Graphene Based Biomolecular Electronic Devices 0128215410, 9780128215418

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Table of contents :
Cover
Copyright
Preface
Graphene-Fundamentals
Introduction
History of graphene
Graphene synthesis
Top-down approach
Mechanical exfoliation and cleavage
Chemical exfoliation
Bottom-up approach
Epitaxial growth
Chemical vapour deposition (CVD)
Morphologies of graphene
Electronic properties of graphene
Graphene-biomolecular interactions
Interactions in DNA-graphene hybrids
Non-covalent interactions
Covalent interactions
Interactions in peptide-graphene hybrids
Non-covalent interactions
Covalent interactions
Interactions in protein-graphene hybrids
Non-covalent interactions
Covalent interactions
Interactions in carbohydrates-graphene hybrids
Non-covalent interactions
Covalent interactions
Graphene-based hybrid biomaterials
Graphene hybrids in tissue engineering
Graphene hybrids in drug delivery
Conclusions
References
Graphene-Based Transduction Systems in Biosensors
Introduction
Graphene-based transduction systems
Electrochemical biosensors
Piezoelectric biosensors
Optical biosensors
Conclusions
References
Graphene in Field Effect Transistor-Based Biosensors
Introduction
Graphene Bio-FET
Substrate preparation
Graphene selection
Exfoliation and cleavage
Chemically prepared graphene
Chemical vapour deposition
Placement of graphene on suitable substrates
Exfoliated graphene
Reduced graphene oxide
Fabrication of FET sensors
Non-covalent and covalent functionalization
Non-covalent functionalization
Covalent attachment
Anti-biofouling
Some graphene-based FET biosensors
Genomic detection
Biomarker detection
Cellular detection
Bio-FET-based label-free detection mechanism
Indirect detection of macromolecules
Direct detection of macromolecules
Detection of oligonucleotides
Detection of proteins
Challenges of using graphene in fabrication of FET-based sensing devices
Protocols for GFET device fabrications
References
Graphene-Based Biosensors for Detection of Protein and Nucleic Acid
Introduction
Graphene-based biosensors for nucleic acid detection
Introduction
Graphene-based aptamer biosensors
Graphene-based DNA (deoxyribonucleic acid) biosensors
Graphene-based PNA (peptide nucleic acid) biosensors
Graphene-based biosensors for protein detection
Introduction
Graphene-based immunosensors
Graphene-based enzyme biosensors
Advanced applications of graphene-based biosensors
Introduction
Graphene-based biosensors in microfluidic chips
Graphene-based biosensors for point-of-care diagnostics
Graphene-based biosensors in integrated lab-on-a-chip
Protocols
Conclusions
References
Graphene-Based Wearable Biosensors
Introduction
Graphene-based flexible and stretchable materials
Bio-integrated devices
Wireless biosensors
Applications of wearable biosensors
Electrophysiological measurements
Biomolecular detection
Kinematic detection
Challenges and future prospectus
Conclusions
References
Graphene 3D Printing
Introduction
Direct 3D printing
Direct ink writing for bioelectronic applications
Direct bioprinting
3D freeze printing
Digital light processing 3D printing
Stereolithography
Graphene nanofiller in stereolithographic printing
Fused deposition technique
Conclusions
References
Graphene-Based Microbial Fuel Cell
Introduction
Modified graphene as electrode material
Synthesis of graphene used for electrode material
MFC designing using graphene-based materials
Graphene as an anode material
Graphene as a cathode material
MFC-based bioelectronic devices
Conclusions
References
Graphene-Based Drug Delivery System
Introduction
Graphene-based drug delivery nano-vehicles
Graphene interaction with cell membrane
Impact of graphene on a human body
Conclusions
References
Graphene in Tissue Engineeringand Electronics: Future Prospects and Challenges
Introduction
Fabrication of conductive scaffolds
Chemical vapour deposition (CVD)
3D printing
Electrospinning
Freeze drying
Free radical polymerization
Self-assembly
Direct vacuum filtration method
Molecular interactions in biopolymers and graphene
Graphene-SF hybrids
Graphene-amyloid hybrids
Graphene-chitosan hybrids
Cellular behaviour on conductive scaffolds
Neural regeneration
Stem cell differentiation
Scaffold as an electronic sensor
Challenges
Protocols
Graphene-SF synthesis
Graphene-chitosan synthesis
References
Commercial Prospects of Graphene-Based Biomolecular Electronic Devices and Challenges
Introduction
Graphene-based electronic devices
Graphene-based biosensors
Graphene-based biofuel cells
Future challenges
Conclusions
References
Index
A
B
C
D
E
F
G
H
I
L
M
N
O
P
Q
R
S
T
U
V
W
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GRAPHENE BASED BIOMOLECULAR ELECTRONIC DEVICES

GRAPHENE BASED BIOMOLECULAR ELECTRONIC DEVICES BANSI D. MALHOTRA

Nanobioelectronics Laboratory, Department of Biotechnology, Delhi Technological University, Delhi, India

SHARDA NARA

Nanobioelectronics Laboratory, Department of Biotechnology, Delhi Technological University, Delhi, 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 © 2023 Elsevier Inc. All rights reserved. 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: 978-0-12-821541-8

For information on all Elsevier publications visit our website at https://www.elsevier.com/books-and-journals

Publisher: Matthew Deans Acquisitions Editor: Ana Claudia A. Garcia Editorial Project Manager: Dan Egan Production Project Manager: Prem Kumar Kaliamoorthi Cover Designer: Miles Hitchen Typeset by STRAIVE, India

Preface Graphene has been found to have excellent electrical properties, large specific surface area and high mobility of charge carriers, resulting in its high sensitivity to electronic perturbations arising due to the conjugation of biomolecules. The advantages offered by the optical, physical, and electrochemical properties of graphene and graphenebased materials have significantly contributed towards the development of many biomolecular electronic devices. Graphene, with its unique sensing characteristics, has recently emerged as an attractive material for the development and production of biomolecular electronics. This interesting electronic material has many applications in semiconductor devices replacing the use of silicon-based materials, due to its semi-metallic nature and tuneable energy band gap. The fine tuning of electron transfer with redox properties of biomolecules has been predicted to lead the development of improved bioelectronic devices. This book, Graphene-based Biomolecular Electronic Devices, explores the synergy emanating from the charge transfer between graphene and biomolecules. This is likely to motivate readers both from industry and academia to comprehend the applications of graphene-based miniaturized bio-devices. We discuss in detail the fundamental concepts relating to graphene and electronics. Besides this, efforts have been made to describe the various budding and advanced applications of graphene-based bioelectronics. This book includes coverage of biosensors, energy storage devices, drug delivery systems, 3D printing, and the use of graphene-based materials to produce conductive scaffolds for tissue-engineering purposes. The first chapter on Graphene fundamentals focuses on the basic concepts of graphene including its electronic properties and information regarding modification of electron transport properties of graphene for biomolecular interactions. The second chapter on Graphene-based transduction systems discusses the role of graphenebased sensing platforms towards the development of electrochemical, piezo-electric, and optical biosensing devices. The third chapter on Role of graphene in field effect transistor-based biosensors involves the use of graphene material in the Bio-FET-based transduction system for biosensing devices. In the fourth chapter, we discuss Graphene-based biosensors for detection of protein and nucleic acid. The fifth chapter on Graphene-based wearable biosensors discusses the development of these biomolecular electronic devices in

ix

x  Preface

detail. And we elaborate on Graphene-based 3D printing in the sixth chapter and discuss methods of preparation of conducting ink for bio-printing applications. The seventh chapter contains useful information pertaining to the fabrication of Graphene-based microbial fuel cell. The eighth chapter deals with the Graphene-based drug delivery system and includes the biology of nanomaterials using a scientometric approach where different biological aspects of graphene including technology, science, and innovation are discussed. In the ninth chapter on Tissue engineering and electronics: Future prospects and challenges, we address the various biomolecular interactions occurring between graphene and biomacromolecules used in developing tissue-engineered constructs. The tenth chapter relates to the Commercial prospects of graphene-based biomolecular electronic devices and challenges. We hope that this textbook will serve as an overall introduction to the scope and prospects of graphene-based biomolecular electronic devices and provide important information related to emerging and advanced applications of this field. We anticipate that it will provide useful information to active researchers working in industry, research establishments, and academia. We are indebted to all the members of our families and especially Mr. Sandeep Nara and Ms. Shashi Malhotra for their valuable inputs, patience, and support rendered during the present-day world affected by COVID-19.

Graphene-Fundamentals

1

1.1 Introduction Solid carbon elements occur in many allotropic forms since it can exist in different structural forms with different chemical properties1 attributed to its valency. Carbon has four valence electrons and can form covalent bonds with adjacent carbon atoms arranged in a variety of different manners to yield diverse lattice arrangements. Diamond and graphite are the two most common allotropes of carbon, and tetrahedral lattice arrangements of carbon atoms can be observed in diamond whilst hexagonal lattice arrangements have been found in graphite. Contrary to diamond, which is the hardest known mineral, graphite is one of the soft naturally occurring substances.2 The most common use of graphite can be seen in lead pencils wherein lead is mainly composed of clay and graphite.3 The basic building block of graphite is a single atomic 2D sheet (Figs 1.1 and 1.2) wherein three out of the four valence electrons undergo sp2 hybridization. These hybridized orbitals form sigma (σ) bonds with the sp2-hybridized orbitals of adjacent carbon atoms with a bond angle of 120 degrees and bond length of 0.142 nm to give a hexagonal lattice structure as shown in TEM images5 (Fig. 1.3), which look like a honeycomb.6,7 These atomically thin carbon films are called graphene.8 Graphene has high mechanical strength owing to its inplane σ bonds whilst its electronic properties along with high thermal stability and transparency are due to π bonds, which are weak and out of plane.9 In biomolecular electronics, where the mobility of electrons is primarily important, graphene has been considered the most suitable platform (Table  1.1). Graphene shows very high electron mobility of approximately 10,000 to 15,000 cm2 V−  1 s−  1 at room temperature under the applied gate voltage8 whilst it could be increased up to 2 × 105 cm2 V−  1 s−  1 by lowering the temperature. Graphene has Young’s modulus of 1 TPa and high thermal conductivity of about 3000 Wm K−  1. Moreover, a single layer of graphene has very high specific area of about 2630 cm2 g−  1. It absorbs only 2.3% of light and allows optical transmittance of about 97.7%.10

Graphene Based Biomolecular Electronic Devices. https://doi.org/10.1016/B978-0-12-821541-8.00009-3 Copyright © 2023 Elsevier Inc. All rights reserved.

1

2  Chapter 1  Graphene-Fundamentals

Fig. 1.1  Mother of all graphitic forms. Graphene is a 2D building material for carbon materials of all other dimensionalities. It can be wrapped up into 0D buckyballs, rolled into 1D nanotubes, or stacked into 3D graphite. Reproduced with permission from Geim, A. K.; Novoselov, K. S. The Rise of Graphene. In Nanoscience and Technology: a Collection of Reviews from Nature Journals; World Scientific: 2010; pp. 11–19.

