdominal pain, and diarrhea, which are very similar to C. perfringens indications (Wang et al., 2017). As a result, the emergence of a correct discovery technique for B. cereus in our food is quite significant. Hu et al. (2014) termed an electrochemical DNA biosensor to study B. subtilis 16SrDNA using a target-induced strand displacement mechanism and nicking endonuclease signal amplification. Yeung et al. (2006) described the design and implementation of a multipathogen microdevice for the monitoring of microorganisms, using gram-positive B. subtilis and E. coli as reference pathogens. Raveendran et al. (2016) described a sensitive electrochemical DNA biosensor for finding pathogenic Bacillus anthracis. Based on EIS measurements, Andrade et al. (2015) developed a detection assay using CNTs and clavanin A to identify Enterococcus faecalis, K. pneumoniae, B. subtilis, and E. coli. Velusamy et al. (2011) described an electrochemical DNA biosensor for the detection of B. cereus DNA. To immobilize DNA, the gold electrode surface was altered with polypyrrole, and then an immobile potential of 0.8 V was applied for 600 seconds to improve immobilization efficacy and constancy. Kang et al. (2013) defined an electrochemical immunosensor for B. cereus discovery in milk samples by means of chronoamperometry (Kang et al., 2013). Liang et al. (2010) described a novel B. cereus electrochemical sensor that used monoclonal antibodies immobilized on double-layer AuNPs to capture the target and chitosan to connect the sensing element to the GCE. The sensor established quick recognition, long-term constancy, and high sensitivity to bacterial contamination. Kang et al. (2013) created a microfluidic impedance sensor for B. cereus detection using a doublelayered gold nanoparticle and chitosan. The use of double-layer AuNPs improved antibody immobilization and retained antibody activity. Ait Lahcen et al. (2018) described a label-free electrochemical biosensor, and Izadi et al. (2016) created a B. cereus electrochemical biosensor based on DNA-based AuNPs-adapted pencil graphite electrodes (PGEs). The target was captured by a sensing element composed of AuNPs self-assembled with single-stranded DNA of the nheA gene immobilized with a thiol linker on the AuNPs modified PGE.

12.3.7 Electrochemical detection of Staphylococcus aureus S. aureus is a gram-positive bacterium that can cause severe purulent infections in humans, including pseudomembranous colitis and even systemic

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infections like sepsis, pneumonia, and pericarditis (Wang et al., 2018). It can secrete enterotoxin and cause food poisoning with symptoms of diarrhea, nausea, vomiting, and dehydration under the right conditions. S. aureus is also the most common cause of furunculosis (Abdalhai et al., 2014). Furthermore, mutations in the S. aureus gene sequence could result in the production of drug-resistant strains (methicillin-resistant S. aureusMRSA) as well as additional resistance to β-lactamases (Xu et al., 2018). Bekir et al. (2015) used impedance spectroscopy to detect S. aureus by observing the alteration in resistance before and after the S. aureus, recognized by anti-S. aureus, was immobilized on a gold electrode using ferri/ ferro cyanide as a redox probe. The biosensor established was then used to identify stressed and resuscitated microbes. An electrochemical biosensor for S. aureus was detected using a triple-helix molecular switch that can control the transfer of electrochemical signals (Cai et al., 2021). Cui et al. (2019) developed an ultrasensitive magnetic fluorescence aptasensor based on fluorescence resonance energy transfer for the isolation and finding of S. aureus. They improved S. aureus aptamers on the surface of Fe3O4 and carbon dots when cDNAs were hydrogen bonded into nanodimers. Jia et al. (2014) used impedance spectroscopy to report an electrochemical sensor for S. aureus detection that used single-stranded DNA as an aptamer linked to reducing graphene oxide-AuNPs nanocomposite. Nemr et al. (2019) combined a magnetic capture unit and an electrochemical discovery unit in a microfluidic platform. Because penicillinbinding protein 2a (PBP2a) causes methicillin resistance, anti-PBP2a antibodies functionalized magnetic NPs to definitely detain MRSA. Kurt et al. (2016) used aptamer-functionalized QDs and up conversion NPs to identify foodborne pathogens, S. typhimurium, and S. aureus.

12.3.8 Electrochemical detection of Clostridium perfringens C. perfringens is the most common type of Clostridium in clinically genital gangrene pathogens. The bacterium was called C. perfringens because it can form a capsule in the body (Saitoh et al., 2015). C. perfringens can break down sugar in muscle and connective tissue and then release a large amount of gas, causing a large area of tissue necrosis, causing severe tissue emphysema, and affecting blood supply. The DPV electrochemical signal could be detected using a “sandwich” reaction. Wang et al. (2018) defined an electrochemical biosensor for identifying the DNA of C. perfringens based on CeO2/chitosan-altered electrodes by observing impedance changes.

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C. perfringens electrochemical detection is primarily due to its DNA. Jiang et al. (2014) published an electro-chemiluminescence sensor for detecting C. perfringens DNA using RCA, similar to that reported by Zhao et al. (2016).

12.4 Electrochemical detection of viruses Viruses are accountable for affecting many various diseases that lead to hundreds of thousands of deaths each year (Saylan et al., 2019), including influenza (Webster et al., 1992), Ebola (Feldmann & Geisbert, 2011), MERS (Zumla et al., 2015), HIV/AIDS (human immunodeficiency virus/acquired immunodeficiency syndrome) (Mellors et al., 1996), and, more recently, COVID-19 (coronavirus disease, 2019). Viruses are regarded as one of the most transferrable pathogens in food manufacturing because of their increased resistance to treatment and the lesser doses necessary to cause infection. These are some of the smallest pathogenic agents known to man, with only a limited number of genes encased in a proteic capsid and a lipidic envelope (Ryu, 2017a). Norovirus, hepatitis A and E, sapovirus, rotavirus, and astrovirus are pathogenic viruses that cause foodborne diseases. About 58% of viral gastroenteritis, winter diarrhea, and acute nonbacteria gastroenteritis are caused by noroviruses. Only the apparatus of the host cell can translate such genes, which are used by the intercellular parasite to synthesize millions of fresh viral particles (Cohen, 2016), which will act similarly, resulting in severe consequences rapidly (Ryu, 2017b). In this situation, quick and exact identification of viral illnesses is significant for improving clinical results and encouraging doctors to take suitable actions. There are works in the literature that report on the use of electrochemical techniques for virus detection and quantification, primarily in blood and other biofluid spread and respiratory transmission (Ribeiro et al., 2020). Biosensor technologies, with less difficult sample preparation stages, have been planned as a more exact and faster approach to viral detection. These sensors can detect and count intact viruses, viral proteins, and nucleic acids, but the direct discovery of whole virus particles has the benefits of operational simplicity and cost-effectiveness in viral diagnostics (Cheng et al., 2012). Zhao et al. (2020) established an aptamer-based biosensor in a sandwich structure for the discovery of hepatitis B virus (HBV) by DPV, combined a geomagnetic assay with DPV detection for HBV analysis. A nanostructured gold electrode conjugated with concanavalin A was used to create an electrochemical biosensor (Hong et al., 2015). Ribeiro et al. (2020) described a comprehensive list of biosensors designed for the

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discovery of respiratory viruses, containing an electrochemical detection method. Hong et al. (2015) reported a sensitive (35 copies/mL), selective (98%), and fast (1h) electrochemical biosensor for norovirus discovery. Bhardwaj et al. (2019) used aptamers to create a label-free electrochemical biosensor capable of distinguishing among influenza A H1N1 virus subtypes. Bai et al. (2018) published an EIS aptamer-based biosensor for detecting the deactivated H1N1 virus. Initially, the SELEX method was used to generate aptamers with great binding affinity to deactivated viruses. The candidates were then tested in a direct enzyme-linked oligonucleotide assay (ELONA), with the best ones chosen for a sandwich ELONA and electrochemical aptasensor production. Veerapandian et al. (2016) developed a voltammetric immunosensor for simultaneous discovery of influenza A H1N1 and H5N1 viruses using MB as a redox probe. Through indirect opposition between the free virus in the sample and immobilized MERS-CoV protein S1 or a stable concentration of antibody additional to the sample, the electrode array enabled multiplexed identification of various strains of CoVs. Dielectrophoretics remains a promising tool for manipulating, separating, and detecting viruses (Nakano et al., 2013). A carbon electrode containing a viral capsidspecific aptamer conjugated with graphene AuNPs was used to capture the virus. Haji-Hashemi et al. (2019) reported an electrochemical immunosensor for mosaic virus (FMV) discovery using CV, DPV, and EIS. Changes in biological recognition actions, such as viral antigens binding to specific antibodies placed on the bioreceptor, are detected by electrochemical biosensors and transformed into a quantitative amperometric, potentiometric, or impedimetric signal. A combined automatic electrochemical immunosensor array has been intended to detect the presence of hepatitis viruses. Que et al. (2019) described a new electrochemical nanobiosensor for detecting Epstein-Barr virus DNA. An electrochemical immunosensor lab-on-chip immobilized with five hepatitis virus antibodies (A, B, C, D, and E) was established for the simultaneous finding of five hepatitis virus antigens in a one-step capture format. According to Brazaca et al. (2021), the technology derived from the use of electrochemical POCs would be the solution for the development of quicker, miniaturized, and more sensitive systems. Specific influenza using SELEX, a mini-hemagglutinin protein, was used to generate aptamers with great binding affinities, permitting the discovery of the preferred virus subtypes (seasonal and 2009 pandemic H1N1). The competitive assessment of an array of carbon electrodes altered with

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AuNPs detected it (Layqah & Eissa, 2019). Electrochemical DNA biosensors for bacteria and virus detection are now extensively used due to their increased sensitivity, low cost, simplicity, portability, and smaller sample size (Huang et al., 2022; Mei et al., 2022). A novel idea was implemented by combining miniaturized microelectromechanical methods and an aptamer to create a portable electrochemical sensor (Kitajima et al., 2016). To bind with the virus, a specific aptamer for norovirus was immobilized on a gold working electrode and measured using CV and fluorescence observation. Cajigas et al. (2022) described an electrochemical biosensor capable of detecting SARS-CoV-2 and distinguishing it from SARS-CoV, MERS, and human coronavirus homologs. Fani et al. (2020) reported an electrochemical DNA biosensor for identifying Human T-lymphotropic Virus-1 using DPV (Fani et al., 2020). Reduced graphene oxide was used to alter SPCEs. Tan et al. (2019) developed yet another label-free immunosensor for the identification of HBV. AuNPs-based electrochemical biosensors have been effectively used for virus identification (Layqah & Eissa, 2019). For example, one of the vastly causing viral pathogens, the MERS-CoV, was revealed to contaminate dairy products (van Doremalen et al., 2014). Ilkhani and Farhad (2018) described an electrochemical DNA biosensor for Ebola virus identification with DPV for the first time. First, gold-screen-printed electrodes with thiolated single-strand probes were immobilized. Karimi-Maleh et al. (2021) identified that electrochemical DNA biosensors are based on the principle of base complementarity, which effects variations in concentration, energy, and other aspects, and this alteration can be changed into visual electrical signals through suitable conversion. A poly-dimethylsiloxane microfluidic chip with SPCE was used in a study to identify norovirus (Chand & Neethirajan, 2017). AuNP-based electrochemical biosensors have been effectively used for virus identification (Layqah & Eissa, 2019). For example, one of the very pathogenic viruses, the MERS coronavirus (MERSCoV), was revealed to contaminate dairy foods (van Doremalen et al., 2014). Virus antibodies were immobilized on an electrochemical sensor array in the device, which took antigens from the solution.

12.5 Electrochemical detection of protozoa Protozoa are unicellular, heterotrophic, and eukaryotic organisms. Furthermore, protozoa have an enormous generative potential, resulting in a large number of pregnancies and short generation periods. It has been well established in recent decades that parasites of protozoa play a

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significant role in the beginning and development of various kinds of illnesses in humans (Dawson, 2005). Protozoa are commonly transmitted from one human to another via arthropod vectors, person-to-person interaction, food, water, sand fly, or mosquito bite (Fletcher et al., 2012). They have a high capacity to replicate in cells, which allows them to live and also allows dangerous contagions to grow from a single organism (Hutchison et al., 2000). Several reports have shown that the extent and occurrence of parasites in protozoan illnesses are influenced by a range of influences, comprising parasite spread mode, host population spatial structure, and host mass (Altizer et al., 2000). The protozoan life cycle is divided into phases that vary in action and structure (Cox, 2002). Foodborne disease in developing countries can be caused by economic and health issues, and parasites such as Toxoplasma and Giardia play important roles in these issues (Pires et al., 2015). Giardia, T. gondii, and Cryptosporidium are the most common developing foodborne parasites (Fletcher et al., 2012). Giardia is a major foodborne parasite that causes diarrhea in children below the age of five in developing countries (Kotloff et al., 2013). Giardia infection causes death or disease in humans by increasing pathophysiological consequences in the host entrails via parasite products (Einarsson et al., 2016). Since Giardia causes fatal disease and has nonspecific symptoms, suitable diagnostic approaches are essential (Flanagan, 1992). T. gondii is another type of foodborne protozoa parasite. Toxoplasmosis is the third most common foodborne infection that requires hospitalization (Vaillant et al., 2005). Furthermore, T. gondii contaminates up to one-third of the global population (Goldstein et al., 2008). Toxoplasmosis is difficult to detect in some people because it is asymptomatic. As a result, it is important to accurately identify toxoplasmosis and distinguish it from other diseases caused by this protozoan (Shieh et al., 2017). Malaria is a potentially fatal infection caused by Plasmodium parasites (Ragavan et al., 2018). Malaria prevalence has decreased in recent years because of the development of effective investigative and treatment approaches, but it has not been extinct (Soraya et al., 2019). The presence of nonpathogenic (asymptomatic) plasmodium parasites and small concentrations of antigen in blood samples of patients, indicate the asymptomatic transmission of the pathogens. Cryptosporidium spp. is the most common waterborne parasite and an important cause of death related to gastrointestinal infections affected by water contamination. Importantly, depending on the kind of electrochemical technique used, the pathogen’s size could have an important effect on the performance of a certain electrochemical biosensor. Pathogens, for example, can be three orders of magnitude in

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size. Norovirus has a diameter of 27 nm (Robilotti et al., 2015), whereas G. lamblia oocysts have a diameter of 14 m (Adam, 2001). Electrochemical biosensors for the identification of protozoa-based pathogens are an area that needs more research. Protozoa, as large pathogens, attain lower electrode analysis than small pathogens, resulting in a lesser influence on charge transfer at the electrode-electrolyte line. Currently, Cryptosporidium parvum is the most commonly identified protozoa by means of electrochemical biosensors (Iqbal et al., 2015). Electrochemical assays based on aptamer sensing stages are more popular than those described previously due to their higher sensitivity, thermos ability, robustness, and selectivity (Hassan et al., 2021). Luka et al. (2019) investigated the effectiveness of a label-free capacitive biosensor in quantifying Cryptosporidium oocysts in water. Anti-cryptosporidium antibodies were used, which allowed for accurate differentiation of various numbers of taken cells and masses on the surface of the biosensor regardless of the size of Cryptosporidium oocysts (5 m in diameter) (Jain et al., 2019). Ilkhani et al. (2019) reported a LOC device based on a three-dimensional TAS microchip for extremely selective and fast Cryptosporidium identification using DPV-EAT and EIS-EAT. Another report by Aguilar and Fritsch (2003) was an identification test with very good results in the determination of C. parvum in water samples. The target DNA was recovered with a LOD of 2 μg mL21 over a linear range of 5
50 μg mL21. Laczka et al. (2013) used an ELISA electrodebased device and potentiometric method to achieve an LOD of 500 C. parvum oocysts/mL in an hour. The flagellated protozoa Trypanosoma cruzi is the most common source of CD infections, accounting for approximately 30% of infected people. As a result, the use of electrochemical approaches to elucidate diagnostic problems is growing. Sleeping sickness, African trypanosomiasis, and CD are major Trypanosoma species complaints, and initial the discovery of these illnesses using optical sensors can assist in reducing disease rates and providing safer treatments. The EIS is a sensitive, label-free method for studying varying surface phenomena in bulk attributes. EIS can deliver direct identification of Abs or Ags by immobilizing biological apparatuses on a working electrode (Katz & Willner, 2003). According to Carneiro et al. (2019), the Ni (II), Pd (II), and HFedtc complex can decrease in vitro trypanocidal action. Leishmaniases affect more than 98 nations and are a major communal health problem, with an increasing problem over the past decade. Leishmania multiplies in tissues such as the spleen, liver, and bone marrow, and the immunocompromised state can result in disease or death if not treated. The VL and CL are two

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common kinds of Leishmaniasis contagion that occur in organs. VL Ags immobilization on a carbon electrode altered with AuNPs can be a beneficial electrochemical means for identifying anti-Leishmania Abs in patient serum (Martins et al., 2020). EIS is a low-cost, quick-application electrochemical tool with high specificity and sensitivity. Diniz et al. (2003) prepared gold and platinum electrodes for EIS adsorption of T. cruzi flagellar repetitive Ag and cytoplasmic repetitive Ag. Several drugs can be decreased in the nitrogen group if they contain nitroaromatic groups (Alvarez et al., 2010). The antiprotozoal nitrofuran drugs were evaluated using the CV method. The SPEs are miniature electrodes used in the EIS method (Yamanaka et al., 2016). The sulfuric acid and 3-mercaptopropionic acid can trigger the useful groups of the SPE electrode, permitting L. infantum Ag to be easily immobilized on an electrode with SH-NH bonds. In less than 30 minutes, the EIS immunosensor identified anti-VL Ab in human and dog serum (Cordeiro et al., 2019). A novel detection method for Leishmania DNA is DNA hybridization in tissue samples. The definite Leishmania DNA probes are directed into the genosensor, which is made of various materials. Moradi et al. (2016) organized an Au electrode altered with Au nanoleaves and immobilized a Leishmania DNA probe on it. Mobed et al. (2020) used electrochemical CV and SWV techniques to measure the target DNA after designing this electrode. The NS-AuNPs were used as an Au electrode surface transformer in the biosensor intended by (Nazari-Vanani et al., 2018) and DPV amounts were effectively accepted for the identification of synthetic L. infantum target sequences. Protozoa parasites like Giardia, T. gondii, and Cryptosporidium can spoil vegetables and soil and are the most common developing foodborne parasites. The severe phase of toxoplasmosis, or Giardia contagious, is usually asymptomatic, and medical symptoms are insufficient to distinguish this contagion from other diseases. Biosensors, which are subtle and specific identification approaches, are thus extremely necessary. Chiwunze et al. (2019) observed that the biosensor was improved with MWCNTs and polymerized methyl orange, and the electrochemical evaluation of AQ was simple and highly subtle. Specific IgG anti-T. gondii antibodies are important markers for detecting toxoplasmosis using electrochemical sensors. Reduced graphene oxide (rGO) has been shown to improve surface area, electron mobility, and electric conductivity. Gokce et al. (2016) reported a voltammetric device in which the T. gondii capture probe was immobilized on a PGE, and the hybridization of the probe and target gene was recorded by means of DPV at a LOD of 40 mg mL21 (Table 12.1).

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Table 12.1 Electrochemical detection of microorganisms. Pathogen

Electrochemical Method

References

Aeromonas hydrophila DNA Avian influenza virus (AIV)

SWV EIS; Fe(CN)632/42

Bacillus anthracis

conductometry

Bacillus subtilis

EIS

B. subtilis Bacillus cereus B. cereus spore simulant

Conductometry DPV, EIS EIS

B. subtilis DNA Bovine viral diarrhea virus Cryptosporidium parvum C. parvum Campylobacter jejuni

DPV conductometry SWV; Fe(CN)632/42 Capacitive; Fe(CN)632/42 EIS; Fe(CN)632/42

Cholera toxin subunit B

DPV

Coliform

CV

Cronobacter sakazakii Cucumber mosaic virus (CMV) Dengue virus 1
4 DNA Escherichia coli

Amperometry Amperometry

E. coli

EIS

E. coli

CV; Fe(CN)632/42

E. coli

FET

E. coli

EIS

E. coli (O157:H7 Serotype)

Electrochemical impedance spectroscopy Chronocoulometry EIS

Ligaj et al. (2014) Callaway et al. (2016) Pal and Alocilja (2009) Saucedo et al. (2019) Yoo et al. (2017) Izadi et al. (2016) Mazzaracchio et al. (2019) Hu et al. (2014) Luo et al. (2010) Iqbal et al. (2015) Luka et al. (2019) Huang et al. (2010) Valera et al. (2019) Badalyan et al. (2018) Yuan et al. (2020) Chartuprayoon et al. (2013) Luna et al. (2015) Bai et al. (2010) Güner et al. (2017) Mallen-Alberdi et al. (2016) Mathelie-Guinlet et al. (2019) Thakur et al. (2018) Zhang et al. (2020) Jaiswal et al. (2018) Li et al. (2018) Brosel-Oliu et al. (2018)

E. coli genome E. coli O157:H7

CV, EIS; Fe(CN)632/42 ASV, EIS Amperometry

(Continued)

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Table 12.1 (Continued) Pathogen

Electrochemical Method

References

E. coli O157:H7 E. coli

EIS Diffusion blockage of redox mediator species towards carbon fiber microelectrode CV, EIS

Wu et al. (2019) Lee et al. (2016)

SWV, DPV, EIS

Luo et al. (2013)

SWV

Adkins et al. (2017) Mannoor et al. (2012) Hai et al. (2017)

Enterobacter cloacae, E. coli, B. subtilis Enterobacteriaceae bacteria DNA Enterococcus ssp. Helicobacter pylori

Conductometry

Human influenza A virus H1N1 Human influenza A virus H1N1 Human influenza A virus H3N2 Human influenza A viruses H1N1 and H3N2 Japanese encephalitis virus Klebsiella pneumoniae

DPV; Fe(CN)632/42, EIS, potentiometry EIS; Fe(CN)632/42; amperometry EIS

Listeria innocua

EIS; Fe(CN)632/42

Listeria monocytogenes

EIS, CV, EIS

L. monocytogenes

EIS

L. monocytogenes

SWV

L. monocytogenes L. monocytogenes L. monocytogenes

ECL DPV Amperometry

Mycobacterium tuberculosis

EIS

mecA gene Melissococcus plutonius

EIS Amperometry

conductometry CV, EIS; Fe(CN)632/42 EIS

Xi et al. (2011)

Hai et al. (2018) Hushegyi et al. (2016) Shen et al. (2012) Chin et al. (2017) de Miranda et al. (2017) Tolba et al. (2012) Wang et al. (2018) Chiriacò et al. (2018) Eissa and Zourob (2020) Liu et al. (2016) Lu et al. (2016) Mubarok et al. (2017) Lillehoj et al. (2014) Xu et al. (2018) Mikuˇsová et al. (2019) (Continued)

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Table 12.1 (Continued) Pathogen

Electrochemical Method

References

Methicillin-resistant Staphylococcus aureus (MRSA) MRSA

Electrochemical impedance spectroscopy

Wang et al. (2011)

SWV

MRSA

DPV

Murine norovirus (MNV)

SWV, fluorescence; Fe (CN)6,32 /Ru(NH3)6 amperometry EIS; Fe(CN)632/42 EIS

Cihalova et al. (2016) Nemr et al. (2019) Giamberardino et al. (2013)

Norovirus Pseudomonas aeruginosa P. aeruginosa P. aeruginosa P. aeruginosa (acyl homoserine lactones [AHLs]) Rotavirus rotavirus S. aureus S. aureus S. aureus

Electrochemical conversion of pyocyanin Amperometric Amperometric

CV amperometry EIS; Fe(CN)632/42 EIS DPV; Fe(CN)632/42

S. aureus

DPV

S. aureus

SWV

Salmonella enterica S. enterica S. enterica

CV & EIS CV EIS

S. enterica serovar typhi

DPV

Salmonella enteritidis

SWAS V

S. epidermidis

EIS; Fe(CN)632/42

Salmonella pullorum & Salmonella gallinarum

CV

Baek et al. (2019) Eissa and Zourob (2020) Elliott et al. (2017) Das et al. (2019) Ozcan et al. (2020) Liu et al. (2011) Liu et al. (2013) Bekir et al. (2015) Choi et al. (2017) Divagar et al. (2019) Farooq et al. (2020) Hoyos-Nogués et al. (2016) Peng et al. (2018) Saini et al. (2019) Soares et al. (2020) Muniandy et al. (2019) Zhang et al. (2010) Golabi et al. (2017) Wang et al. (2014) (Continued)

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267

Table 12.1 (Continued) Pathogen

Electrochemical Method

References

S. pullorum and S. gallinarum Salmonella typhi

CV; EIS

Fei et al. (2015)

EIS

S. typhi

DPV

S. typhi S. typhi

Chronoamperometry Potentiometry

Salmonella typhimurium

EIS

S. typhimurium

CV, EIS; Fe(CN)632/42

Salmonella

OSWV

Salmonella Salmonella Salmonella S. typhimurium S. typhimurium

EIS CV, EIS SWV, DPV, EIS DPV Potentiometry

S. typhimurium

CV, EIS

Salmonella DNA

CV, EIS, DPV

Salmonella spp.

Capacitance measurement

Shigella dysenteriae S. aureus Streptococcus mutans

EIS CV, EIS EIS

Vibrio cholerae

amperometry potentiometry

V. cholerae

EIS; Fe(CN)6

Vibrio cholerae O1 Vibrio parahaemolyticus

EIS CV

Andrade et al. (2015) de Oliveira et al. (2018) Melo et al. (2018) Soares et al. (2020) Dastider et al. (2015) Dong et al. (2013) Capobianco et al. (2019) Jia et al. (2016) Jia et al. (2016) Li et al. (2016) Bu et al. (2020) Hasan et al. (2018) Hasan et al. (2018) Amouzadeh Tabrizi and Shamsipur (2015) Niyomdecha et al. (2018) Zarei et al. (2018) Jia et al. (2014) Lillehoj et al. (2014) Boehm et al. (2007) Tam and Thang (2016) Tam et al. (2016) Kampeera et al. (2019) (Continued)

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Table 12.1 (Continued) Pathogen

Electrochemical Method

References

V. parahaemolyticus (Vp)

DPV

V. parahaemolyticus (Vp) V. parahaemolyticus (Vp)

PV ECL-ASV

Yersinia enterocolitica DNA

DPV

Nordin et al. (2017) Teng et al. (2017) Wang et al. (2019) Sun et al. (2010)

ASV, Anodic stripping voltammetry; CV, cyclic voltammetry; DPV, differential pulse voltammetry; EIS, electrochemical impedance spectroscopy; SWV, square wave voltammetry.

Figure 12.1 Detection of pathogens by using electrochemical methods.

Alves et al. (2017) described a genosensor that noticed T. gondii DNA hybridization with 100 ng mL21 of genomic DNA. The high discrimination of microchip fabrication recovers the system's use in POCs (da Silva et al., 2022). Laczka et al. (2013) also described the development of an ELISA electrode-based potentiometric sensor for the identification of C. parvum oocysts. Similarly to the bacteria section, POC devices could play a significant role in local protozoa measurement/finding, as a protozoon is one of the foremost causes of deaths in children under the age of five worldwide (Hassan et al., 2021) (Fig. 12.1).

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1007.

CHAPTER 13

Electrochemical biosensors for toxic gases monitoring Dipak Maity1,2,3, Gajiram Murmu4,5, Tamanna Harihar Panigrahi6 and Sumit Saha4,5 1

Department of Chemical Engineering, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India Department of School of Health Sciences & Technology, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India 3 School of Engineering and Technology, The Assam Kaziranga University, Jorhat, Assam, India 4 Materials Chemistry Department, CSIR-Institute of Minerals & Materials Technology, Bhubaneswar, Odisha, India 5 Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, India 6 Department of Chemistry, National Institute of Technology, Rourkela, Odisha, India 2

13.1 Introduction Especially in recent years, the standard of human life has improved due to the development of society and technology. However, there is growing concern about the following environmental issues. Containments released by industries, modern factories, and farms threaten the health of humans and even upset the natural ecosystem. The emissions from industries, particularly gases emitted from the burning of petroleum products, coal, fossil fuels, and automobile exhausts (Li et al., 2012), are the major sources of toxic gases, including oxides of nitrogen, oxides of sulfur, hydrogen sulfides, and volatile organic compounds (VOCs) (Trivedi et al., 2018; Wei et al., 2018). Toxic gases released into the air pollute the environment and threaten the health of living organisms. These pollutants lead to the occurrence of acid rain, photochemical smog, and respiratory complications in living organisms. A variety of gas sensors have been developed for the detection of toxic gases. Among these, electrochemical sensors are commonly used for detecting toxic and harmful gases since they are easy to miniaturize, inexpensive, linear, repeatable, and stable over long periods. There has been widespread use of electrochemical sensors to detect trace amounts of heavy metals in natural waters (Batley, 1983), carcinogens (Barek et al., 2001), gas pollutants (Wan et al., 2018), and organic pollutants (Yang et al., 2018). An electrochemical gas sensor measures the Novel Nanostructured Materials for Electrochemical Bio-sensing Applications DOI: https://doi.org/10.1016/B978-0-443-15334-1.00011-0

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concentration of gas by electrochemically oxidizing or reducing it by the detecting principle, thereby distinguishing the composition of the gas and detecting its composition. Electrochemical biosensors have gradually emerged by integrating biorecognition elements and electrochemical sensors. The biorecognition element of biosensors provides strong selectivity, allowing them to be used in multicomponent detection without complicated sample processing. This makes the electrochemical biosensor highly suited for environmental pollution analysis in the laboratory as well as onsite-based. Considering the highly efficient usage of electrochemical biosensors in detecting toxic gases, a detailed discussion of their role in sensing NO2, SO2, H2S, and NO is covered in this chapter.

13.2 Biosensors In today’s world, many inventions make our lives easier. We rely on plenty of gadgets that help us interact with the physical environment, like air conditioners, mobile phones, and smoke detectors, which are quite possible due to sensors. A sensor is a primary measurement system that detects physical and electrical changes, like heat, pH, pressure, current, etc., and converts these signals to detectable forms (Ensafi, 2019). The transducer does the conversion of signals from one form to another. There are a variety of sensors categorized based on the form of signals they detect, such as physical, chemical, thermal, and biological (Khanna, 2012; White, 1987). This chapter will mainly focus on biological sensors, commonly known as biosensors. Cammann coined the term “biosensor” (Cammann, 1977), and it is defined as a device that comprises a biological sensing component incorporated with a physicochemical transducer (Thvenot et al., 1999). The biological sensor includes enzymes, antibodies, and cells, interacting with the analyte and initiating a measurable signal. The biological signal generated is converted into an electrical signal by the transducer. Hence, a biological sensor consists of (1) a biological sensing device to measure analyte concentration, (2) a transducer to convert biological signals into electrical signals, and (3) electronics and displays. The first biosensor invented was Clark’s oxygen electrode (Heineman et al., 1918), and since then, various researches have been done to improve the sensor’s sensitivity, selectivity, reproducibility, and stability. Some other examples of biosensors include glucose sensors (Guilbault & Lubrano, 1973) (for blood glucose monitoring), lactate sensors (Rathee et al., 2016) (to measure the concentration of

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lactate in the blood), urea sensors (Guilbault & Montalvo, 1969), immunosensors (North, 1985), etc. Biosensors have wide applications in food monitoring, the medical field, the fermentation process, biodefense, sustainable food safety, forensic investigation, and environmental detection (Luong et al., 2008), as shown in Fig. 13.1.

13.2.1 Components of biosensors A typical biosensor comprises mainly (1) an analyte, (2) a bioreceptor, (3) a transducer, and (4) electronics, as shown in Fig. 13.2. Modifications in receptors, transducers, and electronic parts are done to improve the efficiency of biosensors and make them more user-friendly. 1. Analyte: Target molecules whose constituents need to be identified and whose concentration is to be measured, like glucose, alcohol, lactate, urea, etc. 2. Bioreceptor: A molecule or biomolecule that aims to identify the analyte using a biochemical mechanism. They bind the analyte of interest to the surface of the biosensor, leading to signal production. This process of generation of signals when an analyte interacts with the bioreceptor is called biorecognition. Examples of bioreceptors include enzymes, antibodies, nucleic acids, cells, and aptamers. 3. Transducer: A transducer is an apparatus that converts one form of energy into another. The interaction of the analyte with the bioreceptor produces biochemical reactions converted into some other

Figure 13.1 Applications of biosensors in different domains.

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Figure 13.2 Schematic diagram of components of biosensors, showing different types of bioreceptors and transducers. Source: From Naresh, V., & Lee, N. (2021). A review on biosensors and recent development of nanostructured materials-enabled biosensors. Sensors, 21(4), 1109. https://doi.org/10.3390/s21041109.

measurable form of signals by a transducer. This process of energy conversion is called signalization. The detectable or measurable form of signals can be optical, electrical, electrochemical, mass change, calorimetric, or magnetic. Biosensors can be classified into various types depending on the signal generated by the transducer, among which electrochemical transducers are the best based on their portability, sensitivity, cost-effectiveness, and user-friendly interface. 4. Electronics and display: The electronic signal is amplified by the electronics and is displayed in digital form. The display shows the output in a readable format, generally in the form of numerical graphs, tables, or figures.

13.2.2 Characteristics of biosensors The requirements to develop a highly efficient biosensor are as follows (Turner, 2013): 1. Selectivity: In a mixture of samples, selecting a particular analyte to be measured is crucial. 2. Sensitivity: Biosensors must be ultrasensitive to analyze the trace elements, which leads to the detection of analytes of very low concentration in a minimal number of steps.

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3. Accuracy: Accurate results are expected from a biosensor after each time use. This property makes a biosensor ideal to be used widely. 4. Response time: A biosensor’s response time is the time required to acquire 95% of the results—the lower the response time, the better the sensor. 5. Stability: Stability is a principal characteristic of a biosensor related to the lifetime of a biosensor and its affinity power toward an analyte. Stability is affected by the internal and external environmental conditions of a biosensor.

13.3 Nanomaterial-based biosensors Biosensors have a wide and diverse way of classification based on different types of bioreceptors and transducers used. Among all the classifications, nanomaterial-based biosensors have hogged the limelight due to their vast range of usage in biosensing owing to their large surface area, high electrical conductivity, adsorption, and modifiable chemical and physical properties (Dolez, n.d.). Another reason for such advancement is their multidisciplinary use of dimensionality. There are four types of nanomaterials: 0D, 1D, 2D, and 3D (Dolez, n.d.) as shown in Fig. 13.3. In zero-

Figure 13.3 Classification of nanomaterials based on dimensionality and the synthesis of different nanobiosensors. Source: From Naresh, V., & Lee, N. (2021). A review on biosensors and recent development of nanostructured materials-enabled biosensors. Sensors, 21(4), 1109. https://doi.org/10.3390/s21041109.

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dimensional nanomaterials (nanoparticles [NPs], quantum dots [QDs]), the material is nanoconfined from the x, y, and z directions. These types of nanostructures can be utilized for increasing the surface area and the active sites. One-dimensional nanostructures (nanowires, nanotubes) are nanoconfined from any two directions and are used for providing stable passage for electron transfer. Two-dimensional nanostructures (nanofilms, nanosheets) are confined from one direction and used to provide a stable surface for immobilization. Lastly, three-dimensional structures (dendrimers, nanoclusters, nanoflowers, etc.) do not have confinement from any direction ($100 nm) and are considered for their geometric volume. Nanobiosensors have advantages over macro/microbiosensors due to (1) calculating the concentration of nanoscopic particles (cell organelles and biomolecules), (2) measuring the ultralow concentration of potentially harmful substances, and (3) determining properties of regions that are hard to reach (Abdel-Karim et al., 2020).

13.3.1 Zero-dimensional nanobiosensors In zero-dimensional nanostructures, the materials are of the nano-range (,100 nm) from all three directions (x, y, and z). These materials are highly used for the detection of very small-sized analytes of nano-range. Nanoparticles and quantum dots are the materials that come under 0D nanostructures. 13.3.1.1 Nanoparticles-based biosensors NPs are used in biosensors due to their small size and alterable physical and chemical properties, which help them bind to the target molecule efficiently. These particles are used to provide excellent selectivity and sensitivity in electrochemical biosensors. Some metal oxide nanoparticles (MONPs), developed as nanoenzymes, act as catalysts in biochemical reactions on biosensors. Some noble metals are also used as part of biosensors due to their electron transfer ability, easy functionalization, facile synthesis, and nonreactive nature. Examples of metals and MONPs include gold (Au), palladium (Pd), silver (Ag), platinum (Pt), copper (Cu), TiO2, SnO2, ZnO, etc. These nanoparticles exhibit excellent optical, magnetic, catalytic, and electrochemical properties for applications in various fields like drug delivery, imaging, health diagnosis, food safety, and environment (Niu et al., 2018; Wang et al., 2011; Zhang et al., 2015).

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13.3.1.1.1 Metal nanoparticles Gold (Au) nanoparticles have been extensively used for biosensing owing to their chemical stability, simple synthesis procedure, extensive electrochemical potential, and high catalytic activity (Vidotti et al., 2011). These are utilized for the electrochemical detection of arsenic ions (As31) (Chen & Huang, 2014), uranyl in natural water (Shi et al., 2021), and mercury (Hg) (Ratner & Mandler, 2015; Zhang et al., 2015). A novel nonenzymatic glucose sensor was developed by Ghasemi et al. based on Au
Ni bimetallic nanoparticles, demonstrating a low glucose detection limit (0.063 uM) (Amiripour et al., 2021). Silver is used for biosensor preparation because of its excellent surface-enhanced Raman scattering (SERS) and catalytic activity. SERS is a very sophisticated and selective technique for the detection of biological samples and single molecules by enhancing the weak Raman scattering by a factor of 1010
1011. Ag nanoparticles embedded in various matrices are used for the detection of nitrobenzene (Kariuki et al., 2016), influenza virus (Mahmoudian et al., 2015), and Fe21, H2O2, and glucose sensing (Basiri et al., 2018). Platinum (Pt) nanoparticles show excellent electrochemical and catalytic properties. These are used in the preparation of highly sensitive H2O2 sensors (Lebègue et al., 2015), trinitrotoluene (TNT) detection (Zhang et al., 2015), hydrogen gas sensors (Jung et al., 2018), and Hg21 detection (Mahmoudian et al., 2016). Palladium (Pd) nanoparticles have an advantage over other noble metals (Au and Pt) due to their natural abundance, making them a cost-effective substitute for biomaterial synthesis. They also possess high catalytic and sensor abilities, and their electrodes have superior electroanalytical ability, making them desirable for use as electrochemical biosensors (Phan et al., 2020). They are utilized for the detection of hydrazine to a detection limit of 0.007 μM (Zhang et al., 2017), for H2 detection (Mohammadi et al., 2020), nitrate sensing (Mahmoudian et al., 2015), and the determination of anticancer drug pemetrexed to a detection limit of 0.33 nM (Afzali et al., 2019). 13.3.1.1.2 Metal oxide nanoparticles MONPs have the advantage of a wide range of usage in varying physical and chemical environments, along with ultrahigh surface area, low production cost, and appreciable absorptivity. They are used for sensing gases with commending sensitivity and selectivity. The most often used MONPs are zinc oxide (ZnO), titanium oxide (TiO2), copper oxide (CuO), tin oxide (SnO2), nickel oxide (NiO), molybdenum oxide

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(MoO3), iron oxide (Fe2O3), manganese oxide (MnO2), cobalt oxide (Co3O4), and cerium oxide (CeO2) (Shi et al., 2014). These MONPs also possess optical and electronic properties due to suitable bandgap. Various studies have been reported on the application of MONPs-based nanobiosensors, some of which are glucose (Wang et al., 2021) and formaldehyde (Maduraiveeran & Jin, 2017) sensing by NiO, detection of glutamate (Hu et al., 2020), urea (Ali et al., 2015), and miRNA-141 (Zhao et al., 2021) by Co3O4, sensing of anticancer drugs by Fe2O3 (Devkota et al., 2014), CO gas sensing by ZnO (Hjiri et al., 2020), etc. 13.3.1.2 Quantum dots-based biosensors These 0D nanostructures of the range 1
10 nm are mainly used for manufacturing optical biosensors due to their appreciable photochemical stability, excellent optical properties (e.g., broad excitation), costeffectiveness, miniature size, specificity, and narrow size-tunable emission spectra (Dewan et al., 2016; Ma et al., 2018). These detect pharmaceutical analytes, organic molecules, and biomolecules like enzymes, carbohydrates, neurotransmitters, etc. (Vashist et al., 2012). Certain developments that are made using quantum dots are constructing electrochemical sensors for the detection of Cu(II) (Wang, Zhao, Li, et al., 2017), ultrasensitive lung cancer cell biomarkers (Kalkal et al., 2020), and sensors for detecting circulating tumor cells (Cui et al., 2019).

13.3.2 One-dimensional nanobiosensors These nanostructures are mostly in the form of wires, rods, and tubes. Due to their structure, shape, chemical, and physical properties, they provide an excellent passage for electron transfer, which can be utilized to manufacture highly sensitive, robust, and selective electrical biosensors. Nanowires are very thin structures whose diameter is comparable to the biological species. Their outstanding transducing properties can be verified by their tunable conducting nature and their capability to bind analytes to their surface (Patolsky et al., 2006), and they can be highly sensitive at a very low ionic concentration of the analytes. Some research utilizing nanowires’ properties include plasmonic biosensing (Kim et al., 2019) and direct genome detection (Leonardi et al., 2018). Among the 1D nanostructures, nanotubes are capsule-shaped structures that are majorly used for the electrochemical detection of molecules like glucose and H2O2. Carbon nanotubes, one of the forms of nanotubes, are extensively used due to their excellent tensile strength (like steel), high conductivity (like

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copper), and outstanding electrocatalytic performance. They are “rolled” graphene sheets in cylindrical form and have unique features like high surface-to-volume ratio, low overvoltage, high chemical and thermal properties, and minimal surface fouling (Simon et al., 2019; Sireesha et al., 2018). Studies have been done to determine lactate (Luo et al., 2018), bovine serum albumin (BSA) (Janssen et al., 2019), toxic phenolic compounds (nitrophenol, catechol, p-cresol) (Young & Lin, 2017), and various environmental pollutants (Ramnani et al., 2016; Zhang et al., 2016).

13.3.3 Multidimensional nanobiosensors Graphene, a two-dimensional sp2 hybridized carbon nanosheet, is known to be an ideal material for the fabrication of electrochemical sensor electrodes due to its chemical and electrical properties. These are known for their high surface area (twice those of CNTs), high thermal and mechanical strength, and excellent charge carrier mobility (Zhang et al., 2016). The functionalization of graphene provides better sensitivity to it, improving its property as a sensor. Certain studies for graphene-based sensors include the development of an electroanalytical tool for nitrite and carcinogenic hydrazine detection (Luo et al., 2015), sensing of TNT (an environmental ticking bomb) in seawater (Goh & Pumera, 2011), detection of NO gas (Li et al., 2011) and various heavy metals (Dai et al., 2016), and as biomarkers for prostate cancer proteins (Xu et al., 2019). Dendrimers are macromolecules of the size of protein that are hyperbranched and consist of surface functional groups in high density. Dendrimers are utilized for their sensitivity, selectivity, specificity, and high surface area. Dendrimeric biosensors can be used to detect proteins, DNA, biomolecules, etc. Recent works suggest dendrimeric biosensor’s use in the detection of glucose, cDNA (Benters et al., 2001), dengue (Mustapha Kamil et al., 2019), TNT (Singh et al., 2009), etc.

13.4 Electrochemical biosensors Electrochemical transducers are used in biosensors because of their low cost, ease of use, mobility, and simplicity. Due to their high sensitivity to biomolecules, electrochemical sensors are widely used in many industries (Charithra & Manjunatha, 2020; Thévenot et al., 2001). Typically, an electrochemical process results in a detectable current (amperometry), a measurable charge accumulation or power (potentiometry), modification of the conductive characteristics of the substance between the electrodes

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(conductometry), and measurement of reactance and resistance in the biosensor (electrochemical impedance spectroscopy). Electrochemical measurement is independent of a reaction volume; therefore measurements can be made with a small sample size. Electrochemical sensors are employed at low detection limits and with great sensitivity (Ronkainen et al., 2010).

13.4.1 Amperometric biosensors Amperometric biosensors measure the concentration of analytes in sample matrices by converting biological recognition events brought on by electroactive species at the surface of the sensor into a current signal. Despite its simplicity, amperometric detection occasionally produces low LOD. In amperometry, which is employed in biocatalytic sensors, the current signal is produced by the reduction or oxidation of an electrical substance, metabolic product, or intermediate on the surface of a working electrode. An amperometric transducer examines the charge transfer between phase interfaces, such as between two electrodes separated by an electrolyte. Amperometric biosensors track variations in the current flowing through the working electrode due to redox species being reduced or oxidized during a biological reaction that is linearly correlated with analyte concentration. Continued addition of analytes typically results in an amperometric signal response with relatively easy-to-distinguish beginning and final currents for each acquisition. One of the drawbacks of amperometry is the formation of charging currents (i.e., the current necessary to apply the potential to the system) at the beginning of the measurements (Ronkainen & Okon, 2014). For use in healthcare, the environment, and industry, amperometric biosensors are affordable, appropriate, and very sensitive. Tucci et al. created an amperometric biosensor for the detection of herbicides using cyanobacteria, namely Anabaena variabilis (Tucci et al., 2019). The target herbicides used for the detection are diuron and atrazine. In the biosensor, the photocurrent is generated due to the oxidation of water depending upon the herbicides’ concentration. As the concentration of the herbicides rises, the current begins to fall. The biosensor’s sensitivity toward atrazine is reported to be 24.6 mAm M21 cm22 with a limit of detection (LOD) of 0.56 mM. Fig. 13.4 shows the herbicides inhibition mechanism in Anabaena variabilis cyanobacteria.

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Figure 13.4 Graphical representation of herbicides inhibiting the process of photosynthesis. Source: From Tucci, M., Grattieri, M., Schievano, A., Cristiani, P., & Minteer, S. D. (2019). Microbial amperometric biosensor for online herbicide detection: Photocurrent inhibition of Anabaena variabilis. Electrochimica Acta, 302, 102
108. https://doi.org/ 10.1016/j.electacta.2019.02.007.

13.4.2 Potentiometric biosensors It assesses the potential differences between the reference and the working electrode, and the measured signal demonstrates the behavior associated with concentration. A gas-sensitive or selective ionic electrode is frequently used as the potentiometric transducer (Bobacka et al., 2008). The selectivity and the selection of the chosen electrode of the target species in the system are crucial for the sensitivity and selectivity of potentiometric biosensors. However, potentiometer application in microbial biosensing is constrained by the necessity and importance of maintaining a steady reference electrode. Mishra et al. fabricated a biosensor for the detection of G-nerve agents using potentiometry (Mishra et al., 2018). The design of the biosensor was in the form of a skull, with one eye as a working electrode and the other as a reference electrode. Fig. 13.5 illustrates the conceptualization, design, and printing of potentiometric biosensors and their application on human skin.

13.4.3 Conductometric biosensors It is a method for measuring the electrical conductivity change of the solution as a result of the creation or consumption of ionic species, such as the

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Figure 13.5 A pictorial illustration of potentiometric biosensor for detection of Gtype nerve agents. (A) Mechanism of the biosensor. (B) A biosensor system is mounted on the hand and wireless transmitting of the signal. (C) Printing of the biosensor on a stickering paper. (D) Potentiometric biosensor for the detection of Gtype nerve drugs on human skin. Source: From Mishra, R. K., Barfidokht, A., Karajic, A., Sempionatto, J. R., Wang, J., & Wang, J. (2018). Wearable potentiometric tattoo biosensor for on-body detection of G-type nerve agents simulants. Sensors and Actuators, B: Chemical, 273, 966
972. https://doi.org/10.1016/j.snb.2018.07.001.

metabolic activity of microorganisms. Most conductometric biosensors contain enzymes whose charged by-products enhance ionic strength due to conductivity. In biosensors, conductivity is a diagnostic method that has been applied to both clinical and environmental analyses. Microbial biosensors are appealing because conductometry measurement is quick and accurate under new synthetic analytical techniques. The fact is that conductometric biosensors do not require the usage of a reference electrode and are made of an insulating substrate embedded with stainless steel, platinum, graphite, or other metallic sensing components. They can be quickly shrunk and integrated using inexpensive thin-film standard technology, are light-insensitive, and frequently function at low-amplitude alternating voltages, which avoids Faraday processes on the electrodes. One drawback of this approach is that the signal-to-noise ratio is less than 2%, so the buffer concentration and other components must be added to balance such issues. The method’s sensitivity is reduced when nonreacting ions are present in the solution. However, until the signal-to-noise ratio is good, low ionic strength buffers can be employed to assess low concentrations (Dzyadevych & Jaffrezic-Renault, 2014). To sum up, the accuracy and sensitivity of conductometric sensors are less than other sensors.

13.4.4 Impedimetric biosensors Constructing an impedimetric biosensor involves immobilizing biological elements on the surface of the electrode. The targeted analyte is

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measured, monitored, and reported via an output electrical impedance signal, which is inversely proportional to the activity of an analyte. Impedance biosensors are electrochemical devices that employ impedance variations for the detection of biological entities or analytes. The most commonly used technique is electrochemical impedance spectroscopy (EIS). EIS makes it simple to determine the characteristics of the bulk electrode and the processes occurring at the electrode interface (Maalouf et al., 2007; Manjunatha et al., 2020). The signal’s amplitude varies in the EIS with incredibly small variations. Additionally, since the biosensor uses components like antibodies, enzymes, bacteria, viruses, etc. (Helali et al., 2006) to monitor a biological event, the measurement of impedance is independent of the presence of redox couples (Elshafey et al., 2013). The impedimetric biosensors aim to create amino acid groups, carboxyl groups, and similar other groups on the surface of the electrode to capture the antibodies. This step is crucial when creating an impedimetric biosensor since it guarantees the sensor’s durability and repeatability. Additionally, nanomaterials have been applied for such purposes. The resistance to electron transfer often rises when the antibody is discovered utilizing antigens, ultimately reducing the capacitance (Sharma et al., 2021). Gold nanoparticles (AuNPs) are used as entrapping antibodies, which do not affect their activity or effectiveness (Chullasat et al., 2011). Similarly, the impedimetric technique was utilized to detect HER-3 (Canbaz et al., 2014) and to estimate the number of bacteria in a laboratory fermentor (Kim et al., 2009). Ankan et al. examined the use of an antigen
antibody binding mechanism in the detection of E. coli bacteria (Chowdhury et al., 2012). A study using EIS was done to examine the sensitivity and efficacy of the sensor, which has an antibody covalently bonded to the surface of the polyaniline film. It was tested and noted that the impedance changes as the bacterial concentration increases; moreover, the biosensor has a high sensitivity toward E. coli. The EIS technique was developed to identify MCF-7 cancer cells by Seven et al. (2013). The study shows that the anti-c-cerbB-2 was captured on a polypyrrole-NHS electrode by covalent linkage. Besides, the sensor successfully identified cancer cells with a sensitivity range from 100 to 10,000 cells per mL. Rushworth et al. created a biosensor to detect amyloid-beta oligomers related to Alzheimer’s disease (Rushworth et al., 2014). The binding of the oligomer increases with increased current flow through the biosensor, resulting in a decrease in the impedance. Fig. 13.6 depicts the effect of Aβ

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Figure 13.6 The effect of Aβ oligomers (AβO) on the surface of the biosensor and electrochemical conductivity analysis. Biosensor designed in the presence of (A) biotinylated AβO, (B) biotinylated antibody (increase the impedance) based on (i) polymer level, (ii) biotin level, and (iii) after incubation of analytes. (C) Biosensor incubated with AβO and current measurement using CV (current vs. potential). (D) Pictorial representation of bounded Aβ oligomer increases the surface conductivity. Source: From Rushworth, J. V., Ahmed, A., Griffiths, H. H., Pollock, N. M., Hooper, N. M., & Millner, P. A. (2014). A label-free electrical impedimetric biosensor for the specific detection of Alzheimer s amyloid-beta oligomers. Biosensors and Bioelectronics, 56, 83
90. https://doi.org/10.1016/j.bios.2013.12.036.

oligomers (AβO) on the surface of the biosensor and electrochemical conductivity analysis (EIS study, CV study, and a pictorial representation). It shows an increase in the surface conductivity of the biosensor upon oligomer binding.

13.5 Detection and monitoring of toxic gases In indoor and outdoor environments, people are subjected to different air pollutants. Many health problems are known to be caused by poor air quality, which can occasionally necessitate expensive and potentially life-

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Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

facilities, sulfur deposits, natural gas, volcanic gas, and decomposing organic compounds (Zeng et al., 2011). Olfactory nerve paralysis and nose/eye irritation are caused by even low levels of H2S gas exposure. A moderate dose may result in pulmonary edema, chest tightness, keratoconjunctivitis, sore throat, and cough. Overexposure can result in headaches, confusion, loss of judgment, convulsions, coma, and even death (Wiheeb et al., 2013). Electrochemical sensing is the most widely used approach for monitoring toxic gases. This technique is superior to other detection methods like optical (Levitsky, 2015), acoustic (Hök et al., 2000), and gas chromatographic methods (Li et al., 2010). Electrochemical detection has several significant benefits over other techniques, including lower cost, low output energy, good selectivity and consistency, and highly accurate detection technique up to ppm level (Yunusa et al., 2014). Although electrochemical sensors have a short shelf life and are extremely sensitive to temperature changes, the working temperature should be kept as constant as possible for optimum sensor performance. High-temperature sensors are typically used in industrial and space applications. Many studies have recently been conducted on appropriate materials for toxic gas sensing of NO2, SO2, and H2S gases. We have reviewed current developments in electrochemical sensors to detect toxic gases, emphasizing NO2, SO2, and H2S gas sensors.

13.5.1 NO2 sensing Recently, epitaxial graphene was employed to detect NO2 gas up to ppb levels, and it was discovered that monolayer graphene had a better carrier concentration response than bilayer graphene (Melios et al., 2018). For the creation of Pd-SnO2-RGO hybrids as sensing materials for NO2 gas, Wang et al. combined SnO2 and Pd NPs on a nanosheet made up of reduced graphene oxide (rGO) (Wang et al., 2018). Accordingly, the image of Pd-SnO2-rGO obtained from high-resolution transmission electron microscopy (HR-TEM) shows that rGO nanosheets have been coated with 3
5 nm NPs. A sensitivity of 3.92 was observed for the response time of 13 s when the nanosheet was exposed to 1 ppm of NO2 gas at ambient temperature, which is superior to rGO nanosheet and SnO2-rGO nanosheet hybrids as shown in Fig. 13.7. The addition of Pd NPs caused the recovery time (105 s) to be slower though. The primary factors improving the sensing efficacy include preferred NO2 adsorption

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Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

recovery is greatly enhanced, providing dependability and sustainability. Therefore the AgNW functionalization on 2D WS2 can be a flexible remedy for the low NO2 sensing performance.

13.5.2 SO2 sensing The study by Zouaghi et al. showed the vertically aligned carbon nanotube (VACNT)-based gas sensors scanned by THz radiation (Zouaghi et al., 2018). The group used a water-enabled chemical vapor deposition (CVD) technique to create VACNT on a Si substrate covered in SiO2 and doped with boron. The vertically oriented CNTs show a thickness of 95 μm. In the vicinity of 0.2 THz, the maximum relative transmittance was attained. When SO2 gas was added, the maximum transmitted electromagnetic field amplitude of the Si/SiO2/VACNT sensor declined to a stable value with a short response time of 2
3 minutes. The recovery time of the materials was more than 70 minutes. It has been hypothesized that the high SO2 gas sticking coefficient caused the system’s poor recovery to steel walls. Physical adsorption between the carbon nanotube and sulfur dioxide molecules was seen after the preparation of a cholestericnematic mixture intercalated with CNT walls (Petryshak et al., 2017). This adsorption process changes the conductance of the CNTs, which produces a signal that could be used to detect SO2. A study was done by Zhang et al. on TiO2/graphene film, made from scratch utilizing the layer self-assembly method for SO2 detection (Zhang et al., 2017). The sensor was subjected to 1, 50, 250, and 1000 ppb of SO2 gas to examine the response and recovery behavior. The sensor responsiveness rises as the gas concentration increases, while the response and recovery time lengthened. The increase in response and recovery times is thought to be caused by the vast interspace as shown in Fig. 13.8. At an ambient temperature, the TiO2-rGO nanofilm sensor demonstrated a much greater sensing ability to 1 ppm SO2 gas. Liu et al. created Ru/Al2O3-catalyzed ZnO nanosheets and combined them with a microsensor for detecting SO2 gas (Liu et al., 2018). The prepared ZnO 2D nanosheet is uniform, and its thickness was 1.5 nm. Ru/Al2O3/ZnO sensor responses were studied after exposure to various SO2 gas concentrations and related resistance responses. It was found that resistance significantly decreased upon exposure to SO2, and sensitivity increased linearly with respect to SO2 concentration. The measured response and recovery times at 25 ppm of SO2 were 1 and 6 minutes, respectively. The

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Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

Figure 13.10 H2S detection mechanism on α-Fe2O3 nanosheets at 135°C. Source: From Zhang, H. J., Meng, F. N., Liu, L. Z., & Chen, Y. J. (2019). Convenient route for synthesis of alpha-Fe2O3 and sensors for H2S gas. Journal of Alloys and Compounds, 774, 1181
1188. https://doi.org/10.1016/j.jallcom.2018.09.384.

methanol, and H2 gases at 135°C. However, under the same conditions, the sensitivity to H2S was quite large, demonstrating the excellent selectivity toward gas, as shown in Fig. 13.10. Li et al. created ZnO
CuO nanotube arrays for detecting H2S gas at low operating temperatures (Li, Qin, et al., 2018). It was found that the nanotube frameworks encouraged gas with several active sites among H2S molecules and oxygen molecules to diffuse and adsorb. As a result, they helped to attain good sensitivity and quick response time. It was discovered that porous In2O3 nanoparticles offer significant pore volumes and surface areas, which generate many active sites for producing active oxygen species (Li et al., 2019). With a 1 ppb detection limit, these sites significantly increase H2S gas sensing, as shown in Fig. 13.11. Additionally, a dense array of intrinsic ZnO NWs for H2S detection via a sulfuration
desulfuration reaction mechanism has been disclosed (Huang et al., 2015). Mesoporous materials typically have pores with a diameter of 2
50 nm. They provide effective gas detection because of their vast surface areas, open porosity, small pore sizes, and capability to cover the exterior of the mesoporous structure with additional compounds. Quang et al. disclosed a mesoporous Co3O4 nanochain-based H2S sensor (Quang et al., 2018). First, hydrothermal synthesis of (Co(CO3)0.5(OH)11H2O) nanowires was carried out. After that, a 5 hours thermal treatment in air at 600°C created mesoporous Co3O4 nanochains with a rough surface. The ideal operating temperature was identified as 300°C by examining gas responses versus working temperatures. Co3O4 nanochains showed sluggish chemical activity, leading to weaker reactions at lower operating temperatures than the optimum.

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Electrochemical biosensors for toxic gases monitoring

UV light

UV light O2

In2O3

O2-

UV sensor

O2-

h+ e-

e-

h

e

O2

O2-

O2-

In2O3

e- h+

O2eO2-

O2-

O2-

-

O2-

O2-

h+ e-

+

O2

O2

O2-

UV light

UV light

In2O3 -

e

O2-

e-

O2-

Depletion layer

O2-

gas sensor H2S

O2-

SO 2

In2O3 O2-

+H

O

SO2 + H2O

e-

2

O2-

O2In2O3

In2O3 O2-

O2-

e H2S

SO 2

O + H2

O2SO2 + H2O

Figure 13.11 A schematic illustration showing the sensing of UV light and H2S gas based on porous In2O3 nanoparticles. Source: From Li, Z., Yan, S., Zhang, S., Wang, J., Shen, W., Wang, Z., & Fu, Y. Q. (2019). Ultra-sensitive UV and H2S dual functional sensors based on porous In2O3 nanoparticles operated at room temperature. Journal of Alloys and Compounds, 770, 721
731. https://doi.org/10.1016/j.jallcom.2018.08.188.

Additionally, due to enhanced activation at a higher temperature, adsorbed H2S molecules begin to escape from the Co3O4 surface. The manufactured sensor demonstrated rapid reactions and recovery to 1
100 ppm H2S at 300°C. The response and recovery times were calculated to be 46 and 24 seconds, respectively, for 100 ppm H2S. Compared to other harmful gases, the nanochain structure’s specified surface area, smaller pore size, and high number of mesopores make the manufactured sensor appropriate for H2S detection. Table 13.1 shows the nanostructured materials that are used for toxic gas detection. In the sections mentioned above, there have been no studies conducted on biosensors used in the detection of toxic gases but rather reports on sensors used to detect toxic gases. Besides, there are reports on biosensors for detecting pesticides, the food industry, biological activity, and water monitoring. There is scope for researchers to study biosensors to detect toxic gases. However, some reports on the detection of nitric oxides (NO) are mentioned in the next section.

13.5.4 Biosensing of nitric oxides NO has been in an intense study because of the denitrification pathway’s significance for the ecosystem (Canfield et al., 2010) and its role in numerous biological processes that occur in all kinds of life (cardio and neurodegenerative diseases, cell differentiation, regulation of blood flow,

H2S sensing AgNP-doped graphene ZnO-C Aligned ZnO α-Fe2O3 α-Fe2O3 ZnO-CuO pIn2O3 ZnO Co3O4

0.5 Nanofibers Nanorods Nanoparticles Nanosheets Nanotube Nanoparticles Nanowire Nanochains

1 1 10 5 5 1 2 -

,100 ppb 2.55 296 1.25 5.80 0.25 26268 25% -

1

20

Ovsianytskyi et al. (2018)

320 30 10.0 37.0 ,65 180 ,60

3540 5 45.0 94.0 ,65 60 , 60

Zhang et al. (2018) Hosseini et al. (2015) Li et al. (2015) Zhang et al. (2019) Li, Qin, et al. (2018) Li et al. (2019) Huang et al. (2015) Quang et al. (2018)

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Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

and others) (Calabrese et al., 2009). NO has a short half-life, which has been reported to be 5
15 seconds. It is because NO reacts quickly with a variety of biological compounds, including thiols (such as cysteine residues, glutathione), heme proteins (such as hemoglobin), O2, and other radicals (such as the superoxide anion radical) (Wood et al., 2017). Additionally, NO is found in a broad range of significant quantities, from pM to μM. These characteristics of NO make detecting and analyzing it especially difficult. As a result, suitable analytical methods for studying NO should have a broad operating range and quick response times (Schreiber et al., 2012). For these studies of NO metabolism and homeostasis, both in vitro and in vivo, electrochemical biosensors are the preferred method for direct, real-time, selective, and sensitive measurements (Qi et al., 2006). A highly specific nitric oxide biosensor was created by merging microperoxidase (MP) onto poly(terthiophene carboxylic acid) (MWCNTPTTCA) nanocomposite (Abdelwahab et al., 2010). On the probe catalase (CA) surface, superoxide dismutase (SOD) was immobilized to successfully protect from the interference of biological compounds such as H2O2 and O22. Gold nanoparticle (AuNP) was electrodeposited on the glassy carbon surface to improve the sensing of the probe. Excellent results were obtained from the CAS/SOD/MP/MWCNT-PTTCA/AuNPs probe in the electrocatalytic reduction of nitric oxide. The detection limit for NO analysis was 4.3 6 0.2 nM, with a dynamic range of 1.0
40 μM, as illustrated in Fig. 13.12. Similarly, gold nanoparticles (AuNPs), chitosan (CS), and mercaptopropionic acid (MPA) were fabricated to form CS-MPA-AuNPs nanocomposite based on the cytochrome C (Cyt c) for the detection of nitric oxide (Pashai et al., 2018). The interference from ascorbic acid (AA) and NO22 was eliminated by a coating of Nafion. The analyzing techniques such as electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV), and chronoamperometry were utilized to examine the electrochemical response of the resulting Nafion-Cyt c-CS-MPA-AuNPs gold electrode. The findings demonstrate that the nanocomposite offered a suitable environment for the biological activity of its components and the passage of electrons between Cyt c and the surface of the gold electrode. The modified electrode was discovered to have perfect electrocatalysis toward NO. Likewise, the gold nanoparticle on a quaternized cellulose (Au@QC) and poly(ethylene glycol diglycidyl ether) (PEGDGE) was made for the immobilization of hemoglobin (Hb), and the direct electron

Electrochemical biosensors for toxic gases monitoring

313

Figure 13.12 Diagrammatic representation of NO detection on a CAS/SOD/MP/ MWCNT-PTTCA/AuNPs biosensor. Source: From Abdelwahab, A. A., Koh, W. C. A., Noh, H. B., & Shim, Y. B. (2010). A selective nitric oxide nanocomposite biosensor based on direct electron transfer of microperoxidase: Removal of interferences by co-immobilized enzymes. Biosensors and Bioelectronics, 26(3), 1080
1086. https://doi.org/10.1016/j. bios.2010.08.070.

transfer between hemoglobin and electrode (Li et al., 2014). Moreover, Au@QC-PEGDGE nanocomposite film retains the bioactivity of hemoglobin. Thus the modified film could provide a suitable microenvironment for the immobilization of hemoglobin and improves the direct electron transfer between hemoglobin and gold surface electrode. The results show excellent catalytic activity toward NO reduction with a low detecting limit and strong affinity. A nitric oxide biosensor was fabricated based on Cyt c, a heme protein, onto a nanostructure conducting polymer (Alvin Koh et al., 2008), as shown in Fig. 13.13. To avoid the interference of biological compounds, namely, oxygen, superoxide, and hydrogen peroxide, Nafion coating was introduced. Cyclic voltammetry and chronoamperometry were used for the study to determine nitric oxide with the Cyt c-bonded poly-TTCA electrode based on the direct electron transfer of Cyt c. The nitric oxide biosensor was successfully injected into the rat striatum for the NO determination after the administration of cocaine. Likewise, the solubilization of MWCNT is done by functionalizing it with azocarmine B (ACB). The functionalized MWCNT (MWCNTACB) forms a film through electropolymerization to obtain polymerized

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Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

Figure 13.13 Development of cytochrome-c-modified conducting polymer electrode. Source: From Alvin Koh, W. C., Rahman, M. A., Choe, E. S., Lee, D. K., & Shim, Y. B. (2008). A cytochrome c modified-conducting polymer microelectrode for monitoring in vivo changes in nitric oxide. Biosensors and Bioelectronics, 23(9), 1374
1381. https://doi.org/10.1016/j.bios.2007.12.008

ACB (PACB), and an MWCNT/PACB nanofilm is formed. The obtained hydrophilic MWCNTs-ACB and PACB were utilized to make biosensor that offers additional active sites for the electrochemical oxidation of nitric oxide (Zheng et al., 2008). The biosensor provides excellent sensing response and selectivity, a broad linear range, strong stability, reproducibility, and a low detecting limit. The obtained biosensor measures the nitric oxide released from the rat liver cells. The results indicated that the biosensor might be used in NO monitoring systems, as shown in Fig. 13.14. In this study, the myoglobin (Myb) and multiwalled carbon nanotube (MWCNT) were fabricated to form the Myb-MWNT nanocomposite. The Myb-MWCNT-modified GC electrode is designed as an unmediated biosensor to detect NO, based on the electroreduction of NO (Zhang et al., 2005). The electrode’s electrochemical activity showed that MWCNTs could increase the rate of e2 transfer between Myb and the electrode. The biosensor created by integrating Myb on MWNTs exhibits superior selectivity when compared to MWNT alone since the

Electrochemical biosensors for toxic gases monitoring

(azocarmine B)

(GCE) 2.Surface modification of GCE

3. Electropolymerization of azocarmine B

L-Arg e 5.Addition of L-Arg L-Arg NO e

7.Addition of cells and L-Arg

(Nafion)

4. Coating electrode with Nafion

1.Surface functionalization of CNTs

315

mitochondrion cell

e

i

6.Addition of cells

Cells + L-Arg

(7)

Cells L-Arg

(6) (5) (4)

t

Figure 13.14 Designing of the NO biosensor and its measurement in a rat liver cell. NO, nitric oxides. Source: From Zheng, D., Hu, C., Peng, Y., Yue, W., & Hu, S. (2008). Noncovalently functionalized water-soluble multiwall-nanotubes through azocarmine B and their application in nitric oxide sensor. Electrochemistry Communications, 10(1), 90
94. https://doi.org/10.1016/j.elecom.2007.10.027

measurement based on electrochemical reduction of NO eliminates the potential influence of oxidizable chemicals, such as dopamine, ascorbic acid, nitrite, etc. The biosensor has strong stability, superior selectivity, and is simple to fabricate, making it useful for quickly determining traces of NO in an aqueous solution. Likewise, hemoglobin (Hb) is trapped in a polyvinyl alcohol (PVA) and sodium montmorillonite (NaMMT) clay multiassembly that is immobilized on a pyrolytic graphite (plG) electrode for the measurement of NO (Pang et al., 2003). Experimental findings show that direct e2 transfer to the protein is accomplished in this multiassembly. MMT improves Hb’s ability to transport electrons and effectively catalyzes NO reduction. This biosensor performs well in selectivity, stability, and moderate sensitivity. The nanostructured materials for toxic gas biosensing are mentioned in Table 13.2.

Table 13.2 Novel nanostructured materials for the biosensing of toxic gas. Materials

CAS/SOD/MP/MWCNT-PTTCA/AuNPs Cyt c/poly-TTCA Nafion/Cyt c/CS-MPA/AuNPs Myb-MWCNT Au@QC/PEGDGE MWCNT-ACB

Range

1.0
40 μM 2.4
55.0 μM 10
215 μM 0.2
40 μM 0.9
160 μM 0.22
120 μM

Sensitivity

Limit of detection 21

1.10 6 0.01 μA μM 0.117 6 0.006 μA μM21 0.1995 μA μM21 200 nM 0.25 μA μmol L21

4.3 6 0.2 nM 13 6 3 nM 4.5 μM 80 nM 12 nM 0.28 nM

Response

Ref. 21

3.6 6 0.03 s μM 15 s 5s 1.8 μM -

Abdelwahab et al. (2010) Alvin Koh et al. (2008) Pashai et al. (2018) Zhang et al. (2005) Li et al. (2014) Zheng et al. (2008)

Electrochemical biosensors for toxic gases monitoring

317

13.6 Conclusion The data discussed above make it abundantly clear that electrochemical biosensors’ success in the future depends on developing cutting-edge technologies at the micro- and nanoscale and on in-depth contributions from the fields of electronics, materials science, biochemistry, and physics. Globally, environmental contamination in many forms is a severe health hazard. Therefore designing and creating biosensor-based measurement techniques that can accurately identify different toxic pollutants from a wider spectrum are also crucial. However, there are several downsides to biosensors for environmental monitoring, such as (1) reaction time, (2) sensitivity, (3) selectivity, (4) compatibility, (5) affinity, (6) stability, and (7) lifetime, among others. These restrictions must be overcome for a competitive analytical tool to be successfully implemented on-site. It is very important to note that using this approach in creating such structures allows researchers to test out different electrochemical reactions of various structured arrays of sensors. The demand for rapid detecting biosensors will rise in the near future due to growing public health worries about environmental contamination’s effects on the ecosystem. Despite much past and present research into the development of electrochemical biosensors, it is still challenging to develop better, more reliable tools to prevent experimental drift. In this regard, comprehensive research is necessary to present the future trends in the biosensor industry and other associated domains like bioelectronics and bionanotechnology that will ultimately and significantly impact the creation of new biosensing techniques in the future.

Acknowledgment Dipak Maity would like to thank the University of Petroleum and Energy Studies (UPES) for in-house financial support (SEED Funding: UPES/R&D-HS/24022022/08) and all other support. Gajiram Murmu would like to thank the Council of Scientific and Industrial Research (CSIR) for providing a Junior Research Fellowship. Sumit Saha wishes to thank Prof. Suddhasatwa Basu, Director, CSIR-Institute of Minerals & Materials Technology, Bhubaneswar, India, for in-house financial support (Grant number: CSIRIMMT-OLP-112) and requisite permissions.

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CHAPTER 14

Nanostructured materialsmodified electrochemical biosensing devices for determination of neurochemicals ˘ Cigdem Kanbes-Dindar1, Tugrul Tolga Demirta¸s2 and Bengi Uslu1 1

Faculty of Pharmacy, Department of Analytical Chemistry, Ankara University, Ankara, Türkiye Faculty of Pharmacy, Department of Basic Pharmaceutical Sciences, Erciyes University, Kayseri, Türkiye

2

14.1 Introduction It is possible to think of neurochemicals (NCs) as the words that are used in the neuronal language. NCs are chemical messengers in the brain and nervous system that play a role in regulating various physiological and behavioral processes (Moon et al., 2018). Alzheimer’s, Parkinson’s, Huntington’s disease, autism, epilepsy, attention-deficit/hyperactivity disorder, and other neurodegenerative diseases have all been linked to abnormalities in the concentration and dysfunction of NCs in the central nervous system (Tjahjono et al., 2022). Psychotic diseases like schizophrenia, depression, dementia, and others have also been linked to these abnormalities (glaucoma, arrhythmias, thyroid hormone shortage, congestive heart damage, sudden infant death syndrome, dejection, anguish, etc.). To diagnose and treat psychiatric problems, it is therefore particularly important to understand the subtleties of neurochemical communication. Neurotransmission happens quickly (in milliseconds) and in a few main steps. Initially, the transmitter is produced by presynaptic mechanisms. Ca21-initiated exocytosis is used to release neurotransmitters from the presynaptic cell into the synaptic space. After being delivered, the transmitter either binds to receptors on the postsynaptic cell or to autoreceptors on the presynaptic cell (Shirane & Nakamura, 2001). Finally, the signal is ended by transporter reuptake into the presynaptic cell, followed by intracellular catabolism or direct extracellular catabolism. The characteristics of NCs include their mode of action (fast or slow acting), their mode of formation (amino acid group, biogenic amines, or Novel Nanostructured Materials for Electrochemical Bio-sensing Applications DOI: https://doi.org/10.1016/B978-0-443-15334-1.00012-2

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soluble gases), and their mode of function (excitatory or inhibitory). The majority of NTs are challenging to categorize using the criteria listed above. Moreover, in the determination of neurological illnesses, there are yet no conclusive diagnostic techniques based on the number of biomarkers (Ou et al., 2019). As a result, unfortunately, effective treatments cannot be developed. The complex chemical structure of the brain and the neurotransmissions occurring in the brain for seconds are the main reasons why it is difficult to determine brain biomarkers. Thus researchers are interested in identifying chemical biomarkers of brain disorders in order to better diagnose and treat neurological diseases (Matys et al., 2020; Mirza et al., 2019; Liu et al., 2022) (Fig. 14.1). Several different techniques were utilized for the qualitative and quantitative determination of NCs, such as high-performance liquid chromatography (Olesti et al., 2019; Jha et al., 2018; Zhou et al., 2020), gas chromatography (Aragon et al., 2017; Maccarrone et al., 2001; Perry et al., 2009), capillary electrophoresis (Huang et al., 2006; Kennedy et al., 2002; T˚uma, 2021), mass spectroscopy (Lee et al., 2018), fluorescence spectroscopy (Migliorini et al., 2020; Sargazi et al., 2022), and Raman spectroscopy (Eremina et al., 2022; Feng et al., 2022; Moody & Sharma, 2018; Vander Ende et al., 2019). However, most of these techniques have

Figure 14.1 Schematic illustration of synapses. On the left are presynaptic cells, and on the right are postsynaptic cells. Neurotransmitters are represented by blue spheres. Postsynaptic receptors are depicted in purple and autoreceptors in orange.

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some disadvantages in the detection of NCs due to expensive instruments, complex sample preparation procedures, and sophisticated operations. For example, Aragon et al. developed the detection of serotonin (5-HT) in zebra fish (Danio rerio) by using gas chromatography. In order to get gas chromatogram data, a two-step sample derivation method had to be applied (Aragon et al., 2017). Thus both sample preparation and analysis were time-consuming methods with expensive instruments. Moreover, fluorescence or Raman spectroscopic methods had limited neurochemical sensing applications in in vivo studies and available studies of the literature due to the interference effect of tissue absorption or autofluorescence. On the other hand, in the last few years, electrochemical-based neurochemical sensing approaches were one of the trending research topics in the clinical and diagnostic field due to their fast responses, high sensitivity, the possibility of real-time in vivo monitoring, portable and miniaturized sensor size (Dinu & Apetrei, 2022; Lakard, 2020; Lin et al., 2022). However, due to the trace concentration of NCs and interference from other biochemical materials affecting biological matrices, electrochemical measurement of NCs was a complex analytical procedure when bare electrodes were used. To solve the problem, modification of electrodes with nanostructured-based materials has been successfully implemented for electrochemical biosensing of NCs (Cernat et al., 2020; Chauhan et al., 2020; Karimian & Ugo, 2019; Lakard, 2020; Lin et al., 2022; Liu et al., 2019). Moreover, carbon nanostructured materials and noncarbon nanostructured materials are two categories of nanostructured materials utilized in electrochemical sensing. Carbon-based nanostructured materials include graphene, nanotubes (Pemmatte et al., 2020), carbon fiber, and fullerene while noncarbon nanostructured materials include metallic/metal oxide nanoparticles (Taheri et al., 2018), quantum dots, polymers, molecularly imprinted polymers (MIPs), and metal
organic frameworks. As a consequence, the focus of this chapter of the book is on the most recent developments and trends in neurochemical electrochemical detection methods as well as the significance of nanostructured modification in electrochemical sensor research for NCs analysis. In-depth descriptions and discussions are provided for the composition and structure of nanostructured materials used in the research of NCs. To describe the benefits, difficulties, and prospects of modification in electrochemical sensor research for both in vitro and in vivo detection, the advantages, limitations, and prospects of nanostructured materials-modified electrodes in NCs analysis are discussed.

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14.2 The properties of some neurochemicals most commonly studied by electrochemical methods 14.2.1 Serotonin One of the monoamine neurotransmitters that are often present in our bodies is serotonin, also known as 5-hydroxytryptamine (ST or 5-HT), which is produced in the brain, stomach, and spinal cord. Many basic behaviors and physiological processes we perform daily depend on the proper functioning of 5-HT (Yin et al., 2021). Sudden infant death syndrome (SIDS), carcinoid syndrome, abnormal hemostasis, blood clots, depression, anxiety, and migraines can all be caused by low levels of 5HT, but 5-HT syndrome, which is caused by excessive amounts of 5-HT, can have serious toxic consequences and can be deadly. Given the above, it is employed as a biomarker in the diagnosis of several diseases, and the detection of 5-HT is necessary to comprehend the function of 5-HT in several neurological disorders (Sharma et al., 2018).

14.2.2 Dopamine Dopamine (DA) is one of the catecholamine neurotransmitters that play a vital role in the operation of the mammalian central nervous system in the brain, such as the kidney, hormone, and cardiovascular systems. DA irregularities are linked to neurological conditions such as schizophrenia and Parkinson’s disease. Managing and monitoring DA levels are essential to maintaining awareness of the analytical processes of the human brain (Yang et al., 2015).

14.2.3 Epinephrine Epinephrine (EPN) assists individuals in handling their stress and fear. EPN is utilized in the treatment of cardiac arrest and anaphylaxis. The normal level range of EPN in biological samples is 0
140 pg mL21 (764.3 pmol L21) (Moon et al., 2018; Santos-Fandila et al., 2013).

14.2.4 Nor-epinephrine Nor-epinephrine (Nor-EPN) plays a role as “alertness,” in the body’s fightor-flight response, body mobilization, which guides the brain in times of danger. Blood pressure is raised by Nor-EPN, which further treats septic shock. An acceptable level range of Nor-EPN in biological samples is 70
1700 pg mL21 (413.8
10048.7 pmol L21) (Ribeiro et al., 2016; Zhang & Beyer, 2006).

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14.2.5 Glutamate Glutamate (GLu), the precursor to GABA, the primary inhibitory neurotransmitter, is the main excitatory neurotransmitter. Neurological diseases such as autism, stroke, Alzheimer’s disease, schizophrenia, and depression arise from deficiencies in the behavior of neurological pathways that use GLu and its receptors. GLu is a key component of cellular metabolism, as it is a very important step in the breakdown of amino acids and is related to the transamination that occurs during deamination. For this reason, it is essential to evaluate the amount of GLu in biological fluids (Arumugasamy et al., 2020; Ye, 1987).

14.2.6 Tyrosine Tyrosine (TYR) is an indispensable amino acid, a precursor of thyroxine, DA, EPN, and Nor-EPN. Its level is normally in the range of 30
120 μM in human plasma. Low levels of TYR may cause depression, hypochondria, and physical and mental exhaustion. High levels of TYR provoke poor liver and kidney function and intellectual disability (Arumugasamy et al., 2020; Dinu & Apetrei, 2022).

14.2.7 Tryptophan Tryptophan (TRYPN), also known as 2-amino-3-(1H-indol-3-yl) propionic acid, is a necessary amino acid that the body requires to create proteins. TRYPN is an important neurochemical precursor involved in the biosynthesis of 5-HT and melatonin (Prinith & Manjunatha, 2020). The acceptable range of TRYPN concentrations in the human body is 2.05
5.15 mg L21. Several types of depression and sleeplessness are brought on by TRYPN concentrations below normal ranges, whereas illnesses of the central nervous system, such as manic
depressive psychosis with delirium and schizophrenia, take place when TRYPN concentrations are above the upper limit value (Arumugasamy et al., 2020; Dinu & Apetrei, 2022).

14.2.8 β-casomorphin-7 β-Casomorphin-7 (BCM-7) is a type of peptide with opioid properties. It is thought to be associated with autism because it is found in higher concentrations in the urine of autistic children (Shahdost-fard & Roushani, 2020b).

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14.2.9 Acetylcholine Acetylcholine (ACh) is one of the key neurotransmitters that is produced by cholinergic neurons. It is responsible for the transmission of neural impulses and may be found in both the peripheral and central nervous systems. It is possible for irregular ACh synthesis and dissociation to take place when cholinergic neurons are not functioning properly. This has the effect of inhibiting brain signaling. Changes in ACh concentration are linked to the existence and progression of a wide variety of disorders of the neurological system, including Alzheimer’s disease, Parkinson’s disease, myasthenia gravis, and other conditions of a similar nature (Bodur et al., 2021; Khan et al., 2013).

14.2.10 Amyloid beta Amyloid beta (AβO) refers to peptides of 36
43 amino acids that are the main components of amyloid plaques found in the brains of people with Alzheimer’s disease. AβO molecules can form flexible, soluble oligomers that can exist in a variety of forms. The oligomers are toxic to nerve cells. It is even thought that these oligomers may cause misfolding of Tau protein, another important Alzheimer’s-related biomarker (Erkmen et al., 2022).

14.2.11 Thrombin A multifunctional serine protease known as thrombin (TB) is essential for blood coagulation. It has the potential to directly participate in the transformation of soluble fibrinogen into insoluble fibrin, hence prompting blood aggregation. In some studies, it is considered to be associated with neurological diseases because it is found in abnormal levels in the blood of Alzheimer’s patients (Konari et al., 2021; Negahdary & Angnes, 2022).

14.3 The significance of integrating nanostructured materials for electrochemical neurochemical sensing NCs are present in biological fluids at ultralow levels, and highly sensitive detection techniques are required (Cho et al., 2020). Therefore, while developing sensors, researchers apply various modification techniques to make the sensor sensitive, selective, stable, and accurate. In this context, the use of nanomaterials in electrode modification comes into prominence (Balliamada Monnappa et al., 2019). A wide variety of nanomaterials

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ranging in size from 1 to 100 nm which are optically, electrically, and mechanically superior to their bulk forms are used in NCs analysis, such as metal/metal oxides, magnetic nanoparticles, graphene, carbon nanotubes (CNTs), polymers, and metal
organic frameworks (Kaya et al., 2019). The bare electrodes are chemically inert and have a low rate of oxidation. For the electrochemical determination of neurotransmitters, these electrodes have been modified using a variety of polymers. Due to the components’ complementary impacts, the development of conducting polymers aims to preserve each component’s beneficial features while also enhancing their sensitive properties (Manjunatha, 2019). In NC determination, polymeric films not only increase the efficiency of the sensors through their integration between the electron transfer mechanism on the electrode surface and the subsequent charge transfer along the polymer backbone but also ensure that interferences such as ascorbic acid and uric acid are eliminated by electrostatic repulsion (Moon et al., 2018). With a two-dimensional layer of carbon atoms organized in a honeycomb-shaped network, graphene is an allotrope of the carbon family (Hareesha et al., 2021). Due to its exceptional and innovative characteristics, including its high active surface area, excellent electrical conductivity, robust mechanical strength, and remarkable chemical stability, graphene has garnered a lot of attention. Some graphene-modified NC sensors have been published (Liu et al., 2019). Several special properties of CNTs related to fast electrode transfer kinetics, high surface area, and a large edge are widely used in electrochemical sensor studies. CNT has compositional heterogeneity and offers ballistic conductivity and structural rigidity (Pushpanjali et al., 2020). Therefore they are ideal for the development of microelectrodes for cell and tissue sensors. In addition, making biodegradable CNTs for wearable NCs sensor studies is an extremely interesting research topic (Wang et al., 2020). Various metals, such as gold, silver, copper, platinum, cobalt, nickel, and iron, have been used in neurotransmitter sensing. However, the greater preference for gold NPs (AuNPs) in versatile NC sensor applications is strongly associated with their easy chemical and biological modifications. In particular, the high affinity of thiols for the surfaces of noble metals also facilitates the biofunctionalization of these metallic nanostructures by exploiting the widely developed metals. Another important reason for the preference is that well-defined gold NPs have organic surface

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Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

chemistry for biological modification (Liu et al., 2019; Rawtani et al., 2018). Nowadays, nontoxic magnetic iron oxide nanoparticles, which have a large surface area and the ability to adsorb proteins, have attracted a lot of attention. Magnetic iron oxide nanoparticles have been used to generate biosensors based on aptamers, proteins, and enzymes with reported enhanced detection limits, sensitivity, and response times. These platforms were nontoxic, stable in high concentrations, and exhibited chemical groups to allow additional coupling with biomolecules (Baig et al., 2021; Hasanzadeh et al., 2015).

14.4 Application of a nanostructured electrochemical sensor for neurochemical detection In this section, the determination of NCs has been explained in detail including how electrochemical sensors were applied. First, the determination of NCs with a nanobiosensor-based electrochemical sensor was reviewed. Then, new trends in neurochemical sensing methods were investigated by nanobiosensor-based electrochemical methods. Also, Table 14.1 indicates selected studies based on the aptasensor for neurochemical detection.

14.4.1 Immunosensor-based nanobiosensor for neurochemical detection The molecular recognition of antigens (often the target analyte) by an antibody on a transducer surface defines the family of biosensors known as immunosensors. Immunosensor-based electrochemical detection is a desirable technique for many NCs due to the unique selectivity and high sensitivity that specific antigen
antibody interactions enable immune sensors (Felix & Angnes, 2018; Kondzior & Grabowska, 2020). According to a recent study, Chaudhary et al. developed a label-free nano-immunosensor based on molybdenum disulfide
reduced graphene oxide (MoS2-rGO) nanocomposite for the determination of 5-HT in sera samples. First of all, MoS2-rGO nanostructured materials were synthesized via the hydrothermal method. Then, another step included the functionalization of MoS2-rGO nanostructured materials with 3-aminopropyl trimethoxy silane (APTES). Following that, the monoclonal antibodies (anti-5-HT) were covalently linked to the APTES/nMoS2-rGO/ITO electrode utilizing N-(3-dimethylaminopropyl)-N0 -ethylcarbodiimide

Table 14.1 Selected applications of neurochemical detection via nanostructured-based aptamer sensors. Biomarker

Related diseases

Method

Electrode surface

Analysis medium

LOD

Real-life sample

Reference

AAT

AD

DPV

50 mM Tris HCl (pH 8.5)

0.01 pM

Human serum

Zhu and Lee (2017)

α-syno

PD

EIS

ALP-AAT antibody/Ag NPs/AAT/Apt/PTCACNTs/SPCE α-syno/Apt/Au NSs/ pTH-GCE

0.07 aM

Human plasma

Tao et al. (2021a)

α-syno

PD

ECL

5 mM [Fe(CN)6]32/42 in 0.1 M PBS (pH 7.4) PBS

0.42 fM

Human serum

Wu et al. (2020)

(pH 8.0) containing 1.0 3 1025 M luminol [Fe(CN)6]32/42

0.38 fM 10 fM

0.01 M PBS (pH 7.4)

0.87 fM

0.01 M PBS (pH 7.4) 0.2 M PBS (pH 8.0)

0.16 pg mL21 0.012 pM

PBS (pH 8.0)

71 fM

Human serum Human serum Human serum Human blood Human serum

50 mM Tris-HCl

0.250 fM

Tao et al. (2021b) Bu et al. (2022) Liu et al. (2021) Tan et al. (2022) Yin, Wang, et al. (2021) Wang, Li, et al. (2021b)

AβO

AD

DPV

Aβ40

AD

PEC

AβO

AD

DPV

AβO

AD

ECL

AβO

AD

ECL

AβO

AD

DPV

α-syno/Apt/Au NPs@MOFs/ITO electrode α-syno/Apt/MOFs/ITO electrode AβO/Apt/Th-rGOMWCNTs/GCE Aβ/Apt/BPQDs-PLL/ ITO electrode Aβ/Apt/AuPt/CFP MCH/Apt/MSM/Au NPs/ITO electrode AβO/BSA/Apt/Au NPs/ Fe-MOFs/ITO electrode AβO/Au NPs@CuMOF/ SD/MCH/Apt/EPd

CSF

(Continued)

Table 14.1 (Continued) Biomarker

Related diseases

Method

Electrode surface

Analysis medium

LOD

Real-life sample

Reference

AβO

AD

DPV

AβO/TA/GNPs-STP/ Apt/Au electrode

Tris
HCl (pH 7.4)

0.5 fM

Human serum

AβO

AD

SWV

AβOAptFc@SA-gold/ dsDNA/Au electrode

5 mM [Fe(CN)6]32/42 in 0.1 M KCl

93 pM

AβO

AD

ACV

Tris
HCl (pH 7.4)

0.3 pM

AβO

AD

DPV

0.01 M PBS (pH 7.4)

0.45 nM

AβO

AD

ACV

AβO/Apt/Au/borosilicate wafer AβO/Apt/Au NPs/CuMOFs/GCE AβO/Apt/AuR electrode

Human serum and CSF CSF

Wang, Li, et al. (2021) Deng et al. (2020)

10 mM Tris
HCl (pH 7.4)

0.002 pM

Aβ

AD

ECL-RET

0.1 M PBS containing 0.1 M S2O822

3.9 fg mL21

Human serum

Zhang et al. (2020) Zhou et al. (2018) Zhang, FigueroaMiranda, et al. (2019) Wang et al. (2019)

AβO

AD

DPV

0.1 M PBS (pH 7.4)

1.22 pg mL21

Human serum

You et al. (2020)

AβO

AD

PEC

0.1 M HEPES(pH 7.4)

5.79 fM

Human serum

Zhang et al. (2021)

Apt2 2 Ru@MOF/Aβ/ BSAT/Apt1/g-C3N4/ GCE Apt-SiO2@Ag NPs/Aβ/ MIP/Au NPs-GO/ GCE AβO/MoS2 QDs@Cu NWs-Apt/BSA/cDNA/ CuO/g-C3N4/ITO electrode

Artificial CSF CSF

GNRs/Apt/Aβ/antibody/ MOCs@Nafion/Ru (bpy)321/MGCE Apt-Au-Th/Aβ/antibody/ carboxyl graphene/GCE BCM-7/Apt/AgNPs/CuIn-S/ZnS QDs/GCE

0.1 M PBS (pH 7.4)

4.2 3 1026 ng mL21

CSF

Ke et al. (2018)

0.1 M PBS (pH 7.4)

100 pM

0.1 M PBS (pH 7.4) containing 0.1 M RU and 0.1 M KCl

332 fM

Zhou et al. (2016) Shahdostfard and Roushani (2020b)

DPV

BCM-7/BSA/Apt/Au NR/SPCE

5 mM K3 [Fe(CN)6]32/ 42 and 0.1 M KCl mixture in 0.1 M PB (pH 7.4)

334 aM

Autism

DPV

BCM-7/Apt/NiO NPs/ SPCE

PBS (pH 7.4)

166.6 aM

BCM-7

Autism

EIS

BCM-7/BSA/Apt/Au NPs@ZnSQDs/GCE

0.1 M PBS (pH 7.4)

350 aM

Artificial CSF Human urine and blood serum Human urine and blood serum Human urine and blood Human urine

Dopamine

AD, PD, attentiondeficit/hyperactivity disorder, HD, schizophrenia AD, PD, attentiondeficit/hyperactivity disorder, HD, schizophrenia

DPV

Dopamine/MB/MCH/ Apt/Au nanostructure/ Au electrode

0.01 M PBS (pH 7.4)

2 pg mL21 (0.01 nM)

Human serum

SWV

Dopamine/MCH/Apt/ rGO/NB/Au NPs/ GCE

0.1 M PBS (pH 7.0)

1 nM

Human serum

Aβ

AD

ECL-RET

Aβ

AD

DPV

BCM-7

Autism

DPV

BCM-7

Autism

BCM-7

Dopamine

Shahdostfard and Roushani (2020c) Shahdostfard and Roushani (2020a) Roushani et al. (2020)

Jin et al. (2018)

(Continued)

Table 14.1 (Continued) Biomarker

Related diseases

Method

Electrode surface

Analysis medium

LOD

Real-life sample

Reference

Dopamine

AD, PD, Attentiondeficit/hyperactivity disorder, HD, schizophrenia AD, PD, attentiondeficit/hyperactivity disorder, HD, schizophrenia AD, PD, attentiondeficit/hyperactivity disorder, HD, schizophrenia AD, PD, attentiondeficit/hyperactivity disorder, HD, schizophrenia PD, Tourette syndrome, AD AD

DPV

Dopamine/Apt/GCSCGO/GCE

100 mM PBS (pH 7.0)

0.75 nM

Human serum

Wei et al. (2019)

DPV

Dopamine/Apt/Au NPs/ PB/CNTs/GCE

0.1 M PBS (pH 7.0)

200 pM

Human serum

Beiranvand et al. (2016)

Amperometry

Dopamine/Apt/nano-Au/ GCE

50 mM PBS (pH 7.4)

1.8 nM

Human serum

Liu et al. (2016)

SWV

m-PdNFs-Apt2-G4-MBs/ dopamine/Ce-MOFApt1-AP-MCH/GCE

20 mM Tris
HCl (pH 7.5)

6 pM

Human serum

Zhang et al. (2022)

ACV

Serotonin/Apt/Au electrode Apt
Au
CS/Tau-381/ anti-tau antibody/ MPA/Au electrode DNA1-Au NPs@Fe-MIL88/thrombin/MCH/ NTH/Au NPs@ILMoS2/GCE

PBS (pH 7.4)

0.017 fM

Rat CSF

0.1 M PBS (pH 7.4)

0.42 pM

Human serum

Geng et al. (2021) Shui et al. (2018)

PBS containing 0.2 mM [Fe(CN)6]32/42

59.6 fM

Human serum

Xie et al. (2020)

Dopamine

Dopamine

Dopamine

Serotonin Tau-381 Thrombin

AD, autoimmune encephalomyelitis, ischemia, and MS

DPV DPV

Thrombin Thrombin Thrombin

Thrombin

AD, autoimmune encephalomyelitis, ischemia, and MS AD, autoimmune encephalomyelitis, ischemia, and MS AD, autoimmune encephalomyelitis, ischemia, and MS AD, autoimmune encephalomyelitis, ischemia, and MS

DPV

Thrombin/Apt/CNT/ ZnCr-LDH/Au electrode Thrombin/Apt/ERGO/ GCE

PBS (pH 7.4) containing 3.0 mM [Fe(CN)6]32/42 0.5 M H2SO4

0.1 fM

Human serum

Konari et al. (2021)

0.03 fM

Human serum

Zhang et al. (2018) e

ECL

Thrombin/Apt/ZnP-NHZIF-8/GCE

58.6 aM

NS

Fang et al. (2020)

DPV

Apt/GLA/PQD/ MWCNTs-PEI/C60/ SPCE

Dichloromethane containing tetra-nbutylammonium perchlorate Tris
HCl (pH 7.4)

6 fM

Human serum

Jamei et al. (2021)

SWV

From Erkmen, C., Aydo˘gdu Tı˘g, G., Marrazza, G., & Uslu, B. (2022). Design strategies, current applications and future perspective of aptasensors for neurological disease biomarkers. TrAC Trends in Analytical Chemistry, 154, 116675. https://doi.org/10.1016/j.trac.2022.116675s Abbreviations: AAT: α 2 1 antitrypsin, ACV: alternating current voltammetry, AD: Alzheimer’s disease, Ag: silver, ALP: alkaline phosphatase, Apt: aptamer, Au: gold, AuR: gold rod, Aβ: β-amyloid, AβO: β-amyloid oligomers, BCM-7: β-casomorphin 7, BPQDs: black phosphorous quantum dots, BSA: bovine serum albumin, BSAT: bovine serum albumin containing Tween-20, CC: chronocoulometry, CFP: carbon fiber paper, CG: carboxyl graphene, CNTs: carbon nanotubes, CS: cysteamine, CSF: cerebrospinal fluid, C60: fullerene, DPV: differential pulse voltammetry, ECL: electrochemiluminescence, EIS: electrochemical impedance spectroscopy, EPd: electrodeposited palladium electrode, ERGO: electrochemically reduced graphene oxide, Exo: exonuclease, Fc: ferrocene, Fe: iron, GCE: glassy carbon electrode, GCSC: grass carp skin collagen, GLA: glutaraldehyde, GNP-STPs: gold nanoparticle-tagged signal transduction probes, GNRs: gold nanorods, GO: graphene oxide, g-C3N4: graphitic carbon nitride, HD: Huntington’s disease, IL: ionic liquid, ITO: tin-doped indium oxide, JH: jellyfish, LDHs: layered double hydroxides, MB: methylene blue, MCH: 6-mercapto-1-hexanol, MGCE: magnetic glass carbon electrode, MCNs: mesoporous carbon nanospheres, MOFs: metal
organic frameworks, MoS2: QDs: molybdenum disulfide quantum dots, MPA: 3-mercaptopropionic acid, Ms: multiple sclerosis, MSM: silica membrane, MWCNTs: multi-wall carbon nanotubes, NB: Nile blue, nHA: nanosized spherical hydroxyapatite, NH-ZIF-8: aminated zeolitic imidazole framework-8, NiO: nickel oxide, NPs: nanoparticles, NRs: nanorods, NSs: nanostars, NWs: nanowires, NTH: nanotetrahedron, PB: Prussian blue, PBS: phosphate buffer saline, PdNFs: palladium nanoflowers, PEC: photoelectrochemical, PEG: poly(ethylene glycol), PD: Parkinson’s disease, PEI: polyethylenimine, PLL: poly-L-lysine, PPy-COOH: polymerized pyrrole-2-carboxylic acid, Pt: platinum, PTCA: 3,4,9,10-perylene tetracarboxylic acid, pTH: polythionine, PQDs: polymer quantum dots, RET: resonance energy transfer, rGO: reduced graphene oxide, RU: rutin, SA: streptavidin, SD: signaling displaced probe, SPCE: screen-printed carbon electrode, SPGE: screen-printed gold electrode, SWV: square wave voltammetry, TA: trithiocyanuric acid, TdT: terminal deoxynucleotidyl transferase, Th: thionine, TNA: titanium dioxide nanotube array, ZnP: zinc protoporphyrin IX, QDs: quantum dots, α-syno: α-synuclein oligomer.

344

Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

hydrochloride-N-hydroxysuccinimide as the crosslinker agent. Finally, overcoming nonspecific interactions, bovine serum albumin was dropped on a modified ITO electrode. After the sensor surface was characterized with Fourier transform infrared spectroscopy, scanning electron microscopy, transmission electron microscopy, and X-ray diffraction, the obtained linear range value with the offered method for determination of 5-HT was 1
5000 nM, and the detection limit was 1 nM. The developed electro-immunosensor was reported to remain stable for up to 8 weeks. Also, the proposed method was applied to 5-HT-spiked sera samples (Chaudhary et al., 2020). Zeynaloo et al. designed a nonenzymatic electrochemical biosensor for direct GLu detection. For this purpose, a nonenzymatic electrochemical biosensor was created by covalently immobilizing a genetically altered periplasmic GLu-binding protein (GLuBP) on gold nanoparticle-modified screen-printed carbon electrodes (GLuBP/AuNPs/SPCEs). As shown in Fig. 14.2, the response of the electrode was tested after each phase of biosensor manufacturing by scanning the potential from 0.2 to 1.0 V at a scan rate of 50 mV s21 in PBS (pH 7.4). When measuring under the same conditions with the electrodes modified with AuNPs, gold oxide formation was observed on the electrode surface at a peak potential of 10.57 V. Then, the immobilization of GLuBP, which carries two cysteines at its C-terminus and allows the formation of thiol bonds between the gold and protein, was achieved on the electrode surface, in order to bind the Au nanoparticle-coated surface. Finally, a decrease in the peak current recorded through the CV of the modified electrode was found when the GLu selective protein was bound to the gold surface because the presence of nonconducting protein on the electrode surface limited the active surface area of the AuNPs. Also, this change in the

Figure 14.2 Electrode response of each phase of GLu biosensor. From Zeynaloo, E., Yang, Y.-P., Dikici, E., Landgraf, R., Bachas, L. G., & Daunert, S. (2021). Nanomedicine: Nanotechnology, Biology and Medicine, 31, 102305. https://doi.org/10.1016/j. nano.2020.102305.

Determination of neurochemicals

345

electrode surface was confirmed by using electrochemical impedance spectroscopy. When the analytical performance of the GLu biosensor is examined, the sensor responded to changing GLu concentration with a linear response ranging from 0.1 M to 0.8 μM (Zeynaloo et al., 2021). In another study, Adumitrachioaie et al. investigated a novel immunosensor platform based on graphene oxide and chitosan (GO-chitosan) for the effective detection of 5-HT. GO was chosen because the antibody units contain carboxylic groups that form covalent bonds with terminal amine groups. Thus it was used to achieve the immobilization of the biocomponent on the electrode surface. GO is negatively charged in water as a result of the ionization of carboxylic acids and hydroxyl groups, while chitosan contains amino and hydroxyl groups that can be protonated in an acidic environment. Thus strong interactions between these two substances are possible, resulting in an increase in the stability of the nanocomposite film formed on the electrode after solvent evaporation. A linear range of 10 nM
100 mM and a limit of detection of 3.2 nM were obtained for 5-HT detection. The proposed sensor was successfully utilized for the determination of 5-HT in human serum, saliva, artificial tears, and urine samples, as well as in the presence of different interferences (Adumitr˘achioaie et al., 2019) (Fig. 14.3).

14.4.2 Enzyme-based nanobiosensor for neurochemical detection Electrochemical analyses are preferred for the determination of important NCs because they are fast, selective, and economical. However, some important NCs are not electrochemically active. In this context, biosensors with enzyme-modified sensing interfaces provide significant improvements in measurement sensitivity as well as making neurologically important but non-electroactive species measurable. For example, Park et al. designed novel polyaniline-grafted reduced graphene oxide field-effect transistors (FETs) for sensitive enzymatic ACh biosensors. In this research, polyaniline was used to modify the rGOmodified surface because it enhances local pH sensitivity and electrostatic ACh enzyme immobilization. As compared to bare graphene-FET, without any pH hysteresis, the grafted polyaniline (PG) increases pH sensitivity (2.68%/pH) and offers adequate electrostatic binding sites for enzyme immobilization. They report that they have developed the polyanilinegrafted reduced graphene oxide field-effect transistors (PGFETs) as a sensing capable sensor for ACh detection, with a nanomolar detection limit

346

Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

Figure 14.3 The steps of the biosensor elaboration. From Adumitr˘achioaie, A., Tertiș, M., Suciu, M., Graur, F., & Cristea, C. (2019). A novel immunosensing platform for serotonin detection in complex real samples based on graphene oxide and chitosan. Electrochimica Acta, 311, 50
61. https://doi.org/10.1016/j.electacta.2019.04.128.

and significantly increased sensitivity (103%) in the concentration range of 108 nM
2 mM. Moreover, they demonstrated that PGFET can be used as a real-time drug screening platform by observing the inhibitory effects of rivastigmine on enzyme reactions (Park et al., 2022). In another recent study, a flow-through biosensor with enzymes immobilized in a disposable reactor constructed of poly(lactic acid) was described using 3D printing technology for the analysis of uric acid and TYR. When the analytical performance parameters of the enzyme biosensor were examined, it was found that the TYR concentration was linear between 2.0 and 10 μM and that the LOD of TYR biosensor was 0.08 μM. Also, the stability of the enzyme biosensor was examined by continuously measuring the current for a 10 μM TYR transition. The enzyme biosensor signal value showed a modest fluctuation of roughly 5% in the first 2 hours and remained constant after 6 hours (Stoikov et al., 2022).

Determination of neurochemicals

347

Bodur et al. designed for the determination of the amount of ACh, a bienzymatic biosensor system containing acetylcholinesterase (AChE) and choline oxidase (ChO) was prepared with a carbon paste electrode modified with synthesized dendritic macromolecule. In recent years, dendrimers have been used for enzyme immobilization due to their high stability and low variability. As a result, graphite powder, nujol, and PAMAM-Sal were mixed to create carbon paste electrodes. Then, a mixture of 1.0 mg bovine serum albumin (BSA), 60.0 μL buffer solution, 10.0 μL AChE (200.0 units mL21), 200 μL ChO (10.0 units mL21), and 30.0 μL glutaraldehyde (2.5%) was dropped on this carbon paste electrode. Moreover, the effects of glutaraldehyde concentration as a crosslinker, pH of the buffer solution, and temperature of the ACh solution on the sensor response were investigated to obtain the optimum enzyme biosensor for detection of ACh. Under optimized condition, the bioenzyme sensor has two linear ranges, 1.0 3 1028
1.0 3 1027 M and 1.0 3 1027
1.0 3 1025 M, and LOD of bioenzyme sensor was 5.0 3 1029 M (Bodur et al., 2021). In another study, Erkmen et al. designed an amperometric electrochemical nanoenzyme sensor based on tyrosinase enzyme immobilization in poly(3,4-ethylenedioxythiophene) (PEDOT) nanoparticles-decorated graphene quantum dots (GQDs) platform crosslinking with glutaraldehyde for multicomponent detection of catechol (CAT), EPN, and Nor-EPN. After optimizing the amount of PEDOT, GQDs, tyrosinase amount, temperature, and pH parameters using each substrate, CAT, EPN, and NorEPN, enzyme biosensor pharmaceutical dosage forms of EPN and NorEPN were successfully applied in CAT analysis from serum samples. The range of NCs determined under optimal settings was 0.005
11 μM for CAT, 0.2
12 μM for EPN, and 0.1
2.5 μM for Nor-EPN. The limit of detection values for CAT, EPN, and Nor-EPN were reported to be 0.002, 0.065, and 0.035 μM, respectively (Erkmen et al., 2021). Santos et al. described the design and implementation of an electrobiosensing platform for the detection of dopamine in environmental and biological fluid samples based on a carbon paste electrode (CPE) and AuNPs modified with laccase enzyme (LaE) and glutaraldehyde (Glut). The amperometric approach was used to employ the biosensor under ideal circumstances, revealing a linear concentration range of 80.0
0.62 mM with a limit of detection of 0.6 nM. The capacity of the offered biosensor to execute repeated tests over a lengthy period is a significant characteristic, as is the ease with which the electrode surface can be cleaned and

348

Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

regenerated by replacing it with LaE and Glut. The biosensor stored in the refrigerator was found to retain 85% of the biosensor signal after 10 days (Santos et al., 2022).

14.4.3 Aptamer-based nanobiosensor for neurochemical detection A noteworthy and popular research field today is the use of aptamers as target analysis capturers in neurochemical biosensing applications. Aptamers are single-stranded, short oligonucleotides that typically range in length from 20 to 100 bases (Erkmen et al., 2022). The aptamers were artificially designed and synthesized by a high-throughput in vitro selection method called systematic evolution of ligands by exponential enrichment (SELEX) (Geng et al., 2021). Also, aptamers have a 3D structure that allows specific binding of the target analyte. The interaction between an aptamer and its target analyte could occur in a variety of ways such as noncovalent, hydrogen bonds, van der Waals forces. As a result of the difference in this type of interaction, different stems create 3D configurations such as loops, hairpins, or G-quad structures (Arshavsky-Graham et al., 2022). In the last decade, aptamer-based electrochemical sensors have come to the fore in neurochemical analyses with their cheaper, more robust, scalable production and superior selectivity due to their nature. For example, Shen et al. developed a highly selective aptamer-based electrochemical sensor for the determination of DA with a combination of MIP and aptamer. In this research, they showed how each modification step improved the sensor selectivity, as shown in Fig. 14.4, and the best improvement was obtained on the electrode surface where aptamer and MIP were combined. In addition, they modified the electrode surface with AuNPs and reduced graphene for more stable and sensitive integration of the aptamer and polymeric structures. Moreover, in this study, the selectivity of the produced sensor was examined using acetic acid (AA), uric acid (UA), EPN, and catechol (CC) as coexisting compounds or structurally related molecules. As shown in Fig. 14.4, regardless of the interference, the dual recognition-based sensor consistently had the lowest current ratio when tested in MIP/aptamer/AuNPs/rGO/GCE, demonstrating its superior anti-interference performance. The developed MIP/AuNPs/ rGO/GCE sensor exhibited a linear range of 5.0 3 1028
1.0 3 1025 M and a LOD of 4.7 3 1028 M for DA under optimized experimental conditions (Shen & Kan, 2021).

Determination of neurochemicals

349

Figure 14.4 (A) Histogram of the i responses of the MIP/aptamer/AuNPs/rGO/GCE, MIP/AuNPs/rGO/GCE, and aptamer/AuNPs/rGO/GCE to 1.0 3 1026 mol L21 DA, 1.0 3 1026 mol L21 CC, 1.0 3 1024 mol L21 AA, 1.0 3 1026 mol L21 UA, and 1.0 3 1026 mol L21 EP solution, respectively. (B) Histogram of the i responses of MIP/ aptamer/AuNPs/rGO/GCE, MIP/AuNPs/rGO/GCE, and aptamer/AuNPs/rGO/GCE to 1.0 3 1026 mol L21 DA, 1.0 3 1026 mol L21 DA 1 1.0 3 1026 mol L21 CC, 1.0 3 1026 mol L21 DA 1 1.0 3 1024 mol L21 AA, 1.0 3 1026 mol L21 DA 1 1.0 3 1026 mol L21 UA, and 1.0 3 1026 mol L21 DA 1 1.0 3 1026 mol L21 EP, respectively. (C) Effect of the i responses of MIP/GCE, NIP/GCE, MIP/AuNPs/rGO/GCE, NIP/AuNPs/rGO/GCE, MIP/aptamer/rGO/AuNPs/GCE, NIP/aptamer/rGO/AuNPs/GCE to 1.0 3 1026 mol L21 DA. And imprinted factor (IF) of MIP/GCE, MIP/AuNPs/rGO/GCE, MIP/aptamer/AuNPs/rGO/GCE. From Shen, M., & Kan, X. (2021). Aptamer and molecularly imprinted polymer: Synergistic recognition and sensing of dopamine. Electrochimica Acta, 367, 137433. https://doi.org/10.1016/j.electacta.2020.137433; Reprinted from [63], copyright 2021, with permission from Elsevier.

Wang designed a switchable electrochemical sensor for ultrasensitive detection of amyloid-β oligomers, the main pathogenesis of Alzheimer’s disease, using a hybrid metal
organic framework decorated with AuNPs and an aptamer specific to the target molecule after electrochemically coating palladium on the glassy carbon electrode surface. In this study, the effect of unlabeled anti-amyloid-β oligomers aptamer and tagged aptamers with double helix switches on sensor performance was compared to form triple helix switches (THSs). In this study, it has been proven that the addition of another nucleotide chain to the double helix switches can be used as a direct label signaling displaced probe, finding that it improves the THS sensor signal, and is a feature that simplifies the process and increases the detection efficiency in the analysis of amyloid-β oligomers. The developed nanomaterial-decorated aptamer-based electrochemical switchable sensor exhibited excellent selectivity and sensitivity for AβO determination, with a linear range from 0.5 to 500 fM and a detection limit of 0.25 fM. Also, recovery studies were successfully applied to the artificial cerebrospinal fluid by utilizing a developed aptasensor (Wang et al., 2021).

350

Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

Jin et al. developed ratiometric electrochemical aptasensors for DA detection by modifying a glassy carbon electrode with rGO, Nile blue, and AuNPs complexes. As internal or external variables, such as sensor concentration, ambient conditions, and instrument efficiency, may readily affect the signal intensity of traditional sensors with single-signal output, measuring it is challenging. Hence, the ratiometric aptasensor strategy was applied to solve this general problem. The ratiometric aptasensor measurement mechanism is based on the gradual decrease in the Nile blue peak current density with the addition of DA, while the peak current density of DA increases. Hereby, the proposed ratiometric aptasensor demonstrated an excellent relation between lg (peak intensity of DA/peak intensity of Nile blue) and the logarithm of DA concentration ranging from 10 nM to 0.2 mM via LOD of 1 nM (Jin et al., 2018).

14.4.4 The last trends in electrochemical systems for neurochemical detection Understanding the origin of neurological disorders requires the simultaneous measurement of certain NCs. It has been demonstrated, for instance, that DA and 5-HT can affect one another’s release (Shirane & Nakamura, 2001). Hence, it is crucial to measure both DA and 5-HT at the same time in order to understand how drug usage affects the release of these neurotransmitters and how the body behaves with regard to neurotransmitter levels. Zhang et al. developed a 3D biosensor constructed with consecutive adenine (CA) DNA on GO and deposited on the AuNPs composite surface since in previous studies CA adsorbed gold with a higher affinity for gold as shown in Fig. 14.5. Since mercapto unlabeled DNA chains were used to generate 3D biosensor in this study, production was both easier and more cost-effective. Moreover, they also designed for the first time a micro-capacity electrolytic cell to adapt microdialysis to an electrochemical system (Fig. 14.5). At the same time, they were able to successfully integrate microdialysis into the electrochemical system while dynamically monitoring the changes in DA and 5-HT levels. Peak currents of DA and 5-HT at concentrations of DA ranging from 9.0 1027 to 7.0 1025 M and 5-HT concentrations ranging from 6.0 1027 to 4.0 1025 M were linear. The detection limits for 5-HT and DA were 7.0 1029 and 5.6 1028 M, respectively (Zhang et al., 2019).

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Figure 14.5 Graphic representation of the microdialysis system in conjunction with a microcapacity electrolytic cell. a: Perfusion pump; b: experimental rabbit; c: microdialysis probe; d: counterelectrode; e: working electrode; f: reference electrode; g: inlet; h: outlet; i: self-designed electrolytic cell of microcapacity; j: determination device; k: output device. From Zhang, S. J., Kang, K., Niu, L. M., & Kang, W. J. (2019). Electroanalysis of neurotransmitters via 3D gold nanoparticles and a graphene composite coupled with a microdialysis device. Journal of Electroanalytical Chemistry, 834, 249
257. https://doi.org/10.1016/j.jelechem.2018.12.043

14.4.4.1 Smartphone-based nanostructured sensor In a newly published paper, a smartphone-assisted electrochemical sensor for sensitive TYR detection was described, including a screen-printed electrode modified with carbon black nanomaterial and a commercially available smartphone potentiostat (Fig. 14.6). Although they developed a very simple and easily applicable nanosensor in this study, the wide operating range of the smartphone-based sensor was found to be 30
500 μM with LOD of 4.4 μM. In addition, before analyzing TYR from biological materials, the sample was preprepared using various extraction cartridges to eliminate the interfering impact of TRYPN (Fiore et al., 2022). 14.4.4.2 Microfluidic device-based nanostructured sensor Besides the sensitivity of electrochemical sensors, the most important disadvantages are the difficulties encountered in multicomponent analysis. However, microfluidic paper-based analytical devices, which are the miniaturized version of capillary electrophoresis amperometric detector systems, have been one of the more interesting electrochemical sensor topics

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Figure 14.6 Schematic diagram of the smartphone-assisted electrochemical TYR sensor. From Fiore, L., De Lellis, B., Mazzaracchio, V., Suprun, E., Massoud, R., Goffredo, B. M., Moscone, D., & Arduini, F. (2022). Smartphone-assisted electrochemical sensor for reliable detection of tyrosine in serum. Talanta, 237. https://doi.org/10.1016/j.talanta.2021.122869

in recent years due to the detection of multiple analytes at once with high sensitivity. For instance, Roychoudhury et al. fabricated a paper-based fluid capillary electrophoresis amperometric detector (CE-AD) microchip for the simultaneous determination of chemicals such as DA, EPN, and 5-HT (Fig. 14.7). Three therapeutically important neurotransmitters (DA, EPN, and 5-HT) were separated and detected with the microchip used in this study in 650 seconds, utilizing a modest sample volume of just 2 μL. To perform the CE-AD method, 2 mL of sample containing equimolar (0.1
50 mM) concentrations of DA, EPN, and 5-HT was added to the sample reservoir after achieving a stable baseline signal in PBS. In the simultaneous detection of three analytes, the limits of detection (LOD) for DA, EPN, and 5-HT were found to be 2.39, 3.59, and 4.56 mM, respectively (Roychoudhury et al., 2020). 14.4.4.3 Wearable nanostructured sensor for neurochemical detection Wearable sensors have revolutionized the field of healthcare by enabling continuous monitoring of various physiological and environmental parameters. In recent years, nanostructured sensors have gained significant attention due to their exceptional sensing capabilities and ability to miniaturize devices (Pereira da Silva Neves et al., 2018). Thanks to their enormous potential for individualized healthcare diagnoses and therapies, wearable biosensors have garnered a great deal of interest. The primary driving force behind this interest is the enhancement

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Figure 14.7 Schematic illustration of the setup and procedure for simultaneous detection of DA, EPN, and 5-HT. From Roychoudhury, A., Francis, K. A., Patel, J., Jha, S. K., & Basu, S. (2020). A decoupler-free simple paper microchip capillary electrophoresis device for simultaneous detection of dopamine, epinephrine and serotonin. RSC Advances, 10(43), 25487
25495. https://doi.org/10.1039/d0ra03526b.

of peak separation and sensitivity in wearable electrochemical sensors modified with nanomaterials (Lin et al., 2022). In addition to these benefits, its quick and immediate data gathering offers a significant advantage in the investigation of NCs. The fabrication of wearable nanostructured sensors involves the integration of various materials, such as nanomaterials, polymers, and metals, onto a flexible substrate (Ates et al., 2020; Campuzano et al., 2021; Lin et al., 2022). The use of nanomaterials, such as carbon nanotubes and graphene, as sensing elements, allows for increased sensitivity and selectivity. The integration of these materials onto a flexible substrate, such as polyimide, allows for the creation of a wearable device that can conform to the shape of the body. The detection of NCs using wearable nanostructured sensors involves the use of specific receptors that can selectively bind to the target analyte. These receptors can be integrated into the sensing element, such as a carbon nanotube, to create a functional sensor. The binding of the analyte to the receptor results in a change in the electrical or optical properties of the sensing element, which can be measured using a readout device. For instance, Liu et al. produced a wearable sensor modified with indium oxide (In2O3) nanoribbon and high-affinity nucleic acid aptamers on the implantable sensor for the real-time detection of 5-HT and DA (Liu et al., 2020). As shown in Fig. 14.8, after spin-coating each 3-inch

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Figure 14.8 Fabrication of flexible In2O3 nanoribbon biosensors. (A) The provided diagram illustrates the sequence of steps involved in the manufacturing process. A PDMS adhesive layer was applied to each Si/SiO2 substrate. Subsequently, a PET film with a thickness of 1.4 μm was applied as a lamination layer on top of the PDMS material. The In2O3 nanoribbons were fabricated by employing a sputtering technique onto the PET layer using a shadow mask. A titanium (Ti) adhesion layer with a thickness of 1 nm was applied, followed by a gold (Au) layer with a thickness of 50 nm. These layers were deposited using a distinct shadow mask technique in order to create patterns for the electrodes of the source, drain, gate, and temperature sensor. Subsequently, the biosensor film underwent delamination from the inflexible carrier wafer. (B) Photograph depicting the array of devices in their original, unaltered state. The scale bar provided has a length of 1 cm. There are a total of 14 arrays, each consisting of four FETs per device. (C) The provided description pertains to an optical microscope image depicting a solitary device. The image showcases several components, including the Au common-gate electrode, four In2O3 nanoribbon FETs enclosed within a dotted blue box, and an Au resistive temperature sensor positioned from top to bottom. The reduced contrast observed in the In2O3 nanoribbons can be attributed to their inherent transparency. The scale bar shown in the image has a length of 500 μm. (D) The versatility of a sensor array is demonstrated by its ability to conformally adhere to the surface of human skin. Scale bar is 2 cm. (E) The biosensor film exhibited wrinkling phenomena in response to human body movement. Scale bar is 1 cm. PDMS, polydimethylsiloxane; PET, polyethylene terephthalate; FETs, field-effect transistors. From Liu, Q., Zhao, C., Chen, M., Liu, Y., Zhao, Z., Wu, F., Li, Z., Weiss, P. S., Andrews, A. M., & Zhou, C. (2020). Flexible multiplexed In2O3 nanoribbon aptamer-field-effect transistors for biosensing. iScience, 23(9). https://doi.org/10.1016/j.isci.2020.101469.

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Si/SiO substrate with a 20-mm polydimethylsiloxane adhesion layer, 1.4mm polyethylene terephthalate films were then bonded to polydimethylsiloxane via van der Waals interactions. To boost sensitivity and attain the low LOD required for in vivo research, biocompatible In2O3 nanoribbons with radio frequency sputtering were utilized to mimic the polyethylene terephthalate layers using a shadow mask. Finally, aptamer was applied to the determination of 5-HT and DA in artificial cerebrospinal fluid after the aptamer field-effect transistor base was prepared. The working range of the sensor for both NCs was linear from 10 fM to 1 mM, and the LOD was 10 fM. The response time of the developed sensor is 5 seconds; however, this time depends on the semiconductor analyzer and its software (Liu et al., 2020).

14.5 Challenges and conclusion The symptoms of many neurological diseases are similar; even when symptoms appear, the disease is very advanced. In this very complex situation, since neurological diseases cannot be fully demonstrated in treatment methods, treatments are aimed at stopping the progression of the disease rather than eliminating the disease. Effective and reliable neurochemical analysis methods are needed for the implementation of more successful treatment processes, the prevention of the disease, and a clearer understanding of the causes of the disease. The two main challenges encountered in the analysis of NCs are the rapid occurrence of neurochemical processes and the overlap of electrochemical signals belonging to NCs. We consider that the first challenge can be solved by focusing on the development of real-time analysis methods and wearable electrobiosensing methods. The use of a wide variety of different structures of nanoparticles and studies that do not cover selective surface enhancement strategies may be the solution to another electrobiosensing challenge. In this section, we have discussed nanostructure-based electrobiosensing techniques for the measurement of NCs to help establish fast, reliable, and selective electrobiosensing processes. Moreover, in this chapter, we have provided details about the most commonly analyzed neurochemical by electrochemical biosensing methods. Then, we gave information about nanomaterials used in bioelectrochemical analysis of NCs and explained their importance. Finally, we shared information about biosensing strategies and application examples when analyzing a neurochemical.

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Acknowledgment Çi˘gdem Kanbe¸s Dindar expresses her gratitude to the Scientific and Technological Research Council of Turkey (TUBITAK) for its support through BIDEB/2218-National Postdoctoral Research Fellowship Program for Turkish Citizens.