However, only a few layered graphene structures, with 10 maximum layers, exhibit peculiar electronic and optical properties. Bulk graphene (>  10 layers) does not depict a monolayer signature because the interactions between layers causes imperfections, which impair the exceptional electronic properties. More interestingly, the electronic properties of monolayered graphene are found to be very sensitive to doping and molecular ­adsorption. Graphene doping especially by N, S and P leads to increased electrocatalytic property that can be used for various applications such as in fuel cells for oxygen reduction and the evolution of

Chapter 1  Graphene-Fundamentals  3

Fig. 1.2  SEM images of (A, D, G) surface and (B, E, H) edge morphology of graphite foil after applying a bias voltage of +  10 V for 0, 10, and 60 s in aqueous (NH4)2SO4 electrolyte solution, respectively. (C, F, I) Magnified images of panels B, E, H, respectively.4 Reproduced with permission from Parvez, K.; Wu, Z.-S.; Li, R.; Liu, X.; Graf, R.; Feng, X.; Mullen, K. Exfoliation of Graphite into Graphene in Aqueous Solutions of Inorganic Salts. J. Am. Chem. Soc. 2014, 136 (16), 6083–6091.

hydrogen in electrolyzers.11 Moreover, the π electron system allows for the interaction of the external entity to the graphene surface. These interactions and perturbations on the graphene surface alter the electron density and electron transport, which make graphene12 a potential bioelectronic and neuroprosthetic material.13

1.2  History of graphene It was previously considered impractical to obtain 2D free-­standing graphene due to theoretical assumptions of quantum and thermal fluctuations. However, in 2004, Andre Geim and Kostya Novoselov discovered the crystallographic existence of graphene. The monocrystalline stable graphitic films, just a few atoms thick, were obtained by ‘the Scotch tape method’. Graphene was prepared by peeling highly oriented pyrolytic graphite (HOPG) using mechanical exfoliation called micromechanical cleavage. Graphene film of size 10 μm with thickness of 3 nm was obtained by this method, and films having

4  Chapter 1  Graphene-Fundamentals

Fig. 1.3  (A) TEM image of synthesized reduced graphene oxide (rGO) where the darker region corresponds to multilayer and the lighter region corresponds to a few layers of graphene. (B) SAED of rGO, which confirms the hexagonal atomic structure and crystalline nature of the sheets. (C) TEM image of PEDOT:PSS/rGO.5 (D) SAED pattern of PEDOT:PSS/ rGO composite. (E) SEM of PEDOT:PSS adsorbed onto Whatman paper. (F) SEM of PEDOT:PSS/rGO Whatman coated paper. Reproduced with permission from Kumar, S.; Kumar, S.; Srivastava, S.; Yadav, B. K.; Lee, S. H.; Sharma, J. G.; Doval, D. C.; Malhotra, B. D. Reduced Graphene Oxide Modified Smart Conducting Paper for cancer. Biosensor. Biosens. Bioelectron. 2015, 73, 114–122.

Table 1.1  Characteristic properties of graphene. Sr. no.

Property

Value

1. 2. 3. 4. 5.

Electron mobility Young’s modulus Thermal conductivity Specific area Optical transmittance

15,000 cm2 V−  1 s−  1 1 TPa 3000 Wm K−  1 2630 cm2 g−  1 97.7%

thickness of more than 3 nm was prepared up to the length of 100 μm (see Section 1.3). The graphene layer showed a semi-metallic nature with overlapped valence and conduction bands. Because of their revolutionary and pioneering experimental work on graphene, Geim and Novoselov were awarded the 2010 Nobel Prize in Physics8 after its

Chapter 1  Graphene-Fundamentals  5

­ iscovery due to the immense potential of graphene in organic elecd tronics. After tuning the band gap of graphene, the material is promising enough to be used as an alternative to silicon. Currently, silicon is the only dominating material used in the semiconductor industry. High-quality monocrystalline silicon wafers are very expensive, and their price has not decreased in the last five decades.14 Scientists have been looking for a silicon substitute that could enhance the performance of electronic devices at a lower cost. Prior to the discovery of graphene, there was a search for an atomically thin metallic film. To induce the electric field and control charge carriers, an energy gap is required in the conduction and valence bands as found in semiconductors. For example, 1.11 eV band gap is found in silicon at room temperature. Overlapping of conduction and valence bands in metals leads to full flow of current, hence a charge cannot be regulated with the applied voltage. Moreover, due to the shielding effect in metals, an external electric field cannot make changes in the inner core of metals. Therefore, attempts were made to fabricate atomically thin metallic films where a surface charge could be induced by application of an external electric field.15 As the electronic properties of the metals depend on its thickness, metallic to semi-metallic transition has been reported in ultrathin metallic films. In this regard, Bui et  al. reported that TiN film, having thickness of 0.65 nm, exhibited 11% current modulation induced by an external electric field.16 However, such thin films were presumed to be thermodynamically unstable and discontinuous at a large scale or when the obtained film was several nanometres thick. Whilst if the gap between the conduction and valence bands of the graphene can be tuned, then the graphene could be used to enhance the performance of electronics-based devices. Prior to 2004, no feasible technique was available to obtain a single stable planar layer of a graphene. The curved forms of graphene were, however, obtainable with different nanoscale morphologies such as toroidal cage, helical coiled forms, etc.17,18 However, these are basically different from their original counterpart of graphene owing to their bending characteristics.19 It was only after the experimental isolation of graphene in 2004 that different synthetic routes were substantially devised to attain a single planar layer of graphene.

1.3  Graphene synthesis Graphene can be synthesized by one of two approaches: (a) Topdown or (b) Bottom-up.

6  Chapter 1  Graphene-Fundamentals

1.3.1  Top-down approach In this approach, the graphite precursor undergoes a structural breakdown and graphene sheets are produced by breaking the interlayer contacts. For example, exfoliation techniques were used that involved the separation of layers by (i) mechanical exfoliation, (ii) chemical exfoliation, (iii) reduction or oxidation of graphene, (iv) arc discharge, or/ and (v) unzipping of CNTs to generate graphene sheets.20 Some of the major exfoliation techniques are described as follows:

Mechanical exfoliation and cleavage Graphite consists of multiple layers of graphene having weak van der Waals forces of attraction. Thus in principle, graphene layers can be separated from each other by applying an external force higher than the force that keeps the layers together. In graphite, the distance between two layers have been found to be 3.34 Å with 2 eV/nm2 bond energy, so external force of approximately 300 nN/μm2 is required to separate a single atomic layer of graphene from the multi-layered stacked graphite.21 Based on this principle, in a micromechanical cleavage process (Figs 1.4 and 1.5), graphene layers can be peeled off repeatedly with the help of a Scotch tape. Care should be taken to obtain a high-­purity graphite source to prevent contamination in the graphene layers thus produced. Novoselov et  al. used commercially available 1 mmthick HOPG, which is actually generated artificially by a thermolytic

Fig. 1.4  The illustrative procedure of Scotch tape-based micromechanical cleavage of HOPG. Reproduced with permission from Yi, M.; Shen, Z. A Review on Mechanical Exfoliation for the Scalable Production of Graphene. J. Mater. Chem. A 2015, 3 (22), 11700–11715.

Chapter 1  Graphene-Fundamentals  7

Epoxy glue

Freshly cleaved Bulk HOPG

Oxidized Silicon chip

(1) Bulk HOPG Bonding (upside down)

(4) HOPG adhesive exfoliation

(3) Bulk HOPG Scalpel Cleaving

(2) Epoxy glue curing under screw press

Fig. 1.5  Schematics of the process flow depicting the reverse exfoliation of graphite leading to graphene layers. Reproduced with permission from Huc, V.; Bendiab, N.; Rosman, N.; Ebbesen, T.; Delacour, C.; Bouchiat, V. Large and Flat Graphene Flakes Produced by Epoxy Bonding and Reverse Exfoliation of Highly Oriented Pyrolytic Graphite. Nanotechnology 2008, 19 (45), 455601.

­ rocess. Prior to peeling off the graphite, the mesas of an area of about p 4 mm2 and 5 μm deep can be created using a dry etching technique in the presence of oxygen plasma. This graphite-containing mesas were kept over the photoresist and then baked to transfer the area of mesas onto the photoresist. The graphite flakes were then peeled off using the Scotch tape from these graphitic mesas; leftover graphite must contain only a few layers of graphene. These graphene layers/graphite flakes were then released in acetone from the photoresist and finally captured onto Si wafers due to capillary and van der Waals forces of attraction.8 This is one of the most reliable and easy methods of producing a single or few graphene layers of high quality and of large area.

Chemical exfoliation Chemical exfoliation is another approach for graphene isolation and it involves intercalation of bulk graphite.22–24 Large atoms or molecules are inserted between the layers of atomic planes, so that individual graphene layers could be separated from each other. However, they remain embedded in a 3D matrix. These intercalating molecules

8  Chapter 1  Graphene-Fundamentals

could be further separated by a chemical reaction that results in a sludge having scrolled graphene sheets. Although the graphene layers could be separated, the non-uniform and uncontrollable behaviour has given this approach limited acceptance. For example, graphite intercalation (GIC) compound was initially synthesized with potassium called K-GIC (Fig. 1.6). The intercalated compound was synthesized by exfoliation of HOPG by heating at a very high temperature of 500°C in the presence of isoprene vapours. These isoprene molecules were intercalated and polymerized into graphene layers with potassium, resulting in separating the layers of graphene from the bulk graphite.25 The use of strong chemical solvents (liquid phase exfoliation) or high thermal shock (thermal exfoliation) yields multi-layered graphene flakes wherein layers of the graphene can not be controlled. Although the exfoliation techniques can be used to produce graphene at large scale, single-layer graphene can not be obtained using this technique. Moreover, the whole process can introduce impurities in the obtained graphene, and this method is not suitable for electronic applications wherein a single layer of pure graphene is required.26

1.3.2  Bottom-up approach In the bottom-up approach, attempts are made to grow the graphene over a desired surface by depositing total organic layers mainly using a source of carbon gas. This approach chiefly includes methods of (i) epitaxial growth and (ii) chemical vapour deposition (CVD).4

Epitaxial growth In this method, graphene can be synthesized with the help of silicon carbide (SiC) wherein atoms of Si are sublimed leaving the graphene

Graphite

After exfoliation and After intercalation of K After intercalation and 1-stage K-GIC polymerization of isoprene removal of polyisoprene

Fig. 1.6  Process of graphene formation through a first-stage potassium intercalation compound. Reproduced with permission from Inagaki, M.; Kim, Y.; Endo, M. Graphene: Preparation and Structural Perfection. J. Mater. Chem. 2011, 21 (10), 3280–3294. Courtesy of Dr. H. Shioyama of AIST, Osaka, Japan.

Chapter 1  Graphene-Fundamentals  9

layers on the surface. This route of graphene synthesis has several advantages such as (1) layers of the graphene can be controlled and (2) graphene can be synthesized over large area with (3) fewer impurities. High temperature treatment required for sublimation and high cost of SiC are the main constraints of this method.

Chemical vapour deposition (CVD) CVD is one of the most central methods of graphene synthesis via the bottom-up approach (Fig. 1.7) wherein high-quality graphene can be synthesized over a wide area. In this method, graphene can be obtained by depositing gaseous carbon on a substrate like copper foil. Interestingly, the synthesized graphene film can be transferred to a wide range of substrates including silicon.

Fig. 1.7  The configurations of plane- and edge-electrodes, and the structure of a CVD graphene sheet. (A) Schematic illustration of the edge-based (left) and basal plane-based (right) electrodes. (B) Raman spectrum of a monolayer CVD graphene sheet on a SiO2/Si substrate. (C) HR-TEM image of a monolayer CVD graphene sheet suspended over a micro grid; inset: a SAED pattern.27 Reproduced with permission from Yuan, W.; Zhou, Y.; Li, Y.; Li, C.; Peng, H.; Zhang, J.; Liu, Z.; Dai, L.; Shi, G. The Edge-and BasalPlane-Specific Electrochemistry of a Single-Layer Graphene Sheet. Sci. Rep. 2013, 3, 2248.

10  Chapter 1  Graphene-Fundamentals

The CVD method can be utilized to synthesize graphene for applications of flexible and transparent electronics, biosensors, energy storage materials such as batteries, etc.14 In this method, initially, catalytic metallic surfaces are chosen, then a single layer of graphene or graphene having few layers can be grown on a metallic surface such as Ni or Pt using carbon-­containing gases.28,29 The graphene layer is formed due to the decomposition of these gases owing to catalytic activity of the surface.30,31 Some metals have high solubility for carbon, for example, nickel‑carbon alloys (Ni-C), and as a result, carbon can be segregated from the bulk of such carbon-rich metallic surfaces.30,31 CVD can be employed to grow good quality graphene.18,32 More recently, it was observed that graphene synthesized by the CVD method exhibits different magnitudes of capacitance on the basal plane and edges, and graphene edges depict four times higher specific capacitance relative to the basal plane with high rate of electron transfer and electrocatalytic activity.27 Furthermore, the employment of graphene synthesis (Fig. 1.8) method depends on the end use and type of application; high quality (purity), large area, and cost effectiveness are some of the criteria on which selection of the graphene synthesis method depends. For example, epitaxial growth and CVD methods produce graphene with high mobility of charge carriers, but the total cost of graphene synthesis by these methods is very high and they also produce toxic by-products. Therefore, methods of CVD, liquid phase exfoliation and oxidative exfoliation-reduction synthesis (rGO synthesis procedure) can be employed wherein graphene is required at a mass level with relatively high purity such as in preparation of photonic and electric circuits, batteries, transparent and flexible electrodes, and for other such commercial uses of graphene.20

Fig. 1.8  Schematic diagram of graphene synthesis methods.