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CHAPTER 15

Real-time utilization of nanostructured biosensors for the determination of food toxins Deepadarshan Urs1, Anil Madesh1, Karrar Mahmood1, Nagaraja Sreeharsha2,3 and K.K. Dharmappa1 1

Inflammation Research Laboratory, Department of Studies & Research in Biochemistry, Mangalore University, Jnana Kaveri Post Graduate Campus, Kodagu, Karnataka, India Department of Pharmaceutics, Vidya Siri College of Pharmacy, Bengaluru, Karnataka, India 3 Department of Pharmaceutical Sciences, College of Clinical Pharmacy, King Faisal University, Al Ahsa, Saudi Arabia 2

15.1 Introduction Fundamental abiotic resources like air, water, sunlight and soil are required for life's existence. Contaminating these abiotic factors by toxicants affect the quality of life of all living beings. Toxicants are either plant-origin, microbial-origin or anthropogenic (human), etc., lead food toxicity. Fertilizers, food additives, dyes, and pesticides are examples of anthropogenic toxins that adulterate food substances. The use of anthropogenic toxins for various purposes, including industrial and agricultural purposes, affect the quality of food substances, like cereals, pulses, grains, coffee, wines, fruits, feed, and other products (Bansi D. Malhotra et al., 2014). Natural toxicants also contaminate food substances, naming a few, cyanogenic glycosides (several plants), solanine (green portions of potatoes), biogenic amines (fish), and fungi toxins (Bansi D. Malhotra et al., 2014). These toxicants, enter the food chain through abiotic factors, which leads to bioaccumulation and in turn, biomagnification. Eventually, these toxicants in human affect hepatocytes, renal, and the immune systems (Bansi D. Malhotra et al., 2014). They also alters the detoxification system, blood pressure, neurotransmission, etc. Consequently, the toxication process enhances mortality (death) and decrease natality (birth). Biosensors are devices that combine a biological component to detect an analyte and a physicochemical component to provide a measurable signal (Fig. 15.1). Toxins are detected by analytical methods such as chromatography (HPLC, thin-layer chromatography, and liquid chromatography), Novel Nanostructured Materials for Electrochemical Bio-sensing Applications DOI: https://doi.org/10.1016/B978-0-443-15334-1.00013-4

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Figure 15.1 Schematic representation of biosensors (Bansi D. Malhotra et al., 2014).

ELISA, polymerase chain reaction, etc. (Gupta et al., 2021). These analytical methods are expensive and time-consuming, and the instruments are not portable. Nanostructured biosensors are portable and inexpensive and give precise and accurate results in short time. These portable devices can be used for onsite detection and are widely used to examine dietary toxicants and nutrition quality. They are also used for various other purposes like examining air quality, pulse rate, pregnancy tests, identifying genomically altered organisms, etc. (Lim & Ahmed, 2016). These nanostructured biosensors are used for both qualitative and quantitative purposes and different field experts like biologists, chemists, physicists, and pharmacologist using this technology. Using a bioreceptor (monoclonal antibody, RNA, DNA, glycan, lectin, enzyme, tissue, or entire cell) and an immobilized sensing element, a biosensor may detect a toxic component. The bioreceptor due to their biochemical characteristics guarantee the high sensitivity and selectivity in biomarker, detection, which also enable the avoidance of interference from other bacteria or chemicals in the tested sample. The transducer transforms the biomarker and bioreceptor's precised biochemical interaction into a quantifiable signal (Fig. 15.1). Therefore, signal recording and presentation enable the qualitative and quantitative toxin detection (Vidic et al., 2017) (Fig. 15.2).

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Figure 15.2 Classification of the pesticide’s sensors (Saeed Ba Hashwan et al., 2020).

15.2 Types of toxins in foods 15.2.1 Bacterial toxins Lipopolysaccharides (LPS) are the most prevalent nonprotein toxins along with bacterial protein and peptide toxins which play an important role in causing toxicity in living being. As many bacterial toxins are big, multipart proteins with several binding sites or epitopes that may be recognized by aptamers or antibodies. This is the most popular design to functionalize the nanomaterials with antibodies or aptamers specific to the toxin. The enzymatic activity of some toxins, such as botulinum toxin (BT), or particular receptors, such as the ganglioside GM1 receptor for cholera toxin (CT), can be used to specifically identify the bacterial toxins in addition to employing antibodies or aptamers as molecular identification element (Sutarlie et al., 2017). An example, a simple sensor can be developed to identify cholera toxin (CT) from solution using the red-to-purple colorimetric shifts which brought on by the aggregation of gold nanoparticles (AuNPs) in solution. The CT B-subunit binds to simple saccharides such as lactose that resemble the GM1 ganglioside receptor because of its high affinity for that receptor. Thiol-modified lactose-coated AuNPs aggregate and change color from red to purple by interacting to CT, with a detection range of 3
122 g mL21 (Schofield et al., 2007). Bacterial toxins can be detected via sandwich-binding with fluorescent probes since they contain many antibody-binding epitopes due to the massive size of the majority of bacterial protein toxins. Among them, the technique uses a sandwich-binding approach for detection of CT, Shiga-like toxin, and streptococcus enterotoxin B (SEB), using colored antibody-functionalized

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Quantum Dots (QDs) and an antibody-functionalized microtiter plate well. The three toxins could all be found using this approach at concentrations between 300 and 1000 ng mL21. Ribulose Bisphosphate doped silica nanoparticles (RuBpy-SiNPs) on a microarray are employed in a similar sandwich-based technique with a detection range of 0.1
1 ng mL21 to identify CT and SEB (Lian et al., 2010).

15.2.2 Fungal toxins Mycotoxins are significant toxins predominantly found in food and enters through the mouth, nose, epithelial contact, etc. Aflatoxin is an example of a fungal toxin that mainly attacks the detoxifying organs. It is of four types: aflatoxin B, aflatoxin G, aflatoxin M, and aflatoxin Q (Gupta et al., 2021). Aflatoxins are insoluble aromatic molecules that exist in crop products and cannot be destroyed during cooking because of their rigid structure (high boiling point). Mycotoxins are secondary metabolites produced by fungi, and they can potentially cause cancer, mutagenesis, teratogenicity, immunotoxicity, and estrogenic effects in both humans and animals. Consequently, the requirement for the appropriate regulation of food items and feed ingredients has been acknowledged. The study by Goud et al. (2018) overviews the current advancements that have been made in electrochemical sensors and biosensors that are used for the detection of mycotoxins. A comprehensive discussion is given on the fundamental features of the toxicity of mycotoxins as well as the implications of their identification. Additionally, various molecular recognition elements and nanomaterials are required to detect mycotoxins (such as portable biosensing systems for point-of-care analysis). In another study by Nirbhaya et al. (2021), an effective electrochemical biosensor based on graphitic carbon nitride nanosheets was developed to detect the food toxin AfB1. Using a polycondensation reaction, graphitic carbon nitride nanosheets were functionalized by a nontoxic thionin (phenothiazine) redox dye. In addition, anti-AfB1 is covalently attached to the Thn/g-C3N4/ITO electrode by employing (1-ethyl-3-(3-dimethylaminopropyl)carbodiimide)-N-hydroxysuccinimide (EDC-NHS) cross-linkers. The electrochemical biosensor that is fabricated for detecting the AfB1 food toxin with a sensitivity of 4.85 lA log (ng21 mL) cm2 and an ultra-sensing lower limit of detection of 0.328 fg mL21 in a wide concentration range from 1 fg mL21 to 1 ng mL21. In addition, the newly created biosensor exhibited high repeatability and had a shelf

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life of 7 weeks. This method can also be applied to identify additional mycotoxins, such as ochratoxin and citrinine, among others, using antibodies specific to those mycotoxins (Sophiya et al., 2022).

15.2.3 Marine biotoxin Toxins found in marine environments appear to rise in many parts of the world. In recent years, palytoxin (PlTX), one of the most potent marine toxins, is prevalent in many types of seafood. This has given rise to a new concern in the Mediterranean Sea. PlTX has a great potential for toxicity to humans; hence, there is a strong and urgent need for sensitive approaches toward its detection and quantification. Zamolo et al. (2012) has developed, an ultrasensitive electrochemiluminescence-based sensor to detect PlTX. This sensor has excellent conductive properties of carbon nanotubes, the specificity provided by anti-PlTX antibodies, and the excellent sensitivity achieved by a luminescence-based transducer. The sensor emits a concentration-dependent light signal, allowing PlTX to be quantifiable. Biosensors are effective screening instruments that can be used in conjunction with confirmatory instrumental analytical methods to produce extremely specific, sensitive, and rapid regular monitoring of developing marine toxins.

15.2.4 Phytotoxins The term “phytotoxins” refers to harmful compounds that are produced by plants. They include secondary metabolites which are hazardous in a dose-dependent manner as well as allergens that are capable of causing anaphylactic shock in persons who are sensitive to them. The identification of phytotoxins in food is becoming an increasingly pressing concern. The traditional methods for detecting phytotoxins are not sensitive enough and are not user-friendly enough to be practical. Assays that are based on nanomaterials have demonstrated a high level of competence in both the rapid and precise sensing of trace chemicals. When the analytes are anticipated to exhibit considerable photoluminescent features, quantum dots (QDs) have been used for a variety of scientific purposes. For the detection of phytotoxins, it is employed. Quantum dot (QD)-based biosensors exhibit significant promise for a diverse range of applications, encompassing both qualitative and quantitative measurement of various physiological parameters such as blood glucose levels, pH levels, electrolyte concentrations, blood gas composition, plasma enzyme activity, cholinesterase activity, and erythrocyte characteristics. Biochemical characteristics play a crucial role in

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clinical toxicology cases involving living patients, when prompt identification of the poison is imperative (Ravi & Ganesan, 2021).

15.2.5 Heavy metals Heavy metal contamination is one of the most important environmental issues threatening world sustainability. Due to pollution, excess mining, industrial disposal, and pesticides, there is a chance of heavy metal contamination in water and food. Contaminated water (heavy metals) used in food production processes has an adverse impact on human and animal health. In cereals, salt, and other food products, metals (iron) are added for nutritional purposes (Dharmappa, 2022). If its concentration is extreme, it is toxic to mankind. However, in our body, metal concentrations are limited, and a high concentration may lead to toxic effects rather than normal ones. The toxicity or cytotoxic effects of heavy metals are determined using nanostructured biosensors. Al, Na, Ca, Mg, and K are not considered heavy metals because their densities are lower than 5 g cm23. Fe, Cu, Zn, Mn, Au, and Ag are considered heavy metals because their densities are greater than 5 g cm23. They either activate or inactivate the enzymes inside the cell, which leads to switching on or off the particular pathway. They also produce ROS by interfering in the electron transport chain (Odobaˇsi´c et al., 2019). Many efforts have been undertaken to develop portable sensors for environmental heavy metal monitoring. Using nanoparticles and nanostructures in sensors improves device performance regarding sensitivity, selectivity, multiplexed detection capabilities, and mobility. Furthermore, as molecular recognition probes, tiny molecules, DNA, proteins, and microorganisms have been combined with inorganic materials to bind heavy metals selectively (Leonardo et al., 2016). This study examines recent developments in optical, electrochemical, and fieldeffect transistor sensors for the heavy metal detection. Colorimetric, fluorescent, surface-enhanced Raman scattering, and surface plasmon resonance devices are the primary optical sensors are used to detect the heavy metals (Ba Hashwan et al., 2020; Li et al., 2013). Nanostructured biosensors help to assess the quality of drinking water, waste water, etc.

15.2.6 Chemicals 15.2.6.1 Pesticides Agricultural pollutants are unfavorable elements that endanger the ecology, the environment, animals, and human health. It is necessary to create

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preventive and detection systems with high sensitivity and selectivity in order to prevent their exposure (Yılmaz et al., 2022). Therefore, it is necessary to design detection platforms that can offer onsite detection via miniaturized and high-throughput devices. Surfaceenhanced Raman scattering (SERS) is a technique that combined with portable spectrometers and detecting devices, may offer distinctive information about the presence of plasmonic nanostructures. Chen et al. employed an AuNP-dropped tape to extract pesticides from the fruit skins in order to remove them from meals. When parathion-methyl, thiram, and chlorpyrifos were sprayed on the cleaned food peels, they first put 25 nm AuNPs on the tape, which was known as SERS-tape, and then pasted it on the apples, oranges, cucumbers, and green vegetables. The sample surface's tape was taken off before SERS analysis with a transportable Raman spectrometer. Commercial adhesive tapes are compared for their ability to remove pesticides and interfere with the SERS signal. They chosen the “3 M transparent adhesive tape” out of the five commercial tapes because it had a stronger SERS signal and less background fluorescence noise (Ba Hashwan et al., 2020; Yılmaz et al., 2022).

15.2.7 Dyes Food colors that are harmful include quick green and metanil yellow. Using cyclic voltammetry, differential pulse voltammetry, and electrochemical impedance spectroscopy, the developed nanosensor (calix8/Au NPs/ GCE) are evaluated for its capacity to sense. To improve the settings and elicit the optimum reaction from the target analytes, the impact of a variety of factors was examined. The calix8/Au NPs/GCE nanocomposite are shown to greatly improve the signals of the chosen food dyes in comparison with bare GCE due to the synergistic action of calix arene and Au nanoparticles. Metanil Yellow and Fast Green Limits of Detection at the Calix8/Au NPs/GCE are reported to be 9.8 and 19.7 nM, respectively, under optimal circumstances. The created sensing platform are showed merit when they are used to detect food colors in samples. Additionally, the developed electrochemical platform's superior repeatability, reproducibility, and stability showed that it may be used for actual sample analysis (Shah, 2020).

15.2.8 Plastics Plastics are not compostable and can be found in everything, including soil, water, and food. It is now one of the most common food adulterants.

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In the past few years, people have heard a lot about plastic rice and plastic eggs being found in food and sometimes stored hot foods and boiling water in plastic containers. As a result, plastics are released at the nanoscale. It is divided into two sorts based on its size, for example, microplastics (5 mm) and nanoplastics (less than 1 μm). Because of their small size, microplastics are eliminated from the body. However, nanoplastics are not expelled; instead, they are retained in the organs. Furthermore, tons of micro- and nanoplastics are dumped yearly into the ocean, and it leads to toxic environment and contamination in the sea food (Yılmaz et al., 2022). The procedures that have been used in the past to determine the presence of microplastics in food are not reliable and also expensive. Because of this, the detection of the food toxin via biosensors is becoming increasingly important in the current context. Nowadays, three approaches are commonly employed to identify microplastics. Both the hot needle test and fluorescent dyeing procedure are extensively used to measure microplastics. Microspectroscopy is another way. Microplastics can be quantified and classified using this technology. However, to reduce interferences, microspectroscopy requires expensive equipment and sophisticated sample pretreatment. As a result, the approach cannot be used to acquire real-time data. Otherwise, the light source beam width is wide in the microspectroscopy method. In the study of Huang et al. (2021), they discovered the small microplastic detection using surface plasmon resonance biosensors based on the bio-affinity-induced particle retention and biosensor-based detection able to detect each small minute particle (Ba Hashwan et al., 2020; Blake et al., 2001).

15.3 Conclusion In conclusion, this chapter has explored the real-time utilization of nanostructured biosensors for the determination of food toxins. The development of efficient and reliable detection methods is crucial for ensuring food safety and protecting public health. Nanostructured biosensors have emerged as promising tools due to their unique properties, including high sensitivity, selectivity, and rapid response. Throughout this chapter, we have discussed various types of nanostructured biosensors, such as nanowires, nanoparticles, and their applications. These biosensors have shown excellent performance in terms of sensitivity, specificity, and real-time monitoring capabilities. Their ability to detect a wide range of food toxins, including pesticides, heavy metals, bacterial and mycotoxins, is crucial for ensuring the quality and safety of food products. The integration of nanomaterials with biological recognition elements, such as enzymes, antibodies,

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or DNA probes, has enhanced the specificity and selectivity of nanostructured biosensors. The use of advanced nanofabrication techniques has allowed for the precise control of sensor properties, leading to improved detection limits and reduced interference from complex food matrices. Real-time monitoring of food toxins is essential for timely intervention and preventing the consumption of contaminated food. Nanostructured biosensors offer the advantage of rapid detection, enabling quick decisionmaking and mitigation strategies. Their miniaturization and compatibility with portable devices facilitate on-site analysis, reducing the need for costly and time-consuming laboratory procedures. However, there are still challenges that need to be addressed in the field of nanostructured biosensors for food toxin detection. These include standardization of detection protocols, validation of biosensor performance, and addressing the potential for false-positive or false-negative results. Additionally, ensuring the long-term stability and reproducibility of nanostructured biosensors is crucial for their practical application. In summary, the real-time utilization of nanostructured biosensors holds great potential for the determination of food toxins. Their high sensitivity, selectivity, and rapid response enable an efficient monitoring of food safety. With further advancements in nanotechnology, biosensor design, and validation protocols, nanostructured biosensors have the opportunity to revolutionize the field of food safety, contributing to a healthier and more secure food supply chain (Table 15.1). Table 15.1 Different types of bioreceptors for detecting heavy metals (Odobaˇsi´c et al., 2019). Type of bioreceptor

Analyzed heavy metal

Reference

2A81G5 Antibody ISB4 12F6 Alkaline phosphatase Pyruvate enzymes Oxidase Urease Glutathione S-transferase Mer R proteins

Cd Cd U Zn Cd Hg Hg, Ag Cd, Zn

Khosraviani et al. (1998) Blake et al. (2001) Melton et al. (2009) Satoh (2002) May and Russell (2003) Malitesta and Guascito (2005)

Metallothionein Whole cells and cardiac cells

Hg, Cu, Cd, Zn, Pb Cd, Zn, Ni Hg, Pb, Cd, Fe, Cu, Zn

Corbisier et al. (1999), Saatçi et al. (2007) Bontidean et al. (2003), Wu and Lin (2004) Varriale et al. (2007) Liu et al. (2007)

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671. Available from https://doi.org/10.2116/analsci.20scR03. Saatçi, E., Nistor, M., Gáspár, S., Csöregi, E., & Iscan, M. (2007). Comparison of two glutathione S-transferases used in capacitive biosensors for detection of heavy metals, . International Journal of Environmental Analytical Chemistry (87, pp. 745
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11. Available from https://doi.org/10.1080/03067310701409309. Satoh, I. (2002). An apoenzyme thermistor microanalysis for zinc (2) ions with use of an immobilized alkaline phosphatase reactor in a flow system. Biosensors and Bioelectronics, 6, 375
379. Available from https://doi.org/10.1016/0956-5663(91)85025. Schofield, C. L., Field, R. A., & Russell, D. A. (2007). Glyconanoparticles for the colorimetric detection of cholera toxin. Analytical Chemistry, 79(4), 1356
1361. Available from https://doi.org/10.1021/ac061462j. Shah, A. (2020). A novel electrochemical nanosensor for the simultaneous sensing of two toxic food dyes. ACS Omega, 5(11), 6187
6193. Available from https://doi.org/ 10.1021/acsomega.0c00354. Sophiya, P., Urs, D., Meti., Banu, H., Shankar, J., & Dharmappa, K. K. (2022). Voltammetric devices for disease advanced detection. Voltammetry for Sensing Applications. Sutarlie, L., Ow, S. Y., & Su, X. (2017). Nanomaterials-based biosensors for detection of microorganisms and microbial toxins. Biotechnology Journal, 12(4). Available from https://doi.org/10.1002/biot.201500459. Varriale, A., Staiano, M., Rossi, M., & D’Auria, S. (2007). High-affinity binding of cadmium ions by mouse metallothionein prompting the design of a reverseddisplacement protein-based fluorescence biosensor for cadmium detection. Analytical Chemistry, 79(15), 5760
5762. Available from https://doi.org/10.1021/ac0705667. Vidic, J., Manzano, M., Chang, C.-M., & Jaffrezic-Renault, N. (2017). Advanced biosensors for detection of pathogens related to livestock and poultry. Veterinary Research, 48 (1). Available from https://doi.org/10.1186/s13567-017-0418-5. Wu, C. M., & Lin, L. Y. (2004). Immobilization of metallothionein as a sensitive biosensor chip for the detection of metal ions by surface plasmon resonance. Biosensors and Bioelectronics, 20(4), 864
871. Available from https://doi.org/10.1016/j. bios.2004.03.026. Yılmaz, D., Günaydın, B. N., & Yüce, M. (2022). Nanotechnology in food and water security: on-site detection of agricultural pollutants through surface-enhanced Raman

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spectroscopy. Emergent Materials, 5(1), 105
132. Available from https://doi.org/ 10.1007/s42247-022-00376-w. Zamolo, V. A., Valenti, G., Venturelli, E., Chaloin, O., Marcaccio, M., Boscolo, S., Castagnola, V., Sosa, S., Berti, F., Fontanive, G., Poli, M., Tubaro, A., Bianco, A., Paolucci, F., & Prato, M. (2012). Highly sensitive electrochemiluminescent nanobiosensor for the detection of palytoxin. ACS Nano, 6(9), 7989
7997. Available from https://doi.org/10.1021/nn302573c.

Further Reading Hareesha, N., Manjunatha, J. G., Amrutha, B. M., Pushpanjali, P. A., Charithra, M. M., & Prinith Subbaiah, N. (2021). Electrochemical analysis of indigo carmine in food and water samples using a poly(glutamic acid) layered multi-walled carbon nanotube paste electrode. Journal of Electronic Materials, 50(3), 1230
1238. Available from https://doi. org/10.1007/s11664-020-08616-7. Manjunatha, J. G. (2018). A novel voltammetric method for the enhanced detection of the food additive tartrazine using an electrochemical sensor. Heliyon, 4(11), e00986. Available from https://doi.org/10.1016/j.heliyon.2018.e00986. Manjunatha, J. G., Kumara Swamy, B. E., Deraman, M., & Mamatha, G. P. (2013). Simultaneous determination of ascorbic acid, dopamine and uric acid at poly (aniline blue) modified carbon paste electrode: A cyclic voltammetric study. International Journal of Pharmacy and Pharmaceutical Sciences, 5(2), 355
361. Available from http:// www.ijppsjournal.com/Vol5Suppl2/6820.pdf. Nanomaterial-Based Biosensors for Food Toxin Detection. (2014). Applied Biochemistry and Biotechnology. Available from https://doi.org/10.1007/s12010-014-0993-0. Raril, C., & Manjunatha, J. G. (2020). A simple approach for the electrochemical determination of vanillin at ionic surfactant modified graphene paste electrode. Microchemical Journal, 154, 104575. Available from https://doi.org/10.1016/j.microc.2019.104575. Tigari, G., & Manjunatha, J. G. (2019). Electrochemical preparation of poly(arginine)modified carbon nanotube paste electrode and its application for the determination of pyridoxine in the presence of riboflavin: An electroanalytical approach. Journal of Analysis and Testing, 3(4), 331
340. Available from https://doi.org/10.1007/s41664019-00116-w.

CHAPTER 16

Nanostructured electrochemical biosensors for estimation of pharmaceutical drugs Ersin Demir1, Nida Aydogdu Ozdogan1 and Muharrem Olcer2 1

Faculty of Pharmacy, Department of Analytical Chemistry, Afyonkarahisar Health Sciences University, Afyonkarahisar, Türkiye 2 Faculty of Pharmacy, Department of Pharmaceutical Technology, Afyonkarahisar Health Sciences University, Afyonkarahisar, Türkiye

16.1 Introduction Bringing biosensors to the literature is not far away. The first biosensor dates back to the middle of the 19th century (Heineman & Jensen, 2006; Sridharan et al., 2022). Leland L. Clark and Lyons brought an oxygen electrode to the literature in the 1950s. Another later work was done in 1962, and in this study, he developed the first amperometric enzyme sensor for glucose determination, and the word biosensor took its place in the literature (Clark & Lyons, 2006; Heineman & Jensen, 2006). In 1975, such biosensors were named “Model 23 A YSI analyzer” (Yoo & Lee, 2010). The general definition of a biosensor is a self-contained integrated device that can provide quantitative or semiquantitative analytical information directly using a biochemical receptor (Lee & Mutharasan, 2005). In its simplest form, it is an analytical device capable of converting a biological response into a signal (Bollella & Katz, 2020; Hammoud et al., 2022). Countless biosensors have been built for the determination of various analytes in the fields of medicine, pharmacy, biology, chemistry, and materials science, up to now. Moreover, biosensors are used in almost all multidisciplinary fields due to their wonderful, specific, and selective properties. Biosensors have low detection limits, short analysis times, and cheapness. They have many advantages such as no processing required, portability, and miniaturization potential. In addition, various biosensors have been fabricated with nanoparticles, hybrid nanomaterials such as conductive polymers, molecularly imprinted polymers (MIPs), and carbonaceous composite sensors which exhibit extraordinary behavior in terms Novel Nanostructured Materials for Electrochemical Bio-sensing Applications DOI: https://doi.org/10.1016/B978-0-443-15334-1.00014-6

© 2024 Elsevier Inc. All rights reserved.

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of strength and stability. Moreover, biosensors with unique properties are preferred for the determination of drug analytes with superior selectivity even in complex matrix environments such as blood and urine. Therefore electrochemical sensors, which have been constructed with nanostructure materials, are widely used in the determination of extremely important analytes such as pharmaceutical drugs, pesticides, etc. Today, scientists need new analytical methods that are on-site, online, and portable, with rapid responses, to provide diagnostics. There is a need for a selective and sensitive biomedical analyzer system that will serve very quickly, especially in determining the factors that directly affect human health. In addition, food analysis and environmental analysis are extremely important, and fast analyzer systems are needed. Although chromatographic or spectroscopic methods are widely preferred for the single and simultaneous determination of the analyte or analytes, these methods have some drawbacks. These drawbacks can be listed as long preprocessing, too much solvent requirement, expensive equipment, and need for expertise. Contrary to traditional methods, electrochemical techniques and nanostructured sensors are used to inspire the world of science. As they are fast, portable, selective, and sensitive, electrochemical techniques are used for the determination of a wide range of analytes such as pharmaceuticals, pesticides, and inorganic and organic substances (Demir & ˙Inam, 2014; Inam et al., 2020; Isildak et al., 2018; Silah et al., 2021). In recent years, all factors such as the widespread use of electrochemical methods, the increase in sensor diversity, and the production of unique new materials have produced analyte targets with excellent properties. Especially in the last two decades, it is understood that sensor studies for the analysis of drugs, food, and other agents in the field of electroanalysis have gained great momentum. Moreover, more specific, selective, and sensitive electrochemical sensors are needed for the detection of numerous analytes in the complex matrix environment. In particular, the discovery of each new material means a new horizon in the world of sensors for analyte analysis. The production of new types of biosensors, their portability, and the development of body-integrated sensors have become possible with advancing technology. Moreover, the poor stability and short shelf life of biosensors are improving day by day. For this, different nanomaterial biosensors are being developed with hybrid materials. In addition, scientific studies are continuing at full speed so that biosensors can be integrated into human health in our daily lives. The main reason here is to provide an early diagnosis with fast-response nanostructured sensors and to

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intervene as soon as possible. Therefore online and portable sensors have gained great importance. In addition, new superconducting and catalytic materials and electrochemical processes produced in parallel with the developing technology are examined in detail. In other words, the fundamentals of biosensor fabrication are well established, and scientists are focusing on nanostructured biosensor building and analytical performance improvement. As a result, it is inevitable to produce sensors that provide more sensitive, selective, and on-site analysis possibilities in the next few years. As a result, the nanostructured biosensor will be an indispensable part of human life, the environment, and even the industry. Biosensors generally consist of (1) an analyte, (2) a bioreceptor, (3) a transducer, (4) electronics, and (5) a display. In its simplest form, we can say that it occurs in the analyte, bioreceptor, and transducer, as shown in Fig. 16.1, where analyte: the substance to be determined in the samples; bioreceptor: a biological element or substance capable of sensing or recognizing a chemical change such as light, heat, pH, charge, or mass during the interaction between the bioreceptor and the analyte; and converter: the part of the biosensor that converts energy from one form to another. According to the working principle, it can be divided into five main classes, namely, electrochemical, optical, electronic, thermal, and gravimetric converters. Electronic: The converted signal is processed to prepare the image. The electrical signals obtained from the converter are amplified

Signal Transducer

Recognition Element

Signal Processor

Biosensor Figure 16.1 Three components of biosensor.

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and converted into digital images. Imaging: It is a system connected to a computer or printer that produces an output of results. The output can be in the form of numerical data, graphics, or tables (Figs. 16.2 and 16.3). It is possible to make different classifications of nanostructured electrochemical biosensors built for the determination of organic substances such as drugs. In particular, different groupings are made on the main component such as analyte, transducer, and bioreceptor. In this chapter, Potentiometric

Amperometric

Conductometric Electrochemical biosensor

DNA Impedmetric Enzyme Ion charge Biological element

Antibody

Optical / visual biosensor

Biomimetic

Metal oxide biosensors

Phage

Field effect type

Biosensors Piezo electric Mass based biosensor Magneto electric

Figure 16.2 Classification of biosensors.

Figure 16.3 General fabrication of nanostructured electrochemical biosensor built by using Ag metal nanoparticles (Aydogdu Tig et al., 2019).

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383

electrochemical biosensors are classified according to the bioreceptor layer in the biorecognition process. According to this classification, types such as cell-based, affinity, aptamers, molecularly imprinted polymers, carbon nanostructures, metal or metal oxide nanoparticle supported biosensors and rarely preferred nanomaterials used in enzyme production are taken as basis.

16.2 Electrochemical biosensors Electrochemical methods are used in the qualitative and quantitative determination of unlimited substances due to their extraordinary selectivity, excellent accuracy, and precision, requiring pretreatment, using very few organic solvents, working with few samples, and being portable. Moreover, due to its integration into combined systems, it enables the development of binary analyzer sets. In addition, there are many superior aspects of electrochemical sensors such as the development of flexible electrodes, the production of miniature sensor kits, and the possibility of field analysis. Among the electrochemical sensors, biosensors are known to be a stand-alone multidisciplinary field. It has a place in different application areas such as health applications, the defense industry, food analysis, and pesticide detection. Moreover, with the unique properties of biosensors, the development, commercialization, and new application areas of electrochemical biosensors have gained great importance. In particular, when the literature is examined, biosensor studies have increased with great momentum in the last two decades (Figs. 16.4 and 16.5).

Figure 16.4 Systematic representation of nanostructured electrochemical biosensor using quantum dots for the analysis of amoxicillin antibiotic (Wong et al., 2020).

384

Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

Figure 16.5 Electrochemical oxidation of amoxicillin on graphene-based nanosensör (Pollap et al., 2018).

The basic working principle of electrochemical biosensors is that the electrical potential difference between the analyte and the bioreceptor depends on the active concentration of the analyte. It consists of biomaterials such as enzymes, aptamers, MIP, and DNA as a bioreceptor. In addition, carbon materials and new-generation nanosensors modified to these material surfaces are also being developed. In this device, the current or potential difference resulting from the redox behavior of the analyte is used to determine the analyte in the sample. We can group biosensors into five classes according to their working principles: (1) electrochemical biosensor, (2) mass-based biosensor, (3) biological element, (4) optical biosensor, and (5) metal oxide biosensor. Electrochemical biosensors are classified into five main techniques, namely, conductometric, amperometric, voltammetric, potentiometric, and impedimetric (Figs. 16.6 and 16.7). The construction process, stability, and shelf life of interfaces are the most challenging processes in biosensor design. The interface structure, which provides exceptional selectivity, must be specific to the target analyte, even in the complex matrix environment. In addition, the nanomaterials in the bioreceptor must be in an inert structure on the surface. There is a need for an auxiliary layer between the biomolecules denatured bioreceptors and the surface of the electrodes, where the biological elements are considered to be highly active. Different nanomaterials can be created at this interface. Sometimes it is used on a solid surface such as silicone, and sometimes it is made from a number of different substrate

Nanostructured electrochemical biosensors for estimation of pharmaceutical drugs

385

Figure 16.6 The quantitative determination of carbamazepine was performed with polymer-supported nanostructured mipedot/GCE biosensor (Hammoud et al., 2021).

Figure 16.7 Production of nanostructured electrochemical sensors using porous organic polymer (POP) (Yuan et al., 2021).

materials such as paper or polymers. On the basis of these materials, it plays an important role in increasing the stability of the interfaces, making them more sensitive, extending the shelf life, and improving selectivity. Therefore building a unique new interface is seen as one of the most important steps in biosensor development. For this, applications are made

386

Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

Figure 16.8 Metal
organic framework (MOF)-supported nanostructured biosensors for the analysis of galantamine (Zhang, & Qiao, Cai, et al., 2021).

to nanostructured materials, and new types of biosensors are produced every day. Moreover, due to the superior selectivity and excellent sensitivity of biosensors, there are countless applications for both qualitative and quantitative analysis of substances such as pesticides, drugs, and organics. The most basic factor here is the variety of biosensors that are formed by combining different nanostructured materials or several nanomaterials seen in the bioreceptor. It is possible to classify these nanostructured unique materials as metallic nanomaterials, carbon-based nanomaterials, polymer, and metal
organic frameworks (Fig. 16.8).

16.2.1 Metal nanostructured biosensors In recent years, the development of nanostructured materials depending on technology has made a positive contribution to the production of biosensors (Song et al., 2021). In particular, these nanomaterials with large surface area, incredible catalytic properties, and excellent conductivity allow the development of more sensitive, stable, and selective biosensors. While sensors such as gold (Au), platinum (Pt), and silver (Ag) are used directly as the main biosensors, more sensitive biosensors are sometimes developed by creating electrochemical synergistic effects with different nanostructures. Not only metal sensors but also metal oxide nanoparticles (TiO2, ZnO, MnO2, Fe3O4, Bi2O3, La2O, VO2, and V2O5), semiconductors (Se, Si), bimetallic nanocrystals (Ni-Fe2O4, Ni-ZrO2, NiCo2O4,

Nanostructured electrochemical biosensors for estimation of pharmaceutical drugs

387

Ni-SiO2), and different metal-based sensors are produced as nanostructured electrochemical biosensors. In addition to these materials, biosensors with microporous structures and microdots (C-dots) have also been produced for the analysis of drugs in real samples. In addition, noble metaland alloy-based nanomaterials have been rare nanostructured materials encountered in the literature, where they are used in the production of biosensors due to their catalytic and biocompatible properties. In the studies carried out so far, nanostructured biosensor production has been observed by coating different materials on the gold (Au) electrode surface, while at the same time, more sensitive, selective, and stable biosensors have been developed by modifying materials such as metal nanoparticles, metal oxides, and bimetallic on the carbon electrode surface. Techniques such as electrodeposition, drop drying, annealing, and physical mixing have been applied in the development of nanostructured electrochemical biosensors (Table 16.1 and 16.2). Cao et al. in their study in 2018, an AuE-based nanostructured electrochemical biosensor was developed for the sensitive, selective, high accuracy, and precise determination of chloramphenicol (Cao et al., 2018). Aptamer-modified magnetic nanoparticles (MNPs-Apt) were coated on the AuE surface. Surface morphology produced by scanning electron microscope (SEM), Fourier transform infrared spectrometer (FTIR), and zeta potentials were elucidated. Then, electrochemical measurements were made with cyclic voltammetry (CV), and they determined the working range as 5
10,000 μg L21. They also calculated the LOD value as 1 μg L21. In addition, the interference effects of some organic substances were examined to examine the selectivity of the method they developed, and they found that they had less than 12% effect on the chloramphenicol determination. Finally, chloramphenicol determination was successfully performed with MNPs/Apt/AuE biosensor in real samples such as milk and water (Table 16.3 and 16.4). In their research, Neda Jazini and colleagues developed a composite nanostructured biosensor for the determination of acetaminophen drug substance known as an anti-inflammatory, analgesic, and antipyretic medicine (Jazini et al., 2020). The carbon paste electrode (CPE) surface was coated with deoxyribonucleic acid (ds-DNA) and chitosan nanocomposites/TiO2 nanoparticles as a double layer. Here, TiO2 nanoparticles have developed a rapid, sensitive, and inexpensive sensor, in which polymers and biological materials are used together. Then, with differential pulse voltammetry (DPV), they determined the dynamic working range of

Table 16.1 Metal-based nanostructured biosensors. Analytes

Biosensor

Technique

Linear range (μM)

LOD (nM)

LOQ (nM)

Interference

Sample

References

Amoxicillin

TiO2/CMK-3/ AuNPs/Nafion/ graphite electrode

CV

0.5
2.5; 2.5
133.0

300




Penicillinase@CHIT/ PtNPs-ZnO/ ZnHCF/FTO electrode MnO2@NiFe2O4/ GCE

CV

0.1
750

100




Pharmaceutical product, mineral, and environmental water Gastric lavage

Pollap et al. (2018)

Cefepime

CV

25
250







Mg21, Ca21, Na1, K1, HCO32, NO32, SO422, Cl2, glucose and ascorbic acid, ciprofloxacin, sulfamethoxazole Amphetamine, ketamine, ephedrine, thebaine, methamphetamine, codeine





Chloramphenicol

MNPs/Apt/AuE

CV

0.0154
30.94

3.094




Milk and water

Ethambutol

GO/Ag-NPs/ CYP2D6/GCE CS-Au NPs/PBPB/ GCE

CV

200
1200

0.0067




Tetracycline, kanamycin, oxytetracycline, doxycycline


Sakthivel et al. (2019) Cao et al. (2018)

CV

50
300










GO/Ag-NPs/ CYP2D6/GCE Ni-ZrO2/MWCNT/ GCE

CV

100
600

0.0029







DPV

0.001
500

2.9

Chitosan/TiNPsDNA/CPE

DPV

0.5
300

140

Chlorambucil

Flutamide

Pyrazinamide 5-Aminosalicylic acid

Acetaminophen




Na1, K1, vanillin, sulfasalazine, dopamine, aspirin, uric acid, acetaminophen, hydroquinone, catechol Ca21, Mg21, Na1, Al31, Cl2, uric acid, folic acid, ascorbic acid, dopamine

Real human sample


Real human sample Human blood, human urine, and tablet

Serum and pill

Chauhan et al. (2021)

Ajayi et al. (2020) Mutharani et al. (2019) Ajayi et al. (2020) Nataraj et al. (2021)

Jazini et al. (2020)

Ca21, K1, Cl2, uric acid, folic acid, citrate, epinephrine, l-tyrosine, saccharose, dopamine, ascorbic acid NaCl, KNO3, tryptophan, cysteine, uric acid, ascorbic acid


Amsacrine

ds-DNA/Eu31doped NiO/CPE

DPV

0.1 3 103
1 3 105

5 3 104

Carbamazepine

Fe3O4/PANI
Cu (II)/CILE

DPV

0.05
30

32




Celecoxib

AgNPs-ChCl-GO/ CPE ds-DNA/PPy/FL-Pt/ NiCo2O4/PGE

DPV

0.0096
0.74

2.51

6.58

DPV

0.018
200

4.0




Chloramphenicol

GO/ZnO/GCE

DPV

0.2
124

10




Clonazepam

CuNPs/PSi/SPCE

DPV

0.05
7.6

15




Diclofenac

CNT/GO/Fe3O4/ GCE

DPV

1 3 1024
13 3 1024

33 3 1023




K1, Cl2, Zn21, sucrose, tyrosine, ascorbic acid lysine, methionine, uric acid, dopamine, norepinephrine, phenylalanine, alanine 21 Ca , Ba21, Cu21, Fe21, Ni21, Co21, K1, NO32, I2, Br2, Cl2, 4-NB, 4-NP, 4-NA, 4-AP K1, Na1, Mg21, Fe31, Cl2, SO422, NO32, HCO32, ascorbic acid, citric acid, uric acid, glucose, lactose, sucrose Glucose, ethanol, tryptophan

Donepezil

CoFe2O4 NPs/CPE

DPV

5.0
20










Pharmaceutical form and urine

Doxorubicin

ds-DNA/PtNPs/ AgNPs/SPE

DPV

0.184
1.839







Guanine, adenine




Chlorambucil

Urine and serum

Akbari Javar et al. (2020)

Blood serum, and urine

Fatahi et al. (2020)

Human plasma

Parsaee et al. (2018) MahmoudiMoghaddam and GarkaniNejad (2022a) Sebastian et al. (2019)

Serum, urine, pharmaceutical formulation

Honey, milk, eye drop

Human blood plasma and pharmaceutical tablets

Allahnouri et al. (2019)

Pharmaceutical form

Azadbakht and Derikvandi (2018) Ramadan et al. (2018) Karadurmus et al. (2021) (Continued)

Table 16.1 (Continued) Analytes

Biosensor

Technique

Linear range (μM)

LOD (nM)

LOQ (nM)

Interference

Sample

References

Epirubicin

ds-DNA/PtNPs/ AgNPs/SPE

DPV

0.55
2.39







Guanine, adenine




Ethambutol

HRP/ZnONPs/ rGO/GCE

DPV

2
32

21.4

671.3

Pharmaceutical form

Etoposide

DNA/GO/ CoFe2O4/ZnAlLDH/FTO bioelectrode

DPV

0.2
10

1.0




Flutamide

Bi2O3/h-BN/SPCE

DPV

0.04
87

9.0




Idarubicin

dsDNA/PP/ La2O3NP@SF-L Cu2S NS/PGE

DPV

0.01
500.0

1.3




Indomethacin

ZnFe2O4/ MWCNTs/CPE

DPV

5.0
200

500




Ca21, K1, Cl2, Ag1, Br2, Na1, SO322, glucose, ascorbic acid, sucrose Na1, K1, Ca21, Mg21, Fe21, uric acid, glucose, ascorbic acid, citric acid, methionine, valine, caffeine, ibuprofen, acetaminophen 1 Na , Zn21, dopamine, urea, uric acid, ascorbic acid, 4nitrophenol, nitrobenzene, methyl parathion, fenitrothion Br2, Cl2, Li1, Mg21, uric acid, glucose, sucrose, citrate, alanine, epinephrine, ascorbic acid, dopamine, folic acid, Ltyrosine


Karadurmus et al. (2021) Chokkareddy et al. (2018) Vajedi and Dehghani (2020)

Isoniazid

ds-DNA/Carbon/ La31/CuO/CPE

DPV

1.0
165.0

35




Na 1 , Ca21, Br2, methionine, phenylalanine, dopamine, epinephrine, uric acid, alanine, ascorbic acid

Human blood plasma, serum, and urine

River water

Kokulnathan et al. (2021)

Human blood serum

Foroughi and Jahani (2022)




Hassannezhad et al. (2019) MahmoudiMoghaddam and Garkani-

Pharmaceutical dosage form, urine

L-tyrosine

Cu-1/GCE

DPV

10
90

5.822




D-Met, L-His, L-Ser, L-Val, L-




Leu, L-Met, L-Phe, D-Cys, L-Cys, L-Ala Meloxicam

AuNPs/ChCl/GO/ CPE ZnFe2O4/ MWCNTs/CPE

DPV DPV

0.6
90

130

Monensin

AuNPs/Zn/Ni-ZIF8
800@graphene composites/GCE

DPV

3.72 3 1024
0.149

0.16

Nilutamide

Co-Ni-Cu-MOF/ NF

DPV

0.5
900.0

0.48

Penicillin G Sodium

PenX-COOHCo@C/PMB/ GCE

DPV

1.79




Prednisone

ds-DNA/AgNPs/P (GBHA)/GCE

DPV

2.80 3 10
4 to 0.028; 0.028
0.28 2.78
139.49

836.98




Rifampicin

IL-f-TiO2NPs/ MWCNTs/GCE

DPV

0.015
2.8

21.8

312.0

Metoclopramide

0.009
0.85

1.008

3.36




Human plasma 21




1

1

SO42
,

Cu , K , Na , NO3 2 , Cl2, glucose, glutamine, lysine, citric acid, ascorbic acid, uric acid, dopamine Maduramycin, dinitolmide, nicarbazin, sulfadiazine, sulfamethoxazole, sulfathiazole, olaquindox, tetracycline, clenbuterol NO3-, SO42-, CO32-, glucose, sucrose, fructose, ascorbic acid, urea, dopamine, citric acid


L-ascorbic acid, urea, dopamine, uric acid, Lcysteine, folic acid, glucose, caffeic acid, citric acid, acetylsalicylic acid, naproxen, flurbiprofen, paracetamol


Human serum, urine, pharmaceutical products

Nejad (2022b) Wu et al. (2020) Bahrani et al. (2018) Hassannezhad et al. (2019)

Milk

Hu, Hu, et al. (2019)

Tablet, human serum

Akhter et al. (2021)

Milk

Xiu et al. (2020)

Human serum

Aydogdu Tig et al. (2019)




Chokkareddy and Redhi (2022) (Continued)

Table 16.1 (Continued) Analytes

Biosensor

Technique

Linear range (μM)

LOD (nM)

LOQ (nM)

Interference

Sample

References

Rivastigmine

γ-FeOOH/ N@CCNS/PAS/ PGE Cyt c/ZnONPs/ MWCNTs/GCE

DPV

0.003
0.09

0.9




Guanine and adenine

Capsule and human serum

DPV

0.02
2.22.8

56.2




Pharmaceutical form

Mohamed et al. (2019) Chokkareddy et al. (2021)

Streptomycin

Sulfamethoxazole

GR-ZnO/GCE

DPV

1
40; 40
170

400




Tamoxifen

DPV

0.0002
0.04

0.132




Tamoxifen

CeO2
MWCNT/ CCE Ni(OH)2
NaY/CPE

DPV

2.0
110.0

650




NaCl, AgNO3, CaCl2, NaSO4, sucrose, glucose, urea, ascorbic acid, dopamine, citric acid Na1, K1, Ca21, Mg21, Fe31, Cl2, NO32, SO422, urea, glucose, ascorbic acid Ascorbic acid, uric acid, dopamine


Tamoxifen

VO2/V2O5/GCE

DPV

0
12.15

390





1

2

Water, serum, urine

Yue et al. (2020)

Human blood serum


Shafaei et al. (2021) Hassasi and Hassaninejad-Darzi (2022) Khudaish (2020) Jahandari et al. (2019)

Pharmaceutical form Blood serum, urine, and pharmaceutical dosage form Milk and honey

Temozolomide

ds-DNA/Au-NPs/ PGE

DPV

0.005
45.0

1.0




Mg , Li , Br , glucose, alanine, uric acid

Tetracycline

MCS@UiO-66NH2/Lac/ABTS/ CHIT/GCE DNA/AuNPs-GSH/ cysteine/AuE GR-ZnO/GCE

DPV

1.0
60

894




Oxytetracycline, tetracycline, streptomycin sulfate

DPV

0.0001
0.10













DPV

1
10; 10
170

300




Water, serum, urine

DPV

0.005
0.08

1.89




Na1, K1, Ca21, Mg21, Fe31, Cl2, NO32, SO422, urea, glucose, ascorbic acid Dopamine, serotonin, uric acid

Maatouk et al. (2022) Yue et al. (2020)

Urine, serum, and pharmaceutical form

Kummari et al. (2022)

Thioguanine Trimethoprim

Valacyclovir

AuNPs/poly-AHP/ CPE

21

Zhong et al. (2021)

Table 16.2 Carbon nanostructured electrochemical biosensors. Analytes

Biosensor

Technique

5-ASA

TiO2 sol
gel film/ PGE

Amperometry 0.1
1

Amoxicillin Donepezil Flutamide

Guaifenesin

Linear range (μM)

LOD (nM)

LOQ (nM)

3300

10000

Gr-AuNP-laccasse/ Amperometry 0.425
292 GCE Acetylcholinesterase/ Amperometry to 10;0.001
1 GCE rGO/CuO/GCE Amperometry 0.005
71.32

425







0.050.10




1.0




Ni-SiO2/MLG/ SPCE

5.7




Ascorbic acid and uric acid Zn21, K1, nilutamide, 4nitrophenol, nitrobenzene, ascorbic acid, catechol, serotonin, histamine, metronidazole, hydroquinone, tryptophan, acetaminophen, lysine Na1, K1, Cl2, NO32, SO422, uric acid, ascorbic acid, dopamine, catechol, resorcinol, hydroquinone, 4aminophenol, nitrophenol, flutamide, chloramphenicol

Amperometry 0.1
317.5

Interference

Sample

References

Pharmaceutical Gomes da formulations Rocha et al. (2021)
Osikoya et al. (2021) Bovine serum Shamagsumova albumin et al. (2019) Human serum Sakthinathan and urine et al. (2019)

Pharmaceutical forms

Huang et al. (2021)

(Continued)

Table 16.2 (Continued) Analytes

Biosensor

Technique

Isoniazid

Nafion-OMC/GCE

Maduramicin

Rivastigmine

Linear range (μM)

LOD (nM)

LOQ (nM)

Interference

Sample

References

Amperometry 0.1
370

83.5




Amperometry 1.07 3 1024
0.05

0.048




Human urine and blood serum Egg

Yan et al. (2011)

Hemin@MOFs/ AuPt-Ab2HRP/HRP/ GCE

BuChE/GCE

Amperometry 50 3 1026
2 3 1023

14.7 3 1023


Uric acid, ascorbic acid, dopamine, glucose Monensin, dinitolmide, nicarbazin, sulfathiazole, sulfadiazine, olaquindox





Ozcelikay et al. (2019) Zhang and He (2021)





2.50










0.0
1.0

230.0

-s




Human serum

CV

0.5
2.5; 2.5
133.0

300




Pharmaceutical product, mineral, and environmental water

CV

0
211.62

8.634 3 103 26.241 3 103

Mg21, Ca21, Na1, K1, HCO32, NO32, SO422, Cl2, glucose and ascorbic acid, ciprofloxacin, sulfamethoxazole Valproic acid and phenytoin

Amperometry 1
10

0.07

Tamoxifen Tamoxifen

VO2/V2O5/GCE Ni(OH)2
NaY/ CPE

Amperometry 50
250 Amperometry 3000
8910





Valacyclovir

AuNPs/Poly-AHP/ CPE MWCNTs/ CYP3A4/SPE TiO2/CMK-3/ AuNPs/Nafion/ graphite electrode

Amperometry 0.0025
0.22 CV

MIPEDOT/GCE

Carbamazepine

21

Urine

TiO2-GO/CPE

Amoxicillin

21

K , Mg , Ca , CO322, HCO3 ̶ , PO43 ̶ , SO422, glucose, ammonia, creatinine, uric acid, urea



Sufentanil

Abiraterone

1








Hu, Wang, et al. (2019)

Khudaish (2020) Hassasi and Hassaninejad-Darzi (2022) Kummari et al. (2022) Aliakbarinodehi et al. (2018) Pollap et al. (2018)

Hammoud et al. (2022)

Chlorambucil Chloroquine

Ethambutol Flutamide Flutamide

MnO2@NiFe2O4/ GCE rGO@WS2/GCE

GO/AgNPs/ CYP2D6/GCE CS-AuNPs/PBPB/ GCE LCO/HNT/GCE

CV

25
250













CV

0.5
82.4

40







CV

200
1200

0.0067







CV

50
300










Human blood serum, pharmaceutical formulation Real human sample


CV

30
180











Real human sample


CV

100
600

0.0029







Quinacrine

GO/AgNPs/ CYP2D6/GCE DNA/Cdots/GCE

CV













Rifampicin

SPIONs/CNT

CV




1178







5-ASA

Ni-ZrO2/ MWCNT/GCE

DPV

0.001
500

2.9




Acetaminophen

Sn@C/GCE

DPV

0.2
30; 30
100

20




Acetaminophen

Chitosan/TiNPsDNA/CPE

DPV

0.5
300

140




Na1, K1, vanillin, sulfasalazine, dopamine, aspirin, uric acid, Acetaminophen, hydroquinone, catechol KCl, NaCl, glucose, sucrose, citric acid, glycine 21 Ca , Mg21, Na1, Al31, Cl2, uric acid, folic acid, ascorbic acid, dopamine

Pyrazinamide

Pharmaceutical formulation Human blood, human urine, and tablet

Tablet and human serum Serum and pill

Sakthivel et al. (2019) Srivastava et al. (2019)

Ajayi et al. (2020) Mutharani et al. (2019) Suvina et al. (2020) Ajayi et al. (2020) Oliveira et al. (2019) Bano et al. (2020) Nataraj et al. (2021)

Qin et al. (2022) Jazini et al. (2020)

(Continued)

Table 16.2 (Continued) Analytes

Biosensor

Technique

Linear range (μM) 21

LOD (nM)

LOQ (nM)

Interference

Sample

References







Pharmaceutical form Urine and serum

Cesme et al. (2019) Akbari Javar et al. (2020)

Blood serum, and urine

Fatahi et al. (2020)

Human plasma

Parsaee et al. (2018) MahmoudiMoghaddam and GarkaniNejad (2022a)

Amisulpride

dsDNA/PGE

DPV

1
10 μg mL

Amsacrine

ds-DNA/Eu31doped NiO/ CPE

DPV

0.1
100.0 mM

0.46 μg mL21 0.05 mM

Carbamazepine

Fe3O4/PANI
Cu (II)/CILE

DPV

0.05
30

32




Celecoxib

AgNPs-ChCl-GO/ CPE ds-DNA/PPy/FLPt/NiCo2O4/ PGE

DPV

0.0096
0.74

2.51

6.58

Chlorambucil

Chlorambucil

MnO2@NiFe2O4/ GCE

DPV

0.018
200

4.0




DPV

0.025
150

4.68




Ca21, K1, Cl2, uric acid, folic acid, citrate, epinephrine, ltyrosine, saccharose, dopamine, ascorbic acid NaCl, KNO3, tryptophan, cysteine, uric acid, ascorbic acid.
1

2

21

K , Cl , Zn , sucrose, tyrosine, ascorbic acid lysine, methionine, uric acid, dopamine, norepinephrine, phenylalanine, alanine Dopamine, uric acid, glucose, mercury, diphenylamine, sodium, potassium, nitrite, diuron

Serum, urine, pharmaceutical formulation

Tablet, human urine, drinking water

Sakthivel et al. (2019)

Chloramphenicol

GO/ZnO/GCE

DPV

0.2
124

10




Chloroquine

rGO@WS2/GCE

DPV

0.5
82.4

40




Clonazepam

CuNPs/PSi/SPCE

DPV

0.05
7.6

15




Daunorubicin

CHIT/PGE

DPV

4.73
18.95

600




Ca21, Ba21, Cu21, Fe21, Ni21, Co21, K1, NO32, I2, Br2, Cl2, 4-NB, 4NP, 4-NA, 4-AP D-glucose, creatine hydrate, Lascorbic acid, uric acid, L-cysteine, urea 1 K , Na1, Mg21, Fe31, Cl2, SO422, NO32, HCO32, ascorbic acid, citric acid, uric acid, glucose, lactose, sucrose


Daunorubicin

LVN-PGE

DPV

18.95
75.82










24

990.938 24

23

Honey, milk, eye drop

Sebastian et al. (2019)

Human blood serum, pharmaceutical formulation Human blood plasma, and pharmaceutical tablets

Srivastava et al. (2019)




Congur et al. (2019) Congur et al. (2021) Azadbakht and Derikvandi (2018) Karimi-Maleh et al. (2018)

Diclofenac

CNT/GO/Fe3O4/ GCE

DPV

1 3 10
13 3 10

33 3 10




Glucose, ethanol, tryptophan

Pharmaceutical form

Didanosine

PPy/rGO/PGE

DPV

0.02
50.0

8




Tablet and urine

Donepezil

CoFe2O4 NPs/CPE

DPV

5.0
20







K1, Cl2, Na1, Br2, glucose, sucrose, uric acid, methionine


Doxorubicin

ds-DNA/PtNPs/ AgNPs/SPE

DPV

0.184
1.839







Guanine, adenine

Pharmaceutical form and urine -

Allahnouri et al. (2019)

Ramadan et al. (2018) Karadurmus et al. (2021) (Continued)

Table 16.2 (Continued) Biosensor

Technique

Linear range (μM)

LOD (nM)

LOQ (nM)

Interference

Sample

References

Epirubicin

ds-DNA/PtNPs/ AgNPs/SPE PP/NrG/ds-DNA/ PGE

DPV

0.55
2.39







Guanine, adenine




DPV

0.004
55.0

1.0




Urine

Ethambutol

HRP/ZnONPs/ rGO/GCE

DPV

2
32

21.4

671.3

Flutamide

Bi2O3/h-BN/SPCE

DPV

0.04
87

9.0




Flutamide

CS-AuNPs/PBPB/ GCE

DPV

0.01
1245

4.8

Flutamide

LCO/HNT/GCE

DPV

0.009
473

2.0

K1, Cl2,Na1, Br2, Mg21, tryptophan, tyrosine, alanine, glucose 21 Ca , K1, Cl2, Ag1, Br2, Na1, SO322, glucose, ascorbic acid, sucrose 1 Na , Zn21, dopamine, urea, uric acid, ascorbic acid, 4nitrophenol, nitrobenzene, methyl parathion, fenitrothion 2 Br , K1, Cl2, glucose, uric acid, ascorbic acid, nitrophenol, chloramphenicol, metronidazole Nilutamide, metronidazole, chloramphenicol, nitro phenol, uric acid, glucose, acetaminophen, histamine, serotonin, nitrobenzene

Karadurmus et al. (2021) Khodadadi et al. (2019)

Epirubicin




Pharmaceutical form

Chokkareddy et al. (2018)

River water

Kokulnathan et al. (2021)

Human urine and human blood serum

Mutharani et al. (2019)

Water

Suvina et al. (2020)

.

Analytes

Flutamide

dsDNA/MCM41/ SPE ZMNS/GCE

DPV

0.7
10

100.0




DPV

0.1
73; 111
1026

3.3




166.6

Human serum

Flutamide

Exfoliated g-C3N4/ GCE

DPV

2
1208

50.0

Galantamine

AChE/L-Ni-BPY/ DpAu/GCE

DPV

1 3 1026
1 3 1023

0.31 3 1023


Ibrutinib

ds-DNA/GCE

DPV

2.0
20.0







Ca21, Zn21, Fe21, Mg21, Na1, K1, Ni21, Cl2, SO422, I2, NO32, chloramphenicol, nitrobenzene, nitro toluene, 4nitrophenol, catechol, dopamine, uric acid, glucose, galactose, sucrose, ascorbic acid 21 Mg , Fe21, caffeine, fructose, glucose, uric acid NO3
, SO422, Cu21, Fe31, Hg21 Zn21, memantine hydrochloride, piracetam, nicergoline, and glucose


Idarubicin

ds-DNA/PtNPs/ AgNPs/SPE

DPV

0.2
2.01







Guanine, adenine

Flutamide




Raoof et al. (2020) Rajakumaran et al. (2020)

River water

Kesavan and Chen (2020)

Human serum

Zhang, and Qiao, Cai, et al. (2021)




Bilge et al. (2022) Karadurmus et al. (2021)




(Continued)

Table 16.2 (Continued) Analytes

Biosensor

Technique

Linear range (μM)

LOD (nM)

LOQ (nM)

Interference

Sample

References

Idarubicin

ds-DNA/PP/ La2O3NP@SF-L Cu2S NS/PGE

DPV

0.01
500.0

1.3




Human blood serum

Foroughi and Jahani (2022)

Indomethacin

ZnFe2O4/ MWCNT/CPE poly(CTABMWCNTs)/ PGE ds-DNA/Carbon/ La31/CuO/CPE

DPV

5.0
200

500




Br2, Cl2, Li1, Mg21, uric acid, glucose, sucrose, citrate, alanine, epinephrine, ascorbic acid, dopamine, folic acid, L-tyrosine





DPV

3.40
852.25

1755







Serum

Hassannezhad et al. (2019) Bolat (2020)

DPV

1.0
165.0

35




Pharmaceutical dosage form, urine

MahmoudiMoghaddam and GarkaniNejad (2022b)

KAN/BSA/poly-C DNA/GO/ MWCNT/GCE Cu-1/GCE

DPV

0.05 3 1026
0.1

47.6 3 1026


Na 1 , Ca21, Br2, methionine, phenylalanine, dopamine, epinephrine, uric acid, alanine, ascorbic acid AMX, CAP, STR, and OTC

Milk

He et al. (2020)

DPV

0.01
0.09 mM

5.822




Wu et al. (2020)

Bahrani et al. (2018) Machini et al. (2019)

Irinotecan

Isoniazid

Kanamycin

L-tyrosine




D-Met, L-His, L-Ser, L-Val, L-Leu, L-

Met, L-Phe, DCys, L-Cys, L-Ala Meloxicam Metformin

AuNPs/ChCl/GO/ CPE CB-DHP/GCE

DPV

0.009
0.85

1.008

3.36




Human plasma

DPV

2.0
10.0

630

2090




Wastewater

Methamphetamine Apta-4/GE

DPV

6.7 3 1024
0.35

3.13

Metoclopramide

ZnFe2O4/ MWCNTs/CPE

DPV

0.6
90

130

Miltefosine

ds-DNA/GCE

DPV










Monensin

AuNPs/ Zn/Ni-ZIF8
800 @graphene composites/GCE

DPV

3.72 3 1024
0.149

0.16




Nivolumab

dsDNA/GCE

DPV










Penicillin G Sodium

PenX-COOHCo@C/PMB/ GCE ds-DNA/AgNPs/P (GBHA)/GCE

DPV

2.80 3 10
4
0.028;0.028
0.28 1.79

DPV

2.78
139.49

Prednisone

836.98




Amphetamine, codeine, morphine, 3hydroxybutyl metabolite 21 Cu , K1, Na1, SO422, NO32, Cl2, glucose, glutamine, lysine, citric acid, ascorbic acid, uric acid, dopamine


Maduramycin, dinitolmide, nicarbazin, sulfadiazine, sulfamethoxazole, sulfathiazole, olaquindox, tetracycline, clenbuterol


Urine

Bor et al. (2022)

Human serum, urine, pharmaceutical products

Hassannezhad et al. (2019)




Machini and OliveiraBrett (2018) Hu, Hu, et al. (2019)

Milk


Milk




L-ascorbic acid, urea, dopamine, uric acid, L-cysteine, folic acid, glucose, caffeic acid, citric acid, acetylsalicylic acid, naproxen, flurbiprofen, paracetamol

Human serum

Machini et al. (2019) Xiu et al. (2020) Aydogdu Tig et al. (2019)

(Continued)

Table 16.2 (Continued) Analytes

Biosensor

Technique

Linear range (μM)

LOD (nM)

LOQ (nM)

Interference

Sample

References

Quinacrine

DNA/Cdots/GCE

DPV
















Rifampicin

IL-f-TiO2NPs/ MWCNTs/GCE

DPV

0.015
2.8

21.8

312.0







Rivastigmine

γ-FeOOH/ N@CCNS/ PAS/PGE Cyt c/ZnONPs/ MWCNTs/GCE

DPV

0.003
0.09

0.9




Guanine and adenine

DPV

0.02
2.22.8

56.2




Sulfamethoxazole

GR-ZnO/GCE

DPV

1
40; 40
170

400




Tamoxifen

CeO2
MWCNT/ CCE Ni(OH)2
NaY/ CPE

DPV

0.0002
0.04

0.132




DPV

2.0
110.0

650




NaCl, AgNO3, CaCl2, NaSO4, sucrose, glucose, urea, ascorbic acid, dopamine, citric acid Na1, K1, Ca21, Mg21, Fe31, Cl2, NO32, SO422, urea, glucose, ascorbic acid Ascorbic acid, uric acid, dopamine


Capsule and human serum Pharmaceutical form

Oliveira et al. (2019) Chokkareddy and Redhi (2022) Mohamed et al. (2019)

Streptomycin

Tamoxifen

Tamoxifen

VO2/V2O5/GCE

DPV

0
12.15

390







Temozolomide

ds-DNA/Au-NPs/ PGE

DPV

0.005
45.0

1.0




Mg21, Li1, Br2, glucose, alanine, uric acid

Chokkareddy et al. (2021)

Water, serum, urine

Yue et al. (2020)

Human blood serum


Shafaei et al. (2021) Hassasi and Hassaninejad-Darzi (2022) Khudaish (2020)

Pharmaceutical form Blood serum, urine, and pharmaceutical dosage form

Jahandari et al. (2019)

MCS@UiO-66NH2/Lac/ ABTS/CHIT/ GCE ds-DNA/GQD/IL/ CPE

DPV

1.0
60

894




DPV

0.35
100.0

100




Trimethoprim

GR-ZnO/GCE

DPV

1
10; 10
170

300




Valacyclovir

AuNPs/Poly-AHP/ CPE

DPV

0.005
0.08

1.89




Vardenafil

CM-03/GCE

DPV

1.0 3 1024
10.0

0.0963

0.089

Dasatinib

Au-NPs/rGO/dsDNA/GCE

EIS

0.03
5.5

9.0




Diclofenac

DCF/Aptamer/ EDC-NHS/fMWCNTs/GCE DNA/CPRCP450/ Ch/MWCNTs/ GCE

EIS

0.25 3 1026
1 3 1026; 3 1026
500 3 1023

1.62 3 1024


EIS

0.1
150

500

Tetracycline

Topotecan

Doxorubicin




Oxytetracycline, tetracycline, streptomycin sulfate


Milk and honey

Zhong et al. (2021)

Urine and serum

Na1, K1, Ca21, Mg21, Fe31, Cl2, NO32, SO422, urea, glucose, ascorbic acid Dopamine, serotonin, uric acid

Water, serum, urine

MahmoudiMoghaddam et al. (2019) Yue et al. (2020)

NaCl, CaCl2, KCl, ascorbic acid,, dopamine 21 Ca , Na1, F2, niclosamide, sulfonamide, amoxicillin, ascorbic acid, glucose, phenylalanine β-Estradiol, paracetamol


Urine, serum, and pharmaceutical form Urine and serum

Kummari et al. (2022)

Tablet, urine

TahernejadJavazmi et al. (2018)




Zou et al. (2022)




Zangeneh et al. (2019)

Bilge et al. (2020)

(Continued)

Table 16.2 (Continued) Analytes

Biosensor

Technique

Linear range (μM) 210

LOQ (nM)

Interference

Sample

References

3.05 3 10




Streptomycin, sulfadiazine, penicillin G Oxycycline, oxytetracycline, diclofenac

Milk

MohammadRazdari et al. (2020) Benvidi et al. (2018)

28

Tetracycline

Aptamer/AuNPs/ rGO/PGE

EIS

1.0 3 10

Tetracycline

PGAMWCNT/ GCE

EIS

1.0 3 10210
1.0

3.7 3 1028




Triclosan

NA-DNA/IrO2 NPs/MWCNTsGr/GCE MWCNT-LAC/ GCE QDs-P6LCPEDOT:PSS/ GCE

EIS

0.01
10.0

1.2

3.7

SWV

10
320

700




SWV

0.90
69

50




Amoxicillin

CB/DPH/GCE

SWV

2.0
18.8

120




Atropine

SWCNT/Chit/ GCE

SWV

0.1
150

16.5

54.9

Carbamazepine

MIPEDOT-GCE

SWV

1.0 3 102
2.0 3 103

0.980 3 106 2.97 3 106

Ethambutol

NiNPs/ERGO/ GCE

SWV

0.05
100

23.0

Acetaminophen Amoxicillin


1.0

LOD (nM)

75.0

Honey

Toothpaste, Jalalvand (2022) handwashing Ascorbic acid, uric Pharmaceutical Sousa Pereira acid, formulations et al. (2020) Drug, milk, Uric acid, Wong et al. and urine paracetamol, urea, (2020) ascorbic acid, caffeine Urine and Na1, K1, Mg21, Deroco et al. water Ca21, Pb21, (2018) Cd21, Ni21, NO32, Cl2, HCO32, SO422, CO322, PO432, glucose, albümin, vermicompost, humic acid Datura Glucose, uric acid, Mane et al. stramonium, ascorbic acid, (2018) pharmparacetamol, xanthine, aceutical hypoxanthine form

Hammoud et al. (2021) 21 21 1 Pharmaceutical Mekassa et al. Ca , Mg , K , 22 22 form, urine SO4 , CO3 , (2019) Cl2, L-ascorbic acid, glucose, urea, citric acid, isoniazid, acetaminophen

Lamotrigine

Ds-DNA/GCE

SWV

1.0
160

210

700







Methotrexate

f-CNTPE

SWV

0.1
1.5

2.9




Ascorbic acid, uric acid, dopamine, serotonin

Nimesulide

CB/DPH/GCE

SWV

2.0
18.8

16




RR-ethambutol

CD/CuMOF/ CNF/GCE

SWV

0.1
100

31




Na1, K1, Mg21, Ca21, Pb21, Cd21, Ni21, NO32, Cl2, HCO32, SO422, CO322, PO432, glucose, albümin, vermicompost, humic acid


Pharmaceutical form, artificial urine and human blood serum Urine and water

SS-ethambutol

CD/CuMOF/ CNF/GCE

SWV

0.5
250

85.2




Tenofovir

ds-DNA/BDDE

SWV

5.0
100

560

1900

K1, Ca21, NO321, NH41, Cl2 or Mg21, pyrazinamide, vitamin-6, isoniazid, rifampicin, ascorbic acid, caffeine, glucose


Morawska et al. (2020) Kummari et al. (2019)

Deroco et al. (2018)

Racemic mixture, blood, urine, and pharmaceutical dosage form Racemic mixture, blood, urine, and pharmaceutical dosage form

Upadhyay et al. (2020)




Morawska et al. (2018)

Upadhyay et al. (2020)

Table 16.3 Polymer-supported nanostructured biosensors. Analytes

Biosensor

Technique

Linear range (μM)

LOD (nM)

LOQ (nM)

Interference 1

1

HCO32,

NO32,

Sample

References

Pharmaceutical product, mineral and environmental water


Pollap et al. (2018)

Amoxicillin

TiO2/CMK-3/ AuNPs/Nafion/ graphite electrode

CV

0.5
2.5; 2.5
133.0

300




Mg , Ca , Na , K , Cl2, glucose and ascorbic acid, ciprofloxacin, sulfamethoxazole

Carbamazepine

MIPEDOT/GCE

CV

0
211.62

8.634 3 103

26.241 3 103

Valproic acid and phenytoin

Cefepime

Penicillinase@CHIT/ PtNPs-ZnO/ ZnHCF/FTO electrode Chitosan/TiNPsDNA/CPE Fe3O4/PANI
Cu (II)/CILE ds-DNA/PPy/FL-Pt/ NiCo2O4/PGE

CV

0.1
750

100




Amphetamine, ketamine, ephedrine, thebaine, methamphetamine, codeine

Gastric lavage

DPV

0.5
300

140




Serum and pill

DPV

0.05
30

32




DPV

0.018
200

4.0




Ca21, Mg21, Na1, Al31, Cl2, uric acid, folic acid, ascorbic acid, dopamine NaCl, KNO3, tryptophan, cysteine, uric acid, ascorbic acid K1, Cl2, Zn21, sucrose, tyrosine, ascorbic acid, lysine, methionine, uric acid, dopamine, norepinephrine, phenylalanine, alanine

Acetaminophen Carbamazepine Chlorambucil

21

21

22

SO4 ,

Blood serum, and urine Serum, urine, pharmaceutical formulation

Daunorubicin

CHIT/PGE

DPV

4.73
18.95

600










Daunorubicin

LVN-PGE

DPV

18.95
75.82

990.938










Didanosine

PPy/rGO/PGE

DPV

0.02
50.0

8




Tablet and urine

Epirubicin

ds-DNA/PtNPs/ AgNPs/SPE PP/NrG/ds-DNA/ PGE CS-Au NPs/PBPB/ GCE

DPV

0.55
2.39







K1, Cl2, Na1, Br2, glucose, sucrose, uric acid, methionine Guanine, adenine

DPV

0.004
55.0

1.0




DPV

0.01
1245

4.8

Epirubicin Flutamide

K1, Cl2, Na1, Br2, Mg21, tryptophan, tyrosine, alanine, glucose Br2, K1, Cl2, glucose, uric acid, ascorbic acid, nitro phenol, chloramphenicol, metronidazole


Urine Human urine and human blood serum

Hammoud et al. (2022) Chauhan et al. (2021)

Jazini et al. (2020) Fatahi et al. (2020) MahmoudiMoghaddam and GarkaniNejad (2022a) Congur et al. (2019) Congur et al. (2021) Karimi-Maleh et al. (2018) Karadurmus et al. (2021) Khodadadi et al. (2019) Mutharani et al. (2019)

Idarubicin

dsDNA/PP/ La2O3NP@SF-L Cu2S NS/PGE

DPV

0.01
500.0

1.3

Irinotecan

poly(CTABMWCNTs)/PGE KAN/BSA/poly-C DNA/GO/ MWCNTs/GCE ds-DNA/AgNPs/P (GBHA)/GCE

DPV

3.40
852.25

1755

γ-FeOOH/ N@CCNS/PAS/ PGE MCS@UiO-66NH2/Lac/ ABTS/CHIT/ GCE AuNPs/Poly-AHP/ CPE

Kanamycin

Prednisone

Rivastigmine

Tetracycline

Valacyclovir

26

Human blood serum

Foroughi and Jahani (2022)




Br2, Cl2, Li1, Mg21, uric acid, glucose, sucrose, citrate, alanine, epinephrine, ascorbic acid, dopamine, folic acid, Ltyrosine


Serum

Bolat (2020)




26

DPV

0.05 3 10
0.1

47.6 3 10




AMX, CAP, STR, and OTC

Milk

He et al. (2020)

DPV

2.78
139.49

836.98




Human serum

Aydogdu Tig et al. (2019)

DPV

0.003
0.09

0.9




L-ascorbic acid, urea, dopamine, uric acid, Lcysteine, folic acid, glucose, caffeic acid, citric acid, acetylsalicylic acid, naproxen, flurbiprofen, paracetamol Guanine and adenine

Capsule and human serum

Mohamed et al. (2019)

DPV

1.0
60

894




Oxytetracycline, tetracycline, streptomycin sulfate

Milk and honey

Zhong et al. (2021)

DPV

0.005
0.08

1.89




Dopamine, serotonin, uric acid

Kummari et al. (2022)

L-alanine, D,L-phenylalanine,

Urine, serum and pharmaceutical form Milk, human serum, and river water Drug, milk, and urine Urine and water

Datura stramonium, pharmaceutical form

Mane et al. (2018)

Ampicillin

POPs/AuE

EIS

2.86 3 1028 0.014

3.30 3 1026




Amoxicillin

SWV

0.90
69

50




Amoxicillin

QDs-P6LC-PEDOT: PSS/GCE CB/DPH/GCE

SWV

2.0
18.8

120




Atropine

SWCNT/Chit/GCE

SWV

0.1
150

16.5

54.9

tetracycline, oxytetracycline, streptomycin sulfate, kanamycin, secnidazole, chloramphenicol Uric acid, paracetamol, urea, ascorbic acid, caffeine Na1, K1, Mg21, Ca21, Pb21, Cd21, Ni21, NO32, Cl2, HCO32, SO422, CO322, PO432, glucose, albümin, vermicompost, humic acid Glucose, uric acid, ascorbic acid, paracetamol, xanthine, hypoxanthine

Yuan et al. (2021) Wong et al. (2020) Deroco et al. (2018)

Table 16.4 Metal-organic framework (MOF) supported nanostructured biosensors. Analytes

Biosensor

Technique

Linear range (μM)

LOD (nM)

LOQ (nM)

Interference

Sample

References

Maduramicin

Hemin@MOFs/ AuPt-Ab2-HRP/ HRP/GCE

Amperometry

1.07 3 1024
0.05

0.048




Egg

Hu, Wang, et al. (2019)

Galantamine

AChE/L-Ni-BPY/ DpAu/GCE

DPV

1 3 1026
1.0

3.1 3 1024




Human serum

Zhang, and Qiao, Cai, et al. (2021)

Monensin

AuNPs/Zn/Ni-ZIF8
800@graphene composites/GCE

DPV

3.72 3 10
4
0.149

0.16




Milk

Hu, Hu, et al. (2019)

Nilutamide

Co-Ni-Cu-MOF/NF

DPV

0.5
900.0

0.48

Tablet, human serum

Akhter et al. (2021)

RRethambutol

CD/CuMOF/CNF/ GCE

SWV

0.1
100

31

Monensin, dinitolmide, nicarbazin, sulfathiazole, sulfadiazine, olaquindox NO32, SO422, Cu21, Fe31, Hg21 Zn21, memantine hydrochloride, piracetam, nicergoline and glucose Maduramycin, dinitolmide, nicarbazin, sulfadiazine, sulfamethoxazole, sulfathiazole, olaquindox, tetracycline, clenbuterol NO3-, SO42-, CO32-, glucose, sucrose, fructose, ascorbic acid, urea, dopamine, citric acid


Racemic mixture, blood, urine, and pharmaceutical dosage form

Upadhyay et al. (2020)




SSethambutol

CD/CuMOF/CNF/ GCE

SWV

0.5
250

85.2




K1, Ca21, NO321, NH41, Cl2 or Mg21, pyrazinamide, vitamin-6, isoniazid, rifampicin, ascorbic acid, caffeine, glucose

Racemic mixture, blood, urine, and pharmaceutical dosage form

Upadhyay et al. (2020)

410

Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

acetaminophen as 0.5
300 μM. They also calculated the LOD value as 140 nM. In addition, to examine the selectivity of the method they developed, the interference effects of some inorganic and organic substances were examined, and acetaminophen was determined with high recovery. Finally, acetaminophen determination was successfully performed with chitosan NCs/TiO2-DNA/CPE biosensor in real samples such as serum and pill (Table 16.5 and 16.6).

16.2.2 Carbon-based nanomaterials Carbon-based biosensors have an important place in electrochemical fields due to their unique properties such as excellent conductivity, large surface area, and stability. They are the most used nanostructured materials in biosensor studies for many reasons such as large surface areas, stability, stability between biomolecules and the surface, unique conductivity, and catalytic effects. While these materials are sometimes used as direct nanosensors, sometimes hybrid biosensors have been developed with different materials. These carbonaceous materials include nanostructures such as single- or multi-walled carbon nanotubes (CNTs), graphite, glassy carbon, porous carbons, graphene, and carbon nanofibers. In addition, these carbonaceous materials have superior properties such as the ability to form a film on the other electrode surface, the ability to be modified, and biocompatibility. Moreover, it can be treated with nanoparticles, polymers, and heteroatoms such as nitrogen, sulfur, and phosphorus to increase the electrocatalytic activity of carbonaceous materials. Due to these unique properties of carbon nanomaterials, it can be said that it is the most important material in the production of biosensors. It is not only the basic building block of biosensors but also the most remarkable nanomaterial in electrochemical study fields. Therefore, in the last two decades, numerous studies using carbonaceous materials have appeared in the literature. Kummari et al., in their study published in 2019, developed a plain functional group multi-walled CNT (f-CNTPE) nanosensor for the analysis of methotrexate drug, known as the chemotherapy agent (Kummari et al., 2019). They illuminated the surface morphology of the proposed fCNTPE biosensor with scanning electron microscopy (SEM) at different magnifications. They found the linear working range of 0.1
1.5 μM for the determination of methotrexate with the square wave voltammetry (SWV) technique, and the LOD value was calculated as 2.9 nM. The

Table 16.5 Biological materials supported nanostructured biosensors. Analytes

Biosensor

Technique

Linear range (μM)

LOD (nM)

LOQ (nM)

Interference

Sample

References

Ethambutol

GO/Ag-NPs/ CYP2D6/ GCE ds-DNA/Eu31doped NiO/ CPE

CV

200
1200

0.0067







Real human sample

Ajayi et al. (2020)

DPV

0.1 3 103
100 3 103

0.05 3 106

Ca21, K1, Cl2, uric acid, folic acid, citrate, epinephrine, l-tyrosine, saccharose, dopamine, ascorbic acid 1 K , Cl2, Zn21, sucrose, tyrosine, ascorbic acid, lysine, methionine, uric acid, dopamine, norepinephrine, phenylalanine, alanine Guanine, adenine

Urine and serum

Akbari Javar et al. (2020)

Serum, urine, pharmaceutical formulation

MahmoudiMoghaddam and GarkaniNejad (2022a) Karadurmus et al. (2021) Vajedi and Dehghani (2020)

Amsacrine

Chlorambucil

ds-DNA/PPy/FLPt/NiCo2O4/ PGE

DPV

0.018
200

4.0




Doxorubicin

ds-DNA/PtNPs/ AgNPs/SPE

DPV

0.184
1.839







Etoposide

DNA/GO/ CoFe2O4/ ZnAl-LDH/ FTO bioelectrode

DPV

0.2
10

1.0




Flutamide

dsDNA/MCM41/ SPE ds-DNA/PtNPs/ AgNPs/SPE

DPV

0.7
10

100.0




DPV

0.2
2.01







Guanine, adenine




dsDNA/PP/ La2O3NP@SFL Cu2S NS/ PGE

DPV

0.01
500.0

1.3




Br2, Cl2, Li1, Mg21, uric acid, glucose, sucrose, citrate, alanine, epinephrine, ascorbic acid, dopamine, folic acid, Ltyrosine

Human blood serum

Idarubicin

Idarubicin

Na1, K1, Ca21, Mg21, Fe21, uric acid, glucose, ascorbic acid, citric acid, methionine, valine, caffeine, ibuprofen, acetaminophen




Human blood plasma, serum, and urine

Human serum

Raoof et al. (2020) Karadurmus et al. (2021) Foroughi and Jahani (2022)

(Continued)

Table 16.5 (Continued) Analytes

Biosensor

Technique

Linear range (μM)

LOD (nM)

LOQ (nM)

Interference

Sample

References

Isoniazid

ds-DNA/Carbon/ La31/CuO/ CPE

DPV

1.0
165.0

35




Na 1 , Ca21, Br2, methionine, phenylalanine, dopamine, epinephrine, uric acid, alanine, ascorbic acid

Pharmaceutical dosage form, urine

Kanamycin

KAN/BSA/polyC DNA/GO/ MWCNTs/ GCE CB-DHP/GCE

DPV

5.0 3 1028
0.1

47.6 3 1026




AMX, CAP, STR, and OTC

Milk

MahmoudiMoghaddam and GarkaniNejad (2022b) He et al. (2020)

DPV

2.0
10.0

630

2090




Wastewater Urine


Metformin

24

Methamphetamine

Apta-4/GE

DPV

6.7 3 10
0.35

3.13




Miltefosine

ds-DNA/GCE

DPV










Amphetamine, codeine, morphine, 3-hydroxybutyl metabolite


Nivolumab

dsDNA/GCE

DPV
















Prednisone

ds-DNA/AgNPs/ P(GBHA)/ GCE

DPV

2.78
139.49

836.98




Human serum

Streptomycin

Cyt c/ZnONPs/ MWCNTs/ GCE

DPV

0.02
2.22.8

56.2




Tetracycline

MCS@UiO-66NH2/Lac/ ABTS/CHIT/ GCE

DPV

1.0
60

894




L-ascorbic acid, urea, dopamine, uric acid, Lcysteine, folic acid, glucose, caffeic acid, citric acid, acetylsalicylic acid, naproxen, flurbiprofen, paracetamol NaCl, AgNO3, CaCl2, NaSO4, sucrose, glucose, urea, ascorbic acid, dopamine, citric acid Oxytetracycline, tetracycline, streptomycin sulfate

Machini et al. (2019) Bor et al. (2022) Machini and OliveiraBrett (2018) Machini et al. (2019) Aydogdu Tig et al. (2019)

Pharmaceutical form

Chokkareddy et al. (2021)

Milk and honey

Zhong et al. (2021)

Table 16.6 Rarely used nanostructured biosensors. Analytes

Biosensor

Technique

Linear range (μM)

LOD (nM)

LOQ (nM)

Diclofenac

Tyrosinase/CNTs/Au NPs/PtE

Amperometry

10 3 1026
1.0







Irinotecan

PPD/[AChE-ChOx 1 PEI]/BSA/GA/PtE Penicillinase@CHIT/ PtNPs-ZnO/ ZnHCF/FTO electrode Fe3O4/PANI
Cu(II)/ CILE

Amperometry

1.7
17.04

2.72

8.01

Ascorbic acid

CV

0.1
750

100




Amphetamine, ketamine, ephedrine, thebaine, methamphetamine, codeine

DPV

0.05
30

32




NaCl, KNO3, tryptophan, cysteine, uric acid, ascorbic acid

Etoposide

DNA/GO/CoFe2O4/ ZnAl-LDH/FTO bioelectrode

DPV

0.2
10

1.0




Na1, K1, Ca21, Mg21, Fe21, uric acid, glucose, ascorbic acid, citric acid, methionine, valine, caffeine, ibuprofen, acetaminophen

Nilutamide

Co-Ni-Cu-MOF/NF

DPV

0.5
900.0

0.48

Tamoxifen

CeO2
MWCNT/ CCE

DPV

0.0002
0.04

0.132




Valproic acid

PVC membrane
based biosensor (valproate
selective)

Potentiometry

1.0
1.0 3 105

975




Tenofovir

ds-DNA/BDDE

SWV

5.0
100

560

1900

Cefepime

Carbamazepine

Interference

NO3-, SO42-, CO32-, glucose, sucrose, fructose, ascorbic acid, urea, dopamine, citric acid Ascorbic acid, uric acid, dopamine K1, Ca21, Cl2, SO422, PO432, CH3COO2, CO322, Zn21, NO32, NO22, Mg21, Na1, phenytoin, levetiracetam, carbamazepine


Sample

References

Cow’s milk

Beilinson et al. (2021) Alvau et al. (2018) Chauhan et al. (2021)

Fetal bovine serum Gastric lavage

Blood serum, and urine Human blood plasma, serum, and urine Tablet, human serum Human blood serum Human blood

Fatahi et al. (2020)




Morawska et al. (2018)

Vajedi and Dehghani (2020)

Akhter et al. (2021) Shafaei et al. (2021) Ozbek et al. (2021)

414

Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

interference effect was investigated in the presence of organic molecules such as ascorbic acid, uric acid, dopamine, and serotonin. No serious effects were observed in the determination of methotrexate. Finally, in vitro analysis of methotrexate was successfully performed in artificial urine and diluted serum samples. Nataraj et al., in their study in 2021, developed an effective, sensitive, selective, and reproducible hybrid sensor for the anti-inflammatory drug 5-amino salicylic acid (5-ASA) (Nataraj et al., 2021). For the hybrid material, the glassy carbon electrode (GCE) surface was first modified with a multi-walled CNT. They then built the Ni-ZrO2/MWCNT/GCE composite electrode using Ni-doped ZrO2 nanoparticles (NPs). Characteristics such as electrode surface morphology and bonding type were examined with advanced analysis techniques of XRD, FT-IR, scanning electron microscopy (SEM) analysis, and energy-dispersive X-ray spectroscopy (EDS). Afterward, they successfully carried out analytical validation studies. For this, the working range for the quantitative determination of 5amino salicylic acid with the DPV technique was calculated as 0.001
500 μM. Based on the calibration chart, they found the LOD value as 2.9 nM. They examined the selectivity of the recommended electrochemical method in the presence of some inorganic and organic substances and determined that there was no obstacle to the determination of 5-amino salicylic acid. Finally, the precision and accuracy tests of the method were performed in complex matrix environments such as human blood, human urine, and tablets.

16.2.3 Polymer-supported nanostructured biosensors The more important the polymers have in our daily lives, the more crucial they are in the production of electrochemical nanosensors. It is one of the most commonly used materials in the construction of bioreceptor. The main reason for this is that they are easy to process, flexible and stable, and have unique physical properties. In addition, conductive polymers contribute greatly to the development of nanostructured sensors. Natural biopolymers such as chitosan have a wide range of uses in the production of analyte-specific biosensors. It shows not only the conductivity of the polymers but also the catalytic effect. In addition, it has an extraordinary effect on the stability of electrochemical biosensors. Considering all these incredible properties, polymers in almost all fields emerge as unique materials for nanostructured sensors. To date, numerous polymer-supported

Nanostructured electrochemical biosensors for estimation of pharmaceutical drugs

415

biosensors have been developed for many different analytes. In these sensors, many polymers such as chitosan, levan, polypyrrole, and polyaniline, especially polyethyleneimine, poly(bromophenol blue), poly-(3-amino-5hydroxypyrazole) (poly-AHP) are preferred. In addition to these, many polymers that provide extraordinary sensitivity and molecular imprinting polymers (MIPs), which are highly selective, are also included in the nanostructured biosensor system. In a very up-to-date article published by Hammoud et al. in 2022, they developed a polymer-supported biosensor. In the first step, they developed a molecular imprinting polymer as poly(3,4-ethylenedioxythiophene) (PEDOT) (Hammoud et al., 2021). Then, the MIPEDOT nanostructure was coated on the GCE electrode surface by the CV technique. The surface morphology of the sensor developed with scanning electron microscopy (SEM) was examined. The MIP structure is explained by ultraviolet
visible (UV-vis) spectroscopy. They determined the working range of the active ingredient carbamazepine, which is used for the treatment of epilepsy and neuropathic pain, as 0
50 mg L21 with the cyclic voltammetric technique. The LOD and LOQ values were calculated as 2.04 and 6.2 mg L21, respectively. They examined the interference effects of valproic acid and phenytoin substances in the determination of carbamazepine and performed the analysis of the analyte with high recovery. As a result, sensitive, selective, and reliable quantitative determination of carbamazepine was performed with polymer-supported nanostructured MIPEDOT/GCE biosensor. In their study published by Mohamed et al. in 2019, a nanostructured pencil graphite electrode (PGE) biosensor was developed using pyrrolidinium acid sulfate (PAS) as an ionic liquid, containing lepidocrocite nanoparticles (γ-FeOOH) dispersed in N-chitosan carbon nanosheets (N@CCNS) (Mohamed et al., 2019). The physical properties of the recommended hybrid electrode are explained using Fourier transform infrared spectroscopy (FT-IR), powder X-ray diffraction (PXRD), scanning electron microscopy (SEM), and energy-dispersive X-ray (EDX) spectroscopy methods. The CV, DPV, and electrochemical impedance spectroscopy (EIS) determinations of rivastigmine (RIV), an acetylcholinesterase inhibitor, were carried out using three different methods. For the analytical performance of rivastigmine with DPV, they found a dynamic operating range of 0.003
0.09 μM and a LOD of 0.9 nM. The interference potentials of guanine and adenine substances in the determination of RIV were examined, and they were determined that they did not have a

416

Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

serious effect. Finally, the polymer-supported γ-FeOOH/N@CCNS/ PAS/PGE nanostructured sensor and capsule and human serum have successfully performed the determination of RIV in real samples and demonstrated the precision and accuracy of the method with the analytical application.

16.2.4 Metal
organic framework In the last decade, a new porous metal
organic framework has been developed. This substance of interest is formed by the strong coordination coupling of metal ions and organic ligands. Due to the incredible catalytic properties of these nanostructured materials, they have come to an important position in the development and application of electrochemical sensors. Moreover, unlike inorganic nanomaterials, MOFs are naturally degradable and biocompatible compounds. Therefore nanostructured sensors with MOF support are being built for the determination of numerous biological agents such as DNA, RNA, and enzymes. It also shows excellent affinity ability with the analyte due to its large surface areas and outstanding catalytic properties. Like 3D chiral Ni-MOFs, it has advantages such as structure-specific lattice structure, large surface area, and being able to have different metal central atoms. Due to all these incredible properties, it has emerged as an important sensor material in recent years. The number of MOF-supported nanostructured sensors is increasing day by day and creating new working areas for themselves.

16.2.5 Biological materials They are mostly enzyme-based nanostructured sensors that make up an important part of biosensors. Biological nanostructures such as deoxyribonucleic acid (DNA), aptamer, cytochrome, and hemeproteins are preferred in the construction of these sensors. Enzyme-assisted biosensors are used in the determination of numerous analytes due to their high selectivity and sensitivity. Moreover, biosensors using redox enzymes are the most preferred nanostructure due to their catalyzing ability. In addition, these sensors allow the simultaneous determination of multiple analytes with two or more enzymes. Although it has advantages such as selectivity, sensitivity, and accuracy, there are stability problems due to the activity of enzymes. In addition, this situation affects the shelf life of enzyme-based nanosensors. Stability and shelf-life improvement studies can be done with other nanostructured materials. As a result, the sensitive, precise, and

Nanostructured electrochemical biosensors for estimation of pharmaceutical drugs

417

accurate determination of many analytes using biological materials is quite successful. Enzyme biosensors have gained an important place in the literature and the scientific world.

16.2.6 Rarely used nanostructured biosensors Nanostructured hybrid biosensors are produced by treating electrode surfaces such as fluorine tin oxide (FTO), carbon ionic liquid electrode (CILE), carbon ceramic electrode (CCE), boron-doped diamond electrode (BDDE) with metal nanoparticles, metal oxide nanoparticles, polymer, MOF. In addition, nanostructured sensors based on platinum electrode and nickel foam (NF) have also been built for drug-active substance determination. A PVC-coated potentiometric biosensor has also been developed. With the developed nanosensors, different drug substances were determined with sensitivity, selectivity, and high recovery. A new sensor was developed for tamoxifen determination by treating the CCE surface with metal oxide with multi-walled CNTs. They found the LOD of this sensor to be 0.132 nM. This value has a sensitivity that can compete with traditional analytical methods.

16.3 Conclusion Biosensors constitute an important part of drug analysis systems. On top of that, it will be one of the most important analyzers shortly. Nanostructured biosensors with fast analysis time, no preprocessing required, high accuracy, and sensitivity is finding new fields of study in different disciplines day by day. In addition, factors such as the extraordinary selectivity, portability, and on-site analysis exhibited by biosensors have gained an important position in drug analysis. In addition, hybrid biosensors have been developed with materials with unique properties such as metal or metal oxides, polymers, carbonaceous materials, 2D or 3D structures, biological materials such as enzymes and DNA, and MOF. Due to the superior selectivity and excellent sensitivity of these hybrid and nanostructured biosensors, the usage areas of biosensors are expanding day by day. Biosensor analyzer sets are emerging in new applications in large industrial areas such as food, defense, and engineering, especially in the pharmaceutical industry. These systems, which allow on-site analysis, are seen as promising developments that can be commercialized and patented. In this chapter, nanostructured materials used in the development of biosensors were classified. Validation parameters such as the method

418

Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

used for drug analysis, working range, and detection limits were examined. Analytical applications and interference types were explored in detail. However, it has been recognized that more concentration is required for biosensors to be included in routine analysis. The correct use of this technology and the discovery of new nanostructured materials will have a positive impact on the development of more sensitive and repetitive biosensors. As a result, in this section, pioneering studies on nanostructured materials in the production of a large number of biosensors for drug determinations are discussed in detail.

Abbreviations 4-AP 4-NA 4-NB 4-NP ABTS AHP AMX AuE BSA BuChE CAP CB/DPH CB-DHP CCE CD ChCl CHIT CILE CNF CPE CTAB Cyt c D-Cys D-Met ds-DNA ERGO f-CNTPE FTO GCE GO IL KAN LAC

4-Aminophenol 4-Nitroaniline 4-Nitrobenzene 4-Nitrophenol 2,20 -Azino-bis(3-ethylbenzthiazoline-6-sulfonic acid) 3-Amino-5-hydroxypyrazole Amoxicillin Au electrode Bovine serum albumin Butyrylcholinesterase Chloramphenicol Carbon black within a dihexadecylphosphate film Carbon black dihexadecylphosphate Carbon ceramic electrode β-Cyclodextrin Choline chloride Chitosan Carbon ionic liquid electrode Carbon nanofiber Carbon paste electrode Cetyl trimethylammonium bromide Cytochrome c D-Cysteine D-Methionine Double-stranded DNA Electrochemically reduced graphene oxide Functionalized multi-walled carbon nanotube paste electrode Fluorine tin oxide Glassy carbon electrode Graphene oxide Ionic liquid Kanamycin Laccase enzyme

Nanostructured electrochemical biosensors for estimation of pharmaceutical drugs

LAC L-Ala LCO/HNT L-Cys LDH L-His L-Leu L-Met l-Phe L-Ser L-Val LVN MCS MIPEDOT MOF MWCNT N@CCNS NA NrG OMC OTC PAS PGA PGE POP PP PSi QDs-P6LCPEDOT:PSS SPCE MLG PVC SPIONs STR VC ZMNS ZnHCF γ-FeOOH

419

Laccase L-Alanine

Lanthanum cobaltite decorated halloysite nanotube L-Cysteine

Layered double hydroxides L-Histidine L-Leucine L-Methionine L-Phenylalanine L-Serine L-Valine Levan Mesoporous carbon sphere Molecular imprinting of PEDOT polymer Metal
organic framework Multi-walled carbon nanotubes N-chitosan carbon nanosheets Naflon Nitrogen-doped reduced graphene Ordered mesoporous carbon Oxytetracycline Pyrrolidinium acid sulfate Poly(L-glutamic acid) Pencil graphite electrode Porous organic polymer Polypyrrole Porous silicon Printex 6L carbon and cadmium telluride quantum dots, poly (3,4-ethylenedioxythiophene) polystyrene sulfonate film Screen-printed carbon electrode Multilayer graphene powder Poly(vinyl chloride) Lecithin stabilized superparamagnetic iron oxide nanoparticles Streptomycin Vulcan α-Zinc molybdate nanospheres Zinc hexacyanoferrate hybrid film Lepidocrocite nanoparticles

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CHAPTER 17

Advanced nanostructured material-based biosensors in clinical and forensic diagnosis Saima Aftab1 and Sevinc Kurbanoglu2 1

Department of Chemistry, Ghazi University, Dera Ghazi Khan, Punjab, Pakistan Faculty of Pharmacy, Department of Analytical Chemistry, Ankara University, Ankara, Türkiye

2

17.1 Introduction Biosensing technology is an outstanding detection tool that has received popularity in recent decades due to its several advantages. Biosensors help in developing the treatment of several health problems (Rodovalho et al., 2015). There are different types of biosensors; among them, electrochemical biosensors are one of the special sensing tools which provide electrical signals from a biological entity. The electrical signals can be current, voltage, and impedance. Based on electrical signals, there are four types of biosensors such as amperometric biosensors, impedimetric biosensors, voltammetric biosensors, and potentiometric biosensors (Kurbanoglu et al., 2020; Singh, Sharma, et al., 2021). Clark fabricated an electrochemical biosensor for the first time to monitor the level of glucose in the blood serum of humans (Wang, 2001). The electrochemical biosensors have been designed to detect numerous biological entities such as proteins, enzymes, antibodies, viruses, illicit drugs, microorganisms, and toxic substances. Moreover, electrochemical biosensors have become more popular in the field of clinical and forensic analysis with a more significant number of relevant applications. Besides, electrochemical biosensors provide alternative methods to the diagnosis of viral antigens or viral nucleic acids and can contribute to the development of point-of-care (POC) challenging (Bahadır & Sezgintürk, 2015; Kudr et al., 2021). The use of POCT approaches is valuable due to the prospect of immediate diagnosis and treatment of the patients within minutes or 1 h at the clinical and forensic levels (Alemu & Alemu, 2022; Quesada-González & Merkoçi, 2018; Wang, 2006). Novel Nanostructured Materials for Electrochemical Bio-sensing Applications DOI: https://doi.org/10.1016/B978-0-443-15334-1.00015-8

© 2024 Elsevier Inc. All rights reserved.

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Electrochemical biosensors have been fabricated by integrating biological recognition elements with electronic transduction elements, as shown in Fig. 17.1. The electrode is a critical component in this type of sensor as it controls the bioagents and flow of electrons. The association of nanotechnology with biosensors increases sensibility since nanoparticles (NPs) improve electrochemical reactions and provide signal amplification (Da Silva-Junio et al., 2022). Because nanomaterials have a large surface area which increases the loading capacity and improves the mass transport of reactants to achieve high performance in terms of sensitivity, on the other hand, the biorecognition layer contributes to the high selectivity of the biosensors due to specific recognition of biomolecules (Hai et al., 2020; Magner, 1967; Thévenot et al., 2001). These advantages make the electrochemical biosensors to be used in various fields such as food safety, environmental monitoring, toxicological analysis, etc. People have been fascinated for years by the beauty of the 400 CE Lycurgus Cup and the power and beauty of a Damascus steel blade, but it has only been recently that we have learned the secret behind these incredible ancient artifacts: nanomaterials (Mahbub & Hoque, 2020). A substance is referred to as a nanomaterial if it has at least one dimension in three dimensions or if its composition has been scaled down to the nanometer scale (1
100 nm) (Wu et al., 2014). Richard Adolf Zsigmondy coined the phrase “nanometer” for the first time in 1914. In 1959, during his speech at the annual meeting of the American Physical Society, American physicist Richard Feynman proposed the specific idea of nanotechnology (Abu-Salah et al., 2010; Pandey et al., 2008; PérezLópez & Merkoçi, 2011; Santamaria, 2012). Nanomaterials have become quite popular due to their superior performance over their bulk equivalents and tunable qualities (e.g., physical,

Figure 17.1 Electrochemical biosensors and their signal transduction principle. From Kim, T. H. (2021). Toward emerging innovations in electrochemical biosensing technology. Applied Sciences (Switzerland), 11(6). https://doi.org/10.3390/app11062461.

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chemical, biological, etc.). This is mostly due to their surface effect, relatively small size, and quantum confinement effect (Chen et al., 2016). It is essential to classify nanomaterials so that their characteristics and uses may be thoroughly investigated. To identify nanomaterials, however, a number of aspects can be taken into account, including their physical and chemical characteristics, manufacturing methods, dimensionality, homogeneity, composition, and so on (Pandey et al., 2008; Pérez-López & Merkoçi, 2011; Sudha et al., 2018). According to the perspective of this chapter, we divide nanomaterials into four groups depending on their chemical makeup: (1) carbon-based, (2) organic-based, (3) inorganicbased, and (4) composite-based nanomaterials (Sudha et al., 2018).

17.2 Nanostructured materials 17.2.1 Carbon nanotubes Carbon nanotubes (CNTs) are made from graphene nanofoils that have hollow coils of atoms arranged in a honeycomb pattern. Single-layered CNTs and multilayered CNTs have diameters as small as 0.7 and 100 nm, respectively, and lengths that typically range from a few micrometers to several millimeters. The ends may be closed with half-fullerene molecules, or they may be hollow (Jana et al., 2021). They resemble the structure of a graphite sheet sliding over one another (Song et al., 2018). The rolled sheets are known as single-walled, double-walled, or multi-walled carbon nanotubes because they can have one, two, or numerous walls (Rubianes & Rivas, 2005; Stankovich et al., 2006; Yaragalla et al., 2018). The CNT is typically divided into two varieties, achiral and chiral, as is customary practice. Whereas achiral tubules have a cylindrical symmetry and are further classified into two varieties, chiral tubules have a screw symmetry. Two of each hexagon’s edges parallel the cylinder axis in one of the achiral CNT variants. They are referred to as zigzag nanotubes. The other variety of achiral CNTs, dubbed “armchair nanotubes,” has two of each hexagon’s edges perpendicular to the cylinder axis (Justino et al., 2013; Zaporotskova et al., 2016). The structures of eight allotropes of carbon are shown in Fig. 17.2. The CNT has several exceptional qualities, including high strength due to its hexagonal structure, unique electronic properties due to the free electron made available after sp2 hybridization, and ease of functionalization with various organic molecules, which enables selective interaction with various analytes (Huang et al., 2011). CNTs can be employed

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Figure 17.2 The structures of eight allotropes of carbon: (A) diamond (3D, network covalent structure), (B) graphite (2D, covalent plates) (graphene is a single of graphite), (C), (D) C60 (0D, molecules) (Buckminsterfullerene or buckyball), (E) C540 fullerene, (F) C70 fullerene, (G) lonsdaleite, amorphous carbon, (H) single-walled carbon nanotube (1D, tubes) (buckytube). From Aqel, A., El-Nour, K. M. M. A., Ammar, R. A. A., & Al-Warthan, A. (2012). Carbon nanotubes, science and technology part (I) structure, synthesis and characterisation. Arabian Journal of Chemistry, 5(1), 1
23. https://doi. org/10.1016/j.arabjc.2010.08.022.

as probe tips in various chemical and biological applications due to their simple functionalization (Mahbub & Hoque, 2020). One of the most advanced applications of CNT is the usage of sensor devices. These sensors are recognized to be the next-generation building block for selective and sensitive biosensing systems (Zaporotskova et al., 2016). CNTs with field-effect transistors (FETs) and antibodies were used to fabricate labelfree ultrasensitive biosensors to detect immunoglobulin G (HIgG) (Maehashi & Matsumoto, 2009). In another study, CNTs coupled with metal
semiconductor FET showed a more sensitive result than CNTsFET biosensors to detect amyloid-β in human serum for early-stage diagnosis of Alzheimer’s disease (Oh et al., 2013).

Advanced nanostructured material-based biosensors in clinical and forensic diagnosis

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Moreover, CNTs are modified with other nanomaterials to develop more reliable biosensors to target clinically significant biomarkers for the diagnosis of various diseases. CNTs-AuNPs-graphene and antibodies Ab1based biosensors have been used to determine human chorionic gonadotropin clinically (Lu et al., 2012). An immunosensor based on CNTsAuNPs and horseradish peroxidase was successfully employed to detect HIgG in the clinical laboratory (Cui et al., 2008). Furthermore, Si/SiO2/ CNTs/anti-SARS-Cov-2 S1 biosensor has been used to detect SARSCov-2 S1 from patients’ saliva (Zamzami et al., 2022). A CNTs-based biosensor can also be used to diagnose dengue fever for medical applications. Dengue antibody is immobilized on the surface of AuNPs/CNTs nanocomposite to target dengue virus 2 NS1 (Palomar et al., 2020). The literature review exhibited that the CNTs and modified CNTs with other nanomaterials have broad and efficient clinical and forensic diagnosis applications (Amrutha et al., 2019; Hareesha et al., 2021; Prinith & Manjunatha, 2020; Pushpanjali et al., 2020).

17.2.2 Nanowires Nanowires are gaining interest from people seeking to exploit nanoscience and nanotechnology. Nanowires have one unconfined direction for electrical conduction and two quantum-confined approaches. Nanowires are anticipated to display markedly different optical, electrical, and magnetic properties to their bulk 3D crystalline counterparts due to their distinct density of electronic states (Dresselhaus et al., 2010). The manufacturing of nanowires has traditionally been separated into topdown and bottom-up methodologies (Hobbs et al., 1975). Vapor
liquid
solid, frequently utilized in semiconductor research, is the primary method to accomplish bottom-up approaches. This technique might provide small, high-quality nanowires with sizes as small as 10 nm (Jia et al., 2019). This method still has several drawbacks, such as metal contamination, random orientation, and the inability to integrate with COMS technology, which could result in a lower fabrication yield and inadequate device uniformity. In contrast, top-down production is CMOS-suitable and can create nanowires with extreme precision in their dimensions, with the potential to scale down to 3 nm and beyond (Noroozi et al., 2017; Radamson et al., 2017). The top-down strategy might offer better alignment at the nanoscale. Top-down technologies employ nanofabrication, which

434

Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

includes lithography, cleaning, functionalization, passivation, and metallization, to create NW arrays (Akbari-Saatlu et al., 2020). Nanowires can be divided into semiconducting, metallic, and dielectric types based on electronic characteristics and chemical composition. Metallic and dielectric nanowires are suitable for photonic and plasmonic waveguiding applications, while semiconducting nanowires show promise for applications in sensing and light generation (Dasgupta et al., 2014; Li et al., 2018; Quan et al., 2019).

17.2.3 Nanoparticles A new strategy for reliable real-world applications of sensors uses nanoparticles (NPs) with sizes between 10 and 100 nm (Xiao et al., 2012). Nanoparticles that are smaller than a nanometer now exhibit distinctive and noticeably different chemical, physical, and biological characteristics from their macro-sized counterparts owing to their large surface-tovolume ratios. In light of this, extensive study has been done on these nanoparticles (Abou El-Nour et al., 2010; Geng et al., 2022). Several scientists have developed a variety of physical and chemical processes to produce nanoparticles that can be used in a wide range of applications. Physical nanoparticle synthesis methods include a photo, ion beam, electron (Chen & Pépin, 2001; Voldman et al., 1999), dip-pen lithography (Piner et al., 1999), electrochemical synthesis, microcontact printing, and nanoimprint lithography (Mandal et al., 2006). The first step in all chemical reactions is the reduction of metal ions to metal atoms, which is then followed by a regulated atom mass (Sotiropoulou et al., 2008). Most of the chemical and physical processes used to synthesize NPs are quite expensive (Boroumand Moghaddam et al., 2015). Biological techniques of NP synthesis involving microbes, enzymes, fungi, and plants or plant extracts are eco-friendly alternatives to chemical and physical approaches (Hasan, 2015; Islam et al., 2020; Wang et al., 2020). Various techniques used for nanoparticle synthesis are shown in Fig. 17.3. Among the various uses, the utilization of nanoparticles for biosensing is gaining more attention in several fields, including clinical diagnosis and forensic applications (Agasti et al., 2010). The trendiest subjects in nanotechnology currently are nanoparticles’ roles in proteins, DNA, and even cell sensor technology (De la Escosura-Muñiz et al., 2010). Various NPs such as Ag, Au, ZnO, Pt, and Cu have been used to develop biosensors for clinical and forensic applications (He et al., 2022; Umar et al., 2009;

Advanced nanostructured material-based biosensors in clinical and forensic diagnosis

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Figure 17.3 Various techniques used for nanoparticles synthesis.

Yu et al., 2021; Zhou et al., 2011). NP-based biosensors will be an admirable alternative for the detection and diagnosis of disease biomarkers. ZnO NPs and CoFe2O4 NPs with DNA showed excellent efficiency in detecting miRNA in clinical and medical analysis. Au and CNTs linked with acetylcholinesterase and glucuronyl transferase were used to detect AB-Fubinaca and AB-Pinaca (Brenes et al., 2022). Moreover, the Ag nanocluster and hybridization chain reaction-based biosensor has been designed to determine sex by targeting the DYS14 marker located on the Y chromosome (Bazzi et al., 2023). NP-based biosensors were found to be a promising tool for the determination of postmortem interval in forensic studies (Cordeiro et al., 2016; Liao et al., 2020). Hepatitis B virus is a big challenge worldwide, which needs a sensitive method to detect this virus to treat and prevent it. In this regard, a biosensor based on multi-cross displacement amplification-linked polymer NPs has been used to diagnose HBV in blood samples (Jiao et al., 2019).

436

Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

Multi-cross displacement amplification coupled with NPs has potential clinical application to the diagnosis of IS6110 and IS1081 Mycobacterium tuberculosis (Chen et al., 2021). A one-step reverse transcription loop-mediated isothermal amplification linked with NP-based biosensor assay has been successfully developed for rapid and accurate detection of COVID-19 in the first-line field, public health, and clinical laboratories, especially for resource-challenged regions (Zhu et al., 2020). Furthermore, magnetic NP-based biosensors have been designed to detect cancer biomarkers (Koo et al., 2021). A biosensor based on TiO2 and MoS2 NPs and decorated with acetylcholinesterase enzyme inhibitor is designed to detect organophosphorus pesticides in forensic visceral samples (Singh, Balayan, et al., 2021). Gold NP-based DNA probes are used for detecting specific DNA sequences (Zhang & Jiang, 2012). AgNPs decorated with antihuman albumin antibodies have been employed to detect albumin in the urine sample from preeclampsia patients. This method opens a new way for clinical analysis applications (Lai et al., 2010). In addition, bimetallic NP-based biosensors are a burgeoning field for real-world clinical applications (Kannan & Maduraiveeran, 2022; Mao et al., 2022). Literature studies revealed that nanoparticle-based biosensors hold great promise for the application of NPs to detect biomarkers in clinical and forensic analysis.

17.2.4 Fullerenes Fullerene C60 was produced initially via laser evaporation of graphite in 1985 (Kroto et al., 1985). Fullerenes are carbon-based molecular allotrope composed of a three-dimensional closed cage constructed of six- and fivemembered rings with varying numbers of hexagons and 12 pentagons, depending on the size of the fullerenes (Shetti et al., 2021; Troshin & Lyubovskaya, 2008; Zaghmarzi et al., 2017). The C60 has a total of 240 electrons, of which up to 180 are required to form the three sigma bonds between each carbon atom and its neighbors. These electrons are far less energetic than the Fermi level (Forró & Mihály, 2001). These electrons do not actually generate conduction; instead, they tend to stabilize the structure. The remaining 60 electrons in the molecule are distributed evenly among its orbitals due to the less compact carbon
carbon p orbitals, which are almost identical to the p orbitals of the graphene plane (Afreen et al., 2015; Shetti et al., 2021). There are presently numerous methods for creating C60, including combustion, laser irradiation (Heath et al., 1987), chemical vapor deposition, arc discharge, and carbon sources vaporization (Mojica et al., 2013).

Advanced nanostructured material-based biosensors in clinical and forensic diagnosis

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In addition to C60, other fullerenes, such as C80, C70, C20, and even larger molecules, were also identified following C60 (Felfli & Msezane, 2018). Fullerenes have received a lot of attention in developing biosensors owing to their increased electron transfer kinetics, high surface-to-volume ratio, and biocompatibility (Sutradhar & Patnaik, 2017). Drugs, DNA, glucose, ATP, and many other biological substances can all be detected using nanocomposites based on fullerenes or, more specifically, C60 (Bezzon et al., 2019).

17.2.5 Carbon dots Carbon quantum dots (CQDs), often known simply as carbon dots (CDs), are tiny, luminous carbon nanoparticles with diameters less than 10 nm (Du, Guo, 2016; Namdari et al., 2017; Sun et al., 2006; Yulong & Xinsheng, 2016). Based on their fundamental structures and morphologies, CQDs can be divided into two types in terms of their structure. The core structure can be either amorphous or crystalline, and the surface shell can contain various polar or nonpolar groups, from short atomic chains to large functional groups (Sciortino et al., 2018). They have garnered much interest in recent years because of their outstanding chemical stability, strong conductivity, luminescence, and broadband optical absorption capabilities (Namdari et al., 2017). Photoluminescence characteristics of carbon dots provide clear routes for sensing applications. Many applications of carbon dots in bio- and chemical sensing are suggested by well-known fluorescent system dynamics, including energy transfer, fluorescence quenching, and fluorescent spectra sensitivity to molecular surroundings (Lim et al., 2015). The viability of employing CQDs in sensing applications for monitoring environmental pollutants, including biomolecules, cations, anions, and tiny organic contaminants, has been extensively researched (Lim et al., 2015). Carbon dots-based compositions are ideal for the visual enhancement of latent fingerprints, affording improved contrast against multicolored and patterned backgrounds (Verhagen & Kelarakis, 2020). Fingerprint scrutiny has played an important role in criminal inquiry for more than a long period and is also crucial in distinguishing victims of disasters and the most extensively employed technique of biometric ID (Milenkovic et al., 2019). Carbon dots and other quantum dots are helpful in expanding the forensic toolkit because these dots, in the form of powders or spray, can combine with fingerprint residue and increase visibility (Hazarika &

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Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

Russell, 2012). Furthermore, they are not only an ideal fluorescent probe or biosensing platform but also can be employed as a unique label for bioimaging for clinical purposes (Jiang et al., 2021; Pirsaheb et al., 2019). CD biosensors exhibited good reproducibility, consistent stability, and acceptable precision; therefore they can provide many potential applications for detecting tumor makers in clinical research (Wu et al., 2013).

17.3 Applications of nanobiosensors in clinical and forensic diagnosis The trace-level detection of illicit drugs is a big challenge in forensic analysis because the abuse of illicit drug addiction is a worldwide social and public health problem (Akgönüllü et al., 2020). Therefore reliable tools for detecting drug abuse are critically important for the current society. Conventional techniques are used to analyze illicit drugs, but these methods have some disadvantages, such as being time-consuming, expensive, and inconvenient for on-site analysis and long-term sample preparation prior to analysis. On the other hand, electrochemical nanobiosensors offer highly attractive analytical tools due to their multiple specificities, low cost, on-site analysis, and speed (Leong et al., 2022; Majeed et al., 2020). In other words, it can be said that affinity-type biosensors have emerged as creditable platforms for the detection of illicit drugs for forensic and clinical purposes. In addition, electrochemical biosensors are also employed to detect toxic substances and microorganisms in clinical and forensic samples such as water, foodstuffs, and biological samples (Gupta et al., 2021). The most common toxic metals, such as arsenic in the form of arsenate(V) and arsenite(III), can affect the environment and accumulate in the body through the food chain, significantly menacing human health due to their carcinogenicity and hypertoxicity. Different studies have been reported to detect these toxic metal ions in several samples; such as the CeO2-DNA nanoprobe was successfully fabricated to detect arsenic(V) in water samples (Yang et al., 2020). In another study, AuNPs were modified with Alcaligenes faecalis bacteria to analyze arsenic(III) with LOD of 0.66 and 1.84 μM in pH 5 7.0 and pH 5 12, respectively, in the Loa river water sample (Nunez et al., 2021) (Fig. 17.4). In another work, the calibration curve ranged linearly between 10 and 4 10 nM, and a LOD of 5 nM was obtained with AuNPs immobilized with arsenite oxidase on the surface of a glassy carbon electrode (GCE)

Advanced nanostructured material-based biosensors in clinical and forensic diagnosis

439

Figure 17.4 (A) Amperometric response of 200 μmol L21 As(III) obtained with different electrodes with and without immobilized Alcaligenes faecalis. (B) Cyclic voltammograms of the Fe(CN)642/Fe(CN)632 5 mmol L21 (KCl 0.1 mol L21) system obtained with SPCE, AuNPs
SPCE, and AF/AuNPS
SPCE electrodes. (C) Nyquist diagrams obtained with SPCE, AuNPs
SPCE, and AF/AuNPS
SPCE electrodes. Conditions: AF 5 μL; GA 13 μmol; incubation time: 15 min (electrode preparation). PBS 0.1 mol L21 (pH 5 7.0); Eapp 300 mV (amperometric response). From Núñez, C., Triviño, J. J., & Arancibia, V. (2021). A electrochemical biosensor for As (III) detection based on the catalytic activity of Alcaligenes faecalis immobilized on a gold nanoparticle
modified screen
printed carbon electrode. Talanta, 223, 121702.

(Tabibi et al., 2022). Moreover, an aptasensor based on AuNPs and CNPs modified with 100-based thiolated arsenic(III) aptamer has been designed to detect arsenide(III). The designed nanoprobe can detect the arsenide (III) at a low level of 0.092 ppb in the presence of other interfering metal ions such as Cu, Cd, and Hg (Mushiana et al., 2019). Several biosensors were fabricated to detect mercury ions due to their toxicity; such as Ag nanowire, chitosan, hydroxymethyl propyl, and urease-modified screenprinted carbon electrode (SPCE) have been reported. Under optimum conditions, the designed probe exhibited exceptional performance for the

440

Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

analysis of Hg(II) ions, with a linear sensitivity range of 5
25 μM. The LOD was found to be 3.94 μM (Saenchoopa et al., 2021). In the same way as studied, 3D graphene oxide (GO) and polyaniline were immobilized with a sensitive layer of DNA for determination of Hg (II) ions within a concentration range from 0.1 to 100 nM with LOD of 0.035 nM (Yang et al., 2015). Another electrochemical biosensor based on thymine (T)-rich stem
loop (hairpin) DNA probe was used to obtain a LOD of 0.08 nM which is much lower than the 10 nM (the US Environmental Protection Agency [EPA] limit of Hg21 in drinking water) within a concentration range of 0.5
5000 nM (Xiong et al., 2015). Dualresponsive magnetic hyperbranched polyamide with heparin biosensor has been reported to detect Hg21 ions in blood samples (Xiong et al., 2015). The designed biosensor showed good results within the range of 0.5
4.8 3 103 pM for fluorescent analysis and 1.5
4.8 3 103 pM for electrochemical analysis, with a LOD of 1.0 pM for fluorescent study and 4.4 pM for electrochemical study for blood lead, opening the potential application for blood lead determination in the future (Fig. 17.5). Hydroxyapatite nanowire linked with chitosan and horseradish peroxidase has been exploited to detect cyanide, with a LOD of 0.6 ngM

0.5 I / μA

Without Hg2-

0.3 0.1 0.0

c Au electrode

-0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 E/V

MCH a Au electrode

b Au electrode

0.5 I / μA

With Hg2Hg2+

MB

d Au electrode

Cys

Fc

O

O

N

N

O

O

N

0.1 0.0 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 E/V

+Mg2-

T-Hg2+-T=

0.3

O Cys-Hg2+-Cys N

O S

= HO NH2

OH

S NH2

Figure 17.5 Schematic illustration of the ratiometric electrochemical biosensor for Hg21 detection. From Xiong, E., Wu, L., Zhou, J., Yu, P., Zhang, X., & Chen, J. (2015). A ratiometric electrochemical biosensor for sensitive detection of Hg2 1 based on thymine-Hg2 1 -thymine structure. Analytica Chimica Acta, 853(1), 242
248. https://doi. org/10.1016/j.aca.2014.10.015.