Chapter 1  Graphene-Fundamentals  11

Liquid phase exfoliation (top-down) is preferred in the case of e­ lectronic printing wherein graphene-based ink is required33 whilst molecular assembly method (bottom-up) is preferred for the synthesis of customized and precise components of nanoelectronic devices.34

1.4  Morphologies of graphene Meyer et  al. reported that graphene has an intrinsic tendency to be corrugated.35 In this study, transmission electron microscopic analysis showed that suspended graphene sheets were not perfectly flat. Corrugations on the graphene surface involved out-of-plane deformations of about 1 nm. These corrugations actually allow electron mobility at submicrometric distances without scattering in perfectly 2D crystal lattice with long range crystalline order. The presence of random microscopic corrugations in 3D may possibly stabilize the 2D crystallographic form of graphene monolayer.35 Also, extrinsic morphology of graphene monolayer was found to be changed according to the stiffness and surface patterns of the substrate on which graphene is transferred. The graphene’s extrinsic morphology was found to follow the surface morphology of the substrate, which actually increased the strain energy due to in-plane stretching and out-of-plane bending of the graphene layer (Fig. 1.9). This strain energy further affects the graphene characteristics, mainly adhesion and frictional properties. For example, graphene, having ultra-flat morphology, can strongly adhere to mica due to its intimate contact between graphene monolayer and substrate with less strain energy.36 In addition to graphene corrugations, other morphologies of graphene can be experimentally designed for specific applications such as nanoribbon. Nanoribbon is one of the most common

Fig. 1.9  The morphology of graphene with the intercalation of a single Si NP of various diameters, dNP . For visual clarity, the top panel shows the top graphene layer, and the bottom one shows the Si NP and the bottom graphene layer (only a portion near the Si NP is shown). Note the ridged morphology formation as dNP increases. NP, nanoparticles. Reproduced with permission from Zhu, S.; Galginaitis, J.; Li, T., Critical Dispersion Distance of Silicon Nanoparticles Intercalated between Graphene Layers. J. Nanomater. 2012, 2012.

12  Chapter 1  Graphene-Fundamentals

Fig. 1.10  (A) The schematic representation of cutting the two-dimensional graphene sheet to obtain zigzag and armchair nanoribbons. (B) Graphene lattice with two sublattice points in the rhombus unit cell (shaded region). Reproduced with permission from Dutta, S.; Pati, S. K., Novel Properties of Graphene Nanoribbons: A Review. J. Mater. Chem. 2010, 20 (38), 8207–8223.

­ orphologies of graphitic nanostructures that have applications in m field-effect transistors37 and as chip interconnects.38 Nanoribbons are considered 1D materials with a large aspect ratio; these are actually graphene sheets with a finite edge having edge geometries of two types, viz., armchair and zigzag or their combinations.39 Interestingly, these two different morphologies exhibit different electronic properties owing to the difference in their edges and constituent sublattices (Fig. 1.10A and B). In the case of a zigzag edge, all the atoms are of the same sublattices whilst in the case of armchair edges, atoms of two different sublattices constitute the bonds. Along with the physical structure of the graphene, including different sublattice arrangements and morphologies; study of exceptionally high electronic properties of graphene has recently sparked much interest. The high electron mobility of graphene allows for biomolecular interactions, envisioning its applications in biomolecular electronic devices.

1.5  Electronic properties of graphene A single crystalline layer of graphene exhibits characteristics like a metal with zero band gap whilst graphite that has multiple layers of graphene exhibit semi-metallic characteristics with 41 meV band overlap.40 A single layer of graphene shows excellent electronic properties wherein charge carriers exhibit characteristics of relativistic particles; the Dirac equation is used to describe the electronic

Chapter 1  Graphene-Fundamentals  13

6

E

1K 0T

ky kx

r (kΩ)

4

EF 2 EF

0 –60

–30

0

30

60

Vg (V)

Fig. 1.11  Ambipolar electric field effect in single-layer graphene. The insets show its conical low-energy spectrum E(k) indicating changes in the position of the Fermi energy EF with changing gate voltage Vg. Positive (negative) Vg induce electrons (holes) in concentrations n = αVg where the coefficient α ≈ 7.2 × 1010 cm−  2 V−  1 for field-effect devices with a 300 nm SiO2 layer used as a dielectric. The rapid decrease in resistivity ρ on adding charge carriers indicates their high mobility (in this case, μ ≈ 5000 cm2 V−  1 s−  1 and does not noticeably change with increasing temperature to 300 K).41 Reproduced with permission from Geim, A. K.; Novoselov, K. S. The Rise of Graphene. In Nanoscience and Technology: A Collection of Reviews From Nature Journals, World Scientific: 2010; pp. 11–19.

properties of graphene as depicted in Fig. 1.11.42 Electronic energy of the conduction band electrons, when plotted in three dimensions, gives an inverted cone-like shape called a Dirac cone. These electrons behave like quasiparticles and are called massless Dirac Fermions.41 Furthermore, graphene electronic properties may perhaps be tuned by multiplying the layers. Partoens et  al. observed a change in the electronic structure whilst moving from graphene to graphite based on tight-binding approach with the computation of the band structure generated by the piling of graphene layers. It was estimated that, in comparison to a single layer of graphene, even two graphene layers have a parabolic-type spectrum at the level of Fermi energy with very small band of 0.16 meV. With the piling of three to four layers, more clear semi-metallic behaviour can be observed whilst 10 layers of graphene exhibited 3D graphite-like properties in context of its electronic structure.40

14  Chapter 1  Graphene-Fundamentals

1.6  Graphene-biomolecular interactions As pristine graphene lacks functional groups, graphene modified in the form of graphene oxide (GO) or reduced graphene oxide (rGO) can be potentially used to conjugate biomolecules such as DNA, RNA, peptides, enzymes, or other proteins. The biomolecular conjugated graphene derivatives have enormous applications in biofuel cells, biomedicine, and bioimaging.43 A wide variety of biomolecules can be conjugated to GO or rGO44 via covalent bonds due to the presence of hydroxyl, epoxide, and carboxyl groups on the edges as well as on the basal planes of the sheet (Figs 1.12 and 1.13).43 GO, which is a graphene derivative, can be obtained by the oxidation of graphite powder following modified

Number of Layer(s) Form

One (single-layer)

Several ~ Several tens (multi-layer)

Many (multi-layer)

Reduced-form fully-reduced

(graphene) (graphite)

partiallyreduced

Oxidized-form (graphene oxide) (graphite oxide)

Other-forms hydrogenated, halogenated, functionalized, etc. Thin-film particle family

Fig. 1.12  The categories of thin-film particles. Reproduced with permission from Hirata, M.; Gotou, T.; Horiuchi, S.; Fujiwara, M.; Ohba, M. Thin-Film Particles of Graphite Oxide 1::High-Yield Synthesis and Flexibility of the Particles. Carbon 2004, 42 (14), 2929–2937.

Chapter 1  Graphene-Fundamentals  15

A

O

B

O

OH

OH O

O

HO

OH

O

OH

O HO

OH

HO

OH

OH

O

HO

O

Fig. 1.13  Schematic models of (A) graphene and (B) GO. Reproduced with permission from Zhang, Y.; Wu, C.; Guo, S.; Zhang, J. Interactions of Graphene and Graphene Oxide with Proteins and Peptides. Nanotechnol. Rev. 2013, 2 (1), 27–45.

Hummers’ method. In this method, strong oxidizing agents like potassium permanganate (KMnO₄), sulphuric acid (H2SO4), and phosphoric acid (H3PO4)45 have been employed to oxidize graphene.46,47 GO basal plane has been found to be rich with functional groups of hydroxyl and epoxide groups whilst the edges are rich in aldehyde, carboxylic, and ketonic groups.48

1.6.1  Interactions in DNA-graphene hybrids Non-covalent interactions Nitrogenous bases present in DNA have ring-like structures and hence can easily interact with graphene hexagons through non-­ covalent π-π interactions. Single-stranded DNA (ssDNA) can interact strongly with graphene whilst double-stranded DNA (dsDNA) has low affinity for graphene due to its interwoven closed structure with unexposed nucleotide bases. This differential affinity of ssDNA and dsDNA can be utilized to fabricate DNA-based biosensors (Fig. 1.14). Approximately a decade ago, DNA biosensors based on fluorescence resonance energy transfer (FRET) were designed that relied on energy transfer from donor molecules having an electronically excited state to acceptor molecules from a ground state of electronic energy.49 More details regarding graphene-based biosensors can be found in Chapters 2–4.

16  Chapter 1  Graphene-Fundamentals

Fig. 1.14  Schematic diagram of DNA immobilization/hybridization onto the surface of G-NH2 via intermolecular force. Reproduced with permission from Zhang, Z.; Liu, S.; Zhang, Y.; Kang, M.; He, L.; Feng, X.; Peng, D.; Wang, P. Easy Amino-Group Modification of Graphene Using Intermolecular Forces for DNA Biosensing. RSC Adv. 2014, 4 (31), 16368–16373.

Electrostatic interactions arising due to the presence of opposite charges, i.e. negative charge on DNA due to phosphate group of the nucleotides and positive charge of the amino functionalized graphene (G-NH2),50 can be used to immobilize DNA onto the graphene surface. In addition to π-π and electrostatic interactions, hydrogen bonding plays an important role in binding DNA at the graphene surface. Moreover, it has been observed that ssDNA can interact strongly with the GO as compared to dsDNA because of hydrogen bonding51 whilst inter-strand binding in dsDNA hinders hydrogen bond formation with graphene.

Chapter 1  Graphene-Fundamentals  17

Covalent interactions All the previously discussed non-covalent interactions can de-link the DNA and graphene in the vicinity of surfactants. Thus, stronger covalent bonding is needed to further stabilize the hybrid of graphene and DNA. Furthermore, GO nanosheets conjugated with a high density of DNA can be achieved using functionalized DNA. For example, azide-functionalized GO and alkynyl-functionalized DNA may lead to stable and multivalent GO-DNA conjugates via azide-alkyne reaction.52

1.6.2  Interactions in peptide-graphene hybrids Both covalent and non-covalent interactions are found to be significant to form stable hybrids of peptide and graphene.

Non-covalent interactions Although covalent interactions facilitate stable conjugates of peptide-­graphene, certain peptides have a high affinity for graphene and can be adsorbed easily. In case of the dodecamer peptide as studied by Katoch et al., in the powder state, the secondary conformation in peptide has been found to be α-helical whereas in aqueous solution, the peptide has a distorted helical secondary structure. After adsorption on the graphene, the peptide secondary conformation has been found to be altered to a complicated reticular-type structure owing to its interaction with the graphene surface. These changes in the secondary structure of the peptide can be estimated by molecular dynamics calculations and hence can be used for balanced and rational functionalization of graphene surface resulting in optimal binding of peptides.53 The peptides having simple, flat, and compact side chains can strongly bind with the graphene surface. Thus, lesser functionalization of graphene is needed in this case. Moreover, there are certain polycyclic aromatic molecules like pyrene that could easily bind with GO via π-π stacking (Fig.  1.15). Therefore, the peptide designed with a pyrene-like domain may interact firmly with GO without using even crosslinkers.54 Hydrophobic interactions play an important role in binding peptide moieties to graphene. The graphene surface was earlier considered as hydrophobic since graphite that has multiple layers of graphene is also hydrophobic. Contrary to this, recent reports suggest that hydrophobicity of graphene is dependent on its thickness. A single layer of graphene has been found to be hydrophilic, and as we increase the number of layers, it becomes more and more hydrophobic (Fig.  1.16).55,56 In the case of GO, edges and planar

18  Chapter 1  Graphene-Fundamentals

A

PyGAGAGY peptide O N H

H N O

O N H

H N O

O

H N

N H

O OH

O OH

Graphene binding motif

B

Graphene

Peptide

Self-assembly

GA repeats

Photo-crosslinking motif

Ru(bpy)32+ (NH4)2S2O8

Fig. 1.15  The design of the hybrid hydrogel. (A) The peptide sequence. (B) The hierarchical construction scheme for the hydrogel. Reproduced with permission from Wu, J.; Chen, A.; Qin, M.; Huang, R.; Zhang, G.; Xue, B.; Wei, J.; Li, Y.; Cao, Y.; Wang, W. Hierarchical Construction of a Mechanically Stable Peptide–Graphene Oxide Hybrid Hydrogel for Drug Delivery and Pulsatile Triggered Release In Vivo. Nanoscale 2015, 7 (5), 1655–1660.