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(Wang et al., 2010). Cyanide has been detected by another electrochemical biosensor in which formate dehydrogenase (FDH, EC 1.2.1.2) and cyanidase (EC 3.5.5.1) were employed to design biosensors. The LOD was found to be in the low micromolar range in the linear range of 0.7
800 μM (Ketterer & Keusgen, 2010). Furthermore, a biosensor based on CRISPR/Cas12a linked with immuno-rolling circle amplification (immuno-RCA) was fabricated to target Escherichia coli O157:H7, a pathogenic bacterium. Under ideal environments, the fabricated probe offered a broad dynamic detection range from 10 to 107 CFU/m with a detection limit of 10 CFU/m (Chen et al., 2021). Recently, a sandwich-type biosensor was developed for selective and sensitive detection of E. coli O157:H7. The biosensor was based on Cu3(PO4)2 and methylene blue and antimicrobial peptide specific to E. coli O157:H7. The developed method displayed admirable performance within the linear range of 102
107 CFU/m and a LOD of 32 CFU/m. The developed approach also has the ability to sense pathogenic bacteria in clinical diagnostics (Bu et al., 2020). Staphylococcus aureus has been detected by an electrochemical biosensor within the range of 30
3 3 108 CFU/m, with a LOD of 8 CFU/m. The biosensor is employed for the analysis of Staphylococcus aureus in tap water, lake water, and honey samples, demonstrating that the biosensor has considerable practicability (Bu et al., 2020). Another biosensor based on cognate pair of aptamers (primary aptamer SA37 as a capturing moiety and secondary aptamer SA81 as a signaling aptamer), which was linked to the target Staphylococcus on a screen-printed gold electrode, was purposed. The LODs of 414 and 39 CFUs in spiked tap water and buffer samples, respectively, were found. In addition, Au-MoS2-PANI nanocomposite immobilized with antibodies specific to bacteria has been successfully employed to detect E. coli with LOD of CFU/mL. Furthermore, the designed biosensor showed good practical efficacy in urine sample studies (Raj et al., 2021). All these studies revealed that nanomaterials-based electrochemical biosensors could efficiently and reliably be implemented in clinical and forensic analysis. Aptamer-based biosensors have been used to detect cocaine. The aptasensor was designed with carbon dots (CDs) AuNPs and immobilized with DNA on the surface of the ITO electrode. The target DNA could be combined with CDs coupled with thionine to give a reduction/oxidation probe to monitor the analyte. Under optimized conditions, the designed biosensor displays a wide linear range of 10
70 pM with an

Table 17.1 Nanobiosensor used for the detection of illicit drugs and other clinical and forensic diagnosis applications. Analyte

Biosensors

Limit of detection (M)

Linear range (M)

References

Methamphetamine

Ab/EDOT-BTDA-Pala

876 3 1026

0.670
6.70 3 1026

Methamphetamine

Aptamer/CoOOH/CDs

3.2 3 1029

8.0
110 3 1029

Demir et al. (2016) Saberi et al. (2018) Bor et al. (2022) Soni et al.(2022) Tseng et al. (2012)

Methamphetamine Aptamer-4/Au electrode Methylenedioxymethylamphetamine Aptamer-SnNPs MethylenedioxyMicrocantilever/ methylamphetamine anti-methylenedioxymethylamphetamine Methamphetamine Aptamer/AuNPs Methamphetamine AuNPs/anti-MEHT

3.13 3 1029 0.33 3 1029 5.0 3 1023

6.7 3 1024
110 3 1026 0.01
1.0 3 1029 5.0 3 1023
50 3 1023

0.82 3 1026 5.0 3 1026

2.0
10 3 1026 Not stated

Methamphetamine

Ab/nano-Au/MPS/PB

7.5 3 1026

1.0 3 1028
5.0 3 1026

Methamphetamine

Hydrogel/ionic liquid/ antibodies MEHT aptamer/ATRP Cytochrome P450 2D6 (CYP2D6) ZnO nanorods

0.72 3 1029 g mL21 17 3 10215 0.0017 3 1029 g mL21 0.1 3 1026

5.0
1000 3 1029 g mL21

dsDNA/mercaptobenzaldehyde/Au electrode

0.01 3 1026

0.05
500 3 1026

Methamphetamine Methylenedioxymethylamphetamine Methylenedioxymethylamphetamine Morphine

100
0.001 3 1029 Not stated 1.0 3 1026
1.0 3 1023

Shi et al. (2015) Alijanianzadeh et al. (2021) Zhang and Liu (2014) Ghorbanizamani et al. (2022) Sun et al. (2022) Lugo et al. (2022) Narang et al. (2018) Talemi and Mashhadizadeh (2015)

Morphine Morphine

Cocaine

MPP/CoNPs 0.12 3 1026 MWCNTs/ionic liquid-n- 0.02 3 1026 hexyl-3methylimidazolium hexafluoro phosphate Aptamer/AuNPs 21 3 1029

2
100 3 1026 0.6
600 3 1026

Kish et al. (2023) Ensafi et al. (2012)

0.05
35 3 1026

100 3 10212

1.0
8.0 3 1029

Tavakkoli et al. (2019) Roushani and Shahdost-Fard (2015a) Asturias-Arribas et al. (2011) Li et al. (2008)

Cocaine

Aptamer/AuNPs/ MWCNTS/Chit

Cocaine

Cytochrome P450 enzyme 23.1 3 1029 /SPCE Cocaine-binding aptamer/ 0.5 3 1026 AuNPs Aptamer/AuNPs 0.228 3 1029

Cocaine Cocaine Cocaine Cocaine Cocaine Cocaine

Cocaine

Aptamer/TdT/CRISPRCas12A Nanochannel/DNA aptamer CDs-thionine/aptasensor Aptamer/AgNPs/ MWCNT/chitosan Cytochrome P450 2B4 immobilized SPCEs

19 3 1026
166 3 1029 1.0
15.0 3 1026 0.3
60 3 1029

15 3 10212

40 3 10212
150 3 1029

1.0 3 1029

1.0 3 1029
10 3 1026

0.26 3 10212 150 3 10212

10
70 3 10212 2 3 1029
2.5 3 1026

0.2 3 1023

0.2
1.2 3 1023

Abnous et al. (2016) Abnous et al. (2022) Wang et al. (2018) Azizi et al. (2022) Roushani and Shahdost-Fard (2015b) Asturias-Arribas et al. (2013) (Continued)

Table 17.1 (Continued) Analyte

Biosensors

Limit of detection (M)

Linear range (M)

References

Cocaine

Hairpin aptamer/QDs/ chitosan/GCE Graphene/AuNPs/cocaine aptamer SWNTs/Au electrode/ complimentary strand of aptamer Aptamer HL7
14/Aumesoporous silica NPs Codeine aptamer/ polyamidoamine dendrimers/chitosan/ AuNPs ZnSNPs-cyclodextrins/ DNA aptamer probe PbSNPS-cyclodextrins/ DNA aptamer COD-aptamer/Fe3O4/ AuNPs/CNTs AuNPs/poly dimethyl diallyl ammonium chloride
graphene/ ractopamine-aptamer

0.3 3 1029

1.0 3 1029
1.0 3 1026

Hua et al. (2011)

1.0 3 1029

1
500 3 1029

Jiang et al. (2012)

105 3 10212

0.1
10 3 1029

Taghdisi et al. (2015)

3.0 3 10212

10 3 10212
100 3 1029

3.0 3 10213

1.0 3 10212
1.0 3 1027

Huang et al. (2013) Niu et al. (2016)

37 3 10212

7.3 3 10212
7.3 3 1029

5.7 3 10212

7.3x10212
7.3 3 1029

3.2 3 10212

0.01
900 3 1029

5.0 3 10213

1.0 3 10212
1.0 3 1028

Cocaine Cocaine

Codeine Codeine

Codeine Codeine Codeine Ractopamine

Xiong et al. (2017) Peng et al. (2016) Azadbakht and Abbasi (2019) Yang et al. (2016)

Ractopamine Glutamate

Glucose

Glucose

DNA Glutathione

CYFRA21
1 DNA Methamphetamine

C-reactive

GQDS/QDS/AgNPs/ ractopamine -aptamer Chitosan/MWCNTs/ glutamate dehydrogenase/NAD1 Ag/CNT/chitosan/glucose oxidase/horseradish peroxidase Chitosan/BSA/ MWCNTs/ferrocene/ glucose oxidase CNT/AuNPs/DNA AgNPs/c-MWCNT/ polyaniline/glutathione oxidase 3D-graphene/AgNPs/ ssDNA CdTeQDs/thiolated methamphetamine aptamer Protein AuNRs/aptamer

330 3 10218 3.0 3 1026

1.0 3 10215
901.4 3 1029 Roushani et al. (2020) 7.5
105 3 1026 Hughes et al. (2015)

0.1 3 1026

0.5
50 3 1026

Lin et al. (2009)

1.5 3 1023

0.01
30 3 1023

Fatoni et al. (2013)

5.2 3 10215 0.3 3 1026

0.1x10212
10 3 1029 0.3
350 3 1026

Han et al. (2020) Narang et al. (2012)

1.0 3 10214

1.0 3 10214
1.0 3 1027

Chen et al. (2018)

40.34 3 10212

1.34 3 10210
1.24 3 1027 Elmizadeh et al. (2023)

2.0 3 1029

2.0
20 3 1029

D-glucose

GO/Co/chitosan/glucose oxidase

2.7 3 1023

1.0
15 3 1023

Hosseinniya et al. (2023) Kim et al. (2022)

DNA Sequence

ssDNA-Fe@AuNPsAETGO

2.0 3 10215

1.0 3 10214
1.0 3 1028

Yola et al. (2014) (Continued)

Table 17.1 (Continued) Analyte

Biosensors

Limit of detection (M)

Linear range (M)

References

Human chorionic gonadotropin Alcohol DNA Sequence

GO-peptide aptamer Fe3O4NPs/alcohol oxidase AuNPs/carboxyl-CdSNPs/ DNA Ag NPr/GQDs nano-ink/ AuNPs-CysA/DNAthiol probe Gene MIPs/SiO2/AgNPs/ DNA probes ssDNA-S-AgNPspolydopamine/graphene MWCNTs/hydroxyapatite NPs/polypyrrole/DNA AuHFGNs/poly(n-butyl acrylate)/MXene/ ssDNA Aptamer/AuNPs

0.065 3 1029 25 3 10215 2.0 3 10211

0.065
8.32 3 1029 100
500 3 1026 2.0 3 10210
1.0 3 1028

Chiu et al. (2017) Kim et al. (2012) Du et al. (2009)

1.0 3 10221

1.0 3 1029
1.0 3 10221

Farshchi et al. (2020)

2.53 3 10215

10 3 10215
100 3 1029

You et al. (2018)

3.2 3 10215

1.0 3 10213
1.0 3 1028

0.141 3 1029

0.25
200 3 1029

Huang et al. (2014) Rizi et al. (2021)

0.0035 3 10218

0.01 3 10218
10 3 1029

Ranjbari et al. (2023)

0.39 3 10212

1.0
1000 3 10212

Qian et al. (2019)

Leishmania infantum

BRCA-1 Complementary DNA Mycobacterium tuberculosis Breast cancer miRNA-122

Platelet-derived growth factor-BB

Advanced nanostructured material-based biosensors in clinical and forensic diagnosis

447

excellent LOD of 0.26 pM (Azizi et al., 2022). Another cocaine biosensor was developed by modifying the 50 -disulfide-functionalized end of an aptamer sequence on the surface of nanoporous Au electrode followed by the conjugation of its 30 -amino-functionalized end to 2,5-dihydroxybenzoic acid as the redox probe. The aptamer enhanced the electron transfer efficacy on a conformational change from an open unfolded state to a closed conformation, which reduces the distance between the electrode surface and 2,5-dihydroxybenzoic acid. The concentration ranges of 0.05
35 μM, with LOD of 21 nM, were found under the ideal experimental conditions (Tavakkoli et al., 2019). Furthermore, single-chain antibody fragments and cobalt oxide NP-based electrochemical biosensor have been reported for the detection of cocaine. The biosensor exhibited an excellent linear range of 5.0
250 ng mL21 and a LOD of 3.6 ng mL21. The outcomes were compared with outcomes attained from QTOF/Ms where four different mediums (saliva, sweat, serum, and urine) were spiked with 100 ng mL21 cocaine and were studied by both approaches (Q-TOF/Ms and biosensor). The higher performance of the biosensor was seen as compared to traditional approaches (Sanli et al., 2020). Studies using nanomaterials-based biosensors for illicit drug detection and other compounds in clinical and forensic analysis have also been reported and are given in Table 17.1.

17.4 Conclusion The development of electrochemical biosensors has been a big achievement in recent years due to their specialty and vast applications in clinical and forensic analysis. Because treatment is frequently dependent on concrete levels of clinical markers, therefore high accuracy and selectivity are needed. In this regard, nanomaterials play an essential to increase the properties of electrochemical biosensors. Nanomaterials have several properties that make them ideal for sensing applications, such as large surface area, high reactivity, easy dispersibility, and rapid fabrication. The design and use of electrochemical biosensors made of nanostructured materials are important in the determination of biological molecules, in the diagnosis of disease, and especially in the analysis of drugs of abuse in forensic sciences. In clinical and forensic diagnostics, POC diagnostic platforms can offer significant advantages by providing rapid, sensitive, user-friendly, and selective analytical tools for detection. For a diagnostic device to reach the market, traditional biological testing formats must be scaled down to the

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size of a portable device that requires low volumes of samples and reagents while providing specific and sensitive multi-analyte analysis with high throughput. It operates with a small sample volume, responds in seconds, enables instrument-free on-site diagnostics, and cost-effective, specific, and sensitive detection. Because more sensitive and portable analytical tools provide a perspective for the better applications of electrochemical biosensors at the commercial level, this chapter summarizes some important nanoparticles and their contribution to preparing more reliable and sensitive analytical tools for clinical and forensic applications. The goal is to highlight recent advances in highly sensitive and flexible nanomaterial-based electrochemical biosensors that have the potential to be developed as next-generation field-ready analytical tools.

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CHAPTER 18

Detection of toxic metals using nanostructured biosensing platforms Raghad Alhardan1, Nur Melis Kilic2, Sevki Can Cevher3, Saniye Soylemez4, Dilek Odaci2 and Sevinc Kurbanoglu1 1

Faculty of Pharmacy, Department of Analytical Chemistry, Ankara University, Ankara, Türkiye Faculty of Science, Department of Biochemistry, Ege University, Bornova-Izmir, Türkiye Institute of Computational Physics, Zurich University of Applied Sciences (ZHAW), Winterthur, Switzerland 4 Faculty of Engineering, Department of Biomedical Engineering, Necmettin Erbakan University, Konya, Türkiye 2 3

18.1 Introduction Heavy metals are a broad phrase that refers to a class of metallic elements and metalloids with atomic densities of more than 4000 kg m23 (Edelstein & Ben-Hur, 2018). Even at low metal ion levels, almost all heavy metals behave as toxic to humans (Hemavathy et al., 2019; Li et al., 2019; Miao et al., 2023). Toxic metals are naturally present hazardous elements with high atomic weight and density. Heavy metal poisoning can result in death and disability (Xiao et al., 2022). Soil pollution, wastewater, mining operations, industrial and sewage wastes, pesticides used in agriculture, and automotive exhaust emissions all conduce to the total metal freightage. Heavy metal poisoning has recently become a significant risk worldwide, affecting 235 million hectares of cropland worldwide (Lin et al., 2022). Cadmium (Cd), zinc (Zn), chromium (Cr), arsenic (As), boron (B), cobalt (Co), copper (Cu), titanium (Ti), strontium (Sr), tin (Sn), vanadium (V), nickel (Ni), molybdenum (Mo), mercury (Hg), and lead (Pb) are some examples of toxic metals. Because of the complex nature of toxic metals and biological interactions, the detrimental health impacts of heavy metals such as As, Pb, Cr, Hg, Cd, and Cu have become more complicated and problematic for the globe. The principal metals researched for their high toxicity levels include Pb, As, Cr, Cd, and Hg (Akoury et al., 2023; Tchounwou et al., 2012). Some toxic metals remain detrimental even at parts per billion (ppb) levels because of their great Novel Nanostructured Materials for Electrochemical Bio-sensing Applications DOI: https://doi.org/10.1016/B978-0-443-15334-1.00016-X

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binding affinity for N, O, and S atoms in biomolecules, which inhibits biological activities and disrupts physiological processes (Buhari, Faillace,. 2019). Metal poisoning significantly reduces the catalytic activity of certain enzymes following Hg21 or Cu21 binding. Excessive heavy metal consumption is also linked to several disorders, including Alzheimer’s, Parkinson’s, and amyotrophic lateral sclerosis. Furthermore, metal are more stable in many conditions than organic substances. As a result, detecting and removing environmentally toxic metals are critical to ecological security (Liu et al., 2023). Although metals’ mechanisms of action differ, the only approach to assist the body in dealing with the toxic metal burden is to remove toxic metal from the body and limit or decrease the potential of reexposure. They can sometimes behave as phantom body elements and even interfere with metabolic processes. Some metals, such as aluminum (Al), may be eliminated by elimination processes, but others accumulate in the body and food chain, demonstrating chronic toxicity. Several public health strategies have been used to manage, prevent, and treat metal toxicity at multiple levels, such as exposure to toxic metals, accidents, and environmental causes. Metal toxicity is determined by the absorbed dosage and the length of exposure, which can be acute or chronic. This can result in various diseases and excessive damage owing to oxidative stress caused by free radical production (Jaishankar et al., 2014). It is hypothesized that using biomarkers to detect early harm to the cardiovascular system caused by low levels of toxic metal exposure may be advantageous. Besides, the patient’s clinical state can be doubted by finding long-term low levels of human exposure to dosages experimentally used to produce cardiotoxicity (Sevim et al., 2020). Modern life, the world’s fast population growth, and the rapid development of agriculture have all led to increased exposure to heavy metals through respiration and food intake. Toxic metals are often used in manufacturing and can infiltrate biological systems through industrial waste (Rabee & Abd El-Salam, 2023). Toxic metals are abundant in the environment but may bioaccumulate in living creatures. Even though metals enter the body in diverse ways, they accumulate in various tissues, eventually reaching the toxicity threshold after bioaccumulating (Ghanim et al., 2023). The pervasiveness of metal dispersion in nature poses a risk to all creatures. Environmental exposure occurs by breathing contaminated air, growing plants on heavy metal-laden soil, or water runoff into drinking water. The harmful effects of toxic metals with various

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transmission paths vary depending on the metal’s characteristics since not all are removed when taken up into the body and can impact different organ systems. Due to their varied routes, toxic metals can induce various illnesses (Palma et al., 2023). Because of industrial activities, toxic metals are transported by runoff water, damaging water supplies. All living things, including plants, animals, and bacteria, require water. Toxic metals can attach to the surface of microbes via bioaccumulation, and they can even penetrate the cell and be chemically changed when the microbe consumes food materials via biochemical processes. Most toxic metals, such as Cd, Hg, As, and Pb, are linked to pollution and hazardous risks, especially when dissolved. Because of their toxicity and mobility, these poisonous metals in high concentrations are dangerous to individuals and can interfere with various earthly advantages. Additionally, cleaning becomes more challenging because these hazardous metals are nonbiodegradable (Kapahi & Sachdeva, 2019). Consequently, assessing, analyzing, and regulating toxic metal contamination in nature are critical.

18.2 Toxic metals 18.2.1 Cadmium Cadmium (Cd) has many applications, including batteries, ceramics, metal refining, electrolytic industries, dyes, petroleum, textiles, television screens, metallurgical industries, synthetic chemicals, and photography (Rahimzadeh et al., 2017). Increased Cd concentrations in air, soil, and water occur near industrial sources, particularly nonferrous mining and metal handling operations. Cd is a very toxic metal that, even at low concentrations, may accumulate in the body and can cause irreparable injury to many biological systems (Genchi et al., 2020). Given the increased toxicological impact of Cd and the widespread contamination accumulation in the environment from many sources, it is critical to determine and eliminate Cd ions even at ultra-trace concentrations (μg L21) (Zhang et al., 2023). Among the numerous harmful toxic contaminants, divalent Cd has been warned to cause several hazardous conducive effects to the environment as a result of its massive discharge activities discovered following its widespread use in industrial product manufacturing such as tobacco industry, textile dyes, corrosion-resistant agents, electroforming, fertilizers, and rechargeable batteries (Noh et al., 2017). As a result, it is critical to develop a unique technology for swiftly

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detecting Cd ions both sensitively and selectively among other coexisting ions (Srinivasan et al., 2023). Toxic metal contamination is one of the most severe environmental problems, posing health hazards and challenging to remedy. Given these health risks, the Environmental Protection Agency (EPA) recommends a maximum permitted level of just 5.0 μg L21 of Cd in drinking water (Ghanei-Motlagh & Taher, 2017). The allowable limit of Cd (0.2 ppm) in grains for human consumption is relatively low, necessitating constant monitoring and preventative actions. Because of the hazardous implications of excessive Cd pollution, a qualitative and quantitative assessment of Cd in the environment is critical. Existing approaches for determining Cd include atomic absorption and atomic emission spectroscopy, the analysis of neutron activation, inductively coupled plasma mass spectroscopy, and others. Even though these procedures are used to determine Cd, they have some drawbacks, such as the need for specialized staff, high maintenance costs, large sample amounts, longer reaction times, and a high cost per sample, among others (Bhanjana et al., 2015). Because of the comprehensive properties of nanomaterials, as well as the possibilities for modifying them with different functional groups, nanomaterial-based electrochemical sensors achieve high sensitivity and specificity, enhanced conductivity, the lowest detection limit, and the shortest response time (Kumar et al., 2015). Because Cd is an electroactive species, it may be identified effectively by electrochemical detection (Gupta et al., 2008; Sharma et al., 2013; Song et al., 2019).

18.2.2 Mercury Rapid industrialization has increased the amount of Hg21 on the planet, posing health risks to humans through ingesting Hg-contaminated foods. As Hg21 is one of the harmful toxic metal ions found primarily in water and living marine life, it enters the human body indirectly by consuming living marine foods. The general population is predominantly exposed to Hg through food, with fish being a significant source of methyl Hg exposure and dental amalgam. Several experiments have revealed that Hg vapor is emitted from amalgam fillings, and chewing might enhance the release rate (Järup, 2003). Hg intake can result in nausea, severe gastrointestinal discomfort, renal damage, kidney problems, neurological disorders, and other side effects (Kim et al., 2016).

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As a consequence, detecting Hg21 in water is critical for protecting both human health and the environment (Sonowal & Saikia, 2023). Inorganic pollutants from hazardous toxic metal contaminants in water resources are a worldwide environmental concern, mainly due to industrial development and inappropriate discharge operations that damage humans and other living organisms directly or indirectly (Järup, 2003). The degradation process cannot eliminate it, but it may be transferred and accumulated in the human body via the food chain, and traces of Hg can harm the central nervous system (Rashid et al., 2022; Wang et al., 2022). As a result, the WHO and EPA have set maximum levels of Hg in drinking water at 30 and 10 nM, respectively (Wang et al., 2020; Wang et al., 2020). Biological Hg poisoning symptoms include depression, memory difficulties, tremors, tiredness, headaches, hair loss, and so on (Jaishankar et al., 2014). As a result, efficient detection technologies for sensitive and precise detection of Hg in an environment and live cells are in high demand (Wang et al., 2020).

18.2.3 Lead Pb exposure occurs mainly by inhaling Pb-contaminated dust particles or aerosols and consuming Pb-contaminated food, drink, and paints (Enogieru & Momodu, 2023). Pb exposure can occur through food, soil, polluted air, and water. According to reports, occupational Pb exposure accounts for around 94% of Pb exposure, and as a result, it represents a public health problem (Shaffer & Gilbert, 2018). Because Pb is very harmful, its usage in many items, such as paints and gasoline, has been significantly curtailed (Saidur et al., 2017; Zhang et al., 2019). Pb has also been linked to carcinogenic consequences in humans and animals (Dotaniya et al., 2022; Enogieru & Momodu, 2023). Soil and water conditions in nature impact Pb, oxides, hydroxide ions, oxoanionic complexes, and their chemistry (Dotaniya & Nagar, 2023). Pb-contaminated irrigation water collected a substantial quantity of Pb in the soil and influenced plant nutrient patterns in the ground and microbial biomass carbon; pollution in the food chain may induce various adverse effects in human and animal bodies (Meena et al., 2019). Industrial Pb exposure has been associated with neurological impairment, reproductive problems, hepatotoxicity, cancer, and hypertension (Collin et al., 2022; Kumar et al., 2020). As a result, detecting Pb at trace levels is critical.

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Pb has been detected using various methods, including inductively coupled plasma mass spectrometry, X-ray fluorescence spectrometry, ultraviolet
visible spectrophotometry, atomic absorption spectrometry, and others (Bang Njenjock et al., 2023; Wang et al., 2023; Wu et al., 2022). Although these approaches have been practical and extensively used, numerous shortcomings remain, like long analysis times, a restricted linear range, an inability to concurrently evaluate many components, and challenging sample preparation (Khan et al., 2019; Ma et al., 2020). Electrochemical detection methods, on the other hand, such as electrochemical impedance spectroscopy, cyclic voltammetry (CV), and squarewave anodic stripping voltammetry (SWASV), demonstrated the ease of operation, high sensitivity, quick analysis, good selectivity, and the ability to detect multiple elements simultaneously (Guo et al., 2017; Dong & Zhang, 2017; Hu et al., 2021; Wang et al., 2015; Xiao et al., 2019).

18.2.4 Arsenic Pollution has garnered significant global attention in recent years owing to the possible health dangers linked to the environment (Wang et al., 2020). As a result of its usage in insecticides, actual mining, and processing, a significant contaminant in wastewater occurs (Sharma & Sohn, 2009). As a recurring chemical in drinking water with quantities exceeding the WHO threshold values (10 μg L21) (Moreira et al., 2021), prolonged exposure to arsenic causes cancer and various other disorders (Yang et al., 2018). There are extremely few As complexes in nature; mostly arsenic is found in nonferrous metal ores as sulfides (Wang et al., 2019). The primary goal of arsenic pollution remediation is to prevent arsenic from leaching into soil and water (Sullivan et al., 2010). Arsenic should be removed and recycled as much as possible from the natural environment (Ma et al., 2023). Modern methods for removing As from waste rely primarily on chemical precipitation techniques such as lime, ferric salt, and sulfide precipitation, which have been extensively researched in laboratory and commercial settings (Chai et al., 2016; Guo et al., 2015; Lakshmanan et al., 2010). This process necessitates much alkali consumption, and acids cannot be recovered. Furthermore, arsenic-containing residues formed following precipitation treatment are hazardous wastes that become unstable during stacking, potentially resulting in secondary contamination (Gutiérrez et al., 2010).

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Consequently, it is very desirable to develop efficient analytical techniques for the detection and monitoring of As (Zhuang et al., 2023). Electrochemical methods have various advantages, including simple and quick processes, low cost, and the ability to do on-site tests with portable equipment and sensing devices (Dinu et al., 2022) (Fig. 18.1).

18.3 Nanomaterials that are used as a detection platform In nanosensor design to detect various analytes, carbon nanotubes, fullerenes, nanoparticles, metallic nanoparticles, and quantum dots, several types of polymers are generally utilized (Hareesha, Manjunatha, Amrutha, Pushpanjali, et al., 2021; Hareesha, Manjunatha, Amrutha, Sreeharsha, et al., 2021; Prinith & Manjunatha, 2020; Pushpanjali et al., 2020; Raril & Manjunatha, 2018). Nanostructured materials are generally used to construct sensors using conjugated polymers and quantum dots for detecting toxic metals. Conjugated polymers (CPs) have to alternate σ and π bonds in the polymer backbone. These bonds allow π-electrons to delocalize on conjugated polymers and provide valuable electronic properties to be used in a variety of electronic devices, that is, photovoltaics (Coakley & McGehee, 2004), field-effect transistors (Yang et al., 2018), and biosensors (Sengodu, 2022). Among the broad extent and ample conjugated polymer family, typical early examples of conjugated polymers were mainly based on polyaniline, polypyrrole, and polythiophene. Their bulk properties usually do not satisfy the needs of physical, optical, and electronic requirements (Zhao et al., 2017). Thus size confinement is a meritorious way to meet the requirements of various applications. The

Figure 18.1 Schematic representation for electrochemical detection of toxic metals.

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specialties and fruitful benefits of these opened a new perspective in science that nanosized entities of polymeric materials are designated as nanostructured conjugated polymers (NCPs) (Ghosh et al., 2016). NCPs can provide superior electrical conductivity, higher and in the case of 1D, 2D, or 3D (D 5 dimension) directional carrier mobility, unique electrochemical activity toward specific targets, improved optical properties, and good biocompatibility owing to their well-defined nanostructures with larger surface areas (Xue et al., 2020). The rapid development of NCPs in recent decades is directly associated with three significant developments in the field. The first one is unfolding the more profound insights into charge transport processes and transfer mechanisms, as well as physicochemical properties and interactions at interfacial boundaries (Fahlman et al., 2019). The next one is simply developing more pathways, convenient methods, and easy procedures to convert, synthesize, and produce nanostructured conjugated polymers (Ghosh et al., 2016). The third one, but not the least important and probably the most effective contributor, is the curiosity of scientists to discover. These three forces unfold the NCP’s excellent properties and extend NCPs to nanoparticles (Novio, 2020), nanospheres (Liao et al., 2010), nanorods (Martín et al., 2012), nanostars (Lee et al., 2013), nanowires (Tatum & Luscombe, 2018), nanofibrils (Ma et al., 2021), nanosheets (Yano et al., 2019), etc. CPs are excellent materials for biosensor applications due to their decent electrical properties and ease of modification to possess various functional groups and surface properties. These unique characteristics of CPs make them a suitable matrix for an enzyme for biosensor applications (Sengodu, 2022). Since morphology and surface features are essential parameters in biosensor electrodes, size confinement (from a few nanometers to hundreds of nanometers) with increased surface area affects conductivity and physicochemical parameters beneficial to the performance of biosensors (Ji et al., 2020). Size confinement resulted in higher surface areas and, in specific cases, introduced a porous structure, increasing the surface area. The increased surface area provides more electrode
electrolyte sites for enzyme deposition or electrochemically active sites for nonenzymatic sensors. Thus the sensing capability and performance of biosensors are increased accordingly. NCPs are well known and widely studied, and there is an abundant amount of literature reviews (Correa et al., 2014; Tuncel, 2019) and books (Ghosh, 2021; Yoon, 2021); here, the synthesis of NCPs is not covered in detail but gives a few examples in various applications to the

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selected synthetic routes for two different approaches: top-down and bottom-up. First, it should be clarified that the top-down method can be divided into two. The lithographic techniques work physically, and the chemical vapor-mediated processes work chemically in the top-down system. The production of NCPs via top-down physical methods and lithography provide a bed for the conjugated polymer to be generated, placed in, or forms the bulk of conjugated polymer into the shape of nanostructures. On the other hand, some methods used in the bottom-up approach include plasma arcing, chemical vapor deposition processes, metal
organic decomposition, laser pyrolysis, molecular beam epitaxy, sol
gel method, wet synthesis, and self-assembly processes. Another family member of nanostructured materials is quantum dots. In this group, the two family members—organic and inorganic—always have competition with one another. In general, quantum dots (QDs) possess unique optical/electrooptical properties with excellent chemical stabilities (Ding et al., 2022; Farzin & Abdoos, 2021). Extended fluorescence lifetime with high quantum yields, confined emission spectra with broad excitation range, and adjustable particle size with adjustable particle geometry are some of the indispensable features of QDs that make QDs scarcely used in various fields such as pharmaceuticals and real-time monitoring (Jahangir et al., 2019; Li et al., 2020; Suo et al., 2020; Yan et al., 2017), material science (i.e., photovoltaics (Hu, Zhao, et al., 2021; Zhang et al., 2020)), and, of course, biosensors, which is our main discussion in this chapter. However, due to highly toxic heavy metals like cadmium, inorganic QDs are intrinsically inconvenient to keep in touch with a live environment (Zhang et al., 2020). Thus this intrinsically restricts inorganic QDs from participating in biomedical applications. Carbon dots (CDs), in the family of quantum dots (QD), are assumed to be zero-dimensional (diameter less than 10 nm) carbon-based nanomaterials. Xu et al. (2004) discovered CDs by chance while purifying singlewalled carbon nanotubes synthesized by the electrophoresis route. Since then, CDs have become rapidly famous in material science. It is worth noting here that there are distinctions in CDs based on the nature of the carbon source, core structure, and quantum effect. Subcategories can be titled as graphene quantum dots—of course, two-dimensional—(GQDs), carbon nanodots (CNDs), and carbon quantum dots (CQDs) (Cayuela et al., 2016). As presented in the name, GQDs are mainly generated by cutting large graphene sheets into smaller parts possessing π-conjugated disk-shaped nanostructures. CNDs have a quasi-sphere shape that lacks

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synthesized or processed, and other unlisted parameters, it is hard to draw a solid line between them. So, NCPs, CQDs, QDs, CNDs, and 2D quantum dots are considered whole nanostructured materials. One bottom-up strategy to obtain nanostructured CPs is template base synthesis. In this approach, there is a template within which monomers can react to form CPs. The advantage of this method is that when the template is removed, the integrity of nanostructured materials can be maintained. One example of rigid template synthesis demonstrates the synthesis of polythiophene-conjugated polymer nanowires (Ambade et al., 2017). In this study, Lee et al. found that hollow titanium dioxide (TiO2) nanotubes (TNTs) provide an exciting mechanism for polymerizing thiophene. It is likely to nucleate and grow polymerization deep inside the hollow TNT because of the higher surface energy of TNTs, and subsequently, formed nanowires inside the TNT are extruded while polymerization progresses. Another typical production method of sheet-like (2D) conjugated nanostructured polymers is ice-templated synthesis. In this method, the ice surface provides a large two-dimensional area for the instant polymerization of monomers along the air
water interface. Barpuzary et al. (2019) demonstrated the synthesis of sheets like PEDOT: PSS films with a thickness of ca. 30 nm in 5 minutes. Ice-templated PEDOT:PSS films were investigated in photoelectrochemical and photovoltaic studies. They revealed that the spin dominates ice-templated onecoated PEDOT:PSS through excellent photoelectrochemical features and superior power conversion efficiency in P3HT:PCBM solar cells with higher conductivity values. Although ultrasound is generally used to exfoliate bulk materials (the top-down method will be exemplified soon), an extraordinary study revealed the usage of ultrasound for bottom-up method. Jasuja et al. (Das et al., 2019) found an unexpected transformation of acetonitrile into QDs during ultrasonication-assisted liquid-phase exfoliation. These QDs are formed in a 2D shape (Fig. 18.2) and are fluorescent. They found a traditionally unknown perspective on the effect of ultrasonication on organic solvents. The solvent itself can act as a carbon source and generate (fluorescent) quantum particles upon being irradiated with ultrasonic energy. Contrary to bottom-up, top-down methodology covers separating, disassembling, or shaping bulk materials into nanosized structures. Once more, among various chemical and physical approaches in top-down methodology, ultrasound exfoliation is widely used in weakly bounded layered materials in their bulk form. For example, atomically thin sheets

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Daylight

(B)

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Emission spectra of acetonitrile before Ultrasonicaon of Acetonitrile Acetonitrile aer ultrasonicaon and aer ultrasonicaon (inset shows the HRTEM image of a CQD)

compression

Nucleus formaon rarefacon

5000 K, 20 MPa Ultrasonicaon of acetonitrile Carbon

Ultrasonic cavitaon (Growth of bubbles) Nitrogen

Implosion of bubbles generang high energy Hydrogen

Carbonizaon of small organic molecules at high temperature

Growth of nucleus to result CQDs

Acetonitrile

Figure 18.2 Synthesis and properties of ultrasound-assisted synthesis CQD from acetonitrile. From Das, S. K., Gawas, R., Chakrabarty, S., Harini, G., Patidar, R., & Jasuja, K. (2019). An unexpected transformation of organic solvents into 2D fluorescent quantum dots during ultrasonication-assisted liquid-phase exfoliation. Journal of Physical Chemistry C, 123(41), 25412
25421. https://doi.org/10.1021/acs.jpcc.9b03975.

ˇ ˇ of MoS2 (Stengl & Henych, 2013), h-BN (Stengl et al., 2014), WS2 ˇ (Stengl et al., 2015), and g-C3N4 (Zhang et al., 2016) were obtained by using ultrasound exfoliation. Chen et al. (Gong et al., 2021) used ultrasonication to form hybrid sheets with abundant GQD/MoS2 van der Waals heterojunctions (Fig. 18.3), which were utilized for electrochemical catalysis of the hydrogen evolution reaction. As-formed hybrid sheets outperformed the bulk or microsheets of MoS2 and provided promising features for other applications such as electrochemical and photocatalysis, optoelectronics, energy conversion, and storage. Although there is a health concern due to heavy metals in inorganic quantum dots, numerous studies (Gupta et al., 2022; Jamei et al., 2021; Liang et al., 2022; Khan et al., 2022; Pourghobadi et al., 2018; Wang et al., 2020) exist. Thus, in the last example here, it must be emphasized that Shi et al. (Xu et al., 2020) extraordinarily used a biosynthetic method in which Phomopsis sp. XP-8 (an endophytic filamentous fungus isolated from Eucommia ulmoides) is a bioreactor to synthesize CdSxSe12x QDs.

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Figure 18.3 Production of GQD/MoS2 van der Waals heterojunctions. From Gong, J., Zhang, Z., Zeng, Z., Wang, W., Kong, L., Liu, J., & Chen, P. (2021). Graphene quantum dots assisted exfoliation of atomically-thin 2D materials and as-formed 0D/2D van der Waals heterojunction for HER. Carbon, 184, 554
561. https://doi.org/10.1016/j. carbon.2021.08.063.

Figure 18.4 Biosynthesis of CdSxSe12x QDs. From Xu, X., Yang, Y., Jin, H., Pang, B., Yang, R., Yan, L., Jiang, C., Shao, D., & Shi, J. (2020). Fungal in situ assembly gives novel properties to CdSxSe1- x quantum dots for sensitive label-free detection of chloramphenicol. ACS Sustainable Chemistry and Engineering, 8(17), 6806
6814. https://doi.org/ 10.1021/acssuschemeng.0c01698.

This synthetic approach (Fig. 18.4) is considered simple, green, and ecofriendly compared to the conventional chemical route. Monodispersed CdSxSe12x QDs, with a uniform spherical shape of 3.22 6 0.07 nm in diameter, exhibited good water solubility and a strong fluorescence signal.

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CdSxSe1-x QDs directly probed the antibiotic chloramphenicol content in the milk samples via static fluorescence quenching. They found minimal interference from other antibiotics, and CdSxSe12x QDs performed the fluorescence quenching in the linear range from 3.13 to 500 μg L21 with a detection limit of 0.89 μg L21.

18.4 Applications of toxic metals detection using nanostructured platforms In the literature, there are many studies on the detection of toxic metals using nanostructured platforms. Some of them are tabulated in Table 18.1. In research by Li et al., a direct pyrolysis method with a 69% mass yield was used to make fluorescence N-doped carbon dots NCDs, and due to their optical characteristics, a luminescence mechanism was investigated with the NCDs. As a fluorescent probe, it shows high selectivity for the detection of iron(III) in water samples in the presence of a Tris-HCl buffer system, which plays an essential role in the formation of ferric hydroxide colloid and forming a hydrogen bond between NCDs and ferric hydroxide that will help in specific recognition by NCDs. Correspondingly, satisfactory recoveries and a wide linear range were obtained from 0 to 400 μM with a detection limit of 0.703 μM for NCDs (Li et al., 2021). In another article related to heavy metals detection, authors designed an optical sensor based on (N-methyl-4-pyridyl)porphyrin toluene sulfonate (TMPP) in an aqueous medium with different organic solvents, THF, and water. Many techniques were utilized to characterize the samples, such as UV
vis absorption, fluorescence stopped flow, and cyclic voltammetry. The results showed the formation of an aggregated form in water approved by fluorescence quenching. In the presence of the cationic CTAB micelles, the CMC value was found to be 5.7 3 1025 M, much lower than the anionic SDS, which was found to be 1.0 3 1024 M. After applying the optical sensor to detect the toxic heavy metal, an observed reversible interaction with TMPP was obtained for Cd21, Ag21, and Cu21 and irreversible interaction for Hg21, Pb21, Ni21, and Co21 (Sallam et al., 2020). Another study recommended a new design of an electrochemical sensor based on nanocomposite, and the authors proposed a glassy carbon electrode covered with a layer of zinc oxide-doped iron oxide (Zn/Fe) nanocomposite. It was utilized for the simultaneous and individual detection of Cd21, Pb21, and Cu21 in water samples. The electrode Zn/Fe-

Table 18.1 Some selected studies for toxic metals detection with nanostructured sensors and biosensors. Analyte

Method

Nanostructure

Linear range

LOD

Application

References

SWASV

N-doped DNRs

0.05
1 μM, 0.01
1.1 μM

NS

SiO2@Au NSs

2
100 ppm

As(III)

Optical detection SWASV

0.05 μM, 0.01 μM 100 ppb

AuNPs

NS

0.42 ppb

NS

As (III)

SWASV

ZnO/NPG

1.0
260 ppb

0.30 ppb

Real water samples

Fe13

Optical detection SWASV

PEG-GQDs

8 2 24 μM

5.77 μM

Human serum

IDB/GCE

NS

0.017 μM

Real water samples

SWV

BC-Au electrode

2.5
7.5 μM

CILE

0.5
6.0 μM

0.733 μM, 0.597 μM 0.09 μM, 0.366 μM, 0.489 μM 0.922, 0.450, 0.309, 0.208, 0.526 nM

Real lakes and cucumber samples

Deshmukh et al. (2018) Daware et al. (2019) Ren et al. (2017) Zhuang et al. (2023) Lou et al. (2020) Wang et al. (2021) Pu et al. (2022)

Drinking water

Han et al. (2022)

Zhang et al. (2022) Yin et al. (2023)

21

Pb , Cd

21

Pb21

Pb(II) Cd21, Pb21, Hg21

Water

Cd21, Cu21, Pb21, Hg21, Zn21

SWASV

COFTDBA-TPA

NS

Pb21, Cd21

SWASV

(Bi-ene)/GCE

0.002
0.68 μM

3.4, 1.8 nM

Tap water

Pb21, Cd21, Zn21

SWASV

0.5
700 ppb, 5
900 ppb, 150
600 ppb

0.081, 0.95, 35 ppb

Hg21, Cu21

ASV

BiCu0.5ANPs@CF/ SPCE GQDs/AuNPs

NS

0.02, 0.05 nM

Human body fluids, finger blood, and urine NS

Ting et al. (2015) (Continued)

Table 18.1 (Continued) Analyte

Method

Nanostructure

Linear range

LOD

Application

References

Cu , Hg

SWASV

Au Microband

5
100 ppb, 1
75 ppb

1.3, 0.63 ppb

River water

Cd21, Pb21, Cu21, Hg21 Zn(II), Cd (II), Pb(II)

DPSV

Fe3O4@SiO2-based extraction

0.1
100 μM

56.1, 16.5, 79.4, 56.7 nM

Milk

Patella et al. (2023) Zhang, Guo (2023)

SWASV

10
80 ppb

6, 3, 8 ppb

NS

Ngoensawat et al. (2022)

(4
800) μg L21, (4
1200) μg L21 4.2 2 21 μM

0.3, 0.2 μg L21 4.2, 2.9 nM

Grain and water samples Drinking water

0.2
1.2 μM

0.01 μM

Seawater

0
10 μM

0.087 μM

Tap water

1
50 μM

26 nM

above 5 ppb

1, 20 ppb

Tap water and lake water Drinking water

NS

9.48, 38.31 nM

Water

Wen et al. (2022) Moutcine et al. (2020) Hamid et al. (2021) Shan et al. (2022) Sun et al. (2021) Jayaraman et al. (2022) Wu et al. (2023)

29
140 nM, 57
203 nM

3, 10 nM

1.5
692 μM

87 nM

Tap water, human hair, and soil samples Water

21

21

Cd21, Pb21

DPASV

PEDOT/PVA/ AgNPs-modified SPCE MXA-CuO/CC

Cd(II), Hg (II) Pb21

SWV

ZnO-NP

SWASV

Cd21

DPV

Fe2O3NPs/ ZnONRs/ITO GR/GO

Co21

Fluorescence quenching SWV

L-cysteine-derived N, S-CDs T-GO-C

DPASV

Monodisperse sphere-(Fe2O3 NPs-550/GCE) Polyrutin/AgNPs/ GCE

Hg(II), Cr (VI) Pb21, Cu21

Pb(II), Cd(II)

ASV

Fe31

Fluorescent probe

BNSCDs

Liuzhu et al. (2022) Song et al. (2021)

Cu21, Pb21, Cd21, Hg21 Cd21, Pb21, Cu21, Hg21

SWASV

Co-TMC4R-BDC

0.05
12.0, 0.05
13.0, 0.1
17.0, 0.75
18.0 μM

13, 11, 26 nM NS

SWASV

COFMELE-BTDD

0.0142
4.0, 0.0037
4.0, 0.0034
4.0, 0.0032
4.0 μM

Cd(II), Pb(II)

SWASV

10
50 μg L21

Pb21

DPV

3 3 10212
5 3 1026 M

0.2 pM

Tap water and orange juice

Cd21, Pb21

SWASV

(CUiO-66/Bi/ GCE) PtNPs@Cu-MOF and DNA walker signal AOrGOC

0.00474, 0.00123, 0.00114, 0.00107 μM 1.16, 1.14 μg L21

0.5
10 μM

86.0, 9.5 nM

Human plasma

Kim et al. (2022)

Cu(II), Hg (II)

DPASV

0.64
63.55 μg L21 4.01
300.89 μg L21

0.19, 1.40 μg L21

Lake water samples

Zuo et al. (2017)

As(III)

SWASV

1B100 ng L21

0.58 ng L21

Water

Cd(II), Pb(II)

DPASV

Xiao, Zhu, et al. (2022) Liu and Zhang (2020)

Cd21, Pb21

Tap water, mineral water, and lake water Water

Wang et al. (2022)

Real water sample

Ding et al. (2021) Dong et al. (2022)

2
100 μg L21 1
100 μg L21

1.11, 0.72 μg L21

Wastewater

SWSV

AuNPs-dotted Sdoped C nanoflakes Fe-MOF-decorated MXene Nitrogen-doped carbon nanofibers N-ZC/GCE nZVI-BPC/GCE

2.0 2 50 μg L21

Drinking water

Hg21

DPV

BiM/GR

0.02
149 μM

0.1926, 0.2082 μg L21 5.0 nM

Cd(II), Pb(II)

SWASV

10 2 100 ppb

0.90, 0.60 ppb

Fe31 Hg21, Pb21, Cu21, Cd21

Optical Optical sensor

IONP-COOH/ APTES-ITO N-doped CDs TMPP

River water, corn, and fish samples Seawater

0
400 μM NS

0.703 μM 0.5, 1.0 μM

Water Water

Pei et al. (2022)

Djebbi et al. (2022) Sakthi Priya et al. (2022) Mohamad Nor et al. (2022) Li et al. (2021) Sallam et al. (2020) (Continued)

Table 18.1 (Continued) Analyte

Method

Nanostructure

Linear range

LOD

Application

References

Cd(II), Pb (II), Cu (II) Pb(II), Cu (II), Hg (II) Cd21, Cu21, Hg21

CV

Zn/Fe/GCE

NS

0.140, 0.070, 0.040 mg L21

Bakhsh et al. (2021)

DPV

1
10 μM

0.029, 0.087, 0.067 μM

0.05
1250 nM

123, 54.1, 86.6 pM

Water and cosmetics

Jyoti et al., (2022)

Pb21, Cu21, Hg21

DPV

A fern leaf-like structure MOF, MIL-47(as) ABT-modified NF@ rGO@ABT (Co3O4-NC)/ SPCE

Seawater, sewage water, university wastewater Water

Yamuna et al. (2021)

SWASV

BCN/GCE

4.1 6 0.2, 0.9 6 0.04, 0.1 6 0.005 nM 0.41, 0.93 μg L21

Monitoring

Cd(II), Pb(II)

Food

Hg(II), Pb (II) Hg21

SWASV

NMO-GR/GCE

0.01
8.38 μM 0.002
20.22 μM 0.001
69.38 μM 1
150 μg L21 2
150 μg L21 0.7
6.7 μM 1.4
7.7 μM

0.027, 0.050 μM

Water

Huang et al. (2023) Lei et al. (2022)

CV

Ag/ZnO/ZIF-8

0.5
140 μM

40 nM

Cd21, Pb21

SWV

Au/CP/MCH/Apt

0.1
1000 nM

89.31, 16.44 pM

River water, orange juice Fruit and vegetables

As(III), Hg (II) Cd21

CV

0
2.5 ppb

1.5, 0.1 ppb

Water

CV and DPV

Whole-cell E. coli and silicon ship PB-PEDOT/LSG/ GCE

1 nM
10 μM

0.85 nM

Hg21

SWV and CV SWASV

Cu3(PO4)2 HNFs/ AuNP Au NW films/ SPE

1 fM - 10 nM

0.19 fM

Packaged drinking water and tap water Water

10
300 μg/L21

2.6, 1.5, 4.2 μg L21

Pb(II), As (III), Hg (II)

SWASV

Tap water

Niu et al. (2021)

Arabbani et al. (2023) Yuan et al. (2022) Sciuto et al. (2021) Machhindra and Yen (2022) He et al. (2021) Wu et al. (2022)

NS

0.03 μg L21

Water

10213
1024 M

0.02 pM

River water

10
30 nM

14 nM

Water samples

Carbon dots

0.35
0.442 μM

0.41 μM

Drugs

Fluorescence

Arg/Glu-CQDs

0.06
10 μM 0.5
50 μM

0.039, 0.386 μM

River water

Optical

N-CDs

0
15 μM 3
60 μM

0.056, 0.31 μM

Cu21

Fluorescence

G-CDs

0.01
0.1 μM

0.0119 μM

Spiked water, serum, and urine Living cells and water

Mg21

Fluorescent probe Fluorescent nanomaterial Fluorescent hydrothermal ASV DPV

B/CDs

0
300 μM

39 μM

Water

Phosphorus-doped CQDs

0.02
3 μM

0.0095 μM

Blood, urine, and water

N, P-GQDs

0
0.15 μM

146 nM

Live cells

Yang et al. (2021)

WO3 nanocrystal 3DGO/UiO-66NH2/SPCE

1
10,000 nM 0.01
0.35 pM

0.029 nM 10.90, 5.98, 2.89, 3.1 fM

Real water samples Food

Gu et al. (2023) Huo et al. (2022)

NU66@Z8/ CMWCNT/ GCE

0.003
70 μM 0.03
50 μM

1, 10 nM

Tap water of laboratory, soil, and Chinese cabbage

Tan et al. (2023)

Cd(II)

SWSV

Fluorescence

GO/MWCNTs/ Nafion AuNPs/CNTs/ nano-CS Sustainable CDs

Cd(II)

EIS

Pb21 Hg21

Optical

Fe(III), Cr (VI) Cu21, Fe31

Fe31 Fe31 Cd21 Cd(II), Pb (II), Cu (II), Hg (II) Pb21, Cu21

DPASV

Yuan et al. (2022) Rabai et al. (2022) Ravi and Jayaraj (2020) Cai et al. (2020) Xu et al. (2021) Bandi et al. (2020) Emami and Mousazadeh (2021) Sadhanala et al. (2021) Kalaiyarasan et al. (2020)

(Continued)

Table 18.1 (Continued) Analyte

Pb

21

Method

Nanostructure

Linear range

LOD

Application

References

EIS

rGO/AuNPs/ ssDNA/GCE COFDATA-TP/SPE

5
50 nM

1.52 nM

water

0.0085
8.00 μM 0.015
8.00 μM 0.0056
8.00 μM 0.0069
8.00 μM 1.0
7.0 μM

2.80, 5.01, 1.83, 2.91 nM

River water

Kushwah et al. (2023) Wang et al. (2022)

698 nM

Water

Hg21, Cu21, Pb21, Cd21

SWASV

Cd(II)

DPV

MIL-53(Fe)/rGO/ GCE

Hue et al. (2022)

3DGO, Three-dimensional graphene; ABT, 2-(anthracen-9-yl)benzothiazole; AgNPs, silver nanoparticles; ANPs, alloy nanoparticles; AOrGOC, an amyloid oligomer
reduced graphene oxide composite; APTES, 3-aminopropyltriethoxysilane; Arg, arginine; ASV, anodic stripping voltammetry; AuNPs, gold nanoparticles; Au-NW, three-dimensional gold nanowire; B, boron; BC, biomass carbon; BCN, boron and nitrogen co-doped carbon; BDC, 1,4-benzenedicarboxylic acid; Bi, bismuthum; Bi-ene, bismuth metallene; BiM, bismuth molybdate; BNSCDs, boron, nitrogen, and sulfur co-doped carbon dots; BPC, biomass-derived porous carbon; BTDD, 4,4’-(benzo[c] [1,2,5] thiadiazole-4,7-diyl)dibenzaldehyde; C, carbohydrazide; CC, chronocoulometry; CDs, carbon dots; CF, carbon film; CILE, ionic liquid carbon paste electrode; Co3O4-NCs, Co3O4 nanocubes; COFs, covalent organic frameworks; CPE, carbon paste electrode; CQDs, carbon quantum dots; Cs, chitosan; Cu, copper; CV, cyclic voltammetry; DATA, 2,5-diamino-1,4-phenyldicarboxylic acid; DNRs, diamond nanorods; DPASV, differential pulse anodic stripping voltammetry; DPSV, differential pulse stripping voltammetry; EIS, electrochemical impedance spectroscopy; Fe3O4, iron oxide; G-CDs, green fluorescent carbon dots; GCE, glassy carbon electrode; Glu, glucose; GO, graphene oxide; GQDs, graphene quantum dots; GR, graphene; HNFs, hybrid nanoflowers; IDB, In-doped Bi2S3; IONPs, iron oxide nanoparticles; ITO, indium tin oxide; LSG, loaded laser-scribed graphene; LSV, linear sweep voltammetry; MELE, 2,5,8-triamino-s-heptazine; MOF, metal
organic framework; MWCNTs, multiwalled carbon nanotubes; MXA, MXene aerogel; N, nitrogen; NCDs, N-doped carbon dots; NF, nickel ferrite; NMO, NiMn2O4; NPs, nanoparticles; NP, natural phosphate; NSs, nanostructures; Nzvi, nanoscale zerovalent iron; P, phosphorus; PB, Prussian blue; PEDOT, poly(3,4-ethylenedioxythiophene); PEG, poly(ethylene glycol); NPG, nanoporous gold; PVA, poly (vinyl alcohol); SPCE, screen-printed carbon electrode; SSP, solid-state polymerization; SWASV, square-wave anodic stripping voltammetry; SWSV, square-wave stripping voltammetry; SWV, square-wave voltammetry; T, thymine; TDBA, 2,4,6-triformyl pyrogallol; TMC4R, tetra(4-mercaptopyridine)calix[4]resorcinarene; TMPP, meso-tetra(N-methyl-4-pyridyl)porphyrin toluene sulfonate; TP, 2,4,6triformylphloroglucinol; TPA, tripolycyanamide; ZIFs, zeolite imidazole frameworks; ZnONRs, zinc oxide nanorods.

Detection of toxic metals using nanostructured biosensing platforms

483

Nafion@GCE was characterized using the cyclic voltammetry technique, and under the optimized conditions, it exhibited high sensitivity with a low detection limit of 0.140, 0.70, and 0.040 mg L21 for Cd21, Pb21, and Cu21, respectively. Thus the proposed electrode was approved for its efficiency and quickness in detecting heavy metals, its simplicity and reproducibility, and its predictable future in environmental monitoring (Bakhsh et al., 2021). Another application for using electrochemical sensors for simultaneous detection and quantification of the heavy metals by using a carbon paste-modified electrode, Niu et al., exhibited a fern-leaf shape MOF(V) and MIL-47(as) by hydrothermal interaction, and characterized by cyclic voltammetry. Then, under optimized conditions like pH, deposition potential, and deposition time, the electrode was applied to detect the ions Pb21, Cu21, and Hg21 using a differential pulse voltammetry technique. The results showed a wide linear range between 1 and 10 mM and a low detection limit of 0.029, 0.087, and 0.067 μM, respectively. The proposed electrode shows good stability and repeatability for detection, and they reported that there is no effect of the interference (Niu et al., 2021) (Fig. 18.5). In order to develop a new type of electrochemical sensor for heavy metal ions, Jyoti et al. designed a modified graphene oxide electrode based on the hydrothermal interaction between 2-(anthracen-9-yl)benzothiazole (ABT) and nickel ferrite (NF@rGO) for the individual and simultaneous detection of Cd21, Cu21, and Hg21 ions. The proposed electrode gave a wide linear range between 0.05 and 1250 nM with an excellent detection limit of 123, 54.1, and 86.6 pM by utilizing anodic stripping voltammetry technique to simultaneously determine Cd21, Cu21, and Hg21 ions, respectively. As a result of their studies, the electrode shows high selectivity, sensitivity, good repeatability and reproducibility, and antiinterference. Due to its good characteristics, it can be used in various applications, such as cosmetics and water (Jyoti et al., 2022). In another work, an efficient electrochemical probe was successfully synthesized by Yamuna et al., where the Co3O4 nanocube (Co3O4-NC) electrode was hydrothermally prepared and utilized to determine highly toxic heavy metals Pb21, Cu21, and Hg21. The electrode characteristics were investigated via XRD, Raman, XPS, FESEM, and HRTEM analyses. The Co3O4-NC/SPCE revealed good sensitivity, high selectivity, and good recoveries for the detection of the metals by differential pulse voltammetry technique in the tap water and pond water samples, and the limit of detection was found to be 4.1 6 0.2, 0.9 6 0.04, and 0.1 6 0.005 nM for

484

Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

Figure 18.5 (A) DPV curves for Pb21, Cu21, and Hg21 in different pH values; the relation of current on (B) pH value; (C) preconcentration potential; and (D) preconcentration time on the voltammetric response of the MIL-44(as)/CPE (unadjusted pH value is used). All data were obtained by DPASV for 20 μM Pb21, 100 μM Cu21, and 20 μM Hg21. From Niu, B., Yao, B., Zhu, M., Guo, H., Ying, S., & Chen, Z. (2021). Carbon paste electrode modified with fern leave-like MIL-47(as) for electrochemical simultaneous detection of Pb(II), Cu(II) and Hg(II). Journal of Electroanalytical Chemistry, 886, 115121. https://doi.org/10.1016/j.jelechem.2021.115121.

Pb21, Cu21, and Hg21, respectively. Consequently, the Co3O4-NC/ SPCE can be used in on-time monitoring apparatuses (Yamuna et al., 2021). In this recent study by Zhang et al., a sensitive electrochemical method based on Fe3O4@SiO2 has been developed for detecting the heavy metal ions Cd21, Pb21, Cu21, and Hg21 individually and simultaneously, an electrostatic force formed between the modified electrode’s negative charge and the heavy metal’s positive charge. The proposed electrode for detecting the heavy metals in milk samples was analyzed using a differential pulse stripping voltammetry technique. It exhibited a wide linear range between 1 and 100 μM with detection limits of 56.1, 16.5,

Detection of toxic metals using nanostructured biosensing platforms

485

79.4, and 56.7 nM for Cd21, Pb21, Cu21, and Hg21, respectively. Also, it showed excellent sensitivity, selectivity with a recovery range of 96.0%
104.3%, and a predictable future due to its simplicity, low cost, and fast pretreatment process (Zhang, & Xia, Deen, et al., 2023) (Fig. 18.6). New electrochemical sensors designed by Huang et al. can identify heavy metal ion toxicity levels in food, with good electrochemical responses to Cd(II) and Pb(II), with sensitivities as low as 0.459 and 0.509 A M21 cm2. Therefore developing novel electrochemical sensors that can accurately detect the different toxicity levels of heavy metal ions in food is of great significance. They effectively synthesized boron and nitrogen co-doped carbon (BCN). A square-wave anodic stripping voltammetry technique was applied to the proposed modified electrode BCN-Nafion/GCE. Under optimal conditions, the SWASV response showed an extensive linear range from 1 to 50 mM with a low limit of detection around 0.41 μg L21 for Cd(II) and 0.93 μg L21 for Pb(II). Therefore this study provides a simple, effective, and environmentally friendly method for synthesizing sensors. It also offers fresh perspectives on creating metal-free materials for electrochemical detection generated

Figure 18.6 DPSV curves of the proposed Fe3O4@SiO2-based sensors toward simultaneous determination of heavy metal ions at different concentrations. From Zhang, M., & Guo, W. (2023). Simultaneous electrochemical detection of multiple heavy metal ions in milk based on silica-modified magnetic nanoparticles. Food Chemistry, 406, 135034. https://doi.org/10.1016/j.foodchem.2022.135034.

486

Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

from MOFs (Huang et al., 2023). For individual and simultaneous electrochemical detection of Pb(II) and Hg(II) metals, recently by Lei et al., a simple, effective way to prepare X-manganate nanocomposite (X-Ni, Zn, and Cu) was found via hydrothermal reaction. Three nanocomposites were prepared and characteristically compared, (NMO-GR), (ZMOGR), and (CMO-GR). As a result, NMO-GR revealed an excellent response via square-wave anodic stripping voltammetry (SWASV). A wide linear range was exhibited around 1.4
7.7 μM for Pb(II) and 0.7
6.7 μM for Hg(II), with the lowest detection limits of 0.050 μM for Pb(II) and 0.027 μM for Hg(II) in comparison with ZMO-GR and CMO-GR. So the electrode shows stability, good reproducibility, and promising applications for detecting heavy meals, especially in environmental pollutant fields (Lei et al., 2022). In another study, a novel electrochemical sensor based on ZIF-8 nanocomposites (Ag/ZnO/ZIF-8) was created to assess the detection of mercury ions (Hg21). The Ag ions can increase the electrochemical properties of ZIF-8 by enhancing conductivity and selectivity, and Ag has localized surface plasmon resonance properties. The composite ZIF-8 sensor demonstrated excellent selectivity for detecting mercury ions (Hg21). It had a high sensitivity and a low detection limit of 40 nM with an extensive linear range of 0.5
140 nM covered. Moreover, with good sensitivity, the real-time applications of the ZIF-8 composite sensor were examined in a variety of samples by using square-wave anodic stripping voltammetry. Therefore Ag/ZnO/ZIF-8 had improved electrocatalytic behavior for mercury identification with good sensitivity for real-time applications (Arabbani et al., 2023). Some selected studies about toxic metals detection with nanostructured sensors and biosensors are tabulated in Table 18.1.

18.5 Conclusion Heavy metal contamination is a critical issue threatening public health and the environment. Using biosensors and nanosensors as monitoring systems is a promising future for detecting and controlling toxic metals, and using nanostructured materials, such as NCPs and QDs, as biosensor detection platforms has shown promising potential in various biomedical and environmental applications. However, the toxicity of heavy metals in inorganic QDs, such as cadmium, limits their use in biomedical applications. CDs, as a subcategory of QDs, offer a safer alternative for biosensing applications because of their zero-dimensional carbon-based structure. It is

Detection of toxic metals using nanostructured biosensing platforms

487

crucial to continue research and development in biosensors to enhance the detection and removal of environmentally toxic metals for ecological security. The high sensitivity and small size characteristics of nanobiosensors offer tremendous promise for usage in the near future for biodiagnosis and other medical procedures. They can be easily inserted into a variety of medical equipment because of their small size. The potential for using nanobiosensors for heavy metal detection purposes is unsurpassed. Future environmental and medical procedures will be outpaced by using nanobiosensors, enabling more accurate, faster, and more sophisticated patient monitoring equipment for heavy metal identification. Furthermore, public health strategies must be in place to manage, prevent, and treat metal toxicity at multiple levels. With continued advancements in biosensor technology, we can take steps toward a cleaner and safer environment, protecting both human health and the natural world.

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180. Available from https://doi.org/ 10.1039/c6ta08038c, http://pubs.rsc.org/en/journals/journalissues/ta. Arabbani, F. K., Vasu, D., Sakthinathan, S., Chiu, T. W., Liu, M. C., & High, A. (2023). Efficient Electrocatalytic activity of metal-organic frameworks ZnO/Ag/ZIF-8 nanocomposite for electrochemical detection of toxic heavy metal ions. Electroanalysis, 35 (3). Available from https://doi.org/10.1002/elan.202200284, http://onlinelibrary. wiley.com/journal/10.1002/. Arora, N., & Sharma, N. N. (2014). Arc discharge synthesis of carbon nanotubes: Comprehensive review. Diamond and Related Materials, 50, 135
150. Available from https://doi.org/10.1016/j.diamond.2014.10.001. Bakhsh, E. M., Khan, S. B., Asiri, A. M., & Shah, A. (2021). Zn/Fe nanocomposite based efficient electrochemical sensor for the simultaneous detection of metal ions. Physica E: Low-dimensional Systems and Nanostructures, 130114671. Available from https://doi. org/10.1016/j.physe.2021.114671. Bandi, R., Dadigala, R., Gangapuram, B. R., Sabir, F. K., Alle, M., Lee, S. H., & Guttena, V. (2020). N-doped carbon dots with pH-sensitive emission, and their application to simultaneous fluorometric determination of iron(III) and copper(II).

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CHAPTER 19

Nanostructured materials-based electrochemical biosensors for hormones Gnanesh Rao1, Raghu Ningegowda2, B.P. Nandeshwarappa3, M.B. Siddesh4 and Sandeep Chandrashekharappa5 1

Department of Biochemistry, Bangalore University, Bangalore, Karnataka, India Department of Chemistry, Jyoti Nivas College Autonomous, Bangalore, Karnataka, India Department of Studies in Chemistry, Shivagangothri, Davangere University, Davangere, Karnataka, India 4 Department of Chemistry, KLE’s S. K. Arts College and H. S. K. Science Institute, Hubballi, Karnataka, India 5 Department of Medicinal Chemistry, National Institute of Pharmaceutical Education and Research (NIPER-R), Raebareli, Transit Campus, Lucknow, Uttar Pradesh, India 2 3

19.1 Introduction Hormones are broadly classified depending on the cell it acts upon as endocrine, paracrine, autocrine, and intracine. Endocrine hormones are the group of hormones which acts on the target cells upon being secreted by endocrine glands and circulate through the bloodstream; paracrine hormones act on the neighboring cells upon release; autocrine hormones act on the cells secreted by it; and intracine are hormones utilized by the cells synthesizing it upon activation of signal transduction pathway. Endocrine hormones are further classified depending on the solubility of water and lipid-soluble. Water-soluble hormones (peptides/amino acid derivatives) are transported readily whereas lipid hormones (steroids) form ligand
protein complexes along with carrier plasma glycoproteins through the circulatory system to target cells. Water-soluble hormones act on the target cell surface by binding to specific receptor proteins in the target cell resulting in the activation of the signal transduction pathway via secondary messengers that activates gene transcription in turn expressing the target protein in target cells. Lipid hormones pass through the plasma membranes of target cells and act directly in the nuclei of the target cells. Hormones are responsible for the physiological functioning of the human body by regulating a variety of metabolic processes and psychological behaviors (Farkas et al., 2020; McHenry et al., 2014). Novel Nanostructured Materials for Electrochemical Bio-sensing Applications DOI: https://doi.org/10.1016/B978-0-443-15334-1.00017-1

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Changes in levels of hormones cause hormonal imbalance, and significant or rapid change diagnosed indicates the possibility of disease and disease condition (Adegoke et al., 2021; Zhang et al., 2022). Thus early detection by measuring the level of hormones has a significant role in the identification of human diseases. The traditional analysis methods of hormone include highperformance liquid chromatography (Ozgocer et al., 2017), liquid chromatography
mass spectrometry (Xu et al., 2021), and enzyme-linked immunosorbent assay (Yuan et al., 2019) which are time-consuming, high cost, and requires technical expertise for analysis. Electrochemical biosensors offer benefits over conventional analytical techniques, due to their quick response time, simplicity of use without technical expertise, cost-effectiveness, intrinsic sensitivity and selectivity which have attracted a lot of attention for use in point-of-care diagnosis (Bian et al., 2022; Chen et al., 2009; Mazloum-Ardakani et al., 2010; Shiraishi et al., 2007; Stoytcheva et al., 2019; Xiao-bo et al., 2004; Zhang et al., 2010).

19.2 Principle of electrochemical biosensors for detection of hormones 19.2.1 Generally, an electrochemical biosensor consists of three components, including biometric components, sensors, and electronic systems Electrodes are often modified with nanomaterials to amplify the detection signal. Biosensor uses immobilized biosensitive materials (antibodies, enzymes, aptamers, nucleic acids, etc.) as biometric elements to recognize the required target molecule. The sensor thus converts the concentration of analytes to electric signals proportionally (Hareesha & Manjunatha, 2020a; Manjunatha, 2017; Ronkainen et al., 2010). Typically in electrochemical sensor, the electric signals are directly proportional to the reaction under investigation which either generate a measurable current at a constant voltage (amperometric) (Amine & Mohammadi, 2018; Kasemo, 2002; Kubáˇn & Hauser, 2015), a measurable current over a potential change (voltammetric) (Goud et al., 2021; Yadav & Sharma, 2019), a measurable potential difference or charge accumulation (potentiometric) (Aragay & Merkoçi, 2012), and measurably altering the conductive properties of a medium (conductometric) between electrodes or impedance, both resistance and reactance, (impedimetric) (Benson, 2005; Charithra & Manjunatha, 2019; Farma et al., 2013;

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Hareesha & Manjunatha, 2020b; Hareesha et al., 2019; Jg, 2017; Katz & Willner, 2003; Manjunatha et al., 2014; Manjunatha, 2018; Manjunathaa et al., 2014; Pushpanjali et al., 2019; Tigari et al., 2019).

19.3 Electrochemical detection of hormones Hormones are categorized into different types depending on the biomolecular nature of the hormone.

19.4 Amino acid derivatives Amino acid hormones are hormones derived from amino acids, mainly tyrosine. Examples of amino acid hormones are adrenaline or epinephrine and noradrenaline or epinephrine released by the adrenal glands. Triiodothyronine and thyroxine are released by the thyroid gland, melatonin is released by the pineal gland, and dopamine is released by the substantia nigra. Amino acid hormones act as a neurotransmitter and neurohormone in the mammalian central nervous system. The detection of these hormones is based on the affinity of the hormone.

19.5 Adrenaline or epinephrine and noradrenaline or norepinephrine Adrenaline or epinephrine and noradrenaline or norepinephrine, which are released by the adrenal glands, are important catecholamine neurotransmitters in the mammalian central nervous system (Nikolajsen & Hansen, 2001). Epinephrine and norepinephrine regulate the blood pressure, immune system, heart rate, lipolysis, and glycogenolysis. Abnormal levels are observed in Parkinson disease. Epinephrine concentration levels are altered in conditions like orthostatic hypotension, stress, and thyroid hormone deficiency, while norepinephrine concentration levels may lead to the occurrence of conditions such as ganglia neuroblastoma, ganglion neuronal, and paraganglioma. Carbon paste electrode modified with single-walled carbon nanotube (SWCNT) and multiwalled carbon nanotube (MWCNT) comprising tyrosinase and Nafion membrane based on catalyzing property of oxidation of epinephrine is used for the voltammetric detection and quantification of epinephrine (EP) without the interference of ascorbic acid and

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uric acid (Apetrei & Apetrei, 2013; Babaei et al., 2011; Patrascu et al., 2011; Zare & Nasirizadeh, 2010). MWCNT modified with chitosan electrode through electrocatalytic oxidation is also used as electrochemical sensor for the detection of epinephrine (Chen et al., 2015; Ghica & Brett, 2013; Koteshwara Reddy et al., 2017; Reddy et al., 2020). The electrochemical behavior of a multiwalled carbon nanotube paste electrode modified with 2-((7-(2,5-dihydrobenzylideneamino) heptylimino)methyl)benzene-1,4-diol (DBHB) (Beitollahi et al., 2018), hexadecyltrimethylammonium bromide (CTAB) (Rajabi et al., 2016; Yu et al., 2016), bromothymol blue (BTB) (Pradhan et al., 2014; Thomas et al., 2014), vinyl ferrocene (VF) (Beitollahi et al., 2014), nickel hydroxide nanoparticles (Babaei et al., 2015; Tsele et al., 2017), and metal oxide nanoparticles (Figueiredo-Filho et al., 2014; Kumar Gupta, 2017). For detection of noradrenaline or norepinephrine, carbon paste electrode (CPE) sensor modified with 3,4-dihydroxybenzaldehyde-2,4-dinitrophenylhydrazone (DDP) and CNT is used for voltammetric detection and quantification (Huang et al., 2010; Queiroz et al., 2018; Salmanpour et al., 2012; Wang et al., 2002).

19.6 Melatonin Melatonin, chemically N-acetyl-5-methoxytryptamine, an indoleamine derived from L-tryptophan is a neurohormone released by pineal gland responsible for the wake and sleep cycle (Zhao et al., 2019). Single-walled carbon nanotubes (SWCNTs)- and multiwalled carbon nanotubes (MWCNTs)-based sensors have been tested for the detection and quantification of melatonin (MT) (Babaei et al., 2013; Gomez et al., 2015; Qu et al., 2005).

19.7 Triiodothyronine and thyroxine Thyroxine (T4) is a thyroid hormone secreted by the thyroid gland. Triiodothyronine (T3) is converted to thyroxine in target cells. Thyroxine plays vital roles in the normal growth, metabolism, development of the body, and in the maturation of sexual organs. MWNTDHP film-coated GCE has been investigated for the detection and quantification of thyroxine by electrochemical characterization (Wu et al., 2004).

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19.8 Dopamine Dopamine (DA) is an essential neurotransmitter in the nervous system of humans responsible for activities such as motor control. CNTs modified with overoxidized polypyrrole (OPPy) have been tested for the detection and quantification of DA (Eom et al., 2019). Similarly, MWCNTs modified with AgAu nanoparticles (Balasubramanian et al., 2020) and graphene quantum dot have been tested and reported (Cesarino et al., 2014; Huang et al., 2020; Wang et al., 2003; Wu et al., 2003).

19.9 Steroids and eicosanoids Steroids are a group of hormones derived from cholesterol. Sex hormones, estradiol and testosterone, and stress hormone, cortisol, are few examples. Quantification of steroid hormones is mainly used for early diagnosis of diseases, pregnancy, food toxicity, and pollution levels (Kelch et al., 2020; Lenard, 1992). Eicosanoid hormones are derived from lipids, prostaglandins, prostacyclin, leukotrienes, and thromboxane that belong to this group of hormone. They regulate pathological processes in female reproductive function (Niringiyumukiza et al., 2018), inflammation, and tissue repair (Rael, 2016).

19.10 Testosterone Testosterone is the most essential steroid released by testicular stromal cells whose levels are related to many hormonal disorders in men and cardiovascular diseases (Gugoasa & Staden, 2018). Carbon paste electrode modified by glutaraldehyde-fixed testosterone antibodies on phenylenediaminebenzodithiophene polymer (pBDBT) (Bulut et al., 2020) and CNT has been tested as the biosensor for testosterone detection in various body fluids (Goyal et al., 2010; Gugoasa et al., 2015; Serafín et al., 2014).

19.11 Estrogen Estrogen is a naturally occurring steroid hormone essential for the female reproductive cycle, menstrual cycle, and growth (Nameghi et al., 2019). Multiple electrochemical sensors are reported for the detection of 17βestradiol (Ahirwar et al., 2019; Li et al., 2018a, 2018b), a natural estrogen secreted by humans (Pu et al., 2019). Estrogens at abnormal levels lead to

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obesity and infertility. Higher levels of estrogen are observed in the case of breast cancer especially in initial tumor formation (Uliana et al., 2018). Detection of 17β-estradiol using NiFe2O4-mesoporous carbon (NiFe2O4-MC) nanocomposite (Tanrıkut et al., 2020), carbon dots, and polyaniline composite (Supchocksoonthorn et al., 2021), screen-printed carbon electrode with 17β-estradiol-imprinted poly(aniline-co-metanilic acid) and tungsten disulfide (Lee et al., 2020) and screen-printed carbon electrode with 4-carboxyphenyl radical (HOOC-PheSPCEs) (Ojeda et al., 2015) has been tested. Detection of estrone using glassy carbon electrode modified with multiwalled carbon nanotubes functionalized with carboxylic groups has been tested (Okina et al., 2021).

19.12 Cortisol Cortisol is a major glucocorticoid that reflects the stress state in the human body. Abnormal levels of cortisol levels have the potency to cause hypertension and damage to muscle tissue and immune system. For noninvasive monitoring of stress level, detection of cortisol in human saliva and sweat have been tested, an aptamer
antibody sandwich sensor modified with multiwalled carbon nanotubes, mesoporous carbon, and silver nanoparticles (Yu et al., 2016), glassy carbon electrodes coated with tin disulfide nanoparticles, cortisol antibody (C-Mab), and bovine serum albumin (BSA) (Rajabi et al., 2016), polydimethylsiloxane thin films layered with carbon nanotubes deposited with silver nanoparticles or poly(GMA-co-EGDMA) (Eom et al., 2019; Liu et al., 2021; MorenoGuzmán et al., 2013; Naik et al., 2022).

19.13 Progesterone Progesterone is the most common biomarker for pregnancy (Goh et al., 2016; Kanninen et al., 2019; Polat et al., 2020). Monitoring of progesterone is helpful in the detection of autoimmune disease and reproduction monitoring (Chang & Wang, 2020; Cui et al., 2021; Yu & Maeda, 2017). Glassy carbon electrode modified using multiwalled carbon nanotubes, AuNPs, and poly-L-serine (Naderi & Jalali, 2020), screen-printed carbon electrode modified with graphene quantum dots, NiO-Au hybrid nanofibers in combination with multiwalled carbon nanotubes (Arvand &

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Hemmati, 2017), and label-free electrochemical progesterone aptasensor have been tested for progesterone analysis (Samie & Arvand, 2020).

19.14 Calcitriol Vitamin D is a lipid-soluble vitamin; vitamins D2 and D3 are the main forms of vitamin D, and it is an immunomodulatory hormone (Binkley & Wiebe, 2013; Charoenngam & Holick, 2020; Farrell & Herrmann, 2013). GCE modified with composite material based on polyaniline
polypyrrole (PANI-PPY) copolymer doped with silver
cobalt (CoAg) and ionic liquid (IL) (Anusha et al., 2021) and graphene nanocomposite sensor (Thangphatthanarungruang et al., 2020) has been tested for the measuring of vitamin D.

19.15 Proteins/peptides Peptide or protein hormones are made of a chain of amino acids; examples include adiponectin, oxytocin, and insulin. These hormones bind to intracellular receptors through an intracrine mechanism or they are packed in vesicles and transported through the membrane.

19.16 Adiponectin Adiponectin is a protein expressed in white adipose tissue; it is an antiinflammatory adipocytokine involved in glucose and lipid metabolism (Thanakun et al., 2014). Adiponectin is a biomarker for obesity, insulin resistance, hyperlipidemia, and atherosclerosis. CNTs functionalized by treatment with 4-aminobenzoic acid in the presence of isoamylnitrite, followed by oriented binding of anti-APN, have been tested for the measurement of adiponectin levels (Ooi et al., 2014).

19.17 Follicle-stimulating hormone Follicle-stimulating hormone is a gonadotropin secreted by basophils of the anterior pituitary gland which can promote human reproduction and development (Fan et al., 2021; Haller-Kikkatalo et al., 2012). Follicle-stimulating hormone in combination with luteinizing hormone promotes the generation and secretion of sex hormones. In men, the hormone promotes the production of sperm, whereas in women the hormone promotes follicle

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development and maturation to produce estrogen and causes ovulation (Pritchard et al., 1995; Santi & Simoni, 2014). High FSH value is observed in the conditions such as ovarian agenesia and primary amenorrhea. Conversely, low FSH value leads to polycystic ovarian syndrome (Robertson et al., 2021). Quantification of the FSH level has an important clinical value for the diagnosis and treatment of endocrine diseases and infertility. Immunosensor based on a screen-printed electrode modified with reduced graphene oxide, multiwalled carbon nanotubes, thionine, and gold nanoparticles composite with anti-FSH for the detection of FSH has been tested (Fan et al., 2021).

19.18 Human chorionic gonadotropin Human chorionic gonadotropin is a glycoprotein secreted by placenta trophoblast cells that functions as a diagnostic biomarker for pregnancy and is also a tumor marker. Immunosensor based on glassy carbon electrode (GCE) modified with carbon nano-onions, gold nanoparticles, and polyethylene glycol composite and sensors based on the modified carbon macro- and microelectrodes immobilized with anti-hCG antibodies to detect hCG have been reported (Damiati et al., 2019; Guo et al., 2014; Lu et al., 2012).

19.19 Insulin Generally, diabetes patients are reliant on the intake of adequate and accurate amounts of insulin to regulate blood glucose levels. Insulin is the hormone which regulates the intake of glucose, glycolysis, and glycogenesis in the liver and muscle and lipids and the synthesis of triglycerides in adipocytes. Screen-printed electrode Nafion
multiwalled carbon nanotubes modified with nickel oxide nanoparticles (Rafiee & Fakhari, 2013), glassy carbon electrode coated with films of chitosan and multiwalled carbon nanotubes (Wang & Musameh, 2004; Zhang et al., 2005), and carbon fiber microelectrode modified with nickel nanoparticle and carbon nanotube (Lu et al., 2018) have been tested for the measurement of insulin.

19.20 Leptin Leptin is a hormone related to obesity, vascular function, regeneration, inflammation, and immunity (Carbone et al., 2012; Onger et al., 2017).

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SWCNT functionalized with chitosan has been tested for the measurement of leptin (Zhang et al., 2018).

19.21 Prolactin Prolactin hormone is produced by lactotrope cells of the anterior pituitary; it plays an important role in the stimulation of lactation and regulates the growth and differentiation of the mammary gland and reproduction. The immunosensor was composed of a carbon nanotube modified with polyethylene dioxythiophene along with gold nanoparticles and polypyrrole propionic acid on which the corresponding antibodies were immobilized for prolactin estimation (Serafín et al., 2014; Serafín Martínez-García et al., 2014; Sun, 2017).

19.22 Conclusion Overall, current electrochemical biosensors for hormone use antibodies and aptamers as recognition elements. The usage of the point-of-care determination of hormones is limited to lateral flow assay, and measurement is not as popular as other biomarkers. The use of functionalized nanomaterials and analytical technologies for the development of electrochemical sensor and biosensor platforms with more selectivity and sensitivity can be suitable for portable wearable sensors.

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CHAPTER 20

Safety, health, and regulation issues of nanostructured biosensors P.V. Vijayarani1, P. Karpagavinayagam1, B. Kavitha2, N. Senthilkumar3 and C. Vedhi1 1

Department of Chemistry, V.O. Chidambaram College, Thoothukudi, Tamil Nadu, India Department of Chemistry, Sri Ranganathar Institute of Engineering and Technology, Athipalayam, Coimbatore, Tamil Nadu, India 3 PG & Research Department of Chemistry, Arignar Anna Government Arts College, Tiruvannamalai, Tamil Nadu, India 2

20.1 Introduction Conventional item has been supplanted by advancements in nanomaterials during the preceding 10 years, as has the development of biosensors that are economically practical. To speed up the diagnosis process, point-ofcare biosensor-based testing is necessary as a detection strategy for the consequences of the current epidemic. Instead of using ultrasensitive label-free biosensors, integrating biosensors with nanostructures may boost sensing and allow for downsizing. Notably, next-generation biosensors might speed up the detecting process. In-depth descriptions of the various functionalized nanomaterial types and their synthetic characteristics are provided. Ultrasensitive label-free biosensors may have competition. Notably, next-generation biosensors might speed up the detecting process. In-depth descriptions of the various functionalized nanomaterial types and their synthetic characteristics are provided (Bhalla et al., 2016; Lowe, 1984). The virus is typically found via serological tests and real-time polymerase chain reaction (qPCR) screening. Because the conventional methods for detecting infectious diseases are so complicated, competent personnel is needed. The currently known recorded traditional processes are expensive, time-consuming, and labor-intensive (Kissinger, 2005). The application of nanotechnology can aid in the diagnosis of viral infections. Nanotechnology has recently supplanted conventional therapy (Tigari, Manjunatha, 2020; Tigari, Manjunatha, 2020). There has been a tremendous increase in the Novel Nanostructured Materials for Electrochemical Bio-sensing Applications DOI: https://doi.org/10.1016/B978-0-443-15334-1.00018-3

© 2024 Elsevier Inc. All rights reserved.

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creation of biosensors for the diagnosis of various ailments in recent decades since they are determined to be fast, simple, responsive, and precise (Hareesha et al., 2021; Lee et al., 2015). Lowering the size of nanoparticles to the nano-range, or 1
100 nm, may boost their usefulness since they offer shrinkage and an improved surface area, which have attracted a lot of attention. The surface-to-volume ratio increases due to their nanoscale, allowing for efficient interactions between the sensor and the analyte (Rahman et al., 2010). By fostering effective interactions between analyte and biosensor, NM-based biosensors have found broad usage in the detection of biomolecules and the diagnosis of illnesses (Jayanthi et al., 2017).

20.2 Biosensors By producing signals proportionate to the concentrations of an analyte in the interaction, a biosensor is an instrument that detects biological or chemical processes. Signal transduction is the basis for how biosensors work (Mun’delanji et al., 2015). A biotransducer, a biorecognition element, and an electrical system made up of a screen, microprocessor, and amplifiers are among these elements. The biorecognition component, which functions as a bioreceptor, is permitted to communicate with a particular analyte (Yoo & Lee, 2010). Leland C. Clark Jr., regarded as the “father of biosensors,” created the first instrument to quickly ascertain the level of glucose in the blood. For self-monitoring, many of the 18.2 million Americans with diabetes today still use Clark’s initial glucose sensor idea. Biosensors have a number of advantages when paired with nanomaterials, such as real-time analysis, detection with a smaller sample, high-throughput screening, label-free detection, and low limit of detection (Eggins, 2013; Turner et al., 1987; Turner, 2013). Nanostructures and nanomaterials study the properties of materials utilized for numerous applications through downsizing. Innovative therapeutic modalities at the nanoscale can be generated by fusing medical research and nanotechnology (Pushpanjali, Manjunatha, 2020). NPs can be utilized as a vehicle to deliver the drug-like molecule to the desired location. These are made up of a variety of chemical and structural components, allowing them to have unique physicochemical properties and creating new possibilities for a variety of biological applications (Zhu et al., 2021). Surface modification can help functionalized

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NMs perform better as biosensors. They stand for the subsequent generation of smart materials and have several uses. The following section explores designed and synthesized NM-based biosensors with biomedical applications (Rahman et al., 2010; Schultz, 1982; Yoo & Lee, 2010).

20.2.1 Metal- and metal oxide-based biosensors Infected mice were treated with the Env plasmid DNA vaccine using PEI f-Au nanorings and poly(diallyldimethylammonium chloride, or PDDA), according to Yu et al. (NRs). The seed solution of CTAB-AuNRs was made by combining AuNRs with a precursor, and this mixture was then used to make f-AuNRs. After that, poly(styrene sulfonate) was applied to CTAB-Au, resulting in the development of negatively charged AuNRs. To create f-AuNRs, these NRs were then subjected to a reaction with PDDA or PEI. AuNRs were coated with contrasting surfaces as vaccination adjuvants, which caused the formation of an Au-Env complex (Ansari et al., 2010; Kaushik, et al., 2009). Flexible materials and metal oxides exhibit broadband gap semiconductors, a high surface-to-volume ratio, and light excitation. They can readily be included in the development of biosensors. Metal oxide-based biosensors have recently been developed for a number of applications, such as the detection of H2O2, urea, glucose, and even cancer cells and viruses. In the instance of enzyme-immobilized biosensors, the configuration of the enzyme’s matrix-binding conformation was unaltered by the immobilization of an enzyme on the surface of nanostructured metal oxide (NMO)-based electrodes. Biosensors are hence more reliable and efficient in signal transmission (Zhang et al., 2011). In order to create a range of biosensors, NMO-based immobilizing matrices are currently gaining a lot of attention. NMOs are nontoxic and biocompatible among their many other attributes. A recent study found that NPs and NMOs can be coupled to enhance the characteristics of biosensors. The extraordinary properties of NMOs may offer a variety of avenues for the design of biosensing devices to satisfy future demands for diagnostic equipment, owing to the substantial surface-to-volume ratio, adsorption potential, and other unique characteristics (Raril & Manjunatha, 2020). Selecting the right NMO is essential for the development of a successful biosensor since the binding between the NMO and the biomolecule determines the performance of the biosensor. This

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binding is crucial for fostering a hospitable environment since the biomolecule activity is rather constant. This creates opportunities for the creation of low-cost, extremely sensitive, long-lasting, and LOD-low biosensors (Nguyen et al., 2019).

20.2.2 CNT-based biosensors Zhang et al. used polyethylene glycol to show functionalization (PEG). On the surface of SWCNTs, a functional group termed -COOH was first added, and subsequently, SOCl2 was added to create a group called COCl. It was also coupled with PEG to produce PEG-SWCNTs, which reduced cytotoxicity, caused less membrane damage, and enhanced biocompatibility. The growth of the SWCNTs in the cell membrane and their subsequent transfer to the cytoplasm were made easier by their unique surface chemistry and fibrous structure. The nanotubes interacted with the mitochondria of the PC12 neuronal cell, regulated a gene involved in metabolism, and improved drug delivery (Prinith et al., 2021; Pushpanjali et al., 2020; Pushpanjali, Manjunatha, & Srinivas, 2020). Singh et al. demonstrated the use of ammonium-functionalized MWCNTs (f-MWCNTs) for effective gene transport. f-MWCNTs condensed DNA in a manner similar to that of f-SWCNTs. MWCNTNH 1 , one of these three functionalized CNTs, condensed more DNA than the other two due to its larger surface area for DNA binding. Tao et al. described using poly(amidoamine) dendrimer (PAMAM) fMWCNTs in a metal template. Nitric acid was used to synthesize MWCNTs, which then interacted with it to produce a carboxyl group at the surface. Moreover, it reacted with hydroxyl-functionalized dendrons via an ester linkage to produce their acid chloride derivative, which was subsequently coupled with thionyl chloride to produce PAMAMMWCNTs. Yu et al. presented their research on DNA condensing and improved genetic transformation using polyethyleneimine (PEI)-triggered MWCNT heterojunctions. The heterostructure was produced when MWCNTs interacted with acid to coordinate the carboxylic group, then with PEI with the aid of the EDC/NHC coupling that covalently bound MWCNTs (Borisov & Wolfbeis, 2008; Ronkainen et al., 2010).

20.2.3 Polymer-based polyphosphoric acid biosensors The high surface energy of the SiO2 NPs tends to cause them to form aggregates. Inappropriate dispersion into the polyurethane (PU) matrix

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comes from this. Gao et al. treated the SiO2 NP surface with poly(propylene glycol) phosphate ester to get around this (PPG-P). The esterification of polyphosphoric acid with PPG produced PPG-P.Thef-SiO2 NPs showed a decrease in surface energy, increase in stability, no aggregation, and uniformly distributed SiO2 NPs into the PU matrix. To improve the mechanical strength, thermal stability, and gas permeability of the polymer material, Naka et al. published the organic form of SiO2 NPs as 3aminopropyltriethoxysilane (APTES), 3-mercaptopropyltriethoxysilane (MPTMS), phenyltrimethoxysilane (PTMS), and vinyltriethoxysilane (VTES). The f-SiO2 NPs are denoted as SNP, AP-SNP, MP-SNP, PSNP, and V-SNP, respectively (Sun et al., 2018).

20.2.4 Enzyme-based biosensors The foundation of an enzyme biosensor is a biochemical reaction between an analyte and a biocatalyst placed on a suitable substrate. With the creation of a new generation of biosensors in which active enzyme sites are directly coupled to an NMO electrode, resulting in direct electron transfer between the enzyme and NMO and better biosensing capabilities, nanostructured metal oxides show strong possibilities for bridging biological recognition events with electronic signal transduction. Nanostructured electrodes made of metal oxides provide a biocompatible electroactive surface for the immobilization of enzymes with improved form, orientation, and biological activity (Amine et al., 2006). A lot of oxido-reductases, for instance, contain protein shells that electrically shield their redox centers. Enzymes cannot be reduced or oxidized at the electrode surface at any voltage. The possibility for direct electron transfer between enzymes and the NMO-based electrode surface, which may eliminate the need for co-substrates or mediators and enable efficient transduction of biorecognition events, may aid in the development of improved reagent-less biosensing devices. A redox site frequently finds it challenging to get close to an electrode without delivering a sizable overpotential, which could contaminate the electrode surface and lead to enzyme denaturation. Direct electron transfer can be enhanced by coating an enzyme or electrode with a mediator or a nanoparticle (Sun et al., 2016). To improve biosensing performance in a variety of applications, many strategies have been used to create biosensor components, particularly in the domain of NMO-based immobilizing matrices and transducers

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(electrochemical and optical). Numerous synthetic methods, including doping nanomaterials and creating organic/inorganic nanocomposites, have been used to create nanostructured metal oxides with important optical, electrochemical, and molecular characteristics. Particularly, it has been discovered that NMOs with tailored shape, size (for biocompatibility), functionality, adsorption capability, and high biomolecule loading capacity provide improved electron transfer between biomolecules and electrodes. An NMO’s microenvironment allows an enzyme to maintain its shape while retaining its full biological activity, improving signal transmission and biosensor stability. Surface plasmon resonance has been used to create sensitive and selective biosensors; however, creating such complicated systems takes a lot of effort, money, and knowledge (Raril & Manjunatha, 2020). On the other hand, simple electrochemical methods like cyclic voltammetry can be used to produce biosensors quickly and inexpensively. Differential pulse voltammetry (DPV) can be used to enhance the properties of an electrochemical biosensor. Recently used for signal transduction, electrochemical impedance spectroscopy (EIS) is a nondestructive electrochemical analytical technique that has been particularly helpful in elucidating the mechanisms of charge transfer resistance arising from electron transport between a biomolecule and the electrode surface. Many biomedical and environmental applications hold considerable potential for electrochemical devices because of their benefits in terms of size, cost, detection limit, response time, long-term stability, and power requirements. Numerous electrochemical biosensing devices with enhanced sensitivity and selectivity have been created using nanostructured metal oxides with a variety of surface designs.

20.3 Recent development in nanostructured biosensors The evolving field of biomedical diagnosis is continuously influencing the development of NBBD. Lab-on-a-chip is the result of advancements in miniaturization, microfluidics, and the integration of all assay procedures and/or reagents onto a miniature device. By combining sensors, fluidics, and signal processing circuits, nanotechnology will enable the continued shrinking of bioanalytical systems, enabling the large-scale integration of many biological reactions on a single platform (Turner et al., 1987; Turner, 2013). Integrated lab-on-a-chip devices are still being developed, and numerous nanotechnology components will be used. In the past 10 years, the

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domains of in vitro diagnostics, imaging, and therapies have seen an extensive application of NMs. They have made it possible to simultaneously identify several disease biomarkers and to diagnose diseases at an extremely early stage. They have also made it possible to investigate the detection of ultra-trace concentrations of target analytes and have produced ultrasensitive, quick, and economical assays that only require a small amount of sample. The most promising options for the creation of high-throughput protein arrays are thought to be the NMs. The necessary materials with precise absorptive, emissive, and light scattering capabilities can be created by adjusting the size, shape, composition, structure, and other physical/chemical features of NMs. Additionally, the bioconjugated NPs have been used for assays and other biomolecule recognition events that need signal amplification. However, point-of-care diagnostics, which will allow patients and primary-care doctors to conduct assays in their various settings, will be the most promising area of nanotechnology use. In addition to their brightness and sharp bandwidth, NPs’ long-term stability will be crucial for developing novel techniques for the identification, validation, and application of ultrasensitive biomarkers in clinical settings. The utilization of nanostructures (nanopores, nanowires, nanopillars, and nanogaps)-based devices can further give the single-molecule detection capabilities. Gold nanoparticles (AuNPs) can be used to identify the genetic sequence in a sample. The NMs-based imaging agents provide extra information relevant to the physiology and function apart from the anatomical information, which enables more accurate and early illness diagnosis, such as the very sensitive identification of early-stage cancer, consequently leading to improved therapy. Similarly, it is possible to track treatment effectiveness more promptly and precisely. Targeted treatments will use plasmonic nanoparticles (NPs) and drug delivery, and the initial applications will undoubtedly be in the treatment of cancer. The pharmacokinetics and bioavailability of medicines are enhanced by the use of NPs (Manjunatha & Hussain, 2022; Manjunatha, 2020). By avoiding the exposure of healthy tissues, they deliver the medications directly to the disease-causing locations in the body, increasing their availability at the target site and lowering the treatment dose. These nanotechnology advancements will be very helpful in converting from late-stage diagnosis (including expensive and socially demanding therapy) to early-stage diagnosis (relatively less expensive and less invasive). The following is a description of the most popular NMs in NBBD (Jeevanandam et al., 2018).

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20.4 Issues: safety Different heavy metal ions, such as Pb2 1 , Hg2 1 , Ag 1 , Cd2 1 , and Cu2 1 , are present and come from a variety of sources. These ions have a dangerous impact on people and their surroundings. The continuous growth of agricultural and industrial achievements, together with the insufficient discharge of heavy metal ions from wastewater and residential emissions, all contribute to the accumulation of heavy metals in various settings (Sun et al., 2015, 2016). The ferreting out of the trace heavy metal ions by skillful procedures is therefore highly wanted to ensure the security of the environment as well as the health analysis (Alocilja & Radke, 2003; Mantecca et al., 2017).

20.5 Issues: health Bionanomaterials may also be linked to risk factors despite their benefits. Bionanomaterials have the potential to harm many human organs and tissues and are linked to a number of illnesses. Neurological problems may be accelerated by nanoparticle exposure (e.g., Parkinson’s disease and Alzheimer’s disease), lung (asthma, bronchitis, emphysema, and cancer), and cardiovascular diseases (atherosclerosis, arrhythmia, thrombosis, and hypertension). Nanoparticle exposure can also result in additional skin issues such as urticaria, dermatitis, and skin irritation. The exposure time and dose are two main elements that affect how harmful the various nanomaterials are. By dividing the molar concentration of nanoparticles in the media by the exposure period, the exposure dose can be calculated. The toxicity of the nanoparticles may, however, also be influenced by additional variables (such as aggregation and concentration effects). For example, some nanoparticles can group together. The toxicity of these aggregates (in the micrometer range) may be reduced since they may not easily enter the body. The size of the nanoparticles also affects their toxicity because smaller nanoparticles, such as those less than 10 nm, can pass through cell membranes and may be more dangerous than bigger ones (Siegrist et al., 2019). The toxicity of nanoparticles is also influenced by their shape, and this toxicity may vary depending on the aspect ratio. For instance, smaller asbestos fibers can cause mesothelioma and asbestosis while larger asbestos fibers can cause lung cancer. The nanoparticles effect is thus directly related to surface area and inversely proportional to nanoparticles size. The crystal structure can also have an impact on oxidative

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processes, subcellular localization, and cell uptake. For instance, a comparison of two polymorphous TiO2 NP structures revealed that one oxidizes DNA damage but not the other. Through oxidation and translocation mechanisms, the surface characteristics of the nanoparticles can potentially contribute to their hazardous effects (Leggiadro, 2000; Verstrepen et al., 2004).

20.6 Issues: food Only foods that are fresh and devoid of pollutants and contaminants are fit for consumption. It is indeed difficult to find food contaminants and adulterants at low levels with standard detection systems. As a result, nanoparticles were investigated for their high sensitivity in detecting harmful substances and bacteria (Manjunatha Charithra & Manjunatha, 2020; Ping et al., 2012). When food items are stored over their expiration date and are exposed to air and moisture, they typically deteriorate. Individual packets cannot be tested for food deterioration in a lab. Instead, spot indicator-based nanoparticles are sensitive and simple to label on individual shipments (Griesche & Baeumner, 2020; Singh et al., 2011). A category of poisonous and cancer-causing substances known as aflatoxins are present in food that has been tainted with Aspergillus flavus and Aspergillus parasiticus. For the detection of aflatoxin B1, bifunctional nanoparticles using antiaflatoxin antibodies have been employed. Aflatoxin M1 has also been found in milk using superparamagnetic beads carrying antiaflatoxin M1 antibodies and gold nanoprobes (Amine et al., 2006; Thakur & Ragavan, 2013). The antioxidants and vitamins included in food products are easily broken down. Vitamins in food items have been detected using nanoparticles. Anemia, cancer development, and heart attacks can all result from folic acid deficiency. It has been claimed that MWCNT and SWCNT
ionic liquid nanocomposites can detect folic acid in wheat flour, fruit juices, and milk samples. NiO NPs have been used for the identification of vitamin and ascorbic acid (Wang et al., 2014; Wang et al., 2022).

20.7 Issues: agriculture The significant concerns from scientists about the detrimental effects of agricultural production on biodiversity have reassured green initiatives

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toward sustainable agricultural practices. To avoid the harmful consequences of soil pollutants and/or toxins, quick identification is necessary. In particular, the community of nanobiosensors values the achievements of nanotechnology. Additionally, the significance of biosensors was noted in the environmental and/or soil health assessment. Due to their outstanding characteristics, nanostructured metal alloys satisfy this requirement, particularly those made of carbon nanotubes, graphene (Kosynkin et al., 2012), and photothermal conversion nanoparticles, and have a promising future in the field of microbial detection in soil (Velasco-Garcia & Mottram, 2003). Along with the rapidly diminishing amount of land and rising production costs, the growing global population and the depletion of natural resources are among the main obstacles to the sustainability of the agricultural and food industries (Silva et al., 2019). The efficient use of natural resources is based on the application of nanosensors. In particular, nanobiosensors have a wide range of uses in the agri-food chain, including the detection of soil conditions, the management of severe infections, the detection of crop diseases brought on by pests and pathogens, and the use of diagnostic tools for pest detection during storage and final quality assurance (Griesche & Baeumner, 2020). In order to give both academic and industrial researchers insightful information, the benefits and limitations are also explored. Additionally, new patents have been highlighted in order to give the agri-food business the most recent developments in biosensors and ensure sustainable development. Due to their wide range in the hereditary and physiological domains, biomaterials have become desirable identification instruments in the worldwide industry. They are able to calculate the behavioral, immune, and metabolic reactions of cattle and fishery animals (Manjunatha Charithra & Manjunatha, 2020). To examine the different aspects influencing the environment and the physiology of animals, innovative biosensing techniques proposed extremely customized monitoring systems. Such devices provide a quick analysis of the monitoring parameters and are dependable, simple to use, extremely sensitive, and selective. Nanobiosensors have significant applications in the management of livestock, including the monitoring of health, the detection of infectious disease-causing agents and reproductive cycles, health status, animal feeding, and grazing behavior, antibiotic side effects, and the living conditions of animals (Tothill, 2001).

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20.8 Regulations Strong chemical bioactivity and reactivity, the ability to permeate cells, tissues, and organs, and improved bioavailability are all characteristics of nanomaterials. NMs are excellent in biomedical applications due to their unique characteristics (Jantzen et al., 2016). These benefits, however, can come with a toxicity risk. As a result, a number of government organizations have implemented controls through laws, statutes, and rules to lessen or completely eradicate worries about NMs. Toxicology testing, environmental impact assessment, and production, handling, and labeling standards, protocols, or legal definitions are all lacking in detail on the worldwide level. The USA and the European Union (EU) currently have strong regulatory frameworks and directive legislation to reduce any hazards associated with NMs. NMs are expressly mentioned in a number of technical recommendations and EU laws that the European Commission has issued. To guarantee regulatory uniformity and that an NM used in one sector would have been regarded similarly when it was used in others, this rule has indeed been applied inside the EU. The requirements of the products and substances meet the requirements of the European Chemical Agency’s (REACH) and the European Classification and Labelling of Chemicals’ (CLP) substance definitions, making the provisions of these regulations relevant. In order to calculate the hazards related to NMs, the EU has also established the Scientific Committee on Emerging and Newly Identified Health Risks (SCENIHR).

20.9 Conclusion Approaches for making synthetic and organic carbon nanoparticles saferby-design primarily focus on lowering risk and preventing the release of bionanomaterials into the surroundings. In reality, the emphasis on dangers is frequently on hazardous situations or portions of said total dangers. Inadequate toxic information, discrepancies between experimental nano and those that individuals or cells are exposed to in real life, and barter between usefulness and safety are significant barriers to safer-by-design. The management of size, doping, loading, regulating form and crystallinity, and lowering the amount of chemicals at the surface of nanoparticles which lead to danger are a few of the suggested methods for reducing the risk for bionanomaterials.

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Nanomaterial releases could be minimized by isolating nanomaterial production and processing, improving the integrity and toughness of nanocomposites, designing products to be disassembled, and effectively recycling materials. When creating nanocomposites, one may try to discharge less dangerous pieces into the environment during the use stage. However, once in the environment, such pieces released from nanocomposites can become more dangerous.

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CHAPTER 21

Advances in green synthesis of nanostructured biosensors Didem Nur Unal1,2, Ipek Kucuk1,2, Cem Erkmen1,3 and Bengi Uslu1 1 Faculty of Pharmacy, Department of Analytical Chemistry, Ankara University, Ankara, Türkiye The Graduate School of Health Sciences, Ankara University, Ankara, Türkiye 3 Faculty of Science, Department of Chemistry, Hacettepe University, Ankara, Türkiye 2

21.1 Introduction Nanotechnology is the branch of science associated with the synthesis of nanosized materials and their use in various applications. Nanoparticles can be defined as materials with sizes between 1 and 100 nm. As the size of the substances decreases, the surface area increases. The very small size of the nanoparticles provides a high surface-to-volume ratio. Increasing this ratio makes the nanoparticles more chemically reactive. They have different and enhanced magnetic, optical, electrical, physical, biological, chemical, and mechanical properties compared to macrosized materials (Rajapaksha et al., 2021). Nanoparticles can easily penetrate the cell, reaching the cell nucleus and mitochondria. Oral, dermal, or respiratory exposure of humans to nanoparticles can lead to a variety of toxicological effects, such as DNA damage and oxidative stress (Kumar Das et al., 2022; Marouzi et al., 2021). Several physical and chemical approaches can be used to create nanoparticles, but both have drawbacks. For example, the chemical method uses hazardous materials and requires long, expensive synthesis processes, whereas the physical method uses expensive machinery and high energy requirements (Campuzano et al., 2021). In recent years, researchers have led to a green synthesis approach, which is an environmentally friendly, less costly, and efficient nanoparticle synthesis method, to reduce these negative effects. The green synthesis method is an approach to reduce the carbon footprint, thus avoiding the climate change problems that have increased in recent years (Garner & Keller, 2014). Natural resources such as microorganisms and plants are extremely valuable because of their accessibility and affordability, and the compounds they contain can serve Novel Nanostructured Materials for Electrochemical Bio-sensing Applications DOI: https://doi.org/10.1016/B978-0-443-15334-1.00019-5

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as reducing agents during the synthesis step. This method, which blends green chemistry with nanotechnology to generate harmless materials, is a crucial step in preventing adverse impacts on both human health and the environment (Aarthye & Sureshkumar, 2021; Agarwal et al., 2017). Electrochemical biosensors attract great attention from researchers due to their simple and convenient design, high sensitivity, and miniaturization and are suitable for the development of portable devices (Maduraiveeran et al., 2018). In recent years, with their rising popularity and advances in science, electrochemical sensing platforms have also made great advances. In electrochemical biosensors, gold, silver, platinum, glassy carbon electrodes (GCEs), carbon paste electrodes (CPEs), pencil graphite electrodes (PGEs), and screen-printing electrodes (SPEs) are used to generate analyte-dependent signals (Balliamada Monnappa et al., 2019; Hareesha, Manjunatha, Amrutha, Pushpanjali, et al., 2021; Hareesha, Manjunatha, Amrutha, Sreeharsha, et al., 2021; Manjunatha, 2019; Pushpanjali et al., 2020; Prinith & Manjunatha, 2020; Prinith et al., 2019; Raril & Manjunatha, 2018). Electrodes that have not been modified with any nanomaterial may pose limited sensitivity and stability problems. In addition, factors such as pH and ionic strength during the immobilization or incubation stages of biological molecules in the sensor affect the responses of important biosensor classes such as immunosensors (Grieshaber et al., 2008). For this reason, these negative effects can be prevented by using nanomaterials (carbonaceous materials, metal, metal oxides, bimetallic, etc.) in the creation of these biosensor platforms. The concept of green chemistry is also reflected in the designs of these platforms (Zhang & Wei, 2016). With the acceleration of green nanotechnology studies, the working electrodes used in electrochemical biosensors have begun to be modified with natural-origin nanomaterials. The use of these nontoxic green nanoplatforms is of great interest as they increase the sensing properties of the biosensor. In this chapter, the types of nanomaterials produced by the green synthesis method, green chemistry, their advantages in terms of human health, and current electrochemical biosensor applications using these nanomaterials are discussed. The advantages of nanoplatforms prepared using naturally sourced consumables for enzyme-based biosensor, immunosensor, and aptasensor applications in terms of parameters such as detection limit, detection range, accuracy, precision, and sensitivity are discussed. In conclusion, possible challenges and solutions in building green nanoplatforms and future prospects are given.

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21.1.1 Green nanomaterials Green synthesis of nanoparticles is simple, cost-effective, and eco-friendly, allowing them to be produced in a minimum time and with less effort, hence obtaining highly functional products with low toxicity. Green synthesis is one step ahead of other synthesis methods because it does not require the use of toxic and carcinogenic substances that threaten human health. The use of renewable chemicals has facilitated the work of researchers in the laboratory and has been a response to their needs. Thus the toxicological effects that will occur from human exposure are eliminated (Kumar Das et al., 2022). This method also offers researchers a sustainable, promising alternative by reducing the possibility of environmental hazards (Dönmez, 2020). Synthesis can be carried out in one step using biological organisms such as bacteria, yeasts, algae, and plants. Using this method, nanoparticles of the desired size and shape can be synthesized and easily characterized. Microorganisms can also be used to produce nanoparticles, but the rate of synthesis is slow, and only a limited number of sizes and shapes are suitable for this method compared to synthesis methods involving plant materials (Alsaiari et al., 2023; Khan et al., 2018), Pseudomonas aeruginosa (Zaynitdinova et al., 2018) and Escherichia coli (Hassan & Mahmood, 2019) are examples of bacterial species most used to obtain green nanoparticles. Plants are the most commonly used materials in the green synthesis method. Various parts of plants such as leaves, roots, latex, fruits, seeds, and stems are used. During the processes of biological synthesis that take place, secondary metabolites belonging to these parts of plants are considered the active component of the synthesis process. These metabolites are phytochemicals used as reducing agents, such as terpenoids, flavonoids, carotenoids, alkaloids, vitamins, tannins, saponins, and phenolic acids. They can be used as a reducing and a capping agent for the synthesis and stabilization of nanoparticles (Hayrunnisa et al., 2017; Noah & Ndangili, 2022). Using various plant extracts, carbon-based such as carbon quantum (Chellasamy et al., 2022; Rezaei et al., 2018; Rooj et al., 2018), carbon nanotube (Sivasakthi et al., 2020), graphene (Chinnaraj et al., 2021; Singh et al., 2016) nanomaterials can be synthesized, as well as metal (Basavegowda & Rok Lee, 2013; Khalilzadeh & Borzoo, 2016) and metal oxide nanoparticles (George & Mathew, 2020; Zheng, Huang, Shi, Fu, 2019). In the literature, many studies have been carried out using different plants in obtaining nanoparticles, and the number of these studies is

544

Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

increasing today. For example, there are a number of studies using various parts of plants such as Camellia japonica leaves (Karthik et al., 2017), Citrus sinensis peels (Masibi et al., 2020), Zingiber officinale roots (Dönmez, 2020), and Annona squamosa seed (Singh et al., 2021) extracts. Fig. 21.1 shows the stages of metal nanoparticle synthesis from plant extracts. These nanomaterials are used alone or with different carbon, metal, and metal oxide nanomaterials in the construction of green biosensors. Moussa et al. performed for the first time a new one-step synthesis of reduced graphene oxide (rGO) decorated with silver nanoparticles (rGO-AgNPs) using Allium sativum (garlic) extract, which is both costeffective and environmentally friendly. For the preparation of garlic extract, which is used as a reducing agent in green synthesis, first garlic cloves were washed and cut into small pieces. About 80 g of crushed garlic was added to 200 mL of distilled water and mixed in a magnetic stirrer at 80°C for 1 hour. The obtained extract was used as a green reducing agent in the synthesis of nanoparticles. The resulting rGOAgNPs were successfully integrated with molecularly imprinted polymer (MIP) to selectively and sensitively detect lactic acid, an important agent in cancer cell screening. In this study, high selectivity and high sensitivity were obtained by replacing expensive enzymes with molecularly imprinted polymers. At the same time, the study has advantages over other reported methods such as simplicity and cheapness thanks to green approaches (Ben Moussa et al., 2022).

Figure 21.1 Synthesis steps of metal oxide nanoparticles (MONPs) by green synthesis method. Modified from Marouzi, S., Sabouri, Z., & Darroudi, M. (2021). Greener synthesis and medical applications of metal oxide nanoparticles. Ceramics International, 47(14), 19632
19650. https://doi.org/10.1016/j.ceramint.2021.03.301.

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Chinnaraj et al. produced a low-cost and environmentally friendly AgNPs/GO nanocomposite using Goniothalamus wightii (G. wightii) leaves as a reducing and stabilizing agent. G. wightii was washed thoroughly with distilled water, cut into small pieces, and then dried. The dried leaves (25 g) were finely ground and pulverized. The extract was prepared by keeping 2 g of biomass (G. wightii leaves) in a 250-mL conical flask with 100 mL of distilled water for 24 hours. As a result of the addition of 10 mL of G. wightii leaf extract to 90 mL of silver nitrate aqueous solution, Ag ions were reduced, and as shown in Fig. 21.2, the color of silver nitrate has changed from colorless to brown. The obtained nanomaterial-modified GCEs were used as sensitive sensors for the quantification of antiprotozoal and antibiotic metronidazole (MIZ). The AgNPs@GO nanocomposites have successfully detected MIZ in pharmaceutical tablets, making them more suitable for applied application (Chinnaraj et al., 2021). In another study, Shivakumar et al. obtained AgNPs by green synthesis method using Eucalyptus extract. Hemicellulose is used as a reducing agent in green synthesis of AgNPs. GCE modified with NPs was used for nitrobenzene determination using differential pulse voltammetric technique (DPV). The study has shown that metal nanoparticles produced by green synthesis can be useful as components of sensors (Shivakumar et al., 2020). Khan et al. used Astragalus membranaceus extract as a reducing and capping agent to stabilize the metal and prevent the aggregation of

Figure 21.2 Synthesis of GO@AgNPs with Goniothalamus wightii extract solution and its UV spectrum. With permission from Chinnaraj, S., Palani, V., Yadav, S., Arumugam, M., Sivakumar, M., Maluventhen, V., & Singh, M. (2021). Green synthesis of silver nanoparticle using Goniothalamus wightii on graphene oxide nanocomposite for effective voltammetric determination of metronidazole. Sensing and Bio-Sensing Research, 32, 100425. https://doi.org/10.1016/j.sbsr.2021.100425.

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nanoparticles during the ZnO nanoflower synthesis procedure. CPE modified with ZnO nanoflowers was used in the determination of 4nitrophenols. In the determination made using the cyclic voltammetry (CV) method, the lower limit of the determination was obtained as 0.08 M. Phenolic compounds from Astragalus membranaceus not only provided a low detection limit but also facilitated electron transfer (Khan et al., 2021). Green nanomaterials have properties such as insulator, optical, antimicrobial, antioxidant, anti-metastasis, biocompatibility, stability, and manipulability. Furthermore, biosynthesized nanoparticles are used in many different applications such as targeted drug delivery (Memon et al., 2020; Zamarchi & Vieira, 2021), cancer therapy (Sharifi et al., 2019), antibacterial agents (Sharmila et al., 2017; Singh et al., 2016), and sensors—biosensors (Dayakar et al., 2018; Thenrajan et al., 2022). The green synthesis method has attracted an increasing amount of interest due to the need for the development and production of biosensors (Lu et al., 2013; Rawtani et al., 2020). Analytical applications of green nanomaterials include catalytic application and used as a component of sensors.

21.1.2 Electrochemical biosensors Sensors are systems that can translate changes in an environment into detectable signals. Biosensors allow a biological event to be converted into an electrical signal. The primary purpose of the biosensor is to provide fast, accurate, and reliable information about the analysis. Biosensors are the result of the reaction of a biological component that selectively interacts with the substance to be analyzed into a meaningful signal and then used with a mechanism that transmits this signal (Chakraborty & Hashmi, 2021; Kim et al., 2023). Biosensors consist of the following basic components. These biological elements called analyte-specific bioreceptors (e.g., enzyme, DNA probe, antibodies, aptamers) and transducer segments are used to convert the signal resulting from the interaction of the analyte with the bioreceptor into an electronic signal. Bioreceptors contain a selective recognition mechanism because they have a biomolecular structure. They are highly sensitive biological structures that selectively interact with the substance to be analyzed. This specific interaction prevents the interference of signals from other substances with the desired biosensor signal (Rezaei et al., 2018).

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The signal is amplified via a signal processor and presented as digital data. Transducers are the part that converts the biological reaction of bioreceptors into a meaningful, measurable electrical signal. These can be of various types such as optical, electrochemical, piezoelectric, calorimetric, and thermal. Electrochemical methods are frequently used in biosensors today because of their low cost, simple design, and minimizable features (Dolatabadi et al., 2011; Maduraiveeran et al., 2018). Nowadays, electrochemical biosensors are widely used in the analysis of biomarkers, vitamins, drug substances, enzymes, chemical residues, and foodstuffs (Grieshaber et al., 2008).

21.2 Fabrication of electrochemical nanobiosensors For the effective development of biosensors, parameters such as stability, fast response time, and low limit of detection (LOD) should be considered for the selective detection of analytes. The following problems can be overcome with the use of nanomaterials in the fabrication of electrochemical biosensors. • Stability: vulnerable to atmospheric and environmental degradation. • Slow response time: by weakly binding analyte-specific bioreceptors. • Low LOD: low sensitivity. • Poor reproducibility: low accuracy. Thanks to the more stable surfaces obtained after nanomaterial modification, it provides reproducible platforms to be obtained. The use of nanomaterials and biorecognition elements of the biosensor, such as DNA, RNA, aptamers, enzymes, and antibodies, is placed on the transducer surface with high stability and stability. As a reflection of nanotechnological developments, the developed nanobiosensors contribute to new technologies such as lab-on-a-chip and wearable sensors, which are integrated into the smartphone and provide bedside analysis. The use of nanomaterials exhibiting unique physical, chemical, and optical properties in electrochemical biosensor platforms leads to increased sensitivity and selectivity. These nanomaterials can be modified to the sensor surface by physical adsorption using electrostatic force, van der Waals forces, and hydrogen or ionic bonds. With the chemical method, modification is carried out using strong chemical bonds, such as covalent bonds, between the functional group of the biological recognition element and the surface of the converter (Sandhyarani, 2019; Sassolas et al., 2012).

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Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

Surface functionalization of nanomaterials increases their binding affinity, which could be useful in the development of nanobiosensors that can detect analytes. Also, surfaces of nanomaterials can be coated with surfactants, biomolecules, and other agents. Nanomaterials have been shown to be particularly beneficial for the construction of nanobiosensors because they have a large surface area, a porous structure, a high loading capacity, and can bind selectively to the analyte (Nayak et al., 2022).

21.2.1 Use of green nanomaterials in electrochemical nanobiosensors Green nanomaterials can be used as components of biosensors with their biocompatible structures, low pollutant waste consumption, and easy synthesis, providing unique properties to the electrochemical biosensor surface. These nanomaterials have important effects on the analytical properties of biosensors such as stability, selectivity, reproducibility, and sensitivity. Improving the mentioned features of biosensors at lower cost allows them to be used in many different areas. Table 21.1 summarizes the information on electrochemical biosensor platforms created with various green nanomaterials. 21.2.1.1 Green nanostructures in enzyme-based biosensors Electrochemical converters are frequently used in enzyme-based biosensors, which are based on quite old enzymes. Enzymes immobilized on the nanobiosensor platform help to determine various analytes according to the catalytic reaction rate that occurs with biological mechanisms. The mode of action for enzymatic measurement may be from the rate of analyte metabolized by the enzyme, the rate of activation/inhibition of enzymes by the analyte, or the rate of change in enzyme change by the analyte (Sassolas et al., 2012; Soylemez & Kurbanoglu, 2021). Current studies show that the development of green synthesis nanostructures for use in various biosensor applications is a relatively new field. There are not many studies available on the use of green synthesis nanomaterials in amperometric biosensors. Gayda et al., discovered the properties of extracellular biological reduction of Cr(VI) through Cr(V) to Cr(III) by some yeasts, including baker’s yeast as well as nonconventional yeasts (Candida guilliermondii, Ogataea polymorpha, etc.). In the previous study of the same group, green gold nanoparticles (AuNPs) were synthesized by the yeast Ogataea polymorpha. Different sizes (20
40 nm) and shapes have been synthesized, from triangular nanoprisms to nearly

Table 21.1 Selective studies of green nanostructured electrochemical biosensors. Analyte

Green sources

Assay strategy

Electrode surface

Technique

Linear range

LOD

Application

References

H2O2

Ficusiacertiolia Maca

Nonenzymatic

PGNSs/Nafion/GCE

CV

0.2
19 mM

2.75 μM




Nonenzymatic

CuO NPs

CV

0.625
5 μM

Liang et al. (2019) Ilgar et al. (2022) Bilge et al. (2020)

Dopamine

5 μM
5



11

Vardenafil

Cystoseira algae biomass

Microbialbased

MWCNT/GCE

DPV

1 3 10
1 3 1

H2O2

Lepidium meyenii

Nonenzymatic

Ag NPs/cotton fabric

I-V

0.5
5000 μM

33.52 nM

Human serum and urine samples, tablet


Lactose

Trametes villosa Zingiber officinale Ocimum tenui florum Ocimum tenui florum Peach fruit

Enzyme-based

AuNPs/graphite

CV

10
300 μM

3.5 μM




Enzyme-based

ZnONPs/CPE

CV

0.01
1.0 mM

14.7 μM




Nonenzymatic

CuNPs/GCE

CV

1
7.2 mM

0.046 μM




Nonenzymatic

ZnONPs/GCE

CV

1
8.6 mM

0.43 μM




Dayakar et al. (2018)

Enzyme-based

ZnO@NDCS/GCE

DPV

0.2
12 mM

6.3 μM

Blood serum samples

Muthuchamy et al. (2018)

Glucose Glucose

Glucose

Glucose

10

M

9.63 3 10 M

Karaku¸s, Baytemir, Ta¸saltın (2022) Bollella et al. (2017) Dönmez (2020) Dayakar et al. (2017)

(Continued)

Table 21.1 (Continued) Analyte

Green sources

Assay strategy

Electrode surface

Technique

Linear range

LOD

Application

References

Glucose

Aspergillus niger Banana peels

Enzyme-based

Au
ZnAgNPs/ITO

CV

0.1
8 mM

0.02 mM




DNA-based

Pd-Au@CDs/GCE

CV

5.0 3 10 216
1.0 3 10210 M

1.82 3 10
17M

Fenugreek seeds Okara

Enzyme-based

Pd-rGO/ITO

CV

25
400 mM

25 mM

Human serum sample


Du et al. (2013) Huang et al. (2017)

Nonenzymatic

N-GMNs/ITO

Amperometry

10
5640 μM

0.51 μM

Colitoxin DNA

Triglycerides Vitamin C Glucose

Aspergillus niger

Enzyme-based

ERGO-AuPdNPs/GCE

DPV

0.5
3.5 mM

6.9 μM

Epinephrine

Cassava tubers

Nonenzymatic

Fe2O3/GCE

SWV

100 nM
1mM

11 nM

Methyl parathion

Burkholderia cepacia

Enzyme-based

MOF nanofibers/ chitosan/GCE

DPV

0.1
38 μM

0.67 μM

Glucose

Aspergillus niger

Enzyme-based

rGO/AuNPs/GCE

CV

2
10 mM

0.9 nM

Lactic acid

Allium sativum

Nonenzymatic

rGO-AgNPs/MIP/AuE

CV

10
250 μM

0.726 μM

Beverage juice Human blood serum sample Black tea and coffee samples Lettuce and cabbage samples Peach juice (cappy), coke (coca cola) Human serum, blood, urine samples

Singh et al. (2016) Sha et al. (2019) Yang et al. (2011)

Thenrajan et al. (2022) Wang et al. (2019) Çakıro˘glu and Özacar (2017)

Ben Moussa et al. (2022)

Enzyme-based

NCD/BSA/PGE

CV

10
250 nM

8.6 nM




Enzyme-based

BiFeO3/CPE

Amperometry

2.0 3 1027
1.0 3 1025 M

0.080 μM

Bambusa arundi nacea leaves Laurus nobilis

Nonenzymatic

AgNPs/SPGE

CV

1
2 mM

2 μM

Milk, straw berry milk, cacao milk samples Human blood samples

Enzyme-based

CNT/GO/C/SPE

CV

1
10 μM

7.0 nM




Pyrazinamide

Pear juice

Enzyme-based

GO/AgNPs/GCE

CV

100
600 μM

0.0029 nM




Ethambutol Glucose

Pine leaves

Nonenzymatic

Ni/CQDs/GCE

CV

200
1200 μM 0.005
8.0 mM

0.0067 nM 0.98 μM

Canavalia ensiformis Convolvulus pluricaulis Manilkara zapota Paederia foetida

Enzyme-based

LNPs/GCE

CV

-

0.85 μM

Chicken serum and human serum samples


Enzyme-based

Gr/PPy/AgNPs

Amperometry

0.001
0.0015 mM

0.47 μM

Tea sample

Enzyme-based

gRGO-PPy/GCE

CV

0.01
6 mM

3.78 μM

Human serum sample

Diazinon H2O2

Glucose

Propofol

Glucose Catechol

Cholesterol

Apis mellifera Lepidium sativum

Bilal et al. (2022) Caglar et al. (2021)

Jayarambabu et al. (2023) Ferrier, Kiely, Luxton (2022) Ajay et al. (2020) Yang et al. (2021)

Capecchi et al. (2020) Sandeep et al. (2019)

Pramanik et al. (2018) (Continued)

Table 21.1 (Continued) Analyte

Green sources

Assay strategy

Electrode surface

Technique

Linear range

LOD

Application

References

Phenylketonuria

Neckera com planata

Enzyme-based

ZnO@Au/SPE

DPV

0.005
100 μM

0.003 μM

Human serum samples

Acetaminophen

Solanum panicu latum L. Abelmoschus esculentus

Enzyme-based

CPE

DPV

5
245 μM

3 μM




RahimiMohseni et al. (2021) Antunes et al. (2018)

Enzyme-based

rGO/PPy/GCE

LSV




0.275 mM




Nitrate

Glucose

Garcinia mango stana

Enzyme-based

rGOAunano/GCE

CV

1.0
8 mM

10 μM

Human serum sample

Prostatic-specific antigen

Calendula officinalis L. Euphorbia hirta Durian extract Ogataea poly morpha p-Glu

Antibodybased

AuNPs-AgNPs/GCE

EIS

0.1 pM
100 nM

0.087 pM

Enzyme-based

Ag/CeO2/GEs

CV







Human serum sample


Antibodybased Enzyme-based

FeNPs/IDE




15 pM

8
250 pM




GPdNPs/GEs

Amperometry




0.014 mM




Antibodybased

WO3/GCE

DPV

50 nM
0.5 pM

0.5 pM




Glucose Anti-CCP Bisphenol HER-2

Umar and Nasar (2018) Amouzadeh Tabrizi and Varkani (2014) Darvishi et al. (2021) Vennila et al. (2018) Zhou et al. (2022) Gayda et al. (2019) Nasrollahpour et al. (2021)

β-casomorphin

Green redox probe

Aptamerbased

AgNP/QD/GCE

EIS

1 pM
20 nM 20 nM
1.3 μM

32 fM

Staphylococcus aureus

Spongin

Aptamerbased

DPV

10
108 CFU mL21

1 CFU/mL

Adenocarcinoma gastric cell

Thyme leaves

Aptamerbased

SponginCu2WO4(OH)2@AgNPs/GCE Au@AgNPs/MWCNT/ SPE

Amperometry

1 3 101
5 3 105 cells mL21

6 cells mL21

Urine and blood serum samples Human serum samples Human blood

Shahdost-fard and Roushani (2020) Shahdost-Fard et al. (2023) Amouzadeh Tabrizi et al. (2017)

AgNPs, Silver nanoparticles; Anti-CCP, anti-cyclic citrullinated peptide antibody; AuNPs, gold nanoparticles; AuE, gold electrode; AuPdNPs, gold palladium (1:1) bimetallic nanoparticles; BCL, Burkholderia cepacia lipase; CeO2 ceric oxide; CFU, colony-forming unit; CILE, carbon ionic liquid electrode; CNTs, carbon nanotubes; CPE, carbon paste electrode; CQDs, carbon dots; Cu2WO4(OH)2, copper tungsten oxide hydroxide; CuONPs, copper oxide nanoparticles; CV, cyclic voltammetry; DPV, differential pulse voltammetry; EIS, electrochemical impedance spectroscopy; ERGO, electrochemically reduced graphene oxide; Fe2O3, iron(III) oxide; FeNPs, iron oxide nanoparticles; GOx, glucose oxidase; gPdNPs, Pd-based gNPs; H2O2, hydrogen peroxide; HER-2, human epidermal growth factor receptor 2; HRP, horseradish peroxidase; IDE, interdigitated electrode; ITO, indium tin oxide; I-V, current
voltage; LS, lignosulfonate; LSV, linear sweep voltammetry; MIP, molecularly imprinted polymer; MOF, metal
organic framework; MWCNTs, multiwalled carbon nanotubes; N-CD, nitrogen-doped carbon dots; N-GMNs, nitrogen-doped graphene-like mesoporous nanosheets; Ni, nickel; NR, nitrate reductase; Pd, palladium; PdNPs, palladium nanoparticles; PGE, pencil graphite electrode; PGNSs, porous graphene-like nanosheets; PPY, polypyrrole; rGO, reduced graphene oxide; SA, saffron; SPGE, screen-printed gold electrode; SWV, square-wave voltammetry; WO3: tungsten(VI) oxide; ZnONPs, zinc oxide nanoparticles; ZnO, zinc oxide.