Fig. 1.16  (A) Raman spectra of single and multi-layer graphene. (B) AFM image of graphene. (C) Thickness profile of graphene layer. Reproduced with permission from Singh, V. K.; Kumar, S.; Pandey, S. K.; Srivastava, S.; Mishra, M.; Gupta, G.; Malhotra, B.; Tiwari, R.; Srivastava, A. Fabrication of Sensitive Bioelectrode Based on Atomically Thin CVD Grown Graphene for Cancer Biomarker Detection. Biosens. Bioelectron. 2018, 105, 173–181.

r­ egions show different hydrophobicity: basal plane has been found to be more hydrophobic whereas the edges are more hydrophilic. The hydrophobic interactions between proteins and graphene are very complex. Proteins in the agglomerated state have been found to be more hydrophobic and hence interact with the hydrophobic

Chapter 1  Graphene-Fundamentals  19

region of GO or multi-layered structure of graphene.57 For example, β-lactoglobulin (BLG), which has both hydrophobic and hydrophilic groups, can be adsorbed onto the rGO sheets by virtue of hydrophobic interactions as well as π-π stacking wherein hydrophilic groups can be aligned in the aqueous solution. Thus the assembly or composite can be used as a hybrid template in water whilst maintaining the steady state.58

Covalent interactions Peptides such as heme and nisin have been used to form protein-­ conjugated graphene. Carboxyl (-CO2H) group of functionalized graphene and amino (-NH2) group of peptide like nisin can be crosslinked by various crosslinkers such as PEG.59,60

1.6.3  Interactions in protein-graphene hybrids Similar to peptide, enzymes can also interact with graphene by covalent, hydrophobic, π-π stacking, or/and electrostatic interactions. Certain enzymes like lysozyme or horseradish peroxidase (HRP), even without the use of any crosslinking agent, can be easily immobilized onto the GO sheets by incubating the sheets in phosphate buffer saline (PBS).61,62 These enzymes can be conjugated electrostatically due to the negative charge of GO sheets and the positive charge on protein species at a wide pH range of 4 to 11. Loading density of the enzymes depends on the initial concentration of the enzymes taken for immobilization.

Non-covalent interactions Guo et al. synthesized rGO at various reduction levels with varying hydrophobicity. Enzymes of oxalate oxidase (OxOx) and HRP were found to have higher affinity towards rGO as compared to that of GO. Additionally, enzymes were found to undergo physical adsorption, and 10 times higher loading of enzymes were achieved in rGO. An analogous relation was also reported with the decreased hydrophobicity.63 Lee et al. showed that anti-coagulant activity of unfractioned heparin (UFH) exhibits a very high order of anti-factor Xa (FXa) activity of 29.6 IU/mL64 when conjugated with the rGO surface through hydrophobic interactions. Furthermore, biomolecular adsorption affinity can be tailored by tuning hydrophobicity of the functionalized graphene surface.

Covalent interactions Since enzymes have both amine and carboxylic groups, they can easily covalently bind with the oxygen-rich surface of GO.

20  Chapter 1  Graphene-Fundamentals

N HCI O

O

98%H2SO4 Sonication KMNO4

EDAC OH

O

N O

NHS

C NH

O

O

BSA O

N

NH-BSA O

Fig. 1.17  Schematic diagram to produce GOs-BSA. Reproduced with permission from Shen, J.; Shi, M.; Yan, B.; Ma, H.; Li, N.; Hu, Y.; Ye, M. Covalent Attaching Protein to Graphene Oxide Via Diimide-Activated Amidation. Colloids Surf. B: Biointerfaces 2010, 81 (2), 434–438.

Nowadays, the most commonly used chemical crosslinking agents are N-ethyl-N-(3-dimethylaminopropyl) carbodiimide (EDC) and N-hydroxysuccinimide (NHS). In the EDC and NHS-mediated crosslinking, first, carboxylic groups of GO are activated by EDC and NHS that results in ester formation. In the second step, the active groups of ester react with amine groups of enzyme resulting in an amide bond formation between GO and enzyme, and the reaction is called diamide-activated amidation reaction. This method is more suitable for the formation of stable and uniform bio-conjugated graphenebased platforms without denaturing the protein species. Jianfeng Shen et  al. immobilized bovine serum albumin (BSA) on the GO sheets by EDC and NHS crosslinking and showed that BSA preserves its bioactivity even after covalently binding with GO (Fig. 1.17).65 In addition to EDC and NHS, another crosslinker that is used to covalently crosslink protein domain is glutaraldehyde. Olad et al. constructed graphene-incorporated scaffolds of gelatin and chitosan using glutaraldehyde as a chemical crosslinking agent (Fig. 1.18). In this study, biopolymeric chains of gelatin and chitosan were bound to the GO and amine-modified GO (GO-NH2). Nanosheets of GO-NH2 carry a positive charge whilst GO has a negative charge and hence can easily interact with gelatin and chitosan that have abundant carboxylic and amino groups. Chitosan-gelatin incorporated with GO and GO-NH2 were used as scaffolds due to high cytocompatibility, shape retention ability, high porosity, and water retention capability owing to its high surface area and enhanced hydrophilicity attributed by graphene components.66

1.6.4  Interactions in carbohydrates-graphene hybrids Non-covalent interactions Non-covalent interactions involving hydrogen bonding and π-π stacking can be used to bind carbohydrate moieties whilst preserving intrinsic graphene properties of charge mobility. For example,

Fig. 1.18  (A) Schematic illustration of the chemical bondings of polymeric chains crosslinked by glutaraldehyde. (B) Schematic illustration of chemical bondings of GO with polymeric chains. (C) Chemical bondings of GNH2 with polymeric chains. (Reproduced with permission from Olad, A.; Hagh, H. B. K. Graphene Oxide and Amin-Modified Graphene Oxide Incorporated Chitosan-Gelatin Scaffolds as Promising Materials for Tissue Engineering. Compos. Part B 2019, 162, 692–702.

22  Chapter 1  Graphene-Fundamentals

c­ ellulose contains abundant hydroxyl groups that can interact effectively with GO through hydrogen bonding.67 Pyrene-conjugated maltose can bind with graphene through π-π interactions attributed to pyrene aromatic hydrocarbons.68

Covalent interactions Similar to the proteins, carbohydrates are also rich in functional groups; therefore, stable conjugates of carbohydrates-graphene can be easily prepared via covalent crosslinking. For example, β-cyclodextrin can be immobilized on the GO surface through epoxide ring-opening reaction.69 Further, dextran and chitosan can be conjugated with GO through reactions between epoxide groups of GO with the hydroxyl and primary amine groups of these polysaccharide units.70 However, the main obstacle of the conjugation through covalent crosslinking is the electron mobility of the graphene sheet decreases which narrows its applications in bioelectronics.43 Small perturbations in graphene may change its electronic properties, and the perturbation could be due to biomolecular binding on its surface (Table 1.2). Similarly, biomolecules, after getting adsorbed or after covalent binding with graphene, also change their secondary conformations due to molecular folding, which may alter their functional and structural behaviour. Thus, while forming hybrids of graphene and biomolecules, care should be taken to preserve the intrinsic properties of graphene as well as the biological entity. In this context, computational simulation tools, molecular modelling study, as well as thermodynamics could be used to develop graphene-based biomolecular electronic devices for applications in biomedicine, tissue engineering, biosensors, bioimaging, energy storage devices, etc. (Fig. 1.19). By the simulation study, Wang et al. recently analysed modified graphene with functional groups of -COOH, -OH, N-containing, O-containing, or N-O-containing groups. They found that, in comparison to graphene, the modified graphene could easily and strongly bind with hyaluronic acid biomolecules by covalent crosslinking. Following density functional theory (DFT), it has been concluded that hyaluronic acid undergoes strong interfacial interactions with graphene, through the functional groups of epoxy, -OH, and -COOH. The density of functional groups at the graphene surface can be tuned, and interactions can occur in a controlled manner.71 Moreover, these interactions between graphene and biomolecules enable the fabrication of hybrid biomaterials, which have promising applications in tissue engineering and drug delivery systems.

Biomolecules having aromatic rings interact with graphene surface through π-π stacking.

Strong electronegative groups or atoms present on graphene derivative or biomolecules interact with hydrogen atoms. Attractions between electroactive positive and negative groups present on modified graphene surface and biomolecules result in electrostatic interactions. Chemical reactions occur between functional groups of biomolecules and group present on modified graphene surface, interactions facilitated by chemical reagents.

π-π

Hydrogen bonding

Co-valent binding

Electrostatic

Explanation

Interactions

Highly stable interactions, can be used for wider applications.

Biomolecules assembled on graphene surface rapidly, reaction time is very short.

Preserve intrinsic properties of graphene and biomolecules; two surfaces interact without modifying secondary structure of proteins. Interactions can occur in very mild conditions.

Benefits

Results in various by-products, reactions are time taking, strong chemical reagents are required.

Interactions are weak; assembly gets disintegrated, e.g. in presence of strong solvent. Biomolecular activity is compromised, have limited applications.

Interactions are not very strong and are easily disrupted.

Disadvantages

Table 1.2  Interactions between graphene and biomolecules.

70

50

51

49

References

24  Chapter 1  Graphene-Fundamentals

Fig. 1.19  Applications of G-biomolecule nanohybrids. Reproduced with permission from Li, D.; Zhang, W.; Yu, X.; Wang, Z.; Su, Z.; Wei, G. When Biomolecules Meet Graphene: From Molecular Level Interactions to Material Design and Applications. Nanoscale 2016, 8 (47), 19491–19509.

1.7  Graphene-based hybrid biomaterials 1.7.1  Graphene hybrids in tissue engineering Bioimplants, especially for neural regeneration, can be generated using graphene-based 3D hydrogel that may support the growth of nerve cells. In attempts to recover from neurological damages, graphene hybrids formed by incorporating tungsten, cobalt, sulphur, and molybdenum have been used as scaffold for neural tissue engineering.72 More interestingly, the reactive and functionalized surface of GO can easily adsorb the biomolecules of extracellular bodies, enhancing the cellular attachment and growth. The specified

Chapter 1  Graphene-Fundamentals  25

­ iomolecules released from the cells or present on the cell membrane, b and/or the serum proteins, could specifically bind with the graphene surface owing to surface adsorption ability of the graphene involving hydrophobic, hydrogen bonding, and electrostatic interactions. Moreover, graphene nanosheets and flakes have large specific surface areas with planar 2D structures, which further endorse its application in regenerative medicine.73 Adsorption ability of GO allows strong interactions of the stem cell like mesenchymal stem cell (MSC) to extracellular matrix (ECM) surface without hampering the cell’s bio-functionality. In a chronic condition like myocardial infarction, a heart attack condition in which the cellular adhesion to the cardiac tissue is impaired, GO-incorporated engraftment sustains cellular adhesion to the ECM proteins. Moreover, components of GO in hybrid scaffolds resist the action of reactive oxygen species (ROS) that otherwise hinder cellular adhesion.73 The ECM proteins such as fibronectin and fibroblast growth factors can easily attach to the GO promoting cellular adhesion without obstructing cellular activity (more details are given in Chapter 9).74 It has been observed that graphene has free radical scavenging ability and thus may reduce oxidative stress. On the other hand, GO has not been found to facilitate radical resonance stabilization.75 Thus, it can be deduced that pristine graphene allows the presence of catalytic sites for scavenging ROS due to a network of sp2-hybridized carbon atoms whilst functional groups on the GO surface reduce the scavenging action of the graphene.75 Thus, by reducing the functional groups on GO, the graphene surface can be switched towards ROS scavenging ability.