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Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

spherical and hexagonal ones. In this study, different green metallic nanoparticles such as AuNPs, AgNPs, Cr2O3NPs, PdNPs, and PtNPs were synthesized by using extracellular metabolites of Maya Ogataea polymorpha as reducing agents. They investigated the inhibition properties of laccase and alcohol oxidase enzymes of these synthesized green metallic nanoparticles. According to the results obtained with various characterization techniques such as X-ray microanalysis (SEM-XRM), AFM, and FTIR, PdNPs with the most effective results were selected for the enzyme biosensors to be created (Gayda et al., 2019). These enzyme-based amperometric nanobiosensors were prepared with green PdNPs. The graphite working electrodes (GE) were modified with green PdNPs by the drop-casting method. Then, enzyme biosensors were obtained by dripping laccase, alcohol oxidase (AO), and horseradish peroxidase (HRP) enzymes onto modified GE/PdNPs. For the stability of the biorecognition element, a mixture containing 1% chitosan and 0.5% polyethyleneimine solutions (1:1, v/v) was used on the biosensor surfaces. The analytical properties of laccase/GE and PdNPs-modified laccasegPdNPs/GE were studied by chronoamperometry to show their activities against two known laccase substrates, bisphenol A (BPA) and 2,2'-azinobis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS). Laccase-gPdNPs/GE was found to have a 1.5 times smaller sensitivity but a 1.2 times wider linear range compared to laccase-GE. Similarly, AO/HRP-gPdNPs/GE has a 1.6-fold wider linear range for methanol than results obtained by chronoamperometry of unmodified AO/HRP/GE and modified AO/HRPgPdNPs/GE against substrate methanol. found. As a result, according to the results obtained with different enzyme biosensors, green PdNP came to the forefront with the advantages of being less sensitive to substrates but with both a wide linear range and high stability (Gayda et al., 2019). In another study, zinc oxide nanoparticles (ZnONPs) embedded with nitrogen-doped carbon sheets (ZnONPs@NDCSs) were synthesized and used in biosensor design for glucose determination by Muthuchamy and coworkers. In this study, while ZnONPs@NDCS composite was synthesized using a simple hydrothermal method, peach extract precursor was used to obtain ZnONPs (Fig. 21.3). After washing and drying the GCE surface used as the working electrode, it was modified using ZnONPs@NDCS. Afterward, the glucose oxidase (GOx) enzyme was immobilized on the modified surface, and the enzyme biosensor was used. Both CV and electrochemical impedance spectroscopy (EIS) results showed that the developed GCE/ZnONPs@NDCS/GOx biosensor

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555

Figure 21.3 Schematic illustration of the synthesis and application of ZnO@C nanocomposite With permission from Muthuchamy, N., Atchudan, R., Edison, T. N. J. I., Perumal, S. & Lee, Y. R. (2018). High-performance glucose biosensor based on green synthesized zinc oxide nanoparticle embedded nitrogen-doped carbon sheet. Journal of Electroanalytical Chemistry, 816, 195
204. https://doi.org/10.1016/j.jelechem.2018.03.059.

provided a more efficient electron transfer path between the electrode and glucose. While designing the biosensor, some parameters including applied voltage, GOx loading, pH, and temperature were optimized to achieve maximum amperometric performance. A linear working range of 0.2
12 mM was achieved when optimal conditions were set. Moreover, using the developed biosensor, glucose determination in human serum samples was successfully performed with a LOD level of 6.3 μM (Muthuchamy et al., 2018). By using green nanomaterials, different analytes can be determined without using enzymes (Dayakar et al., 2017; Erkmen et al., 2021). Ilgar et al. developed a nonenzymatic biosensor for dopamine determination with CuO NPs synthesized from maca extract (MaE-CuONPs). MaECuONPs synthesized simply by the green method were characterized by scanning electron microscopy (SEM), energy-dispersive X-ray (EDX), high-resolution transmission electron microscopy (HRTEM), and Fourier transform infrared (FTIR) spectroscopy. According to the characterization results, while the surface area of MaE-CuO NPs is 344.645 m2 g21, they have a regular spherical shape with an average diameter range of 10
20 nm, as shown in the SEM images in Fig. 21.4. It has also been found to have antimicrobial activity against Staphylococcus aureus (S. aureus), Pseudomonas aeruginosa, Escherichia coli, Candida albicans, and Aspergillus brasiliensis (Ilgar et al., 2022).

556

Novel Nanostructured Materials for Electrochemical Bio-sensing Applications

Figure 21.4 SEM images of (A) pure maca powder and (B) synthesized MaE-CuONPs. With permission from Ilgar, M., Baytemir, G., Ta¸saltın, N., Güllülü, S., Ye¸silyurt, ˙I. S. & Karaku¸s, S. (2022). Journal of Photochemistry and Photobiology A: Chemistry, 431, 114075. https://doi.org/10.1016/j.jphotochem.2022.114075.

By developing a dual smartphone electrochemical and colorimetric detection platform based on a three-electrode system with MaECuONPs, nonenzymatic measurements were performed. With this developed green nanoplatform, dopamine was determined with a detection limit of 16.9 nM in the linear concentration range of 0.625
5 μM. Various advantages of green synthesis nanostructures such as increasing the sensitivity of the sensor by providing high surface area, synthesis from plant extract without creating harmful waste for the environment, and easy and fast synthesis have come to the fore. Ultimately, the combined use of these multifunctional MaE-CuO NPs and smartphone technology enabled rapid, selective determination of dopamine with high sensitivity of 667 μA μM21 cm22 (Ilgar et al., 2022). Although enzymes are widely used biorecognition elements due to their high catalytic activity and substrate specificity, they have disadvantages such as high cost for preparation and purification, low operating stability, the sensitivity of the catalytic activity to environmental conditions, and difficulties in recycling and reuse. To overcome these limitations, as an alternative to enzymes, novel molecules that can mimic the catalytic properties of enzymes and the synthesis of complexes or nanoparticles have attracted attention in recent years (Erkmen et al., 2021). In 2022, novel green-synthesized nickel oxide nanoparticles (NiO NPs) were

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synthesized by Youcef and coworkers, and this material was used for nonenzymatic glucose determination. In this study, NiO NPs were synthesized using seed extract of Nigella sativa. Briefly, after the surface of the working electrode was mechanically cleaned, NiO NPs were dripped onto the surface and dried and made used for measurement. While no anodic or cathodic peaks were observed in the cyclic voltammograms recorded using bare GCE, electrical signal was obtained on the NiO NPsmodified surface. The glucose oxidation process was effectively catalyzed by the electrically generated Ni(III) species on the modified electrode. After determining the optimum conditions and the oxidation mechanism, linearities in the range of 50
600 μM and 1
10 mM with LOD of 3.2 μM were obtained according to the amperometric measurements. In addition, glucose determination from serum samples was successfully performed using the developed nonenzymatic sensor (Youcef et al., 2022). As can be seen from the previous study mentioned above, more sensitive results can be obtained using nanomaterials-based sensors that mimic enzymes without using enzymes. 21.2.1.2 Green nanostructures in immunosensors Immunosensors are biosensing platforms based on strong interactions and affinity between antibody and antigen (Mollarasouli et al., 2019). Antibodies, which can be classified as IgA, IgD, IgE, IgG, and IgM according to the distinctive heavy chains of their immunoglobulins, are attached to the electrochemical converter. A signal is generated by the detection platform for the detection of target biomarkers. To date, important studies have been carried out on the development of sensitive, fast, and selective sensors for the rapid diagnosis of various diseases with antibody-based sensors (Chen et al., 2021; Roda et al., 2021; Sun et al., 2017). Immunosensor platforms created using various nanomaterials are frequently encountered in the literature. With the rise of nanoplatforms synthesizing green approaches, green nanomaterial-based immunosensors have also begun to be developed in recent years. For example, Darvishi et al. developed an immunosensor platform using both biopolymers obtained from quince seed mucilage and AgNPs and AuNPs obtained from Calendula officinalis L. extract. Quince seed gum has a special polymeric structure due to the cellulose and polysaccharide components it contains (Darvishi et al., 2021). Therefore this immunosensor platform has helped to create platforms with high detection capability thanks to the stable immobilization of nanomaterials and antibodies on the electrode

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surface and bioactive negatively charged components in surface modification. Secondary metabolites of Calendula officinalis L. extract are used as a reducing agent for metal ions. Due to the functional groups of this biopolymer and synthesized green AgNPs and AuNPs, they detected prostatespecific antigen (PSA), a biomarker of prostate cancer, with an unlabeled immunosensor platform on the GCE surface (Darvishi et al., 2021). CV and EIS techniques were used for the electrochemical characterization of the developed immunosensor platforms. In this study, Nyquist plots are given in Fig. 21.5A, where quince seed berry-modified GCE (mucilage/GCE) (b), green AuNPs- and AgNPs-modified mucilage/GCE (c and d), both green AuNPs- and AgNPs-modified mucilage/GCE (f), antibody incubated-modified electrode (g), and PSA-incubated modified electrode (h) were given. The decrease in the diameter of the semicircle electron transfer resistances (Rct) compared to bare GCE (a) demonstrates a successful modification of biopolymer and green nanomaterials and increased electrode conductivity, as well as increases in post-modification Rct values, evidence of adequate and successful incubation of antibody and PSA. As shown in Fig. 21.5B in studies with CV, in the presence of Fe(CN)632/42 redox probe, AgNPs and AuNPs increased the surface area of GCE, while mucilage increased the stability of the antibody thanks to the covalent bonds between it and the antibody. In this way, it was possible to easily bind and detect PSA to the antibody-coated surface. As a result, PSA determination was performed in the linear concentration range of 0.1 pg mL21
100 ng mL21 with a low detection limit of 0.078 pg mL21 by the EIS method under optimum conditions. The developed green immunosensor is biocompatible and environmentally friendly, which can be used for the detection of PSA in clinical analysis (Darvishi et al., 2021). Sangili et al. using a green nanoplatform detected the deadly dengue virus of type E-protein (DENV-E protein), the source of dengue fever. L-cysteine (L-cys) was used as the green source in this green immunosensor platform design. L-cys is a nontoxic, natural proteinogenic amino acid with sulfur, amino, and carboxyl groups. In this way, it provides stable binding of biomolecules such as antibodies when used in nanomaterial synthesis. Therefore they prepared L-cys-based, environmentally friendly, and nontoxic AuNPsdecorated heteroatom-doped reduced graphene oxide nanocomposites (AuNPs/NSG) for use in the immunosensor platform. The strong binding of AuNPs/NSG nanocomposite with antibodies with strong amide bonds provides a significant advantage in terms of the stability of the developed

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Figure 21.5 Nyquist diagrams (A) and cyclic voltammograms (B) of 0.1 M KCl solution containing 5.0 mM K3Fe(CN)63/42 recorded at GCE (a), mucilage/GCE (b), mucilage-AuNPs/GCE (c), mucilage-AgNPs/GCE (d), mucilage-AuNPs-AgNPs/GCE (f), Ab/ mucilage-AuNPs-AgNPs/GCE (g), and Ab-Ag/mucilage-AuNPs-AgNPs/GCE (h). With permission from Darvishi, E., Ehzari, H., Shahlaei, M., Behbood, L. & Arkan, E. (2021). Bioelectrochemistry, 139, 107744. https://doi.org/10.1016/j.bioelechem.2021.107744.

immunosensor. Under optimum conditions, DENV-E determined a wide linear working range of 0.01
100 ng mL21, with a low detection limit of 1.6 pg mL21 and high specificity. The sensor showed a wide linear operating

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range of 0.01
100 ng mL21. In addition, the researchers used the immunosensor platform they developed to detect viral E-protein contents in serum samples collected from patients. It is envisaged that the AuNPs/NSG immunosensor could be a green and reliable potential tool in clinical diagnostic applications in the future (Sangili et al., 2022). In another green nanostructured immunosensor study, Zhou et al. synthesized iron oxide nanoparticles (FeNPs) by green synthesis method to detect anti-cyclic citrullinated peptide antibody (anti-CCP), a biomarker of rheumatoid arthritis (RA) autoimmune disease. FeNPs from durian plant extract were used in an interdigitated electrode (IDE) modification developed with aluminum and silicon dioxide (SiO2) as the base. Green FeNPs were characterized by field emission scanning electron microscopy and field emission transmission electron microscopy (FESEM), and X-ray photoelectron spectroscopy analysis. High immobilization of cyclic citrulline peptide (CCP) and amine-aldehyde surface chemistry formed by aldehyde-amine linkers on the green FeNPs IDE surface was achieved. The detection limits of the developed immunosensor and anti-CCP in the linear range between 8 and 250 pg mL21 were found to be 8 and 15 pg mL21. Anti-CCP levels in biological fluid will be found using this green immunosensor nanoplatform to diagnose RA (Zhou et al., 2022). 21.2.1.3 Green nanostructures in aptasensors Compared to other biological molecules, aptamers are highly stable over wide temperature and pH (B4
9) ranges without losing their activity. They can be produced easily and cheaply and also can be stored at room temperature. Moreover, they can be synthesized in high quantity and purity. Aptamers are important as very useful molecules for in vitro and in vivo therapeutic, diagnostic, imaging, and analysis uses of many molecules, such as drugs, proteins, and pesticides. This is because of their special recognition properties of molecular targets (Erkmen et al., 2022). In the design of electrochemical aptasensors, the development of biocompatible, easily prepared, and low-cost label-free aptasensors has attracted the attention of many researchers. In their study, Shahdost-fard and Roushani developed a label-free aptasensor for the determination of β-casomorphin-7 (BCM-7) using a nanocomposite-modified electrode consisting of quantum dots (QDs) and AgNPs. In the study, AgNPs were synthesized using a very simple green method with less chemicals. As shown in Fig. 21.6A, the bare GCE was modified with QD and AgNPs by

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Figure 21.6 (A) A schematic presentation of fabrication steps of the BCM-7 aptasensor, (B) the CVs and (C) Nyquist curves of the GCE, QD/GCE, AgNP/QD/GCE, Apt/ AgNP/QD/GCE, and BCM-7/Apt/AgNP/QD/GCE in the 0.1 M PB (pH 5 7.4) containing 0.1 M RU and 0.1 M KCl as the redox probe at a scan rate of 50 mV s21. Inset: the corresponding equivalent circuit. Modified from Shahdost-fard, F. & Roushani, M. (2020). Microchemical Journal, 159, 105514. https://doi.org/10.1016/j.microc.2020.105514.

layer-by-layer method, respectively. Then, the aptamers were immobilized to the modified surface at the optimum incubation time. In the last step, increasing concentrations of BCM-7 were immobilized to the surface, and the aptasensor was made ready for measurement. At each modification step of the aptasensor, the electrochemical responses of rutin (RU) as a redox probe were investigated by following CV (Fig. 21.6B) and EIS (Fig. 21.6C). Compared to bare electrodes, the decrease in current signals and increase in impedance values in modified electrodes with QD, AgNPs, aptamer, and BCM-7, respectively, confirmed the characterization of the developed aptasensor. Under optimum conditions, linearity was obtained in two different ranges of 1 pM
20 nM and 20 nM
1.3 μM with LOD of 32 fM against reductions in the current signals of the RU using the DPV method. Moreover, the determination of BCM-7 in urine and blood serum samples was successfully performed using the label-free aptasensor (Shahdost-fard & Roushani, 2020). In another study, Shahdost-Fard and coworkers prepared a sponginbased nanocomposite and used this nanocomposite in the aptasensor design developed for the detection of S. aureus. As shown in Fig. 21.7,

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Figure 21.7 The aptasensor fabrication procedure for Staphylococcus aureus detection.

first the sponge obtained from the sea sponge was modified with copper tungsten oxide hydroxide. In the next step, sponge copper tungsten oxide hydroxide was functionalized by AgNPs and used as a modification agent for the design of the label-free electrochemical aptasensor. When the surface of the bare working electrode was coated using the synthesized nanocomposite, both electron transfer was enhanced and the electroactive surface area was increased. In addition, AgNPs in the nanocomposite provided more efficient immobilization of the thiol functional aptamer to the surface. After examining the surface characterization of the electrodes, the incubation time of S. aureus on the aptasensor was optimized. Under optimal experimental conditions, a linear concentration range of 10
108 colony-forming units per milliliter with a LOD of 1 colony-forming unit

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per milliliter was obtained for S. aureus detection using the developed label-free aptasensor. Furthermore, the determination of S. aureus in human serum samples, which are real samples, was successfully applied with acceptable recovery values (Shahdost-Fard et al., 2023). The use of sandwich-based methods in sensor designs, unlike labelfree methods, significantly increases sensitivity and selectivity. In their study, Tabrizi and coworkers designed a flow-injection electrochemicalbased aptasensor for the detection of adenocarcinoma gastric (AGS) cancer cells when hydrogen peroxide (H2O2) was present. The measurement principle in this study was based on the preparation of a sandwich-based aptasensor with amperometric measurements. To enhance the electroactive surface area to immobilize primary thiolated aptamers and enhance the electrode’s ability to transfer electrons, the bare surface of the SPE was modified by multiwalled carbon nanotube decorated with gold nanoparticles (MWCNT-Aunano). Afterward, the surface was incubated with primary aptamers and subsequently bovine serum albumin (BSA) to prevent specific binding. In the next step, increasing concentrations of AGS cells were immobilized on the surface. In the last step, labeled secondary aptamers synthesized using gold core and silver shell (Au@Ag) nanoparticles (NPs) were immobilized to the surface. Thyme leaf extract was used as green reducing agent for the synthesis of used AuNPs. Morphological examination of synthesized nanoparticles and electrode surfaces was characterized using transmission electron microscopy (TEM) and EDX methods, while all preparation steps of the apatsensor were characterized using CV and EIS. The electrocatalytic activity of Au@Ag nanoparticles toward the reduction of H2O2 caused the selective interactions between aptamers and AGS cells to improve the response of aptasensor for the determination of AGS cancer cells in the presence of H2O2. Under optimum conditions, the developed sandwich-type amperometric aptasensor exhibited a linear response to the logarithmic value of AGS cancer cells in the concentration range of 1 3 101
5 3 105 cells mL21, with a low LOD of 6 cells/mL21. Moreover, the developed aptasensor was used to determine AGS cancer cells in a sample of human blood (Amouzadeh Tabrizi et al., 2017).

21.3 Conclusions and future perspectives It has opened new doors in nanoscale material synthesis, drug delivery, electronics, food, cosmetics, and sensors. The application of the green chemistry approach to these areas is aimed to reduce resource and energy

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consumption, preventing environmental pollution, safe production for human health, and economically low costs. The rapid growth of the world market of nanomaterials causes a high amount of waste and health safety problems. Therefore the use of environmentally friendly and safe materials is an issue that needs urgent attention. Nanoparticles of various shapes and sizes can be synthesized using physical, chemical, or biological means. Utilizing physical and chemical means leads to high energy consumption, low efficiency, high cost, and environmental damage through the use of harsh reducing agents. The biological green approach is carried out with the use of microorganisms (bacteria, fungi, yeast, algae, etc.) or plants. The green synthesis approach comes to the fore today with its advantages such as its contribution to recycling, not containing toxic chemicals, affordable costs, and easy synthesis. The increase in the use of nanoplatforms consisting of green-sourced nanomaterials in biosensor applications in the last decade draws attention. As a result of the studies, it is seen that green nanoplatforms can be used to detect various disease biomarkers, biochemical substances, pathogens, and enzymes. Green nanoplatforms bring advantages such as sensitivity, low waste consumption, and low cost to electrochemical biosensors. The size and morphological properties of nanoparticles used for the modification of the sensor surface in electrochemical biosensors affect the sensor efficiency. However, the shape and size controls of nanomaterials synthesized from biological sources and the effect of the natural source used on the synthesis mechanism are not clearly understood. Therefore there is a need for further research and also large-scale production of these environmentally friendly nanomaterials and synthesis methods. In addition, the use of nontoxic solvents, low amount of samples, and energy consumption, which are the subjects brought by the green chemistry perspective, are among the topics researched in the field of electrochemical biosensors, apart from these nanomaterials. In this chapter, green electrochemical nanobiosensor applications developed in recent years are mentioned. It is seen that the origin of nanomaterials used in the developed biosensor platforms is mostly plant origin rather than microbial origin. In addition, green nanoplatforms continue to be developed in aptamer-based biosensors, known as newgeneration antibodies, with their frequent use in enzyme- and antibodybased biosensors. While electrochemical biosensors serve sustainable world goals such as low sample and waste production, their ability to be

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downsized with developed technologies, their integration into chip technology, and the establishment of platforms that can be formed from recyclable materials such as paper bring additional advantages in this regard. Therefore green nanoplatforms, which combine green nanotechnological approaches with developments in the field of electrochemical biosensors, hold promise for a sustainable environment in the future. As a result, new green nanomaterials have many applications for a sustainable world. It is predicted that its applications in the field of biosensors will continue to gain momentum. Therefore these environmentally friendly, safe, and low-cost nanomaterials are produced in high quantities, and their use in green nanotechnological developments and nanobiosensor platforms is supported.

Acknowledgments Didem Nur Unal greatly appreciates the Council of Higher Education (YOK) for providing scholarships under the special 100/2000 scholarship program. Didem Nur Unal and Ipek Kucuk also thanks the financial support from the Scientific and Technological Research Council of Türkiye (TÜB˙ITAK) under the BIDEB/2211-A doctoral scholarship program. Cem Erkmen thanks the Scientific and Technological Research Council of Türkiye (TÜB˙ITAK) through the 2218-National Postdoctoral Research Fellowship Programme (Project number: 122C252).

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CHAPTER 22

Future sustainability and sensitivity of nanostructured material
based electrochemical biosensors over other technologies R. Rajkumar1, J. Antony Rajam2, P. Karpagavinayagam3, M. Kavitha3 and C. Vedhi3 1 Department of Chemistry, Kamaraj College, Thoothukudi, Tamil Nadu, India Department of Chemistry, St. Mary’s College (Autonomous), Thoothukudi, Tamil Nadu, India Department of Chemistry, V.O. Chidambaram, Thoothukudi, Tamil Nadu, India

2 3

22.1 Biosensor If the word “biosensor” is divided into “bio” and “sensor,” it will be easier to understand what they are. A biosensor is an analytical tool that combines a biological element with a physicochemical detector to be utilizd in the detection of chemical substances. Biological samples can be sensed using biosensors, which are bioanalytical devices. They are compact, effective tools that can examine biological materials to determine their content, function, and structure. By transforming a biological signal or response into a quantifiable response, this is accomplished. Leland C. Clark created the first biosensor, also referred to as the “Clark electrode,” in 1956 to measure oxygen levels. He was known as the “father of biosensors” for his contributions to the field of biosensing. Yellow Springs Instruments created the first biosensor for use in industry in 1975. Biosensors include devices like pulse oximeters, smartwatches, and glucometers. This technology is not only useful in the healthcare industry. They can monitor the quality of the environment, soil, water, and food and are essential for the development of new medications and the prevention of disease. They are also employed in biodefense and metabolic engineering to monitor the proper operation of prosthetic devices (Fig. 22.1).

Novel Nanostructured Materials for Electrochemical Bio-sensing Applications DOI: https://doi.org/10.1016/B978-0-443-15334-1.00020-1

© 2024 Elsevier Inc. All rights reserved.

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Figure 22.1 Various types of nanomaterials used in biosensor 1.0.

22.2 Types of biosensors The biosensors can be categorized as invasive or noninvasive depending on how the necessary biological analyte is applied. 1. The use of the transduction mechanism and the kind of biological recognition element. DNA, an antibody, an enzyme, a phage, tissues, cell receptors, and microbial entire cells can all serve as the recognition component of a biosensor (Manjunatha & Hussain, 2011). 2. There are three different types of transducers that can be utilized to create biosensors: optical biosensors, electrochemical biosensors, and mass-based biosensors. a. Optical fibers are essential to the operation of optical biosensors because they detect biological analytes based on their fluorescence, absorption, and scattering of light characteristics. The measurements are based on changes in the refractive index, and they are not electrical in nature.

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b. Electrochemical biosensors are electrical in nature and include interactions between the sample analyte and the recognition component or sensing molecule. The electrical signal generated is frequently inversely correlated with the analyte concentration (Manjunatha et al., 2020; Manjunatha, 2020b). c. Electrical biosensors called mass-based biosensors provide electrical signals in direct proportion to the mechanical or acoustic (sound) vibrations of the molecules that are being detected.

22.3 Nanowire-based biosensors Biomedical sensors’ main function is to identify chemical and biological species for use in everything from drug discovery to illness diagnosis. These fundamental biomedical activities are easily accomplished using nanomaterials (e.g., nanowires, carbon nanotubes, and nanoparticles) with different optical, magnetic, and electrical properties (Kurkina & Balasubramanian, 2012). The most suitable alternative for biomedical sensors that have high sensitivity, homogeneity, reproducibility, and scalability with a reasonably easy fabrication technique is hence nanostructures made by nanowires (Hareesha et al., 2021; Zhang & Ning, 2012).

22.4 Receptor for DNA and RNA Nanowire sensors can be used to find certain DNA and RNA sequences (Zhang et al., 2008). PNA single-stranded sequences are arranged on the surfaces of silicon nanowires so that they can serve as DNA receptors (Wu et al., 2009). Nanowires can be used to detect the bonding between proteins and DNA in addition to the identification of individual DNA strands (Yang & Zhang, 2014). Similar to PNA or DNA, nanowire devices can be functionalized to create RNA sensors. The application of nanowirebased DNA sensors for cancer diagnosis and treatment is made possible by their ability to monitor different cancer indicators at the DNA level, including telomerase and carcinoembryonic antigen (Lu et al., 2014; Zheng et al., 2005).

22.5 Receptor for viruses Many harmful viruses, including dengue, influenza A H3N2 (Zhang et al., 2010), H1N1 (Kao et al., 2011), and HIV (Inci et al., 2013), have

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been detected using Si nanowire sensors. Antibodies that precisely bind to the target viruses are functionalized onto the nanowire sensor surface, which alters the conductivity of the nanowire (Tigari & Manjunatha, 2020). For instance, an EBC sample containing up to 29 flu viruses/L and an Ebola VP40 matrix protein could both be detected by a Si nanowirebased biosensor (Ibarlucea et al., 2018).

22.6 Nanorod-based biosensors TiO2, SnO2, and ZnO are common semiconductor materials used in biosensor construction (Kong et al., 2009). When it comes to sensitivity and the lower limit of GOx, TiO2-based biosensors have excelled. TiO2 has a poorer charge mobility than SnO2 and ZnO, for this reason. Due to ZnO nanostructure’s favorable isoelectric point, it produces remarkable results in glucose biosensors (IEP). Nanorods, among other ZnO nanostructures including nanowires, spheres, belts, rings, and nanoneedles, are of particular study interest because they have promising electrical characteristics for biosensors (Lu et al., 2008). A composite semiconductor-based biosensor significantly boosts the device’s effectiveness. Recently, biosensors based on carbon-decorated ZnO (C-ZnO) nanostructures have increased efficiency with lower glucose detection thresholds. For immobilization, the C-ZnO nanowires directly interact with GOx (Ahmad et al., 2010). The hexagonal face of ZnO nanowires, which is more sensitive to GOx because of the higher IEP of ZnO nanowires, is where enzymes or GOx interact. Furthermore, for the immobilization of GOx, hybrid platinum-fullerene-like ZnO nanospheres (50
200 nm) are placed on glassy carbon electrodes to form highly sensitive GOx biosensors. This biosensor has better sensitivity and higher stability (Lu et al., 2008). For the application of DNA immobilization, composite sensors made of carbon nanotube and zinc oxide have been developed. The electrical response of carbon nanotubes (CNTs), whose electrical conductivity is substantially greater, is crucial to the sensitivity of the biosensors (Tigari & Manjunatha, 2020). The lower limit of GOx and other enzymes for immobilization is reduced as a result of this increase in biosensor sensitivity (Wang et al., 2010). The researcher’s attention has also been piqued by ZnO nanorodbased biosensors with high surface-to-volume ratios and simple growth processes (Lu et al., 2008). The most straightforward and affordable way of manufacturing is hydrothermal ZnO growth, which significantly

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Figure 22.2 Constructing ZnO nanorod array photoelectrodes for highly efficient quantum dots sensitized solar cells clicking.

reduces the cost of fabrication when done in batches. The biosensors made of comb-shaped ZnO nanorods were produced in a batch using traditional photolithography (Lu et al., 2010) (Fig. 22.2).

22.7 Carbon nanotube
based biosensors The field of electrochemical biosensing has made substantial use of carbon nanotubes (CNTs) (Najma et al., 2018). CNTs are made up of one or more layers of carbon-based needle-like cylindrical hollow structures with high aspect ratios (Rivas et al., 2007). MWCNTs are multiple rolled assemblies of SWCNT, whereas SWCNTs are nanometer diameter wrapped sheets of sp2-bound graphene (Iijima, 1991; Odom et al., 1998). Due to their active involvement in speeding electron transfer, CNTs have the potential to be used in the field of electrochemical detection of biomolecules (Wang, 2005). Highly sensitive and appropriate for detecting nucleobases are CNT-modified electrodes (Wang et al., 2006). A large number of nucleobases may be adsorbed on the CNT-modified GCE surface in comparison to the naked GCE surface, and this appears to improve the oxidation signals (Wu et al., 2003). Additionally, this is a low-cost and

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effective technique for detecting oxidative DNA damage. The exceptional oxidation signal sensitivity of CNT serves as a catalyst for the electrochemical detection of Gua and 8-hydroxyGua (Goyal et al., 2011).

22.8 Carbon nanotube
modified electrodes Utilizing CNTs, biosensors with new modified electrode architectures were created for the measurement of glucose. They increase the electrodes’ electroactive surface area, which improves charge transfer and conductivity. They can thereby facilitate charge transfer between biomolecules and electrode surfaces and catalyze biological reactions (Barsan et al., 2015). Polybenzimidazole and carboxylated MWCNTs were utilized to create a three-dimensional composite, which was then used to modify a gold electrode for hydrogen peroxide detection (Hua et al., 2011). With the aid of microwave energy, graphene oxide nanoribbons were created, and a glassy carbon electrode modified with MWCNTs and GONR was created to detect ascorbic acid, dopamine, and uric acid (Sun et al., 2011). When compared to either CNTs or polymer materials alone, composites made of CNTs and conducting polymers are mechanically stronger, more conductive, and less prone to heat deterioration (Ghica & Brett, 2010). Multiwalled carbon nanotubes (CNTs) and polyazine redox polymers, such as poly(neutral red) or poly(brilliant cresyl blue), have been combined in various ways to create biosensors on glassy carbon electrodes (GCEs) (Yogeswaran & Chen, 2008).

22.8.1 Quantum dot-based biosensors Nanomaterials with zero dimensions are called quantum dots. They are graphene quantum dots (GQDs) and carbon quantum dots (CQDs), both of which have been utilized in bioimaging and biosensing. They have special electrochemiluminescent, fluorescent, photoluminescent, chemiluminescent, and electronic features (Li et al., 2019). An efficient platform for screening, monitoring, early diagnosis, and disease surveillance is provided by the quantitative detection of cancer biomarkers with greater accuracy and sensitivity (Lu et al., 2008; Shen et al., 2012). The fluorescent turnon biosensor, which uses biofunctionalized graphene quantum dots as the energy donor and gold nanoparticles (AuNPs) as the energy acceptor, was used for the ultrasensitive detection of small cell lung cancer (Manjunatha Charithra & Manjunatha, 2020; Manjunatha, 2020a).

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For the purpose of detecting neuron-specific enolase, a label-free and effective fluorescent biosensor based on nanosurface energy transfer between anti-NSE/amine-N-GNOs and AuNPs has been created. Fluorescence response experiments of anti-NSE/amine-N-GNOs at AuNPs nanoprobe performed in response to NSE antigen showed quick response, a broad linear detection range, and astonishingly low detection limit. Additionally, the fluorescent biosensor performed superbly with real samples (Kalkal et al., 2020).

22.8.2 Dendrimers-based biosensors Due to their three-dimensional structure and internal void space, dendrimers, which are ideal for monodisperse macromolecules with highly branching and regular architectures, are regarded as acceptable host molecules for accommodating guest molecules (Bosman et al., 1999). Dendrimers are ideal matrices for biomolecule immobilization because of their promising properties, which include high chemical and mechanical strength, adjustable size, globular geometry, hydrophilicity, high surface functionality, homogeneity, and biocompatibility (Hasanzadeh et al., 2014). These characteristics help biosensors to be more stable, sensitive, capable of collecting targets, and selective. Since PAMAM contains a lot of terminal amino groups that facilitate the attachment of biomolecules, it can be employed in biosensor applications in particular, as highly branched dendritic macromolecules (PAMAM) (Demirci et al., 2012). Dendrimers’ use in biosensors is nonetheless restricted by their low conductivity and greasy nature. Dendrimers can be fixed on a solid-state carrier, such as multiwalled carbon nanotubes (MWCNTs) or nanoparticles, to function efficiently and get around these issues (Kavosi et al., 2014). MWCNT-PAMAM dendrimer-modified glassy carbon electrode and methylene blue redox indicator make up an electrochemical microRNA biosensor. Here, PAMAM dendrimers are chosen because of their suitability for immobilizing the capture probe due to their highly branched polymeric structure and MWCNTs because of their outstanding electrochemical performance for methylene blue electrochemistry (Li et al., 2015). The polypyrrole film was wrapped around MWCNTs during the electrochemical polymerization of pyrrole on a gold electrode, resulting in the MWCNTs
polypyrrole nanocomposite. Due to the high number of amine groups on the dendrimer surface, which led to improved sensitivity and a lower detection limit, this nanocomposite layer

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was modified with PAMAM dendrimers in order to offer association with a broad number of bioreceptors (Pushpanjali & Manjunatha, 2020; Pushpanjali, Manjunatha, & Srinivas, 2020).

22.9 Nanostructured material
based electrochemical biosensor 22.9.1 Gold nanoparticles It is possible to dissolve captured gold nanoparticles with or without preenlargement to produce gold(III) ions for electrochemical measurement. Dequaire et al. measured the released gold(III) ions using anodic stripping voltammetry on screen-printed carbon electrodes after dissolving the trapped gold nanoparticles in a solution of hydrobromic acid (1 M) and bromine (0.1 mM). Goat immunoglobulin G (IgG) detection had a dynamic range of 0.5
100 nanograms per milliliter (ng mL21), with a detection limit of 0.5 ng mL21 (Dequaire et al., 2000). Liao and Huang autocatalytically deposited gold on gold nanoparticles using formaldehyde/Au31. The extra Au31 was removed, and the expanded gold nanoparticles were then dissolved using a solution of bromine and hydrobromic acid. Then, using square-wave stripping voltammetry, the amount of gold placed on the electrode was determined. With a detection limit of 0.25 picograms per milliliter (pg mL21), this resulted in a linear dynamic range (semilog plot) of 1
500 pg mL 2 1 of rabbit IgG (Liao & Huang, 2005).

22.9.2 Gold nanoparticles with silver deposition A sandwich immunoassay based on silver-enhanced gold nanoparticles was described by Chu et al. in 2005. To precipitate silver on the gold labels, the immunocomplexes were treated with hydroquinone and silver nitrate. Nitric acid was then used to dissolve the silver that had been deposited, and anodic stripping voltammetry was used to identify the metal ions. According to estimates, the detection threshold for human IgG is 1.0 ng mL21 (6 pM) (Chu et al., 2005). To create electrochemical signals proportional to human and mouse IgG on dual working electrodes using anodic stripping voltammetry, Lai et al. employed gold nanoparticles functionalized with an antibody and labeled with alkaline phosphatase (Hareesha et al., 2021; Prinith et al., 2021). For human and mouse IgG, respectively, detection limits of 4.8 and 6.1 pg mL21 were obtained when enzyme and gold nanoparticles worked

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together to catalyze silver deposition (Lai et al., 2011). Shim et al. likewise employed silver deposition and stripping to produce an analytical signal, but in this instance, sandwich immunocomplexes were functionalized with a cysteamine
silver complex by interacting the free amine group of cysteamine with gold nanoparticles on the detecting antibodies (Noh et al., 2011). The limit of detection was reported to be 0.4 femtograms per milliliter (fg mL21), and the amount of cysteamine attached was proportionate to the amount of IgG present. In a similar manner to Lin et al., detection antibodies were assembled on gold nanoparticles connected to poly(styrene-co-acrylic acid) microbeads, whereas capture antibodies were assembled on a graphene-coated glassy carbon electrode. With a limit of detection of 0.12 pg mL21, silver stripping using linear sweep voltammetry responded linearly to the logarithm of CEA concentration in the range of 0.5 pg mL21
0.5 ng mL21 (Lin et al., 2012) (Figs. 22.3 and 22.4). The schematic for an immunoassay uses magnetic beads and silver nanoparticles starting at the top left: in the first step, an antigen is exposed to magnetic beads conjugated to an antibody to create antibody
antigen complexes linked to the magnetic beads; in the second step, silver nanoparticles conjugated to a second antibody are added to the reaction mixture to create conjugates containing the antigen linked to both the magnetic beads and the silver nanoparticles; in the third step, a magnet is used to capture the magnetic beads while unbound materials (including unbound silver nanoparticles) are washed. Moreover, ammonium thiocyanate is added to the trapped conjugates in the fourth stage to disintegrate them and stabilize silver. The silver nanoparticles are finally determined by (1) electrochemical dissolution to produce silver ions, (2) silver nucleation on the electrode surface, (3) silver accumulation on the electrode

Figure 22.3 Schematic of an immunoassay using silver nanoparticles and magnetic beads.

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Figure 22.4 Schematic representation of (A) preparation of tracing tag and labeled detection antibody and (B) immunosensor fabrication and sandwich immunoassay.

surface, and (4) rapid removal of silver from the surface to generate a measurably large stripping charge.

22.9.3 Silver nanoparticles Similar to gold nanoparticles but with less aggressive reaction conditions, captured silver nanoparticles can be employed to provide an electrochemical signal with or without preenlargement. To test myoglobin using ammonium thiocyanate to dissolve the trapped silver nanoparticles using stripping voltammetry to provide a dynamic range spanning 0.2
20 ng mL21, Szymanski et al. combined magnetic beads and silver nanoparticles that were each tagged with antibodies (Szymanski et al., 2010; Szymanski et al., 2011). An immunoassay without the need for silver nanoparticle dissolution before measurement was published by Hao et al. (2011). Glutathione was used to activate the silver nanoparticles, and glutaraldehyde was used to conjugate them to goat antihuman IgG. Preadsorption of IgG to screen-printed carbon working electrodes was done, and the functionalized particles were treated with the IgG. Unbound materials were removed by washing, and differential pulse voltammetry was used to strip the remaining silver metal-labeled immunocomplexes. The limit of detection was 0.4 ng mL21, and the dynamic range was 1
1000 ng mL21.

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22.9.4 Graphene nanomaterials used in electrochemical biosensor fabrication For the construction of electrode matrices for sensing and biosensing, graphene and its derivative structures (graphene oxide, graphene platelets, and graphene nanoflakes) have gained popularity (Ambrosi et al., 2010). All graphitic forms, such as three-dimensional graphite, one-dimensional carbon nanotubes, and zero-dimensional fullerenes, are descended from graphene (Rao et al., 2009). Undoubtedly, the material that is being examined the most in-depth at the moment is graphene, which is described as a single-layer, two-dimensional, sp2-hybridized carbon. The world’s thinnest, stiffest, and strongest material is a single carbon atom thick sheet that is arranged in a honeycomb pattern. It also conducts heat and electricity very well (Georgakilas et al., 2012). It is sometimes divided into three categories according to how many layers are stacked: single layer, few layer (2
10 layers), and multilayer, also known as thin graphite. The use of graphene should ideally be restricted to single- or few-layer geometries to preserve its unique features (Raril & Manjunatha, 2020; Raril, Manjunatha, Ravishankar, et al., 2020). Due to its distinct electrical, optical, mechanical, thermal, and electrochemical properties, graphene is receiving a lot of attention as a next-generation electronic material. Graphene can be used to achieve molecular sensing since it has excellent low-noise electrical properties (Artiles et al., 2011). A wide electrochemical potential window, low electrical resistance in comparison to glassy carbon (GC), atomic thickness, and two welldefined redox peaks linearly aligned with the square root of the scan rate magnitude make graphene appealing for electrochemistry. This suggests that the material’s redox processes are primarily diffusion-controlled. Its apparent electron transfer rate is orders of magnitude higher than that of GC, and peak-to-peak values under cyclic voltammetry are low, implying rapid electron transfer kinetics. The formation of particular surface functional groups has been demonstrated to greatly increase this rate of electron transfer, which is surface-dependent. Numerous electrochemically active sites are provided by the graphene’s high density of edge-plane defect sites. Due to its 2D form, which exposes its full volume to the environment, it is particularly effective in detecting molecules that have been adsorbed. The increased surface area of graphene-based electrodes results in significant enzyme loading as well. This can therefore help with high sensitivity, some enzymes’ outstanding ability to promote electron

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transfer, and many macromolecules’ excellent catalytic behavior (Bao et al., 2012). In addition to having the necessary biocompatibility, graphene-based devices are suitable for in situ biosensing. Similar to carbon nanotubes (CNTs), graphene has a large surface area (2,630 m2 g21) and a small unit size. It also has some additional advantages, such as low cost, two external surfaces, ease of fabrication and modification, and the absence of metallic impurities, which can produce unintended and uncontrolled electrocatalytic effects as well as toxicological risks. Additionally, it has been noted that graphene sheets’ edges include a range of oxygenated species that can facilitate effective electrical wiring of numerous metalloproteins with heme-containing redox centers to the electrode and also improve molecule adsorption and desorption (Bao et al., 2012). Graphene-based nanomaterials can be categorized based on how they were made. They can be made through mechanical exfoliation of graphite, chemical vapor deposition (CVD) development, or exfoliation of graphite oxide. Neither graphene created by CVD nor graphene exfoliated mechanically has significant amounts of flaws or functions. For example, sono-assisted exfoliation of graphite oxide to graphene oxide (GO), which can then be further reduced chemically or electrochemically, and thermal exfoliation of graphite oxide to produce a material known as thermally reduced graphene (GO) are typical methods used to prepare bulk quantities of graphene-based nanomaterials. Chemically reduced GO (CRGO) or electrochemically reduced GO (ERGO) are common names for the end products. The TRGO is drastically different from pure graphene, which has a flawless honeycomb lattice structure and has a lot of flaws. Due to severe damage to the sp2 carbon network, the GO’s structure is not entirely planar. It has a lot of oxygen-containing groups, which can help with functionalization when biomolecules are used to trigger biorecognition events during biosensing. Reduced versions of GO still contain some fraction of oxygencontaining groups despite having a partially recovered sp2 lattice. To select the appropriate type of graphene for the application and transduction process, one may need a big graphene “toolbox”. The majority of graphene used in electrochemistry is graphene made from GO chemical/thermal reduction, also known as functionalized graphene sheets or chemically reduced GO. This type of graphene typically has a large number of structural flaws and functional groups, which is advantageous for electrochemical applications. It has been shown that ERGO performs significantly

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better for electrochemical applications than CRGO. Furthermore, Chua and Pumera (2013) research showed that not all graphene materials are useful for lab-on-chip device detection. Their research may offer important new information on the potential practical applications of graphene materials in the future. Future development of electrochemical graphenebased nanobiodevices should be based on a better understanding of some electrochemical details, such as the function of defects and oxygencontaining groups at graphene sheets’ edges, the mechanism by which biomolecules interact with graphene surfaces, and the function of doping heteroatoms in graphene. It is also vital to note that inventive techniques for carefully monitored graphene manufacturing and processing should be created. Although graphene has been created using a variety of techniques, the cost-effective, high-yield production method is still not publicly accessible.

22.9.5 ZnO nanostructures used in the fabrication of electrochemical biosensors As immobilizing matrices for the creation of better electrochemical biosensors, nanostructured metal oxides (NMOs) based on metals like zinc, iron, cerium, tin, zirconium, copper, titanium, and nickel have recently attracted a lot of interest. They have been discovered to have intriguing nanomorphological, functional, biocompatible, nontoxic, and catalytic properties. As a result, they offer an efficient surface for immobilizing biomolecules with the desired orientation, better conformation, and high biological activity, which improves biosensing characteristics. The NMOs with the requisite capabilities and surface charge characteristics offer intriguing platforms for integrating transducers for signal amplification with biorecognition components. Additionally, these materials have better electron transfer kinetics and robust adsorption properties, which create favorable microenvironments for the sustained immobilization of biomolecules and boost biosensing capabilities. Selecting an NMO that is appropriate for the immobilization of the intended biomolecule is essential for the fabrication of an effective biosensor. It is well known that the interface created as a result of the binding of an NMO and a biomolecule has a major impact on the performance of the biosensor. The nature of the NMO determines the formation and characteristics of a nanobiointerface; factors influencing the formation of a biointerface include effective surface area, surface charge, energy, roughness and porosity, valence/conductance states, functional groups, physical

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states, and hygroscopic nature (Solanki et al., 2011). Among NMOs, ZnO nanostructures have distinct physical and chemical advantages. These include a high surface-to-volume ratio that allows for greater enzyme loading, a favorable microenvironment that can maintain the activity of the immobilized biomolecules, nontoxicity, chemical stability with a high isoelectric point (9.5), electrochemical activity, high electron communication features, and high ionic b. In fact, enzymes with insulated redox centers can benefit from direct electrochemistry because of ZnO nanostructures’ excellent electron transfer rate, which can bring forth the biomolecules’ hidden electrochemical capabilities. With improved conformation, strong biological activity, and binding of biomolecules in the appropriate orientation they have demonstrated, the features of sensing have improved (Zhao et al., 2010). They also make good candidates for tiny integrated biosensor devices due to their interoperability with complementary metal oxide semiconductor technology for building integrated circuits. They are among the most promising materials for intracellular electrochemical measurements and biosensing applications because of all these beneficial features. These nanostructures can be designed to have a diameter that is equivalent to the size of the chemical and biological species being sensed, which makes them good primary transducers for generating electrical signals. It is interesting to note that ZnO may be grown to form highly anisotropic nanostructures on a variety of substrates, such as sapphire, glass, silicon, and conductive surfaces with diverse morphologies (such as indium-tin-oxide [ITO] and gold). Additionally, the many options for fabricating ZnO and their various growth settings have produced a pretty diverse array of nanostructures in the ZnO nanoworld. The production of nanostructured materials using ZnO’s polymorphism properties presents a significant opportunity for fundamental research into the functions of dimensionality and size-based physical features. ZnO-based matrices are a viable foundation for low-cost biosensors due to their simplicity in synthesis employing inexpensive techniques that can produce a variety of nanostructures (Yakimova et al., 2012). A wide variety of ZnO nanostructures have been reported by researchers for use in biosensor applications, including nanowires (ZnONWs), nanorods (ZnONRs), nanowalls, nanobelts, nanonails, nanoneedles, nanotubes (ZnONTs), nanocombs, nanoforks, nanofibers (ZnONFs), nanoflakes, nano-waxberries, nanobundles, and nanospheres (ZnONSs). ZnO films that are nanoporous and nanostructured have also

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been applied to biosensor applications. After an enzyme is immobilized, these nanostructures lead to the creation of various structures with a variety of characteristics, which may further affect the microenvironments. For instance, compared to ZnONW arrays, tiny dimensional ZnONT arrays offer a greater effective surface area, subsurface oxygen vacancies, and a higher surface-to-volume ratio, enabling sensors with higher sensitivity (Ali et al., 2011). A prickly ZnO/Cu nanocomposite’s nanostructure offers significant advantages over ZnONRs in terms of facilitating direct electron transfer, according to comparative studies that also show that nanosheet-based ZnO microspheres are more effective than solid ZnO microspheres at facilitating the electron transfer of immobilized enzymes.

22.10 Conclusion and future prospects In this review article, we have covered several biosensor designs and working principles based on transducers, such as electrochemical, electrical, optical, gravimetric, and acoustic sensors, as well as receptors like enzymes, antibodies, entire cells, and aptamers (gold nanoparticles, Ag nanoparticles, nanowires, nanorods, carbon nanotubes, quantum dots, and dendrimers). In the disciplines of engineering and technology, medicine and biomedicine, toxicology and ecotoxicology, food safety monitoring, medication delivery, and disease progression, biosensors have a wide range of applications. The use of nanomaterials in biosensors has caused the field of biosensing technology to advance quickly in the last 10 years. This is due to the use of new biorecognition components and transducers, advancements in the design, manufacture, and miniaturization of nanostructured devices at the micron scale, and novel methods for the synthesis of nanomaterials, all of which unite the fields of engineering, technology, and life sciences. The use of nanoparticles has increased the sensing technology’s adaptability, durability, and dynamic nature. The use of various nanomaterials, each of which has unique properties within biosensors (such as nanoparticles, nanorods, nanowires, carbon nanotubes, quantum dots, and dendrimers), has significantly improved the transduction mechanism (like greater sensitivity, faster detection, shorter response time, and reproducibility). Although the usage of nanostructured materials in biosensor applications has significantly improved, there are still a few restrictions that prevent these applications from progressing to the next level. For instance, the use of CNT-based gas sensors in CNT-based systems is limited by the lack of selectivity. However, by joining CNTs with

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other substances, this difficulty can be solved. These sensors also have problems with the production of nanostructures, the sustainability of nanostructures in sensor applications, and the toxicity, which varies depending on the physical characteristics of the material type. While developing new nanostructured materials for use in biosensors, these problems should be looked at and addressed. The majority of nanobiosensors used in biomedical applications need a big sample to be detected, which could result in false-positive or false-negative results. Apart from electrochemical glucose sensors and lateral flow pregnancy tests, very few biosensors have achieved commercial success on a global scale. Additionally, there is a need for user-friendly, economical nanostructure-based biosensors that provide findings quickly and accurately (Wildöer et al., 1998). For multiplexed clinical diagnostics, nanomaterials should be coupled with a micro-biochip (lab-on-chip) for sample handling and processing. More study is needed in this area, and we anticipate that companies will soon translate the current academic research into prototypes that are practical from a commercial standpoint. Electrochemical biosensors can be built using platforms based on graphene and ZnO nanostructures as immobilization matrices for the detection of physiologically significant analytes. These novel bioplatforms open up new possibilities for novel functions with a range of crucial medical diagnostic applications. They enable the development of numerous new signal transduction technologies in biosensors due to the submicrometer dimensions that can be used for quick and easy in vivo analysis. These electrochemical miniaturized sensors’ exceptional performance paves the way for the execution of biologically significant measurements inside living cells. Some of these biosensors have also proven to perform exceptionally well in FIA tests. By utilizing such platforms, it will be possible to create point-of-care systems for clinical analysis and commercially viable electrochemical biosensors.

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Index Note: Page numbers followed by “f” and “t” refer to figures and tables, respectively.

A a-AfB1. See Anti aflatoxin (a-AfB1) AA. See Acetic acid (AA)Ascorbic acid (AA) Ab anti-Dr1. See Anti-Dr1 antibodies (Ab anti-Dr1) Absolute sensors, 99 ACB. See Azocarmine B (ACB) Accuracy, 291 Acetaminophen drug, 387
410 Acetic acid (AA), 348 Acetylcholine (ACh), 336 Acetylcholinesterase (AChE), 147, 347, 415
416 ACh. See Acetylcholine (ACh) AChE. See Acetylcholinesterase (AChE) Acid Yellow 23, 218 Acinetobacter spp., 244 Active sensors, 99 Adenine (A), 223
224 Adenocarcinoma gastric cancer cells (AGS cancer cells), 563 Adiponectin, 511 Adrenal glands, 507 Adrenaline, 507
508 Adsorption process, 27 Advanced transition metal oxides, 106
107 Affinity-based biosensor systems, 222 Aflatoxins, 370 AFM. See Atomic force microscopy (AFM) Agarose, 134 Agricultural pollutants, 372
373 Agriculture, 533
534 AGS cancer cells. See Adenocarcinoma gastric cancer cells (AGS cancer cells) Alcaligenes faecalis, 438 Alcohol oxidase (AO), 554 Alkane thiol SAMs, 149 Alkoxides, 9

Alkoxysilanes, 9 Allium sativum. See Garlic (Allium sativum) Aluminum (Al), 464 Alzheimer’s disease, 299
300, 331, 431
432 Alzheimer’s disorders, 22
23, 463
464 Amino acid derivatives, 507 hormones, 507 5-amino salicylic acid (5-ASA), 414 2-amino-3-(1H-indol-3-yl) propionic acid, 335 3-aminopropyl trimethoxy silane (APTES), 338, 528
529 Ammonium thiocyanate, 583
584 Amperometric biosensors, 119
120, 296 Amperometry, 169
170, 179
180, 296 Amyloid beta oligomers (AβO), 300f, 336, 349 Anabaena variabilis, 296 Analog sensors, 99 Analyte, 100, 289, 381
382 Analytical chemistry, 147 Analytical methods, 21
22 for determination of antioxidants in beverages, 163
165 Annona squamosa, 543
544 Anodic stripping voltammetry (ASV), 247 Anterior pituitary gland, 511
512 Anthocyanins, 163
164 2-(anthracen-9-yl)benzothiazole (ABT), 483
484 Anthropogenic toxins, 367 Anti aflatoxin (a-AfB1), 90
91 anti-CCP. See Anti-cyclic citrullinated peptide antibody (anti-CCP) Anti-cyclic citrullinated peptide antibody (anti-CCP), 560 Anti-Dr1 antibodies (Ab anti-Dr1), 225
229 Anti-inflammatory drug, 414

597

598

Index

Antibody/antibodies, 224, 252
253, 557, 577
578 aptamer, 129, 132 based biosensors, 104 Antioxidants, 161, 165, 176, 533 in beverages, reference analytical methods for determination of, 163
165 compounds, 162 fraction, 178 AO. See Alcohol oxidase (AO) Aptamer-modified magnetic nanoparticles (MNPs-Apt), 387 Aptamers, 234
236, 560
561 aptamer-based nanobiosensor for neurochemical detection, 348
350 biosensors, 104, 441
447 Aptasensors fabrication procedure for Staphylococcus aureus detection, 562f green nanostructures in, 560
563 Armchair nanotubes, 431 Arrhenius theory, 137 Arsenic (As), 463
464, 468
469 Asbestos fibers, 532
533 Ascorbic acid (AA), 24, 30
31, 175
176, 184
185, 312
313 Aspergillus A. brasiliensis, 555 A. flavus, 533 A. parasiticus, 533 Astragalus membranaceus, 545
546 ASV. See Anodic stripping voltammetry (ASV) Atomic absorption spectroscopy, 465
466 Atomic emission spectroscopy, 465
466 Atomic force microscopy (AFM), 89, 233
234 Autism, 331 Automobile exhausts, 287 2,2-azino-bis-3-ethylbenzothiazoline-6sulfonic acid reagent (ABTS), 163, 554 Azo dyes, 217 Azocarmine B (ACB), 313
314 AβO. See Amyloid beta oligomers (AβO)

B Bacillus spp. B. cereus, 244 B. subtilis, 244 electrochemical detection of, 255
256 Bacteria, 250 Bacterial infections, 250 Bacterial toxins, 369
370 BChE. See Butyrylcholinesterase (BChE) BCN. See Boron and nitrogen co-doped carbon (BCN) BDDE. See Boron-doped diamond electrode (BDDE) β-Casomorphin-7 (BCM-7), 335, 560
561 Beverages, 161
162 application of enzymatic biosensor for determination of specific antioxidant or total content in, 170
186 reference analytical methods employed for determination of antioxidants in, 163
165 Bio-labeling, 4 Bio-nanoelectromechanical systems (bio-NEMS), 110 bio-NEMS. See Bionanoelectromechanical systems (bio-NEMS) Biochemical receptor, 379
380 Biocompatible surface, 132
133 Biological materials, 416
417 Biological sensors, 100, 120 Biological synthesis, 10 Biomedical analyzer system, 380
381 Biomedical sensors, 577 Biometric components, 506
507 Biomolecules carbon-based quantum dots and graphene-based QD, 28
31 CNTs, 24
28 ND, 31
33 neurochemicals as, 22
33 Bionanomaterials, 532
533 Biopolymers, 129

Index

Bioreceptors, 58, 101, 120, 131
132, 197, 219, 221, 223
224, 289, 368, 381
382, 546 antibody-based biosensors, 104 aptamer-based biosensors, 104 classification of biosensors based on, 102
105 enzyme-based biosensors, 103 nanoparticle-based biosensors, 105 whole-cell-based biosensors, 104
105 Biorecognition, 289 component, 526 elements, 248
249 process, 382
383 Biosensing applications metal oxide and metal nanoparticles for, 65t nanoparticles for, 65t of nitric oxides, 309
316 technology, 429 Biosensors, 37
38, 57, 63
64, 79, 97
98, 100
102, 120
121, 129
132, 162, 181, 195
197, 200, 216, 219
220, 231
233, 287
292, 367
368, 371, 379
382, 429, 526
530, 546, 575 based on bioreceptors, 102
105 basic components of, 131f biosensor-based wearable devices, 137 biosensor
based testing, 525 characteristics of, 41
42, 101
102 classification of, 43 constituents of, 100
101 design and principle of, 130
132 devices, 62 distinct platforms in fabrication of advanced, 108
111 electrospinning, 109 FIB technique, 109 MEMSs, 110 paper-based microfluidics, 110 surface plasmon resonance-based biosensor, 111 WGM biosensors, 111 emerging nanomaterials used in fabrication of, 105
108

599

two-dimensional organic polymers, 107
108 two-dimensional transition metals, 105
107 enzyme-based biosensors, 529
530 evolution of, 101 interface of, 132
133 interfaces used in, 141t materials of biosensor interfaces, 133
135 carbon-based nanomaterials, 134 metal-based nanomaterials, 133 MOF, 134
135 polymer, 134 principle of, 58, 59f rate-limiting step, 135
136 recent trends in, 121
122 by transducer class, 138f applications of, 289f characteristics of, 290
291 classification of biosensors, 382f CNT-based biosensors, 528 components of, 289
290, 290f metal-and metal oxide-based biosensors, 527
528 polymer-based polyphosphoric acid biosensors, 528
529 schematic representation of, 368f types, 121 biosensors, 576
577 nanomaterials in biosensor, 576f Biotransducer, 526 Bisphenol A (BPA), 554 Black phosphorous (BP), 108 Black phosphorous nanosheets (BPNSs), 108 Blood elements, 120 Blue phosphorene (BlueP), 106 BlueP. See Blue phosphorene (BlueP) Boron (B), 463
464 Boron and nitrogen co-doped carbon (BCN), 485
486 Boron-doped diamond electrode (BDDE), 417 BOT. See Botryosphaeran (BOT) Botryosphaeran (BOT), 181

600

Index

Bottom-up approach, 8
15, 81
87. See also Top-down approach CVD, 83
84 dry chemical methods, 12
15 electrochemical process, 87 sol
gel method, 82
83 wet chemical methods, 9
12 wet route, 84
87 Bottom-up strategy, 9 Botulinum toxin (BT), 369
370 Bovine serum albumin (BSA), 47, 147, 182
184, 294
295, 347, 510, 563 BP. See Black phosphorous (BP) BPA. See Bisphenol A (BPA) BPNSs. See Black phosphorous nanosheets (BPNSs) Bromothymol blue (BTB), 508 BSA. See Bovine serum albumin (BSA) BT. See Botulinum toxin (BT) Bulk materials, 5, 7, 168 Butyrylcholinesterase (BChE), 147

C c-SWCNT. See Carboxyl-functionalized single-walled carbon nanotube (c-SWCNT) C-ZnO. See Carbon-decorated ZnO (C-ZnO) CA. See Catalase (CA)Consecutive adenine (CA) Cadmium (Cd), 463
466 Caffeic acid, 170
173 Calcitriol, 511 Calendula officinalis L., 557
558 Camellia japonica, 543
544 Campylobacter spp., 244
245 C. jejuni, 244 Cancer, 161 Candida C. albicans, 555 C. guilliermondii, 548
554 Capillary electrophoresis (CE), 22
23, 215
216, 332
333 Capillary electrophoresis amperometric detector (CE-AD), 352 Carbamates, 199
200 Carbamazepine, 415

Carbogenic dots, 29 Carbon, 247 biosensors, 410 compounds, 21
22 electrode, 169 materials, 58
59, 121 molecular allotrope, 436 nanohorns, 23
24 nanomaterials, 5, 134, 171
176, 182
186, 183t, 410
414 enzymatic biosensors reported in, 172t nanoparticles, 63
66, 87 for biosensing applications, 65t metal oxide and metal nanoparticles for biosensing applications, 65t nanostructured materials, 333 nanostructures, 23
24 quantum dots, 28
31, 472 Carbon black paste electrode (CBPE), 176 Carbon ceramic electrode (CCE), 417 Carbon dots (CDs), 87, 437
438, 441
447, 471
472 based compositions, 437
438 Carbon ionic liquid electrode (CILE), 417 Carbon nanodots (CNDs), 29, 471
472 Carbon nanofiber-gold nanoparticles (CNFs-AuNPs), 198
199, 203
205 Carbon nanotubes (CNTs), 24
28, 31, 48f, 64, 119
120, 140, 168
169, 182
184, 197, 203, 206, 247
248, 294
295, 336
337, 410, 431
433, 533
534, 578
580, 586 carbon nanotube
modified electrodes, 580
582 dendrimers-based biosensors, 581
582 quantum dot-based biosensors, 580
581 CNT-based biosensors, 528, 579
580 CNT-based glucose biosensors, 148t structures of eight allotropes of carbon, 432f Carbon nanotubes-coated niobium (CNT-Nb), 27 Carbon paste electrode (CPE), 173, 229, 347
348, 387
410, 508, 542