1.7.2  Graphene hybrids in drug delivery Low aqueous solubility has been found to be responsible for poor delivery and less effectiveness of various aromatic and hydrophobic drugs like camptothecin, which is an aromatic anticancer drug. In this context, graphene and GO have emerged as potent carriers for effective delivery of the water-insoluble drugs. Depending on the interactions with graphene, a drug like doxorubicin hydrochloride (DXR) can be loaded and released due to change in environmental conditions. The nanohybrid formation mainly involves non-covalent bonding, viz., hydrogen bonding and π-π interactions.76 Liu et al. reported that nanohybrids of PEG-conjugated nanoscale graphene oxide (NGO) have been found effective in the delivery of SN38, which is an anticancer drug analogue of camptothecin.77 The drug and nanohybrid interactions result in NGO-PEG-SN38 complex formation

26  Chapter 1  Graphene-Fundamentals

mainly involving van der Waals forces. The GO content actually imparts hydrophilicity to the complex, and GO faces and edges both act as drug carriers for delivery of the drug to specific locations within the body (more details are given in Chapter 8).

1.8 Conclusions Graphene, having a semi-metallic nature and tuneable energy band gap, has promising applications in semiconductor electronics replacing the use of traditional silicon-based devices. Tuning of electron transfer ability of graphene with redox properties of the electroactive biomolecules can potentially lead to the development of miniaturized bioelectronic devices. Thus, graphene with its special electronic characteristics, along with advanced techniques of sensing platform fabrication and bio-interface knowledge may accelerate developments in the field of bioelectronics. Herein, the biological entity and electronic components synergistically work to evolve the biodevices based on the principle of donating and receiving the electrons mediating the redox reactions. The discovery of graphene has revolutionized this field and is progressing towards the development of bioelectronic devices such as graphene earphones, biosensors, bolometers, conductive tattoos, memory devices, biofuel cells, tissue-engineered constructs, graphene-based batteries, and terahertz sensors. In the next chapter, the design and fabrication of graphene-based sensing platforms and transduction systems are discussed highlighting its applications for various biosensors based on optical, piezo-electric, and electrochemical transducers.

References 1. Nasir, S.; Hussein, M. Z.; Zainal, Z.; Yusof, N. A. Carbon-Based Nanomaterials/ Allotropes: A Glimpse of their Synthesis, Properties and some Applications. Materials 2018, 11 (2), 295. 2. Hoffmann, R.; Kabanov, A. A.; Golov, A. A.; Proserpio, D. M. Homo Citans and Carbon Allotropes: For an Ethics of Citation. Angew. Chem. Int. Ed. 2016, 55 (37), 10962–10976. 3. David, I. G.; Popa, D.-E.; Buleandra, M. Pencil Graphite Electrodes: A Versatile Tool in Electroanalysis. J. Anal. Methods Chem. 2017, 2017. 4. Parvez, K.; Wu, Z.-S.; Li, R.; Liu, X.; Graf, R.; Feng, X.; Mullen, K. Exfoliation of Graphite into Graphene in Aqueous Solutions of Inorganic Salts. J. Am. Chem. Soc. 2014, 136 (16), 6083–6091. 5. Kumar, S.; Kumar, S.; Srivastava, S.; Yadav, B. K.; Lee, S. H.; Sharma, J. G.; Doval, D. C.; Malhotra, B. D. Reduced Graphene Oxide Modified Smart Conducting Paper for cancer Biosensor. Biosens. Bioelectron. 2015, 73, 114–122. 6. Basu, J.; Basu, J. K.; Bhattacharyya, T. K. The Evolution of Graphene-Based Electronic Devices. Int. J. Smart Nano Mater. 2010, 1 (3), 201–223.

Chapter 1  Graphene-Fundamentals  27

7. Chowdhury, S.; Balasubramanian, R. Recent Advances in the Use of GrapheneFamily Nanoadsorbents for Removal of Toxic Pollutants from Wastewater. Adv. Colloid Interf. Sci. 2014, 204, 35–56. 8. Novoselov, K. S.; Geim, A. K.; Morozov, S. V.; Jiang, D.; Zhang, Y.; Dubonos, S. V.; Grigorieva, I. V.; Firsov, A. A. Electric Field Effect in Atomically Thin Carbon Films. Science 2004, 306 (5696), 666–669. 9. Amieva, E. J. C.; López‐Barroso, J.; Martínez‐Hernández, A. L.; Velasco‐Santos, C. Graphene‐Based Materials Functionalization with Natural Polymeric Biomolecules. Recent Adv. Graphene Res. 2016, 257–298. 10. Kuzmenko, A.; Van Heumen, E.; Carbone, F.; Van Der Marel, D. Universal Optical Conductance of Graphite. Phys. Rev. Lett. 2008, 100 (11), 117401. 11. Wang, L.; Sofer, Z.; Pumera, M. Will any Crap we Put into Graphene Increase its Electrocatalytic Effect? ACS Nano 2020. 12. Rodríguez, S.; Makinistian, L.; Albanesi, E. Electronic Transport upon Adsorption of Biomolecules on Graphene. In Handbook of Graphene Set; Vol. 1; 2019; pp. 767–792. 13. Kireev, D.; Offenhäusser, A. Graphene & Two-Dimensional Devices for Bioelectronics and Neuroprosthetics. 2D Mater. 2018, 5 (4), 042004. 14 Jang, H.-S.; Lim, J.-Y.; Kang, S.-G.; et al. Toward Scalable Growth for Single-Crystal Graphene on Polycrystalline Metal Foil. ACS Nano 2020, 14, 3141–3149. 15. Kuzik, L.; Petrov, Y. E.; Pudonin, F.; Yakovlev, V. Optical and Electrical Properties of Ultrathin Metallic Films. Sov. J. Exp. Theor. Phys. 1994, 78, 114–118. 16. Van Bui, H.; Kovalgin, A. Y.; Schmitz, J.; Wolters, R. A. Conduction and Electric Field Effect in Ultra-Thin TiN Films. Appl. Phys. Lett. 2013, 103 (5), 051904. 17. Ihara, S.; Itoh, S. Helically Coiled and Toroidal Cage Forms of Graphitic Carbon. Carbon 1995, 33 (7), 931–939. 18. Land, T.; Michely, T.; Behm, R.; Hemminger, J.; Comsa, G. STM Investigation of Single Layer Graphite Structures Produced on Pt (111) by Hydrocarbon Decomposition. Surf. Sci. 1992, 264 (3), 261–270. 19. Terrones, M.; Botello-Méndez, A. R.; Campos-Delgado, J.; López-Urías, F.; VegaCantú, Y. I.; Rodríguez-Macías, F. J.; Elías, A. L.; Munoz-Sandoval, E.; CanoMárquez, A. G.; Charlier, J.-C. Graphene and Graphite Nanoribbons: Morphology, Properties, Synthesis, Defects and Applications. Nano Today 2010, 5 (4), 351–372. 20. Lee, X. J.; Hiew, B. Y. Z.; Lai, K. C.; Lee, L. Y.; Gan, S.; Thangalazhy-Gopakumar, S.; Rigby, S. Review on Graphene and its Derivatives: Synthesis Methods and Potential Industrial Implementation. J. Taiwan Inst. Chem. Eng. 2019, 98, 163–180. 21. Zhang, Y.; Small, J. P.; Pontius, W. V.; Kim, P. Fabrication and Electric-FieldDependent Transport Measurements of Mesoscopic Graphite Devices. Appl. Phys. Lett. 2005, 86 (7), 073104. 22. Dresselhaus, M. S.; Dresselhaus, G. Intercalation Compounds of Graphite. Adv. Phys. 2002, 51 (1), 1–186. 23. Viculis, L. M.; Mack, J. J.; Kaner, R. B. A Chemical Route to Carbon Nanoscrolls. Science 2003, 299 (5611), 1361. 24. Horiuchi, S.; Gotou, T.; Fujiwara, M.; Asaka, T.; Yokosawa, T.; Matsui, Y. Single Graphene Sheet Detected in a Carbon Nanofilm. Appl. Phys. Lett. 2004, 84 (13), 2403–2405. 25. Inagaki, M.; Kim, Y.; Endo, M. Graphene: Preparation and Structural Perfection. J. Mater. Chem. 2011, 21 (10), 3280–3294. 26. Hess, L. H.; Seifert, M.; Garrido, J. A. Graphene Transistors for Bioelectronics. Proc. IEEE 2013, 101 (7), 1780–1792. 27. Yuan, W.; Zhou, Y.; Li, Y.; Li, C.; Peng, H.; Zhang, J.; Liu, Z.; Dai, L.; Shi, G. The Edge-and Basal-Plane-Specific Electrochemistry of a Single-Layer Graphene Sheet. Sci. Rep. 2013, 3, 2248.

28  Chapter 1  Graphene-Fundamentals

28. Berger, C.; Song, Z.; Li, T.; Li, X.; Ogbazghi, A. Y.; Feng, R.; Dai, Z.; Marchenkov, A. N.; Conrad, E. H.; First, P. N. Ultrathin Epitaxial Graphite: 2D electron Gas Properties and a Route toward Graphene-Based Nanoelectronics. J. Phys. Chem. B 2004, 108 (52), 19912–19916. 29. Berger, C.; Song, Z.; Li, X.; Wu, X.; Brown, N.; Naud, C.; Mayou, D.; Li, T.; Hass, J.; Marchenkov, A. N. Electronic Confinement and Coherence in Patterned Epitaxial Graphene. Science 2006, 312 (5777), 1191–1196. 30. Aguiar-Hualde, J.-M.; Magnin, Y.; Amara, H.; Bichara, C. Probing the Role of Carbon Solubility in Transition Metal Catalyzing Single-Walled Carbon Nanotubes Growth. Carbon 2017, 120, 226–232. 31. Avouris, P.; Dimitrakopoulos, C. Graphene: Synthesis and Applications. Mater. Today 2012, 15 (3), 86–97. 32. Nagashima, A.; Nuka, K.; Itoh, H.; Ichinokawa, T.; Oshima, C.; Otani, S. Electronic States of Monolayer Graphite Formed on TiC (111) Surface. Surf. Sci. 1993, 291 (1–2), 93–98. 33. Wang, J.; Liu, Y.; Fan, Z.; Wang, W.; Wang, B.; Guo, Z. Ink-Based 3D Printing Technologies for Graphene-Based Materials: A Review. Adv. Compos. Hybrid Mater. 2019, 2 (1), 1–33. 34. Lee, W. H.; Park, J.; Sim, S. H.; Lim, S.; Kim, K. S.; Hong, B. H.; Cho, K. SurfaceDirected Molecular Assembly of Pentacene on Monolayer Graphene for HighPerformance Organic Transistors. J. Am. Chem. Soc. 2011, 133 (12), 4447–4454. 35. Meyer, J. C.; Geim, A. K.; Katsnelson, M. I.; Novoselov, K. S.; Booth, T. J.; Roth, S. The Structure of Suspended Graphene Sheets. Nature 2007, 446 (7131), 60–63. 36. Cho, D.-H.; Wang, L.; Kim, J.-S.; Lee, G.-H.; Kim, E. S.; Lee, S.; Lee, S. Y.; Hone, J.; Lee, C. Effect of Surface Morphology on Friction of Graphene on Various Substrates. Nanoscale 2013, 5 (7), 3063–3069. 37. Obradovic, B.; Kotlyar, R.; Heinz, F.; Matagne, P.; Rakshit, T.; Giles, M.; Stettler, M.; Nikonov, D. Analysis of Graphene Nanoribbons as a Channel Material for FieldEffect Transistors. Appl. Phys. Lett. 2006, 88 (14), 142102. 38. Mermin, N. D. Crystalline Order in Two Dimensions. Phys. Rev. 1968, 176 (1), 250. 39. Dutta, S.; Pati, S. K. Novel Properties of Graphene Nanoribbons: A Review. J. Mater. Chem. 2010, 20 (38), 8207–8223. 40. Partoens, B.; Peeters, F. From Graphene to Graphite: Electronic Structure around the K Point. Phys. Rev. B 2006, 74 (7), 075404. 41. Geim, A. K.; Novoselov, K. S. The Rise of Graphene. In Nanoscience and Technology: a Collection of Reviews from Nature Journals; World Scientific, 2010; pp. 11–19. 42. Semenoff, G. W. Condensed-Matter Simulation of a Three-Dimensional Anomaly. Phys. Rev. Lett. 1984, 53 (26), 2449. 43. Li, D.; Zhang, W.; Yu, X.; Wang, Z.; Su, Z.; Wei, G. When Biomolecules Meet Graphene: From Molecular Level Interactions to Material Design and Applications. Nanoscale 2016, 8 (47), 19491–19509. 44. Sandil, D.; Srivastava, S.; Malhotra, B.; Sharma, S.; Puri, N. K. Biofunctionalized Tungsten Trioxide-Reduced Graphene Oxide Nanocomposites for Sensitive Electrochemical Immunosensing of Cardiac Biomarker. J. Alloys Compd. 2018, 763, 102–110. 45. Tarekegne, A. H.; Worku, D. A. Synthesis and Characterization of Reduced Graphene Oxide (rGO) Started from Graphene Oxide (GO) Using the Tour Method with Different Parameters. Adv. Mater. Sci. Eng. 2019, 2019. 46. Hummers, W.; Offeman, R. Preparation of Graphitic Oxide. J. Am. Chem. Soc. 2015, 9, 8165–8175. ACS Publications. 47. Hirata, M.; Gotou, T.; Horiuchi, S.; Fujiwara, M.; Ohba, M. Thin-Film Particles of Graphite Oxide 1:: High-Yield Synthesis and Flexibility of the Particles. Carbon 2004, 42 (14), 2929–2937.

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48. Bhawal, P.; Ganguly, S.; Chaki, T.; Das, N. Synthesis and Characterization of Graphene Oxide Filled Ethylene Methyl Acrylate Hybrid Nanocomposites. RSC Adv. 2016, 6 (25), 20781–20790. 49. Massey, M.; Algar, W. R.; Krull, U. J. Fluorescence Resonance Energy Transfer (FRET) for DNA Biosensors: FRET Pairs and Förster Distances for Various Dye– DNA Conjugates. Anal. Chim. Acta 2006, 568 (1–2), 181–189. 50. Zhang, Z.; Liu, S.; Zhang, Y.; Kang, M.; He, L.; Feng, X.; Peng, D.; Wang, P. Easy Amino-Group Modification of Graphene Using Intermolecular Forces for DNA Biosensing. RSC Adv. 2014, 4 (31), 16368–16373. 51. Xue, T.; Cui, X.; Guan, W.; Wang, Q.; Liu, C.; Wang, H.; Qi, K.; Singh, D. J.; Zheng, W. Surface Plasmon Resonance Technique for Directly Probing the Interaction of DNA and Graphene Oxide and Ultra-Sensitive Biosensing. Biosens. Bioelectron. 2014, 58, 374–379. 52. Wang, Z.; Ge, Z.; Zheng, X.; Chen, N.; Peng, C.; Fan, C.; Huang, Q. Polyvalent DNA– Graphene Nanosheets “Click” Conjugates. Nanoscale 2012, 4 (2), 394–399. 53. Hughes, Z. E.; Walsh, T. R. What Makes a Good Graphene-Binding Peptide? Adsorption of Amino Acids and Peptides at Aqueous Graphene Interfaces. J. Mater. Chem. B 2015, 3 (16), 3211–3221. 54. Wu, J.; Chen, A.; Qin, M.; Huang, R.; Zhang, G.; Xue, B.; Wei, J.; Li, Y.; Cao, Y.; Wang, W. Hierarchical Construction of a Mechanically Stable Peptide–Graphene Oxide Hybrid Hydrogel for Drug Delivery and Pulsatile Triggered Release In Vivo. Nanoscale 2015, 7 (5), 1655–1660. 55. Singh, V. K.; Kumar, S.; Pandey, S. K.; Srivastava, S.; Mishra, M.; Gupta, G.; Malhotra, B.; Tiwari, R.; Srivastava, A. Fabrication of Sensitive Bioelectrode Based on Atomically Thin CVD Grown Graphene for Cancer Biomarker Detection. Biosens. Bioelectron. 2018, 105, 173–181. 56. Belyaeva, L. A.; van Deursen, P. M.; Barbetsea, K. I.; Schneider, G. F. Hydrophilicity of Graphene in Water through Transparency to Polar and Dispersive Interactions. Adv. Mater. 2018, 30 (6), 1703274. 57. Rabe, M.; Verdes, D.; Seeger, S. Surface-Induced Spreading Phenomenon of Protein Clusters. Soft Matter 2009, 5 (5), 1039–1047. 58. Lu, F.; Zhang, S.; Gao, H.; Jia, H.; Zheng, L. Protein-Decorated Reduced Oxide Graphene Composite and its Application to SERS. ACS Appl. Mater. Interfaces 2012, 4 (6), 3278–3284. 59. Kanchanapally, R.; Nellore, B. P. V.; Sinha, S. S.; Pedraza, F.; Jones, S. J.; Pramanik, A.; Chavva, S. R.; Tchounwou, C.; Shi, Y.; Vangara, A. Antimicrobial PeptideConjugated Graphene Oxide Membrane for Efficient Removal and Effective Killing of Multiple Drug Resistant bacteria. RSC Adv. 2015, 5 (24), 18881–18887. 60. Singh, C.; Ali, M. A.; Reddy, V.; Singh, D.; Kim, C. G.; Sumana, G.; Malhotra, B. Biofunctionalized Graphene Oxide Wrapped Carbon Nanotubes Enabled Microfluidic Immunochip for Bacterial Cells Detection. Sensors Actuators B Chem. 2018, 255, 2495–2503. 61. Zhang, J.; Zhang, F.; Yang, H.; Huang, X.; Liu, H.; Zhang, J.; Guo, S. Graphene Oxide as a Matrix for Enzyme Immobilization. Langmuir 2010, 26 (9), 6083–6085. 62. Zhang, F.; Zheng, B.; Zhang, J.; Huang, X.; Liu, H.; Guo, S.; Zhang, J. Horseradish Peroxidase Immobilized on Graphene Oxide: Physical Properties and Applications in Phenolic Compound Removal. J. Phys. Chem. C 2010, 114 (18), 8469–8473. 63. Zhang, Y.; Zhang, J.; Huang, X.; Zhou, X.; Wu, H.; Guo, S. Assembly of Graphene Oxide–Enzyme Conjugates Through Hydrophobic Interaction. Small 2012, 8 (1), 154–159. 64. Lee, D. Y.; Khatun, Z.; Lee, J.-H.; Lee, Y.-K.; In, I. Blood Compatible Graphene/ Heparin Conjugate through Noncovalent Chemistry. Biomacromolecules 2011, 12 (2), 336–341.

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65. Shen, J.; Shi, M.; Yan, B.; Ma, H.; Li, N.; Hu, Y.; Ye, M. Covalent Attaching Protein to Graphene Oxide Via Diimide-Activated Amidation. Colloids Surf. B: Biointerfaces 2010, 81 (2), 434–438. 66. Olad, A.; Hagh, H. B. K. Graphene Oxide and Amin-Modified Graphene Oxide Incorporated Chitosan-Gelatin Scaffolds as Promising Materials for Tissue Engineering. Compos. Part B 2019, 162, 692–702. 67. Feng, Y.; Zhang, X.; Shen, Y.; Yoshino, K.; Feng, W. A Mechanically Strong, Flexible and Conductive Film Based on Bacterial Cellulose/Graphene Nanocomposite. Carbohydr. Polym. 2012, 87 (1), 644–649. 68. Chen, Q.; Wei, W.; Lin, J.-M. Homogeneous Detection of Concanavalin a Using Pyrene-Conjugated Maltose Assembled Graphene Based on Fluorescence Resonance Energy Transfer. Biosens. Bioelectron. 2011, 26 (11), 4497–4502. 69. Liu, J.; Chen, G.; Jiang, M. Supramolecular Hybrid Hydrogels from Noncovalently Functionalized Graphene with Block Copolymers. Macromolecules 2011, 44 (19), 7682–7691. 70. Maity, A. R.; Chakraborty, A.; Mondal, A.; Jana, N. R. Carbohydrate Coated, Folate Functionalized Colloidal Graphene as a Nanocarrier for both Hydrophobic and Hydrophilic Drugs. Nanoscale 2014, 6 (5), 2752–2758. 71. Wang, Q.; She, W.; Lu, X.; Li, P.; Sun, Y.; Liu, X.; Pan, W.; Duan, K. The Interaction of Hyaluronic Acid and Graphene Tuned by Functional Groups: A Density Functional Study. Comput. Theor. Chem. 2019, 1165, 112559. 72. Askari, N.; Askari, M. B.; Shafieipour, A. Investigation the Molecular Structure of Novel Graphene Hybrid Scaffold in Nerve Regeneration. J. Mol. Struct. 2019, 1186, 393–403. 73. Park, J.; Kim, B.; Han, J.; Oh, J.; Park, S.; Ryu, S.; Jung, S.; Shin, J.-Y.; Lee, B. S.; Hong, B. H. Graphene Oxide Flakes as a Cellular Adhesive: Prevention of Reactive Oxygen Species Mediated Death of Implanted Cells for Cardiac Repair. ACS Nano 2015, 9 (5), 4987–4999. 74. Shi, X.; Chang, H.; Chen, S.; Lai, C.; Khademhosseini, A.; Wu, H. Regulating Cellular Behavior on Few‐Layer Reduced Graphene Oxide Films With Well‐ Controlled Reduction States. Adv. Funct. Mater. 2012, 22 (4), 751–759. 75. Qiu, Y.; Wang, Z.; Owens, A. C.; Kulaots, I.; Chen, Y.; Kane, A. B.; Hurt, R. H. Antioxidant Chemistry of Graphene-Based Materials and its Role in Oxidation Protection Technology. Nanoscale 2014, 6 (20), 11744–11755. 76. Yang, X.; Zhang, X.; Liu, Z.; Ma, Y.; Huang, Y.; Chen, Y. High-Efficiency Loading and Controlled Release of Doxorubicin Hydrochloride on Graphene Oxide. J. Phys. Chem. C 2008, 112 (45), 17554–17558. 77. Liu, Z.; Robinson, J. T.; Sun, X.; Dai, H. PEGylated Nanographene Oxide for Delivery of Water-Insoluble cancer Drugs. J. Am. Chem. Soc. 2008, 130 (33), 10876–10877.

Graphene-Based Transduction Systems in Biosensors

2

2.1 Introduction Graphene has recently gained much scientific interest as it is anticipated to bring new approaches to biosensing transduction systems.1,2 Graphene is biocompatible and has a honeycomb-like two-­ dimensional (2D) structure with sp2 hybridized carbon atoms, which gives this material unprecedented properties of high surface area, high electrical conductivity, good mechanical strength, and compatibility for surface functionalization for multiple applications.3–5 More interestingly, different properties can be observed in the layers of multistacked graphene nanostructures6; for example, single-, double-, and few-layered nanostructures exhibit different electronic,7 mechanical,8 as well as optical properties.9 As a result, graphene materials can serve as a transduction system in various modes and can be widely applied in a variety of biosensors.1 Basically, a biosensor includes a bio-recognition system for the detection of biomolecules using enzymes, antibodies, aptamers, DNA, etc., and a physicochemical transducer, which converts the biochemical reaction to an electrical signal. The transduction system of a biosensor is, in fact, a key element that can easily convert biochemical information into some measurable data by further processing through some electronic system. In addition, there may be different (piezoelectric, electrochemical, optical, electronic, gravimetric, or pyroelectric) types of transducers depending on the transduction principle involved1,10–12 as shown in Fig. 2.1.12

2.2  Graphene-based transduction systems Over the past decade, with the discovery and development of a diversity of graphene isolation and synthesis methods, the use of graphene as a transduction system in small biomedical sensing devices has increased significantly.12,13 Improvements have been

Graphene Based Biomolecular Electronic Devices. https://doi.org/10.1016/B978-0-12-821541-8.00007-X Copyright © 2023 Elsevier Inc. All rights reserved.

31

32  Chapter 2  Graphene-Based Transduction Systems in Biosensors

Fig. 2.1  Examples of biosensors and components on a graphene platform. Reproduced with permission from PeñaBahamonde, J.; Nguyen, H. N.; Fanourakis, S. K.; Rodrigues, D. F. Recent Advances in Graphene-Based Biosensor Technology with Applications in Life Sciences. J. Nanobiotechnol. 2018, 16 (1), 1–17.