Index

Carbon quantum dots (CQDs), 437, 471
472, 580 Carbon screen-printed electrode (CSPE), 171 Carbon-decorated ZnO (C-ZnO), 578 Carbonaceous composite sensors, 379
380 Carbonaceous materials, 134, 410 Carbonaceous structures, 168 Carboxyl-functionalized single-walled carbon nanotube (c-SWCNT), 203
205 Carboxylated MWCNTs, 580 Carboxymethyl-botryosphaeran (CMB), 176 Carcinogenic consequences, 467 Cardiovascular disease, 161 CAT. See Catechol (CAT) Catalase (CA), 312 Catalysts, 4 Catechin, 164
165 Catechol (CAT), 170, 175
176, 347
348 Cathode ray tubes, 4 CBPE. See Carbon black paste electrode (CBPE) CCE. See Carbon ceramic electrode (CCE) CCP. See Cyclic citrulline peptide (CCP) CDs. See Carbon dots (CDs) CE. See Capillary electrophoresis (CE) CE-AD. See Capillary electrophoresis amperometric detector (CE-AD) Cell biology, 123 Cell sensor technology, 434
435 Central nervous system (CNS), 22, 467 Ceramic nanomaterials, 5 Ceramic-based nanoparticles, 7 Cerium oxide (CeO2), 293
294 Cetyl trimethyl ammonium bromide (CTAB), 38 Chemical analysis, 123 Chemical precipitation techniques, 468 Chemical reduction, 11 Chemical sensors, 100, 216, 219 Chemical vapor deposition (CVD), 13, 39
40, 40f, 83
84, 106, 304, 586 Chemical vapor-mediated processes, 470
471 Chemically reduced GO (CRGO), 586

601

Chemicals, 372
373 pesticides, 372
373 Chemiluminescence, 22
23 Chemistry, 467 Chemotherapy agent, 410
414 Chitosan (CS), 29, 134, 312
313 nanocomposites, 387
410 Chloramphenicol, 387 Chlorogenic acid, 170, 181 Chlorpyrifos, 373 Chlorpyrifos aptasensor (CPF), 90 ChO. See Choline oxidase (ChO) Cholera, 254
255 Cholera toxin (CT), 369
370 Choline oxidase (ChO), 347 Choline-phenylalanine [Ch][Phe], 173
174 Chromatography, 21
23, 367
368, 380
381 Chromium (Cr), 463
464 Chronoamperometry, 313 CILE. See Carbon ionic liquid electrode (CILE) Citrinine, 370
371 Citrobacter C. freundii, 244 C. koseri, 244 Citrus sinensis, 543
544 Clark electrode, 288
289, 575 Class of synthesized chemicals, 199
200 Classification and Labelling of Chemicals (CLP), 535 Clinical diagnosis, applications of nanobiosensors in, 438
447, 440f Clitoria ternatea, 40
41 Clostridium difficile, 244 Clostridium perfringens, 244 electrochemical detection of, 257
258 CLP. See Classification and Labelling of Chemicals (CLP) CMB. See Carboxymethyl-botryosphaeran (CMB) CNDs. See Carbon nanodots (CNDs) CNFs-AuNPs. See Carbon nanofiber-gold nanoparticles (CNFs-AuNPs) CNS. See Central nervous system (CNS) CNT-Nb. See Carbon nanotubes-coated niobium (CNT-Nb)

602

Index

CNTs. See Carbon nanotubes (CNTs) Co3O4 nanocube electrode (Co3O4-NC electrode), 483
484 Coal, 287 Coating materials, 4 Cobalt (Co), 463
464 Cobalt oxide (Co3O4), 293
294 NP-based electrochemical biosensor, 441
447 Cocaine biosensor, 441 Composites, 97
98, 129 nanostructured biosensor, 387
410 semiconductor-based biosensor, 578 Computer-connected system, 130
131 Conductive polymers, 129 Conductivity, 297
298 Conductometric biosensors, 297
298 Conjugated polymers (CPs), 469
470 Consecutive adenine (CA), 350 Contact sensors, 99 Contaminated water, 372 Contemporary approaches, 123
124 Conventional electroanalytical sensing systems, 221 Converter, 381
382 Copolymer doped with silver
cobalt (CoAg), 511 Copper (Cu), 292, 463
464 Copper oxide (CuO), 197, 293
294 Copper oxide nanoflowers (CuO NFs), 203
205 Core layer, 6 Corona phase molecular recognition (CoPhMoRe), 26 Coronavirus disease, 2019 (COVID-19), 244
245, 258 Cortisol, 510 COVID-19. See Coronavirus disease, 2019 (COVID-19) CPE. See Carbon paste electrode (CPE) CPF. See Chlorpyrifos aptasensor (CPF) CPs. See Conjugated polymers (CPs) CQDs. See Carbon quantum dots (CQDs) CRGO. See Chemically reduced GO (CRGO) Cryptosporidium spp., 261
262 C. parvum, 261
262 oocysts, 262

CS. See Chitosan (CS) CSPE. See Carbon screen-printed electrode (CSPE) CT. See Cholera toxin (CT) CTAB. See Cetyl trimethyl ammonium bromide (CTAB) Cultural methods, 245 CV. See Cyclic voltammetry (CV) CVD. See Chemical vapor deposition (CVD) Cyanide, 440
441 Cyclic citrulline peptide (CCP), 560 Cyclic voltammetry (CV), 24, 31, 225
229, 246, 312
313, 387, 468 cycles, 150 method, 545
546 Cytoplasm, 528 Cytosine (C), 223
224

D DA. See Dopamine (DA) Danio rerio. See Zebra fish (Danio rerio) DEAE-dextran. See Diethylaminoethyldextran (DEAE-dextran) Degradation process, 467 Demineralized water (DM), 38 Dendrimers, 295, 581 dendrimers-based biosensors, 581
582 Dengue antibody, 433 Dengue virus of type E-protein (DENV-E protein), 558
560 DENV-E protein. See Dengue virus of type E-protein (DENV-E protein) Deoxyribonucleic acid (DNA), 129, 132, 220, 222
224, 245, 387
410, 416
417 probe, 440 receptor for, 577 DEs. See Disk electrodes (DEs) Detection limit (LOD), 89 Determination of drug analytes, 379
380 of lactose, 130
131 of toxic dyes based on electrochemical biosensors and applications, 225
236, 226t Device fabrication, 105 1,12-diaminododecane (DADD), 229

Index

1,7-diaminoheptane (DAH), 229 Diethylaminoethyl-dextran (DEAEdextran), 147 Differential pulse voltammetry (DPV), 24
27, 229, 246, 387
410, 529
530, 545 Digital sensors, 99 2-((7-(2,5-dihydrobenzylideneamino) heptylimino)methyl)benzene-1,4diol (DBHB), 508 3,4-dihydroxybenzaldehyde-2,4dinitrophenylhydrazone (DDP), 508 2,5-dihydroxybenzoic acid, 441 Dimethylsulfoxide (DMSO), 90
91 Diphenolase activity, 166 2,2-diphenyl-1-picrylhydrazyl (DPPH), 163 Disease-causing microbes, 249
250 Disk electrodes (DEs), 198
199, 203
205 Disperse Red 1 (Dr1), 225
229 Display, 290 unit, 101 Dithiocarbamic acid, 199
200 DM. See Demineralized water (DM) DMSO. See Dimethylsulfoxide (DMSO) DNA. See Deoxyribonucleic acid (DNA) Dopamine (DA), 22, 24
26, 176, 334, 509 Double-stranded DNA (ds-DNA), 223 Double-walled carbon nanotubes, 431 DPV. See Differential pulse voltammetry (DPV) Dr1. See Disperse Red 1 (Dr1) Drift, 136 detection, 135 Drugs, 384
386 delivery, 528 Dry chemical methods, 12
15. See also Wet chemical methods chemical vapor deposition, 13 electro-explosion, 13 electrospinning, 15 flame spray synthesis, 14 ion implantation, 14 laser ablation, 13 mechanical grinding/ball milling, 12
13

603

photochemical synthesis, 14 PVD, 13
14 solvent-free synthesis, 14 ds-DNA. See Double-stranded DNA (ds-DNA) Dyes, 215
218, 367, 373 molecules, 215, 218

E E-DNA. See Electrochemical DNA (EDNA) E102, 218 Ebola virus, 260 Eco
friendly nanoparticles, 543 EDC. See Ethylene carbodiimide (EDC) EDX spectroscopy methods. See Energydispersive X-ray spectroscopy methods (EDX spectroscopy methods) Eicosanoids, 509 EIS. See Electrochemical impedance spectroscopy (EIS) Electric signals, 506
507 Electrical biosensors, 577 Electrical nanobiosensors, 119
120 Electrical signal, 577 Electro-explosion, 13 Electroanalysis process, 21
22 Electrocatalytic behaviour, 485
486 Electrochemical analysis, 21
22, 345 Electrochemical assays, 262 Electrochemical biosensing experiment of, 38
41 fabrication of inorganic/organic nanostructures, 38
41 of hybrid nanomaterials, 47
49 of inorganic nanomaterials, 43
44 nanomaterials-based biosensors, 43
49 of organic nanomaterials, 45
46 results, 41
43 characteristics of biosensors, 41
42 characterization, 41 classification of biosensors, 43 typical synthesis of inorganic and organic nanomaterials, 38

604

Index

Electrochemical biosensors, 57
58, 79, 119
120, 122, 132
135, 196
197, 199
200, 218
224, 245
246, 287
288, 295
300, 370
371, 382
417, 430, 438, 542, 546
547, 577 amperometric biosensors, 296 biological materials, 416
417 biosensors, 120
121 carbon-based nanomaterials, 410
414 classical biosensor comprising of bioreceptor, transducer, electronic circuit, 220f components, 506
507 conductometric biosensors, 297
298 design and principle of biosensors, 130
132 determination of toxic dyes based on, 225
236, 226t electrochemical oxidation of amoxicillin on graphene-based nanosensör, 384f future reliability, 122
124 graphene nanomaterials in electrochemical biosensor fabrication, 585
587 impedimetric biosensors, 298
300 importance of, 207 interface of biosensor, 132
133 materials of biosensor interfaces, 133
135 metal nanostructured biosensors, 386
410 metal
organic framework, 416 nanostructured biosensors, 417 nanostructured electrochemical sensors using POP, 385f oxidoreductase enzymes used in development of, 165
167 polymer-supported nanostructured biosensors, 414
416 potentiometric biosensors, 297 principle of electrochemical biosensors for detection of hormones, 506
507 quantitative determination of carbamazepine, 385f recent trends in biosensors, 121
122 relative simplicity, 119

reproducibility and lifetime, 135
152 definition of stability, 136 operational stability, 137
152 shelf stability, 136
137 systematic representation of nanostructured electrochemical biosensor, 383f systems, 222 ZnO nanostructures in fabrication of, 587
589 Electrochemical cell, 169
170 Electrochemical converters, 548 Electrochemical detection of Bacillus spp., 255
256 of Clostridium perfringens, 257
258 of Escherichia coli, 250
252 of hormones, 507 of Listeria monocytogenes, 253
254 of microorganisms, 249
258, 264t of protozoa, 260
268 of Salmonella spp., 252
253 of Staphylococcus aureus, 256
257 of Streptococcus spp., 255 of Vibrio spp., 254
255 of viruses, 258
260 Electrochemical detectors, 23 Electrochemical DNA (E-DNA), 149 Electrochemical enzymatic biosensors, general aspects of construction of, 168
170, 170f Electrochemical fields, 410 Electrochemical graphene-based nanobiodevices, 586
587 Electrochemical immunosensors, 150 for mosaic virus, 259 Electrochemical impedance spectroscopy (EIS), 175
176, 223, 246, 298
299, 312
313, 415
416, 468, 529
530, 554
555 Electrochemical methods, 129
130, 245, 383, 469, 547 properties of NCs studied by, 334
336 Electrochemical nanobiosensors fabrication of, 547
563 green nanomaterials in electrochemical nanobiosensors, 548
563

Index

green nanomaterials in, 548
563 green nanostructures in aptasensors, 560
563 green nanostructures in enzyme-based biosensors, 548
557, 555f green nanostructures in immunosensors, 557
560 Electrochemical NCs sensing, significance of integrating nanostructured materials for, 336
338 Electrochemical process, 87, 130 Electrochemical sensing, 249, 302 Electrochemical sensors, 57
58, 79, 119, 122
123, 198
199, 223, 246, 287
288, 351
352, 379
380, 383, 506
507 Electrochemical synthesis, 11 Electrochemical systems for neurochemical detection, last trends in, 350
355 Electrochemical transducers, 295
296 Electrochemically reduced GO (ERGO), 586 Electrochemistry, 218
219 Electrodes, 21
22, 221
223, 246, 430, 476
483, 506, 542 conductivity, 558 material, 221 Electronic systems, 101, 290, 381
382, 506
507 Electrons, 57
58 shuttles, 61 transfer, 57
58 Electrospinning, 15, 109 Electrostatic force, 484
485, 547 ELISA. See Enzyme-linked immunosorbent assay (ELISA) ELONA. See Enzyme-linked oligonucleotide assay (ELONA) Emulsion polymerization, 12 Endocrine hormones, 505 Endogenous biomolecules, 22 Energy source, 99 Energy-dispersive X-ray spectroscopy methods (EDX spectroscopy methods), 414
416, 555

605

Enterobacter E. cloacae, 244 E. faecalis, 256 E. sakazakii, 244 Entrapment, 169 Env plasmid DNA vaccine, 527 Environmental Protection Agency (EPA), 440, 465
466 Enzymatic biosensors, 102
103, 162, 165, 167, 224, 416
417, 529
530 carbon-based nanomaterial/metal nanoparticle, 182
186 carbon-based nanomaterials, 171
176 for determination of specific antioxidant or total content in beverages, 170
186 green nanostructures in, 548
557, 555f metal nanoparticles, 176
182 Enzymatic system, 162 Enzyme-linked immunosorbent assay (ELISA), 215
216, 506 Enzyme-linked oligonucleotide assay (ELONA), 258
259 Enzymes, 132, 139, 222, 248, 416, 470 enzyme-based nanobiosensor for neurochemical detection, 345
348 enzyme-based nanostructured sensors, 416
417 enzyme-linked biosensor systems, 224 immobilization, 173
174 EPA. See Environmental Protection Agency (EPA) Epichlorohydrin, 169 Epilepsy, 331 Epinephrine (EPN), 22, 25
26, 30, 176, 334, 507
508 EPN. See Epinephrine (EPN) ERGO. See Electrochemically reduced GO (ERGO) Escherichia coli, 244, 441, 543, 555 electrochemical detection of, 250
252 Essential nervous system functions, 22 17β-estradiol, 509
510 17β-estradiol-imprinted poly(aniline-cometanilic acid), 510 Estrogen, 509
510 Ethanol, 186

606

Index

1-ethyl-3-(3-[dimethylamino] propyl) carbodiimide hydrochloride (EDC), 169 Ethylene carbodiimide (EDC), 90
91 EU. See European Union (EU) Eucommia ulmoides, 474
476 European Union (EU), 535 Exogenous biomolecules, 22

F f-MWCNTs. See Functionalized MWCNTs (f-MWCNTs) Fabrication of electrochemical nanobiosensors, 547
563 ZnO nanostructures in fabrication of electrochemical biosensors, 587
589 Factor information, 135
136 FE-SEM. See Field emission scanning electron microscopy (FE-SEM) Ferrocene (Fc), 90 Fertilizers, 367 Ferulic acid, 164
165 FETs. See Field-effect transistors (FETs) FIA. See Flow injection analysis (FIA) FIB technique. See Focused ion beam technique (FIB technique) Field emission scanning electron microscopy (FE-SEM), 86, 560 Field-effect transistors (FETs), 45, 197, 345
346 Fingerprint scrutiny, 437
438 First amperometric enzyme sensor, 379
380 Flame spray synthesis, 14 Flat-panel displays, 4 Flexible electrodes, 383 Flow injection analysis (FIA), 173
174 Fluorescence N-doped carbon dots, 476 Fluorescence resonance energy transfer (FRET), 66 Fluorescence response experiments, 581 Fluorescence spectroscopy, 332
333 Fluorescent analysis, 440 Fluorimetry, 22
23

Fluorine tin oxide (FTO), 417 Focused ion beam technique (FIB technique), 109 Folin
Ciocalteu method, 164
165, 171, 173
174, 179 Folin
Ciocalteu spectrophotometric method, 182
184 Follicle-stimulating hormone, 511
512 Food, 533 additives, 367 chain, 467 cleanliness, 243 colorants, 218 colors, 373 evaluation, 121
122 security, 243
244 Food toxins types of, 369
374 bacterial toxins, 369
370 chemicals, 372
373 dyes, 373 fungal toxins, 370
371 heavy metals, 372 marine biotoxin, 371 phytotoxins, 371
372 plastics, 373
374 Food Yellow 4, 218 Foodborne disease, 261 Foodborne illnesses, 243
244 Foodborne pathogens, 244, 249
250 Forensic diagnosis, applications of nanobiosensors in, 438
447, 440f Fossil fuels, 287 Fourier transform infrared spectroscopy (FTIR spectroscopy), 387, 415
416, 555 Free radicals, 161 FRET. See Fluorescence resonance energy transfer (FRET) FTIR spectroscopy. See Fourier transform infrared spectroscopy (FTIR spectroscopy) FTO. See Fluorine tin oxide (FTO) Fullerenes, 168
169, 436
437 Functionalized MWCNTs (f-MWCNTs), 528 Fungal toxins, 370
371

Index

G Gallic acid, 170, 173
174 Garlic (Allium sativum), 544 Gas chromatography (GC), 195
196, 215
216, 332
333 Gas hydrogen sulfide (H2S), 301
302 sensing, 307
309 Gas sensors, 287 Gas-sensitive electrode, 297 GC. See Gas chromatography (GC)Glassy carbon (GC)Glycol chitosan (GC) GCEs. See Glassy carbon electrodes (GCEs) GE. See Graphite working electrodes (GE) Genosensors, 223
224 Glassy carbon (GC), 585
586 Glassy carbon electrodes (GCEs), 29, 140, 225
229, 229f, 373, 414, 438
440, 510
512, 542, 580 GLu. See Glutamate (GLu) GLu-binding protein (GLuBP), 344
345, 344f GLuBP. See GLu-binding protein (GLuBP) Glucose, 429 determination, 379
380 oxidation process, 556
557 Glucose oxidase (GOx), 49, 90, 554
555 Glut. See Glutaraldehyde (Glut) Glutamate (GLu), 335 Glutaraldehyde (Glut), 147, 169, 347
348 Glycol chitosan (GC), 175
176 GNPl. See Graphene nanoplatelets (GNPl) GNRs. See Gold nanorods (GNRs) GO. See Graphene oxide (GO) Gold (Au), 292
293, 386
387 electrode, 251 Gold nanoparticles (AuNPs), 60
61, 90, 106, 178, 203
205, 231
232, 247, 299
300, 312
313, 337
338, 530
531, 548
554, 580, 582 with silver deposition, 582
584 Gold nanorods (GNRs), 306 Gold screen-printed electrode (Au-SPE), 184 Goniothalamus wightii, 545 GOx. See Glucose oxidase (GOx)

607

GQDs. See Graphene quantum dots (GQDs) Grafted polyaniline (PG), 345
346 Graphene, 123, 168
169, 203, 247
248, 295, 585 graphene-based biosensors, 66 graphene-based electrochemical biosensors, 206 graphene-based FRET, 66 graphene-based QD’s, 28
31 graphene-based sensors, 295 graphene-coated glassy carbon electrode, 582
583 nanoflowers, 23
24 nanofoams, 23
24 nanomaterials in electrochemical biosensor fabrication, 585
587 nanorods, 23
24 paste electrode, 31 Graphene nanoplatelets (GNPl), 171, 184 Graphene oxide (GO), 174
175, 345, 440, 586 Graphene quantum dots (GQDs), 171, 186, 234
236, 347, 471
472, 580 Graphite, 119
120 Graphite working electrodes (GE), 554 Graphitic carbon nitride (g-C3N4), 472 nanosheets, 370
371 Graphitic oxide, 66 Green chemistry, 541
542 Green nanomaterials, 546, 548 in electrochemical nanobiosensors, 548
563 Green nanostructures in aptasensors, 560
563 in enzyme-based biosensors, 548
557 in immunosensors, 557
560 selective studies of green nanostructured electrochemical biosensors, 549t Green synthesis, 10, 40
41, 543 electrochemical biosensors, 546
547 fabrication of electrochemical nanobiosensors, 547
563 green nanomaterials, 543
546 method, 541
542 Guaiacol, 170, 176 Guanine (G), 223
224

608

Index

H h-BN. See Hexagonal boron nitride (hBN) Hb. See Hemoglobin (Hb) HD-CNTf. See High density carbon nanotube fiber (HD-CNTf) Headspace sampling (HS), 306, 306f Health, 532
533 Heavy metals, 287
288, 372, 463
464, 484
485 Hemoglobin (Hb), 312
315 Heparin biosensor, 440 Hepatitis B virus, 435
436 Hexadecyltrimethylammonium bromide (CTAB), 508 Hexagonal boron nitride (h-BN), 472 High density carbon nanotube fiber (HDCNTf), 25
26 High resolution transmission electron microscopy (HR-TEM), 87, 89 High-performance electrochemical biosensors, 197 High-performance liquid chromatography (HPLC), 176, 195
196, 215
216, 332
333 High-resolution transmission electron microscopy (HR-TEM), 302
303, 555 Highly active biomolecules, 132
133 Highly oriented pyrolytic graphite (HOPG), 66 HOPG. See Highly oriented pyrolytic graphite (HOPG) hOR. See Human olfactory receptor (hOR) Hormones, 505 adiponectin, 511 adrenaline or epinephrine and noradrenaline or norepinephrine, 507
508 amino acid derivatives, 507 calcitriol, 511 cortisol, 510 dopamine, 509 electrochemical detection of hormones, 507 estrogen, 509
510

follicle-stimulating hormone, 511
512 human chorionic gonadotropin, 512 insulin, 512 leptin, 512
513 melatonin, 508 principle of electrochemical biosensors for detection, 506
507 progesterone, 510
511 prolactin, 513 proteins/peptides, 511 steroids and eicosanoids, 509 testosterone, 509 triiodothyronine and thyroxine, 508 Horseradish peroxidase (HRP), 49, 61, 167, 554 HPLC. See High-performance liquid chromatography (HPLC) HR-TEM. See High resolution transmission electron microscopy (HR-TEM)High-resolution transmission electron microscopy (HR-TEM) HRP. See Horseradish peroxidase (HRP) HS. See Headspace sampling (HS) Human antioxidant defense system, 162 Human chorionic gonadotropin, 512 Human olfactory receptor (hOR), 48f Human T-lymphotropic Virus-1, 260 Huntington’s disease, 331 Huntington’s disorders, 22
23 Hybrid metal oxide nanomaterials, 37
38 Hybrid nanomaterials, 80
81 electrochemical biosensing of, 47
49 Hybrid nanostructures, 80 Hybridization chain reaction-based biosensor, 434
435 Hydrogel, 134 Hydrogen evolution reaction, 473
474 Hydrogen peroxide (H2O2), 563 Hydrogen sulfides, 287 Hydrothermal interaction, 476
483 Hydrothermal method, 11, 84
87 Hydroxyapatite nanowire, 440
441 Hydroxylase activity, 166 5-hydroxytryptamine (ST or 5-HT), 334 5-hydroxytryptophan (HTRP), 32
33 Hyperactivity disorder, 331

Index

I IC. See Indigo carmine (IC) ICPE. See International Conference on Precision Engineering (ICPE) IDE. See Interdigitated electrode (IDE) Ig. See Immunoglobulins (Ig) IgG. See Immunoglobulin G (IgG) Imaging system, 381
382 immuno-RCA. See Immuno-rolling circle amplification (immuno-RCA) Immuno-rolling circle amplification (immuno-RCA), 441 Immunoassay techniques, 215
216 Immunoglobulin G (IgG), 582 Immunoglobulins (Ig), 104 Immunosensors, 338, 433, 512, 557 green nanostructures in, 557
560 immunosensor-based nanobiosensor for neurochemical detection, 338
345 Impedimetric biosensors, 298
300 Indigo carmine (IC), 229 Indium oxide (In2O3), 353
355 Indium-tin-oxide (ITO), 587 Inductively coupled plasma mass spectroscopy, 465
466, 468 Infirmity-adjusted life years (DALYs), 243
244 Infrared thermometers (IR thermometers), 98 Inorganic nanomaterials, 4 electrochemical biosensing of, 43
44, 47
49 synthesis of, 38 Inorganic nanostructures, fabrication of, 38
41 Inorganic pollutants, 467 Insecticides, nanostructured electrochemical biosensors fabricated for detection of, 199
206 Insulin, 512 Interdigitated electrode (IDE), 560 International Conference on Precision Engineering (ICPE), 3 Ion implantation, 14 Ionic liquid (IL), 511 IR thermometers. See Infrared thermometers (IR thermometers)

609

Iron oxide (Fe2O3), 293
294 Iron oxide nanoparticles (FeNPs), 560 Iron(II) phthalocyanine (FePc), 171

K Klebsiella K. oxytoca, 244 K. pneumoniae, 244

L L-cysteine (L-cys), 558
560 Lab-on-a-chip, 530 Label-based electrochemical detection, 248
249 Label-free electrochemical aptasensor, 561
563 Label-free electrochemical progesterone aptasensor, 510
511 Laccase biosensor, 181 laccase-based electrochemical enzyme biosensor, 232 Laccase enzyme (LaE), 347
348 LaE. See Laccase enzyme (LaE) Lap. See Laponite (Lap) Laponite (Lap), 179
180 Laser ablation method, 13, 90
91 Laser desorption/ionization (LDI), 215
216 LC. See Liquid chromatography (LC) LDI. See Laser desorption/ionization (LDI) Lead (Pb), 463
464, 467
468 Lepidocrocite (γ-FeOOH), 415
416 Leptin, 512
513 Lifetime of electrochemical biosensors, 135
152 Light scattering capabilities, 530
531 Limit of detection (LOD), 23
25, 171, 225
229, 296, 352, 547 Limit of quantification (LoQ), 25 Linear sweep voltammetry, 246 Linearity, 102 Lipid hormones, 505 Liquid chromatography (LC), 215
216 Liquid chromatography
mass spectrometry, 506

610

Index

Liquid microjunction surface sampling probe mass spectrometry (LMJ-SSP Ms), 215
216 Listeria monocytogenes, 244 electrochemical detection of, 253
254 Lithography, 38
39, 39f, 470
471 LMJ-SSP Ms. See Liquid microjunction surface sampling probe mass spectrometry (LMJ-SSP Ms) LOD. See Detection limit (LOD)Limit of detection (LOD) LoQ. See Limit of quantification (LoQ) Low-energy excitation sources, 4 Luminescence, 21
22

M m-benzenediols, 166 Magnetic iron oxide nanoparticles, 338 Magnetic nanoparticles (MNPs), 62, 63f Magnetite/carbon quantum dots (MagNP/ C-dots), 87 MagNP/C-dots. See Magnetite/carbon quantum dots (MagNP/C-dots) Malachite green, 234
236 Malaria, 261
262 MALDI. See Matrix-assisted laser desorption/ionization (MALDI) Mammalian central nervous system, 507 Manganese oxide (MnO2), 293
294 Marine biotoxin, 371 Marine environments, 371 Mass spectrometry (MS), 22
23 Mass spectroscopy, 332
333 Mass-based biosensors, 577 Matrix-assisted laser desorption/ionization (MALDI), 215
216 MB. See Meldola’s blue (MB)Methylene blue (MB) Mechanical grinding/ball milling method, 12
13 Melatonin (MT), 508 Meldola’s blue (MB), 82
83 MEMSs. See Microelectromechanical systems (MEMSs) 6-mercapto-1-hexanol (MCH), 234
236 4-mercapto-pyridine (Mpy), 306

Mercaptopropionic acid (MPA), 312
313 3-mercaptopropyltriethoxysilane (MPTMS), 528
529 Mercury (Hg), 463
464, 466
467 MERS. See Middle East respiratory syndrome (MERS) MERS coronavirus (MERS-CoV), 260 MERS-CoV. See MERS coronavirus (MERS-CoV) Mesoporous materials, 308 Mesoporous silica, 203 Meta-benzenediols, 166
167 Metabolic engineering, 575 Metal nitrate (Mx (NO3)2), 38 Metal oxide nanoparticles (MONPs), 8, 62
63, 292
294, 386
387, 543
544 synthesis steps of, 544f Metal oxides, 44 for biosensing applications, 65t biosensor, 384, 527 electrochemical biosensors, 206 Metallic nanomaterials, 384
386 Metallic nanoparticles, 84, 121, 168
169 Metallic nanostructure (MN), 82 Metallic nanostructured electrochemical biosensors bottom-up process, 82
87 methods employed for synthesizing nanoparticles and nanostructure, 81t top-down process, 88
91 Metal
organic frameworks (MOF), 107, 129, 134
135, 203, 384
386, 416 MOF-supported nanostructured biosensors for analysis of galantamine, 386f Metals, 129 ions, 134
135 metal-and metal oxide-based biosensors, 527
528 metal-based electrode, 169 metal-based nanomaterials, 133 metal-based nanoparticles, 7 nanoparticles, 5, 168, 176
186, 177t, 183t, 293 nanospheres, 8 nanostructured biosensors, 386
410

Index

biological materials supported nanostructured biosensors, 411t carbon nanostructures electrochemical biosensors, 393t metal-based nanostructured biosensors, 388t MOF supported nanostructured biosensors, 408t nanostructured biosensors, 413t polymer-supported nanostructured biosensors, 406t toxicity, 464 Methanol, 163
164 Methicillin-resistant Staphylococcus aureus (MRSA), 256
257 Methotrexate drug, 410
414 Methylene blue (MB), 251
252 Metronidazole (MIZ), 545 Micro-fabrication technologies, 122 Microbial biosensors, 297
298 Microdots, 386
387 Microelectromechanical systems (MEMSs), 110 Microemulsion method, 11
12 Microfluidic device, 250
251 microfluidic device-based nanostructured sensor, 351
352 Micromolecules, 22 Micronanotechnology technique, 252 Microorganisms, 543 electrochemical detection of, 249
258, 264t Microperoxidase (MP), 312 Microplastics, 373
374 Microspectroscopy, 373
374 Microwave-assisted synthesis, 12 Middle East respiratory syndrome (MERS), 244
245 Milling process, 90 MIPs. See Molecularly imprinted polymers (MIPs) MIZ. See Metronidazole (MIZ) MN. See Metallic nanostructure (MN) MNPs. See Magnetic nanoparticles (MNPs) Model 23 A YSI analyzer, 129 MOF. See Metal
organic frameworks (MOF)

611

Molecularly imprinted polymers (MIPs), 129, 132, 222, 246, 333, 379
380, 414
415, 544 Molybdenum (Mo), 463
464 Molybdenum disulfide (MoS2), 171, 186 Molybdenum disulfide
reduced graphene oxide (MoS2-rGO), 338 Molybdenum oxide (MoO3), 164
165, 293
294 MONPs. See Metal oxide nanoparticles (MONPs) MP. See Microperoxidase (MP) MPA. See Mercaptopropionic acid (MPA) MRSA. See Methicillin-resistant Staphylococcus aureus (MRSA) MS. See Mass spectrometry (MS) MT. See Melatonin (MT) Multi-walled carbon nanotubes (MWCNTs), 24, 64
66, 140, 171, 232
233, 314
315, 431, 507
508, 580
581 based sensors, 508 decorated with gold nanoparticles, 563 polypyrrole nanocomposite, 581
582 Multidimensional nanobiosensors, 295 MWCNTs. See Multi-walled carbon nanotubes (MWCNTs) Myb. See Myoglobin (Myb) Mycobacterium tuberculosis, 435
436 Mycotoxins, 370
371 Myoglobin (Myb), 314
315

N N-hydroxysuccinimide (NHS), 176 N-methyl carbamic acid, 199
200 (N-methyl-4-pyridyl)porphyrin toluene sulfonate (TMPP), 476 Nafion biosensor, 185
186 Nafion-immobilized BChE biosensor, 147 Nano-thin films, 60 Nanobiosensors, 291
292, 534 in clinical and forensic diagnosis, applications of, 438
447, 440f for detection of illicit drugs and clinical and forensic diagnosis, 442t Nanocomposites, 436
437 Nanodiamond (ND), 31
33

612

Index

Nanoelectromechanical systems (NEMSs), 110 Nanoelectronics, 45 Nanofabrication, 122, 433
434 Nanofibers, 59
60 Nanomaterials, 3
5, 58
59, 79
80, 97
98, 122, 129, 133, 230
231, 291
292, 369
372, 384
386, 430
431, 469
476, 526, 548, 580 electrochemical detection of toxic metals, 469f nanomaterial-based biosensors, 43
49, 291
295, 380
381, 441
447 classification of, 291f electrochemical biosensing of hybrid nanomaterials, 47
49 electrochemical biosensing of inorganic nanomaterials, 43
44 electrochemical biosensing of organic nanomaterials, 45
46 multidimensional nanobiosensors, 295 one-dimensional nanobiosensors, 294
295 potentiometric biosensors, 44
45 voltammetric determinations, 45 zero-dimensional nanobiosensors, 292
294 nanomaterials-based electrochemical biosensors, 441, 466 production of GQD/MoS2 van der Waals heterojunctions, 475f synthesis and properties of ultrasoundassisted synthesis CQD, 474f used in fabrication of biosensors, 105
108 Nanoparticles (NPs), 6, 8, 57
59, 79
80, 97
98, 120, 123, 195, 203, 247, 291
292, 372, 414, 430, 434
436, 526, 530
531, 541, 563 approaches involved in, 7f for biosensing applications, 65t classification of, 5
6, 59
60 one-dimensional nanomaterials, 59
60 three-dimensional nanomaterials, 60 two-dimensional nanomaterials, 60 zero-dimensional nanomaterials, 59

exposure, 532
533 nanoparticle-based biosensors, 105, 292
294 metal nanoparticles, 293 metal oxide nanoparticles, 293
294 from several procedures, 8t synthesis methods, 6
7, 9f, 434 techniques used for nanoparticles synthesis, 435f Nanoplastics, 373
374 Nanoprobe, 438
440 Nanorods, 59
60, 97
98 nanorod-based biosensors, 578
579 ZnO nanorod array photoelectrodes for highly efficient quantum dots sensitized solar cells clicking, 579f Nanoscale, 120, 526
527 Nanoscience, 433 Nanosensors, 469
470, 534 Nanosheets, 60 Nanospheres, 79
80 Nanostructure biosensors, 372 Nanostructure materials, 379
380 Nanostructured biosensors, 367
368, 417 agriculture, 533
534 biosensors, 100
102, 526
530 classification of biosensors based on bioreceptors, 102
105 classification of sensors, 98
100 distinct platforms in fabrication of advanced biosensor devices, 108
111 emerging nanomaterials used in fabrication of biosensors, 105
108 food, 533 health, 532
533 recent development in, 530
531 regulations, 535 safety, 532 Nanostructured conjugated polymers (NCPs), 469
470 Nanostructured electrochemical biosensors, 382
383 applications of, 207 challenges, 207
208 fabricated for detection of pesticides and insecticides, 199
206

Index

fabrication of, 198
199 future scope, 208 importance of electrochemical biosensors, 207 properties of, 198 Nanostructured electrochemical sensor application NCs detection, 338
355 aptamer-based nanobiosensor for, 348
350 enzyme-based nanobiosensor for, 345
348 immunosensor-based nanobiosensor for, 338
345 last trends in electrochemical systems for, 350
355 via nanostructured-based aptamer sensors, 339t Nanostructured electrodes, 529 Nanostructured hybrid biosensors, 417 Nanostructured materials (NMs), 37
38, 195
196, 207, 431
438, 469
470 bottom-up approach, 8
15 carbon dots, 437
438 carbon nanotubes, 431
433 for electrochemical NCs sensing, 336
338 fullerenes, 436
437 nanomaterials and nanotechnology, 3
5 nanoparticles, 434
436 nanoparticles classification of, 5
6 synthesis of, 6
7 nanostructured material
based electrochemical biosensor, 582
589 gold nanoparticles, 582 gold nanoparticles with silver deposition, 582
584 graphene nanomaterials in electrochemical biosensor fabrication, 585
587 silver nanoparticles, 584 ZnO nanostructures in fabrication of electrochemical biosensors, 587
589 nanostructured materials-based electrochemical biosensor devices

613

application of enzymatic biosensor for determination of specific antioxidant or total content in beverages, 170
186 general aspects of construction of electrochemical enzymatic biosensors, 168
170 oxidoreductase enzymes used in development of electrochemical biosensors for determination of phenolic compounds, 165
167 reference analytical methods employed for determination of antioxidants in beverages, 163
165 nanowires, 433
434 top-down approach, 7 Nanostructured metal oxides (NMOs), 527, 587 Nanostructured platforms, applications of toxic metals detection using, 476
486, 477t Nanostructures, 80
81, 134, 197, 372, 526
527 Nanotechnology, 3
5, 58
60, 79
80, 195, 433, 525
526, 541 classification of nanoparticles, 59
60 Nanotubes, 3, 59
60 Nanowalls, 60 Nanowire (NW), 3, 59
60, 97
98, 203, 294
295, 303
304, 433
434, 577 nanowire-based biosensors, 577 sensors, 577 2,3-naphthalocyanine (Nc), 25
26 Natural biopolymers, 414
415 Natural colorants, 218 Natural dyes, 217 Natural toxicants, 367 NCPs. See Nanostructured conjugated polymers (NCPs) NCs. See Neurochemicals (NCs) ND. See Nanodiamond (ND) Near-infrared fluorescence (nIR fluorescence), 26 NEMSs. See Nanoelectromechanical systems (NEMSs)

614

Index

Neurochemicals (NCs), 331 application of nanostructured electrochemical sensor for NCs detection, 338
355 as biomolecules, 22
33 carbon-based quantum dots and graphene-based QD’s, 28
31 CNTs, 24
28 ND, 31
33 challenges, 355 detection aptamer-based nanobiosensor for, 348
350 enzyme-based nanobiosensor for, 345
348 immunosensor-based nanobiosensor for, 338
345 last trends in electrochemical systems for, 350
355 microfluidic device-based nanostructured sensor, 351
352 smartphone-based nanostructured sensor, 351 wearable nanostructured sensor for, 352
355 properties of NCs commonly studied by electrochemical methods, 334
336 ACh, 336 AβO, 336 BCM-7, 335 DA, 334 EPN, 334 GLu, 335 Nor-EPN, 334 serotonin, 334 TB, 336 TRYPN, 335 TYR, 335 schematic illustration of synapses, 332f significance of integrating nanostructured materials for electrochemical NCs sensing, 336
338 Neurotransmitters, 22
33 carbon-based quantum dots and graphene-based QD’s, 28
31 CNTs, 24
28 ND, 31
33

Next-generation biosensors, 525 NF. See Nickel foam (NF) NHS. See N-hydroxysuccinimide (NHS) Nickel (Ni), 463
464 metallic surface, 83
84 Nickel foam (NF), 417 Nickel oxide (NiO), 293
294 Nickel oxide nanoparticles (NiO NPs), 556
557 NiFe2O4-mesoporous carbon nanocomposite (NiFe2O4-MC nanocomposite), 510 Nigella sativa, 556
557 nIR fluorescence. See Near-infrared fluorescence (nIR fluorescence) Nitric oxides (NO), 309 biosensing of, 309
316 biosensor, 313 Nitrogen, 134, 287 Nitrogen dioxide (NO2), 300
301 NO2 sensing, 302
304, 303f NMOs. See Nanostructured metal oxides (NMOs) NMs. See Nanostructured materials (NMs) NO. See Nitric oxides (NO) Noncarbon nanostructured materials, 333 Nonconductive polymers, 134 Noncontact sensors, 99 Nonenzymatic biosensors, 79 Nonenzymatic defense system, 162 Nor-epinephrine (Nor-EPN), 22, 25
26, 334, 507
508 Nor-EPN. See Nor-epinephrine (Nor-EPN) Noradrenaline, 507
508 Norovirus, 258, 261
262 NPs. See Nanoparticles (NPs) Nucleic acids, 57, 223 Nucleotides, 223
224 NW. See Nanowire (NW)

O o-phenylenediamine, 233
234 Ochratoxin, 370
371 OFDs. See Tiny organic fluorescent dyes (OFDs) Ogataea polymorpha, 548
554

Index

Olfactory nerve paralysis, 301
302 One-dimension (1D) nanobiosensors, 294
295 nanomaterials, 59
60, 64 nanorods and nanowires, 37
38 nanostructures, 291
292 Operational stability, 136
152 OPs. See Organophosphates (OPs) Optic-based biological sensors, 123
124 Optical amplifiers, 4 Optical biosensor, 384 Optical fibers, 576 Organic chemistry, 57
58 Organic ligands, 134
135 Organic metal oxides, 45 Organic molecules, 431
432 Organic nanomaterials electrochemical biosensing of, 45
49 synthesis of, 38 Organic nanostructures CVD, 39
40 fabrication of, 38
41 green synthesis, 40
41 lithography, 38
39 sol
gel nanofabrication, 40 Organic NMs, 45 Organic solvents, 383 Organophosphates (OPs), 199
200 Organophosphorus pesticides, 435
436 Ortho-benzenediols, 166
167 Overoxidized polypyrrole (OPPy), 509 OVs. See Oxygen vacancies (OVs) Oxides metal inorganic and organic structures, 37
38 of sulfur, 287 Oxidoreductase enzymes used in development of electrochemical biosensors for determination of phenolic compounds, 165
167 Oxidoreductase-related applications, 121 Oxygen vacancies (OVs), 302
303

P p-benzenediols, 166 PAb. See Polyclonal antibodies (PAb) PACB. See Polymerized ACB (PACB)

615

PADs. See Paper-based analytical devices (PADs) Palladium (Pd), 180
181, 292
293 Palladium nanoparticles (PdNPs), 182 Palytoxin (PlTX), 371 Paper-based analytical devices (PADs), 306, 306f Paper-based microfluidics, 110 Para-benzenediols, 166
167 Paracetamol, 176 Parametric sensors, 99 Parathion-methyl, 373 Parkinson’s disease, 331 Parkinson’s disorders, 22
23, 463
464 Particulate matter (PM), 300
301 PAS. See Pyrrolidinium acid sulfate (PAS) Passive sensors, 99 Pathogenic microbes, 243 Pathogens, 249
250 foodborne illnesses, 244 in water and food samples electrochemical detection of microorganisms, 249
258 electrochemical detection of protozoa, 260
268 electrochemical detection of viruses, 258
260 label-based electrochemical detection, 248
249 PB. See Prussian blue (PB) PBP2a. See Penicillin-binding protein 2a (PBP2a) PBS. See Phosphate buffered saline (PBS) PC. See Phthalocyanine (PC) PC12. See Pheochromocytoma (PC12) PCB. See Printed circuit board (PCB) PdNPs. See Palladium nanoparticles (PdNPs) PDs. See Polymer dots (PDs) Pencil graphite electrodes (PGEs), 232
233, 256, 415
416, 542 Penicillin-binding protein 2a (PBP2a), 256 Peptides, 511 Peroxidase (PO), 180
181 Persistent luminescence nanorods (PLNRs), 203
205

616

Index

Pesticides, 195
196, 199
200, 367, 372
373, 384
386 nanostructured electrochemical biosensors fabricated for detection of, 199
206, 201t sensors, 369f Petroleum products, 287 PG. See Grafted polyaniline (PG) PGE. See Pyrolytic graphite electrode (PGE) PGEs. See Pencil graphite electrodes (PGEs) PGFETs. See Polyaniline-grafted reduced graphene oxide field-effect transistors (PGFETs) Pharmaceutical drugs electrochemical biosensors, 383
417 three components of biosensor, 381f Phenol, 166
167 Phenolic compounds, 163, 175
176, 179 oxidoreductase enzymes used in development of electrochemical biosensors for determination of, 165
167 Phenylenediamine-benzodithiophene polymer (pBDBT), 509 phenyltrimethoxysilane (PTMS), 528
529 Pheochromocytoma (PC12), 25
26 Phosphate buffered saline (PBS), 47, 225
229 Phosphomolybdic acid (H3PMo12O40), 164
165 Phosphors, 4 Phosphorus, 134 Phosphotungstic acid (H3PW12O40), 164
165 Photochemical synthesis, 14 Photolithography, 38
39 Photoluminescence, 437
438 Phthalocyanine (PC), 25
26 Physical adsorption, 169 Physical sensors, 99 Physical vapor deposition (PVD), 13
14 Phytotoxins, 371
372 PI. See Polyallylamine (PI) Pigments, 215
218 PILs. See Polymeric ionic liquids (PILs)

Plants, 10 Plasma membranes, 505 Plasma sputtering method, 88
89 Plasma-containing ions, 88 Plasmonic nanoparticles, 530
531 Plastics, 373
374 Platinum (Pt), 180
181, 292
293, 386
387 Platinum nanoparticles (PtNPs), 181 PLNRs. See Persistent luminescence nanorods (PLNRs) PlTX. See Palytoxin (PlTX) PM. See Particulate matter (PM) PO. See Peroxidase (PO) POC. See Point-of-care (POC) Point-of-care (POC), 149
150, 429 Pollution, 468 Poly-(3-amino-5-hydroxypyrazole) (polyAHP), 414
415 Poly-(o-phenylenediamine)-based surface, 233
234 Poly(3,4-ethylenedioxythiophene) (PEDOT), 347, 415 Poly(4-styrenesolfonic acid)-doped polyaniline films (PSSA/PANI), 371 Poly(AAm-co-EMA)-modified electrode, 232 Poly(amidoamine) dendrimer (PAMAM dendrimer), 528 Poly(bromophenol blue), 414
415 Poly(diallyldimethylammonium chloride) (PDDA), 232
233, 527 Poly(ethylene glycol diglycidyl ether) (PEGDGE), 312
313 Poly(indole-5-carboxylic acid) (PIn-5COOH), 150 Poly(lactic acid), 346 Poly(propylene glycol) phosphate (PPG-P), 528
529 Poly(styrene-co-acrylic acid), 582
583 Poly(terthiophene carboxylic acid) (PTTCA), 312 Polyallylamine (PI), 84 Polyaniline, 171
173 Polyaniline-grafted reduced graphene oxide field-effect transistors (PGFETs), 345
346

Index

Polyaniline
polypyrrole (PANI-PPY), 511 Polybenzimidazole, 580 Polyclonal antibodies (PAb), 255 Polyethylene glycol (PEG), 134, 528 Polyethyleneimine (PEI), 414
415, 528 Polymer, 134 polymer-based polyphosphoric acid biosensors, 528
529 polymer-supported nanostructured biosensors, 414
416 Polymer dots (PDs), 472 Polymeric ionic liquids (PILs), 151 Polymeric nanomaterials, 5 Polymerized ACB (PACB), 313
314 Polyphenols, 170
171, 173
174 Polypyrrole (PPy), 178
179 Polyurethane (PU), 528
529 Polyvinyl alcohol (PVA), 314
315 POP. See Porous organic polymer (POP) Porous organic polymer (POP), 385f Potentiometric biosensors, 44
45, 297 Powder X-ray diffraction (PXRD), 415
416 PPy. See Polypyrrole (PPy) Presynaptic cell, 331 Primary dye classification systems, 217 Printed circuit board (PCB), 255 Printer-connected system, 130
131 Progesterone, 510
511 Prolactin, 513 Prostate-specific antigen (PSA), 132, 557
558 Proteins, 222, 511 Protozoa, electrochemical detection of, 260
268 Prussian blue (PB), 147, 151
152 PSA. See Prostate-specific antigen (PSA) Pseudomonas aeruginosa, 543, 555 PSSA/PANI. See Poly(4-styrenesolfonic acid)-doped polyaniline films (PSSA/PANI) PtNPs. See Platinum nanoparticles (PtNPs) PTTCA. See Poly(terthiophene carboxylic acid) (PTTCA) PVA. See Polyvinyl alcohol (PVA) PVD. See Physical vapor deposition (PVD)

617

PXRD. See Powder X-ray diffraction (PXRD) Pyrolytic graphite electrode (PGE), 32
33 Pyrrolidinium acid sulfate (PAS), 415
416

Q QDs. See Quantum dots (QDs) qPCR. See Real-time polymerase chain reaction (qPCR) Quantum dots (QDs), 3, 5, 203
206, 291
292, 371
372, 437
438, 471
472, 560
561 quantum dots-based biosensors, 294, 580
581

R RA. See Rheumatoid arthritis (RA) Raman spectroscopy, 332
333 RCA. See Rolling circle amplification (RCA) REACH. See Requirements of European Chemical Agency (REACH) Real-time polymerase chain reaction (qPCR), 525
526 Receptor, 195
196 receptor
transducer sensor device, 97
98 Redox cycling, 249 Redox enzyme biosensing, 61 Redox probes, 121 Redox-active species, 150 Reduced graphene oxide (rGO), 23
24, 30, 171, 174
175, 263, 302
303, 544 Reducing power, 163
164 Refractive index (RI), 111, 576 Relative sensors, 99 Renewable chemicals, 543 Reproducibility, 102 of electrochemical biosensors, 135
152 Requirements of European Chemical Agency (REACH), 535 Resistance temperature detectors (RTDs), 99 Resorcinol (RS), 31 Response period, 102

618

Index

Response time, 291 RF. See Riboflavin (RF) rGO. See Reduced graphene oxide (rGO) Rheumatoid arthritis (RA), 560 Rhodium nanoparticles, 85 RI. See Refractive index (RI) Riboflavin (RF), 30 Ribonucleic acid (RNA), 223
224, 416 receptor for, 577 RIV. See Rivastigmine (RIV) Rivastigmine (RIV), 415
416 RNA. See Ribonucleic acid (RNA) Rolling circle amplification (RCA), 251 Room temperature (RT), 38 RS. See Resorcinol (RS) RT. See Room temperature (RT) RTDs. See Resistance temperature detectors (RTDs) RU. See Rutin (RU) Rutin (RU), 560
561

S Salmonella spp., 244
245 electrochemical detection of, 252
253 SAMs. See Self-assembled monolayers (SAMs) Sandwich immunoassay, 582 Scanning electron microscopy (SEM), 41, 89, 232
233, 387, 410
416, 555 SCENIHR. See Scientific Committee on Emerging and Newly Identified Health Risks (SCENIHR) Scientific Committee on Emerging and Newly Identified Health Risks (SCENIHR), 535 Screen printed carbon electrodes (SPCEs), 24
25, 198
199, 203
205, 246, 438
440 Screen printing technology, 248 Screen-printed gold electrode, 441 Screen-printing electrodes (SPEs), 542 SCS. See Solution combustion synthesis (SCS) SDS. See Sodium dodecyl sulfate (SDS) Sulfate surfactant (SDS) SEB. See Streptococcus enterotoxin B (SEB)

Selective ionic electrode, 297 Selectivity, 101, 290 SELEX. See Systematic evolution of ligands by exponential enrichment (SELEX) Self-assembled monolayers (SAMs), 149 SEM. See Scanning electron microscopy (SEM) Semiconductor, 123 nanomaterials, 5 Semiconductor manufacturing technology (SMT), 149
150 Semiconductor QDs (SQDs), 28
29 Sensing electrode, 119 Sensitivity, 102, 207
208, 290 Sensors, 4, 37
38, 63
64, 195
196, 219, 288, 371, 506
507, 546 classification of, 98
100 Serotonin (5-HT), 22, 25
26, 332
334 SERS. See Surface-enhanced Raman scattering (SERS) Shelf stability, 136
137 Shell layer, 6 SIDS. See Sudden infant death syndrome (SIDS) Signal detection, 99 Signal-to-noise ratio (SNR), 139 Signalization process, 289
290 Silicon, 132
133 Silicon dioxide (SiO2), 560 Silver (Ag), 292, 386
387 gold nanoparticles with silver deposition, 582
584 immunoassay using silver nanoparticles and magnetic beads, 583f nanocluster, 434
435 nanoparticles, 583
584 Sinapic acid, 164
165 Single-molecule enzyme nanocapsules (SMENs), 147
149 Single-walled carbon nanotubes (SWCNTs), 24, 26, 64
66, 171, 431, 507
508 Size impact, 5 Smartphone-based nanostructured sensor, 351 SMENs. See Single-molecule enzyme nanocapsules (SMENs)

Index

SMT. See Semiconductor manufacturing technology (SMT) SNR. See Signal-to-noise ratio (SNR) SOD. See Superoxide dismutase (SOD) Sodium dodecyl sulfate (SDS), 24, 31 Sodium montmorillonite (NaMMT), 314
315 Sodium tri-citrate, 60
61 Solar energy converters, 4 Sol
gel method, 9, 82
83 Sol
gel nanofabrication, 40, 41f Solid metal, 13 Solution combustion synthesis (SCS), 10 Solvent-free synthesis, 14 Solvents, 11 Solvothermal method, 11, 84
87 SPCEs. See Screen printed carbon electrodes (SPCEs) Spectroscopy, 21
22, 380
381 SPEs. See Screen-printing electrodes (SPEs) SPR. See Surface plasmon resonance (SPR) SQDs. See Semiconductor QDs (SQDs) Square wave voltammetry (SWV), 25
26, 233
234, 246, 410
414 Square-wave anodic stripping voltammetry (SWASV), 468, 485
486 Stability, 102, 136, 291 Staphylococcus aureus, 244, 441, 555 electrochemical detection of, 256
257 Steroids, 509 Streptococcus enterotoxin B (SEB), 369
370 Streptococcus pneumoniae, 255 Streptococcus spp., electrochemical detection of, 255 Strontium (Sr), 463
464 Sudden infant death syndrome (SIDS), 22
23, 334 Sulfate solution, 47 Sulfate surfactant (SDS), 31 Sulfur, 134 Sulfur dioxide (SO2), 301 sensing, 304
306 Sulfur oxides (Sox), 301 Superoxide dismutase (SOD), 312 Superparamagnetic behavior, 62 Supramolecular chemistry, 81

619

Surface layer, 7 Surface plasmon resonance (SPR), 5, 61 surface plasmon resonance-based biosensor, 111 Surface-enhanced Raman scattering (SERS), 108, 215
216, 293, 373 Surface/interface-generated effects, 5 SWASV. See Square-wave anodic stripping voltammetry (SWASV) SWCNTs. See Single-walled carbon nanotubes (SWCNTs) SWV. See Square wave voltammetry (SWV) Synthesis method, 8 Synthetic dyes, 217
218 Synthetic process for conc, 49f Synthetic routes bottom-up approach, 8
15 nanomaterials and nanotechnology, 3
5 nanoparticles classification of, 5
6 synthesis of, 6
7 top-down approach, 7 Systematic evolution of ligands by exponential enrichment (SELEX), 348

T Tannic acid, 164
165 TB. See Thrombin (TB) TEA. See Triethanol amine (TEA) TEAC. See Trolox equivalent antioxidant capacity (TEAC) TEM. See Transmission electron microscopy (TEM) TEOS. See Tetraethoxysilane (TEOS) Testosterone, 509 Tetraethoxysilane (TEOS), 9 Tetramethoxysilane (TMOS), 9 Thermal sensors, 100 Thermoluminescence dosimeter (TLD), 4 Thin films, 3 multilayers, 60 Thin-layer chromatography (TLC), 215
216 Thiocarbamide acid, 199
200 Thionine, 441
447

620

Index

Thiram, 373 Third-generation biosensors, 57
58 Three-dimension (3D) nanomaterials, 60, 80 NS like polymorphic crystals, 37
38 structures, 104 Thrombin (TB), 336 THSs. See Triple helix switches (THSs) Thymine (T), 223
224 Thyroxine (T4), 507
508 Time-of-flight secondary ion mass spectrometry (TOF-SIMS), 215
216 Tin (Sn), 463
464 Tin oxide (SnO2), 293
294 Tiny organic fluorescent dyes (OFDs), 28
29 Titanium (Ti), 463
464 Titanium carbide (Ti3C2), 140 Titanium nanotubes (TNTs), 473 Titanium oxide (TiO2), 293
294, 387
410, 473 TLC. See Thin-layer chromatography (TLC) TLD. See Thermoluminescence dosimeter (TLD) TMDCs. See Transition metal dichalcogenides (TMDCs) TMOS. See Tetramethoxysilane (TMOS) TMOs. See Transition metal oxides (TMOs) TNT. See Trinitrotoluene (TNT) TNTs. See Titanium nanotubes (TNTs) TOF-SIMS. See Time-of-flight secondary ion mass spectrometry (TOF-SIMS) Top-down approach, 7, 88
91. See also Bottom-up approach laser ablation, 90
91 milling process, 90 in nanoparticle synthesis, 7f plasma sputtering, 88
89 Toxic dyes, 215
216 determination of toxic dyes based on electrochemical biosensors and applications, 225
236, 226t dyes and pigments, 216
218 electrochemical biosensors, 218
224

Toxic gases, 287 biosensors, 288
291 detection and monitoring of, 300
316 biosensing of nitric oxides, 309
316 H2S sensing, 307
309 NO2 sensing, 302
304 novel nanostructured materials for, 310t SO2 sensing, 304
306 electrochemical biosensors, 295
300 nanomaterial-based biosensors, 291
295 Toxic metals, 465
469 applications of toxic metals detection using nanostructured platforms, 476
486, 477t arsenic, 468
469 cadmium, 465
466 lead, 467
468 mercury, 466
467 nanomaterials are used detection platform, 469
476 Toxicants, 367 Toxins, 367
368 Toxoplasma gondii, 244
245 Transducers, 100
101, 132, 220, 289
290, 368, 381
382, 576 Transition metal chalcogenides, 106 Transition metal dichalcogenides (TMDCs), 106, 303
304, 472 Transition metal oxides (TMOs), 106, 472 Transmission electron microscopy (TEM), 41, 86, 89, 563 Transportable electrochemical sensors, 221 Triethanol amine (TEA), 38 Triiodothyronine (T3), 507
508 Trinitrotoluene (TNT), 293 Triple helix switches (THSs), 349 Tris-HCl buffer system, 476 Trolox, 164
165 Trolox equivalent antioxidant capacity (TEAC), 163 Trypanosoma cruzi, 262 TRYPN. See Tryptophan (TRYPN) Tryptophan (TRYPN), 335 Tungsten disulfide nanosheets (WS2), 234
236 Tungsten oxide (W8O23), 164
165

Index

Two dimension (2D), 303
304 conjugated nanostructured polymers, 473 nanomaterials, 60, 80 nanostructures, 291
292 NS like nanosheets, 37
38 organic polymers, 107
108 BP, 108 MOFs, 107 structures, 104 transition metals, 105
107 advanced transition metal oxides, 106
107 transition metal chalcogenides, 106 TYR. See Tyrosine (TYR) Tyrosinase, 166, 171
175, 178
179 Tyrosine (TYR), 335

U UA. See Uric acid (UA) Ultrasonication-assisted liquid-phase exfoliation, 473 Ultraviolet radiation, 38
39 Ultraviolet
visible spectrophotometry, 163, 215
216, 468 Ultraviolet
visible spectroscopy (UV-vis spectroscopy), 86, 415 Uracil (U), 223
224 Uric acid (UA), 24, 30
31, 348 UV-vis spectroscopy. See Ultraviolet
visible spectroscopy (UV-vis spectroscopy)

V VACNT. See Vertically aligned carbon nanotube (VACNT) Vanadium (V), 463
464 Vancomycin (Van), 253
254 Vertically aligned carbon nanotube (VACNT), 304 Vibrio cholerae, 244 Vibrio spp., electrochemical detection of, 254
255 Vinyl ferrocene (VF), 508 Vinylbenzylthymine groups, 179
180

621

Vinyltriethoxysilane (VTES), 528
529 Viruses, 244
245, 525
526 electrochemical detection of, 258
260 receptor for, 577
578 Vitamin D, 511 Vitamin E, 173 Vitamins, 533 VOCs. See Volatile organic compounds (VOCs) Volatile organic compounds (VOCs), 287 Voltammetric determinations, 45 Voltammetric techniques, 247

W Water, 11 cleanliness, 243 pollutants, 217 water-based toxins, 244 water-soluble hormones, 505 Wearable biosensing applications, 139 Wearable nanostructured sensor for neurochemical detection, 352
355 Wet chemical methods, 9
12. See also Dry chemical methods chemical reduction, 11 electrochemical synthesis, 11 emulsion polymerization, 12 green and biological synthesis, 10 microemulsion method, 11
12 microwave-assisted synthesis, 12 SCS, 10 sol
gel process, 9 solvothermal/hydrothermal method, 11 Wet route, 84
87 WGM biosensors. See Whispering-gallerymode biosensors (WGM biosensors) Whispering-gallery-mode biosensors (WGM biosensors), 111 Whole-cell-based biosensors, 104
105 Working electrode, 119 World Health Organization, 243

X X ray diffraction (XRD), 41, 86, 89 X-ray fluorescence spectrometry, 468

622

Index

X-ray microanalysis (XRM), 548
554 X-ray photoelectron spectroscopy (XPS), 41, 87, 88f, 89 XPS. See X-ray photoelectron spectroscopy (XPS) XRD. See X ray diffraction (XRD) XRM. See X-ray microanalysis (XRM)

Z Zebra fish (Danio rerio), 332
333 Zero-dimension (0D) nanobiosensors, 292
294 nanomaterials, 59, 79
80 nanoparticles-based biosensors, 292
294 nanostructures, 294 quantum dots-based biosensors, 294 Zinc (Zn), 463
464 Zinc oxide (ZnO), 140, 197, 293
294 nanostructures in fabrication of electrochemical biosensors, 587
589 Zinc oxide nanofibers (ZnONFs), 588
589 Zinc oxide nanoparticles (ZnONPs), 554

Zinc oxide nanorods (ZnONRs), 588
589 array photoelectrodes for highly efficient quantum dots sensitized solar cells clicking, 579f Zinc oxide nanospheres (ZnONSs), 588
589 Zinc oxide nanotubes (ZnONTs), 588
589 Zinc oxide nanowires (ZnONWs), 588
589 Zinc oxide-doped iron oxide nanocomposite (Zn/Fe nanocomposite), 476
483 Zingiber officinale, 543
544 ZnONFs. See Zinc oxide nanofibers (ZnONFs) ZnONPs. See Zinc oxide nanoparticles (ZnONPs) ZnONRs. See Zinc oxide nanorods (ZnONRs) ZnONSs. See Zinc oxide nanospheres (ZnONSs) ZnONTs. See Zinc oxide nanotubes (ZnONTs) ZnONWs. See Zinc oxide nanowires (ZnONWs)