­ bserved in biosensing devices with wide detection range, higher seno sitivity, and better catalytic behaviour in graphene derivatives and hybrid nanocomposites. The conductivity as well as the surface area of the graphene-based sensing platform can be further improved with the accumulation of catalytic nanoparticles, which ultimately enhance electrochemical biosensing.14 Along with excellent electrical and mechanical properties, the graphene possesses unprecedented optical properties with tuneable absorption levels, including broadband as well as high ­polarization-dependent effects, and these unique properties of the graphene lead to the construction of graphene-based optical biosensors.15 These biosensors can be applied to a variety of applications including antigen–antibody interactions, anticancer drug detection, single cell detection, cell line determination, and protein interactions.16 Nowadays, advanced high-performance, graphenebased, optical biosensors have been employed to measure the analytes through structural changes occurring on the graphene surface.16 In this chapter, emphasis has been given to electrochemical-, piezoelectric-, and optical-type transduction systems of biosensors.

Chapter 2  Graphene-Based Transduction Systems in Biosensors  33

2.2.1  Electrochemical biosensors As described in Chapter 1, graphene can be synthesized by various routes including chemical vapour deposition17 and mechanical exfoliation of graphite and graphite oxide.18,19 Nevertheless, it has been reported that the defects in the graphene structure and heterogenous electron transfer make the material more electroactive.20 Electrochemical biosensors have been found to be highly sensitive, and the selectivity of the analytes could be more accurate as molecules with different redox potentials can be estimated with differences in their ability to be oxidized or reduced.21 The graphene has zero band gap and thus can easily conduct the electric charge. Furthermore, the electrochemical interactions with graphene preferably occur at the edges or at the defects of the graphene basal plane resulting in heterogenous electron transfer between the graphene and biomolecular level. The higher the surface area of the graphene material, higher the chance of defects, and, therefore, relatively more electroactive sites will be there.1,22 Glucose sensing, i.e. the detection of glucose by the biosensors can be efficiently done electrochemically using the graphene in the form of a multi-stacked, ultrathin nanoplatform as a transducing element.23 The immobilized enzyme glucose oxidase can be used as a biorecognition element that can oxidize glucose, thus generating gluconic acid and hydrogen peroxide.24 Here, the electrons are transferred to watersoluble oxygen molecules and eventually converted into hydrogen peroxide, that can be sensed through an electrochemical transduction system.24,25 In comparison to pristine graphene material, the nitrogendoped graphene sheet provides high electrochemical sensitivity with enhanced oxidation current for the glucose biosensing.26 Glucose oxidase also exhibits direct electron transfer without the involvement of oxygen as an electron acceptor.24 For example, the nanosystem fabricated using the enzyme glucose oxidase and graphene in the presence of an ionic liquid has been reported for direct electron transfer.27 In another report, the nanoplatform fabricated by the incorporation of graphene nanoplatelets within the Nafion polymer film has been used to immobilize glucose oxidase by simple adsorption.28 The interaction between the enzyme and substrate without any strong chemical bonds was further found to increase the overall redox current.29 In addition, the incorporation of gold nanoparticles within the composite of graphene and chitosan has been used to detect the glucose level by immobilizing the glucose oxidase enzyme.30 Moreover, DNA can be detected electrochemically using a graphene-based electrochemical transduction system.31 There are two ways of the DNA detection; one is the direct method of DNA

34  Chapter 2  Graphene-Based Transduction Systems in Biosensors

­ ybridization and recognition by the oxidative signals generated h through DNA bases,32 and the other method is by electroactive labels.33 The method of direct detection is comparatively easy, though sensitivity appears to be poor.1,33 Further, various methods are available to produce the chemically modified graphene, viz., electrochemically reduced graphene oxide, chemically reduced graphene oxide, and thermally reduced graphene oxide, graphite oxide, and graphene oxide (Fig. 2.2).34 Zhou et al.35 have reported that when chemically reduced graphene oxide was used, well-resolved signals were observed for the bases adenine, guanine, cytosine, and thymine (A, G, C, and T). However, when conventional a carbon-based sensing platform or graphite was used, the obtained signals were poorly resolved. Therefore, the higher the density of the defects, the better the electrochemical performance of the graphene material is obtained. This feature makes the system more sensitive, which can be used to detect single mutation polymorphism even without the use of a label.36 Similar to reduced graphene oxide obtained by the chemical reduction method, electrochemically oxidized pristine graphene exhibits high electrochemical performance owing to its high defect density. Further, it has been observed that the large defects in the graphene material, as in the case of stacked multi-layered graphene platelets as described by Ambrosi et  al.,37 also lead to high electrochemical sensitivity for DNA detection. These authors have described that the difference in performance is due to the arrangement of the fibres in different directions. Unlike carbon nanotubes (CNTs), the graphene nanofiber stacked structure consists of a vertical arrangement of graphene sheets along the c-axis, with the edges of the graphene sheets that are more electrically active. As a result, the signals for all four types of DNA bases are enhanced as compared to other conventional carbon-based materials including glassy carbon, CNTs, and graphite. In case of the electrochemical immune detection, response is identified using an electrochemically active label. Graphene can be used by either of the two strategies. In the first strategy, graphene can be applied to the electrode surface for label detection at high sensitivity. In another strategy, graphene can be loaded with a desired labelled nanocarrier.1,38 Initially, Shang et al. used a catalyst-free method to deposit a film of graphene nanoparticles on the surface of a silicon substrate; here, a multi-layered graphene structure was assembled to accelerate the electron transfer to eventually transduce the biochemical signal.39 The use of graphene nanoparticles in the biosensing element has been found to accelerate the kinetics of electron transfer and could be applied to detect a wide range of analytes including uric acid, dopamine,

Chapter 2  Graphene-Based Transduction Systems in Biosensors  35

Fig. 2.2  High resolution-transmission electron microscopy (HR-TEM) micrographs of (A) graphite, (B) graphite oxide, (C) graphene oxide, (D) thermally reduced graphene oxide (TR-GO), (E) electrochemically reduced graphene oxide (ER-GO), and (F) chemically reduced graphene oxide (CR-GO). Reproduced with permission from Ambrosi, A.; Bonanni, A.; Sofer, Z.; Cross, J. S.; Pumera, M. Electrochemistry at Chemically Modified Graphenes. Chem. A Eur. J. 2011, 17 (38), 10763–10770.

36  Chapter 2  Graphene-Based Transduction Systems in Biosensors

ascorbic acid, etc.40 The electrode made of graphene nanoparticles exhibits high electrochemical performance compared to an electrode of glassy carbon electrode (GCE), and the performance has even been found to be comparable to that of an edge-plane pyrolytic graphite (EPPG) electrode.40 In another report, Zhou et  al. investigated the use of reduced graphene oxide for the electrochemical transduction system. Here, atomic force microscopic measurements were used to reveal that 1 nm-thick graphene oxide nanoplatelets were composed of two or three layers; the fabricated electrochemical probes of this graphene have been shown to detect various analytes including acetaminophen, dopamine, cytosine, uric acid, etc.35 More interestingly, the layer of graphene sheets affects the overall performance of the electrochemical biosensor. For example, the results of Shang et al.39 and Zhou et al.35 relating to the dopamine detection could be compared; herein, Shang et al.39 used several stacks of graphene sheets, whilst Zhou et al.35 utilized fewer layers of graphene, and the sensitivity and selectivity was different for each. Further, Zou et  al. studied the detection of dopamine and ascorbic acid using a graphene-modified electrode. It was reported that the peaks corresponding to dopamine and ascorbic acid did not overlap in graphene-based material, whilst they were reported to overlap in the case of GCE. Therefore, it could be concluded that the number of graphene layers affect the electrochemistry and performance of the biosensor transducing element.41 Further, Kim et al., have conducted the comparative study for the detection of dopamine in the presence of ascorbic acid using graphenebased electrode and bare GCE. Here, the graphene nanoparticles were synthesized using Hummer’s method. In this study, the rapid electron transfer rate in the case of graphene-modified electrodes has been attributed to the fast response of dopamine.42 The graphene-modified electrode has also been used for electrochemical detection of the heavy metals like cadmium, lead, etc., which have been found to show better sensitivity relative to the unmodified electrode.43–46 Xu et al. designed an electrochemical sensor using furfural/reduced graphene oxide composites for the efficient detection of various heavy metal ions simultaneously. The presence of reduced graphene oxide nanoparticles enhances the conductivity of the composite and increases the specific surface area. In addition, reduced graphene oxide provides enough oxygen-carrying functional groups that provide binding sites for the heavy metal adsorption through the interactions between the hydrophilic groups of reduced graphene oxide and metal ions.46 Shan et al. used a graphene/chitosan-modified GCE using an ionic liquid. Here, the amperometric technique was used to detect a reduced form of nicotinamide adenine dinucleotide (NADH) by using

Chapter 2  Graphene-Based Transduction Systems in Biosensors  37

a prepared nanocomposite modified surface; it was found to exhibit stable and low potential output of the analytes. The surface was found to have low surface fouling effect, and the modified surface with the film of ionic liquid-graphene/chitosan decreased the overvoltage occurring due to NADH oxidation. The strategy was used to fabricate an ethanol biosensor.47 Electrochemiluminescence, a highly sensitive technique, is another type of electrochemical detection. In this type of detection, the reactants are generated electrochemically and electron transfer produces luminescence. Graphene nanoplatforms can be used to detect the presence of thrombin even in interference studies through electrochemiluminescence.48 Further, the graphene-based sensing platform can be utilized for electrochemical genosensing of bacteria, like E. coli (Fig. 2.3).49

2.2.2  Piezoelectric biosensors The electricity generated by applying mechanical stress to a desired material is called piezoelectricity. This physical phenomenon also works in the opposite direction, i.e. mechanical deformations or oscillations can occur under the applied voltage. Consequently, oscillations can be produced in the case of piezoelectric materials by applying alternating voltage.50 Piezoelectric-type biosensors are analytical devices that work on the principle of affinity interaction. In this type of biosensor, a piezoelectric crystal has been employed as the sensing platform of the biosensor. Changes in the loaded mass on the piezoelectric crystal surface results in changes in the oscillations, generating detectable signals.50,51 Piezoelectric materials are largely anisotropic crystals, which do not have any centre of symmetry and thus do not exhibit uniformity in all directions. Quartz, barium titanate, lithium niobate, polyvinylidene fluoride, polylactic acids, tartrate tetrahydrate, aluminium phosphate, etc. are examples of the materials with anisotropic crystals exhibiting piezoelectric behaviour.52,53 The working of the piezoelectric biosensor involves the application of alternating voltage to two given electrode surfaces. Mechanical oscillations are created due to an applied alternating voltage of a specific frequency that can be measured when the piezoelectric crystal is placed in a circuit of oscillation.54 The bio-analyte has a specific mass, and when it is adsorbed on the crystal electrode surface, a change in the frequency of oscillations can be observed depending on the mass of the bio-analyte, as reported by Sauerbreay et al.55 Later, various other factors including changes in the viscosity of the fluid were found to affect the oscillations and hence can sense the bio-analyte through the piezoelectric material.56

Fig. 2.3  Schematic representation of (A) electrode fabrication based on graphene materials and (B) electrochemical genosensing of E. coli using the fabricated electrode. Reproduced with permission from Jaiswal, N.; Pandey, C. M.; Soni, A.; Tiwari, I.; Rosillo-Lopez, M.; Salzmann, C. G.; Malhotra, B. D.; Sumana, G. Electrochemical Genosensor Based on Carboxylated Graphene for Detection of Water-Borne Pathogen. Sens. Actuators B 2018, 275, 312–321.

Chapter 2  Graphene-Based Transduction Systems in Biosensors  39

The piezoelectric immunosensors are a type of biosensors that use antibodies or antigens as the bio-recognition elements of the bio-­ analytical device.2,57 Piezoelectric immunosensors have been used to detect and analyse a wide range of analytes including various types of biomolecules and microorganisms.58 The immunosensors are highly specific and relatively less sensitive for the interfering compounds. Since antigens can be immobilized on the sensing platform, various infectious diseases could be diagnosed with the help of piezoelectric immunosensors.58,59 To design these piezoelectric immunosensor, quartz crystal microbalance (QCM) has been widely used owing to its commercial availability along with its optimal piezoelectric behaviour. In this context, Muratsugu et  al. postulated the label-free assay for the detection of albumin protein by piezoelectric immunosensor using QCM. Antihuman serum albumin antibodies were conjugated on the electrode surface to detect the presence of albumin in a urea sample.60 This immunoassay could be utilized to estimate albumin in the range of 0.1– 100 μg mL−  1.60 In another study, a QCM immunosensor was employed to determine the complement component 4 (C-4); here, Nafion was first used to modify the electrode and then antibodies against complimentary system protein C-4 were immobilized on the modified surface. The process was reported to show regeneration with 90% to 112% recovery of protein C-4.61 The major disadvantage associated with QCM is its low sensitivity. The analytes with high molecular weight can be detected because they cause changes in the frequency of oscillation on a large scale, whereas the signals need to be amplified by the assistance of some nanoparticles like gold nanoparticles to analyse small analytes like that of morphine at a lower limit of detection in the range of μg mL−  1.62,63 To overcome low sensitivity, graphene-based field effect transistors (FET) have emerged as a powerful biosensing tool to detect analytes in a wide range with higher sensitivity64 (discussed further in Chapter 3). Nivasan Yogeswaran et al. reported the design of a dynamic pressure sensor using biodegradable piezoelectric material of β-glycine/chitosan composite and graphene-based FET that could work at a very low voltage of 50 mV. The piezoelectric material structure was a metalinsulator-metal type that was connected to the graphene-based FET with the configuration of the gate. The fabricated device displayed a sensitivity of 2.70 × 10−  4 under an applied pressure range of 5 to 20 kPa. When the pressure range increased from 20 to 35 kPa, it displayed a sensitivity of 7.56 × 10−  4 kPa−  1. The device was postulated to apply to electronic skin with high energy efficiency and large area.65 One of the important applications of graphene-based piezoelectric biosensors that these can be used as wearable biosensing devices. More details related to graphene-based pressure sensors are given in Chapter 5 of this book.

40  Chapter 2  Graphene-Based Transduction Systems in Biosensors

2.2.3  Optical biosensors Graphene has no band gap; thus, the electron band structure allows very high electron mobility in the graphene layer. In addition, graphene and its derivatives have good optical properties with both broadband and saturation absorption.66 Although the graphene sheets do not exhibit any photoluminescence, the method can be employed to modify the graphene and a certain band gap could be created. For example, graphene quantum dots exhibit excellent photoluminescence properties.67 The unique lattice and electronic structure of graphene is thought to be responsible for its optical properties. Although the thickness of the graphene layer is very low (about 3.35 Å), the presence of linear distribution of the Dirac electrons in graphene allows high optical absorption.68,69 As a result, the single layer of graphene could absorb approximately πα (2.3%) of the broadband light from a range of visible to terahertz wavelength (Fig. 2.4).16 For the visible spectral range of light, graphene has been found to exhibit absorption (~   2.3%), which largely depends on the graphene’s ultra-structure, indicating the optimal transparency level of the graphene sheets. Graphene has Dirac electrons that exhibit high kinetics, whilst the tapered band structure shows Pauli blocking. This results in changes in the nonlinear optical properties of the graphene material. At the Dirac point, the electrons show a linear energy and momentum dispersion relationship. Consequently, in the ­ultraviolet-visible-infrared region, graphene shows a resonant optical response.16,66 High optical absorption in the broadband range of light further allows graphene to have a difference in reflectance value in the case of total internal reflectance across the transverse magnetic and electric modes. This is further found to be sensitive to the refractive index of the medium to the surface.70 In the case of the graphene sheets, inter-band transitions are possible due to collisions of the carriers,

Fig. 2.4  Electron band structure and Dirac point of graphene. Purple represents the n-typedoped Fermi surface, and light blue represents the p-type-doped Fermi surface. Reproduced with permission from Li, Z.; Zhang, W.; Xing, F. Graphene Optical Biosensors. Int. J. Mol. Sci. 2019, 20 (10), 2461.

Chapter 2  Graphene-Based Transduction Systems in Biosensors  41

e­ specially when the electrons and holes energy becomes close to the Dirac point. As a result, a layer of graphene provides a high absorption value of saturation.71 When the graphene interacts with light, two main types of interactions occur, viz., intra- and inter-band transitions. In the case of the high wavelength spectral range of far-infrared and tetra hertz, the electronic level response is mainly found to be in-band transition as described by the Drude model72 which is almost similar as that of a metal. Whilst going towards the lower wavelength spectral range, viz., energy bands of near-infrared and visible light, the photo-response is largely of the inter-band transition type.73 In the visible region, the optical transmittance value is determined by the number of graphene layers, which decreases with the increase in the number of layers. Shou-En Zhu et al. have reported that the optical transmittance value of graphene can be used to evaluate the number of graphene layers in a multi-layered graphene structure, more reliably than Raman spectroscopy.74 In the graphene material, the light absorption coefficient is determined by graphene’s ultra-structural constant, and it does not depend on the wavelength of the light to be absorbed. In addition, according to the principle of Pauli blocking, the absorption of light in graphene can be controlled through the adjustment of positions of the Fermi surface.75 In case of absorption of the ultraviolet region, the inter-band transitions occur, which is found to be close to that of the saddle point; this is the point at which the absorption of light transcends the universal absorption value and thus shows an exciton effect.76 More efforts should be made in the direction of enhancing the interactions between graphene and photons to increase the light absorption value in this region.16 However, graphene polarization-dependent effects, as well as broadband and tuneable light absorption, make graphene optical properties unique and have led to the fabrication of graphene-based optical sensors and biodevices.77 More recently, efforts have been made to design graphenebased optical sensors using surface plasmon resonance (SPR)78 and graphene spatial light sensors.79 Here, SPR-based graphene optical sensors have been in great demand because of their real-time response, high sensitivity, comprehensive analysis of data, real-time tracking, and analysis of ligand stability. Therefore, more efforts are underway on designing SPR sensors based on the use of graphene optical fibres.80 Basically, the principle behind optical sensors is to measure the rate of change in the refractive index for various applications including biosensing.81 These graphene-based optical ­biosensors can be

42  Chapter 2  Graphene-Based Transduction Systems in Biosensors

applied for single cell detection,82 immuno-sensing involving the antigen–antibody reactions,83 protein detection,84 cell line ­detection, detection of anti-cancerous drugs, etc. The working principle behind the graphene-based optical biosensor is related to the changes in the surface properties of the graphene due to the graphene and biomolecular interactions.16,84 Although many biosensors based on graphene as an optical sensing element have been developed, the major challenge is the control of the graphene synthesis parameters, such as the defects appearing on the graphene surface during its synthesis, the number of graphene layers, the size and shape of the graphene nanoparticles, and the graphene’s electronic band gap in the modified structure.85 These parameters alter the physical properties that ultimately change the graphene’s conductivity and surface interactions with biomolecules, affecting the performance and sensitivity of graphene-based optical biosensors.86,87 Therefore, there is a need to explore and find more efficient production methods of high-quality graphene-based nanomaterials. Moreover, the applications of graphene in optics are mainly limited to the medical field of biosensing.88 For example, the disorder related to the neurological activities, including the brain degeneration, can be diagnosed at the early stage using the graphenebased optical biosensor.15 Nevertheless, new innovative designs should be explored by researchers for more applications and to investigate the multiple analytes in more complex conditions of media and surroundings.89 In addition, more efforts should be made for the commercialization of graphene-based optical biosensors by using low-cost raw materials of graphene and exploring ways of high reusability. The issues related to graphene biocompatibility, including toxicity at high doses, should be considered and addressed prior to commercialization of graphene-based optical products.90 Graphenebased materials modified with functional moieties are found to be more biocompatible and could be applied in many ways to humans. Therefore, graphene-based materials modified with functional domains can be used to make the surface more biocompatible and can be utilized by humans in many ways.

2.3 Conclusions Graphene is a zero-band gap semiconductor material that is highly electroactive and is optically transparent, especially at mono-layered thicknesses. Due to the special properties, such as absence of metal impurities, high electronic conductivity, biocompatibility, and being a low-cost graphene source material, it has been used as a transducing element in various biosensing applications, including e­ lectrochemical,

Chapter 2  Graphene-Based Transduction Systems in Biosensors  43

optical, FETs, etc. The use of graphene-based transduction systems in biosensing devices may provide new breakthroughs in advanced areas of biomedical devices. However, the major issue is the mass production of pure single-sheet graphene and the prevention of re-stacking. Furthermore, in the case of multi-layered graphene nanostructures, there is an urgent need to develop an effective new strategy that can provide precise regulation in the number of layers.

References 1. Pumera, M. Graphene in Biosensing. Mater. Today 2011, 14 (7–8), 308–315. 2. Nara, S.; Malhotra, B. D. Applications of Immuno-Electrochemical Detection Strategies for Food Analysis. In Rapid Antibody-based Technologies in Food Analysis; Royal Society of Chemistry (RSC), 2019; pp. 154–174. 3. Nara, S.; Kandpal, R.; Jaiswal, V.; Augustine, S.; Wahie, S.; Sharma, J. G.; Takeuchi, R.; Takenaka, S.; Malhotra, B. D. Exploring Providencia rettgeri for Application to Eco-Friendly Paper Based Microbial Fuel Cell. Biosens. Bioelectron. 2020, 165, 112323. 4. Rao, C.; Biswas, K.; Subrahmanyam, K.; Govindaraj, A. Graphene, the New Nanocarbon. J. Mater. Chem. 2009, 19 (17), 2457–2469. 5. Abergel, D.; Apalkov, V.; Berashevich, J.; Ziegler, K.; Chakraborty, T. Properties of Graphene: A Theoretical Perspective. Adv. Phys. 2010, 59 (4), 261–482. 6. Casiraghi, C.; Hartschuh, A.; Lidorikis, E.; Qian, H.; Harutyunyan, H.; Gokus, T.; Novoselov, K. S.; Ferrari, A. Rayleigh Imaging of Graphene and Graphene Layers. Nano Lett. 2007, 7 (9), 2711–2717. 7. Neto, A. C.; Guinea, F.; Peres, N. M.; Novoselov, K. S.; Geim, A. K. The Electronic Properties of Graphene. Rev. Mod. Phys. 2009, 81 (1), 109. 8. Baimova, A.; Korznikova, E.; Dmitriev, S.; Liu, B.; Zhou, K. Review on Crumpled Graphene: Unique Mechanical Properties. Rev. Adv. Mater. Sci. 2014, 39 (1). 9. Falkovsky, L. Optical Properties of Graphene. J. Phys. Conf. Ser. 2008, 012004. IOP Publishing. 10. Suvarnaphaet, P.; Pechprasarn, S. Graphene-Based Materials for Biosensors: a Review. Sensors 2017, 17 (10), 2161. 11. Tabish, T. A.; Abbas, A.; Narayan, R. J. Graphene Nanocomposites for Transdermal Biosensing. Wiley Interdiscip. Rev. Nanomed. Nanobiotechnol. 2021, 13 (4), e1699. 12. Peña-Bahamonde, J.; Nguyen, H. N.; Fanourakis, S. K.; Rodrigues, D. F. Recent Advances in Graphene-Based Biosensor Technology with Applications in Life Sciences. J. Nanobiotechnol. 2018, 16 (1), 1–17. 13. Zhu, Y.; James, D. K.; Tour, J. M. New Routes to Graphene, Graphene Oxide and their Related Applications. Adv. Mater. 2012, 24 (36), 4924–4955. 14. Kumar, S.; Bukkitgar, S. D.; Singh, S.; Singh, V.; Reddy, K. R.; Shetti, N. P.; Venkata Reddy, C.; Sadhu, V.; Naveen, S. Electrochemical Sensors and Biosensors Based on Graphene Functionalized with Metal Oxide Nanostructures for Healthcare Applications. ChemistrySelect 2019, 4 (18), 5322–5337. 15. Ramon-Marquez, T.; Medina-Castillo, A. L.; Fernandez-Gutierrez, A.; FernandezSanchez, J. F. A Novel Optical Biosensor for Direct and Selective Determination of Serotonin in Serum by Solid Surface-Room Temperature Phosphorescence. Biosens. Bioelectron. 2016, 82, 217–223. 16. Li, Z.; Zhang, W.; Xing, F. Graphene Optical Biosensors. Int. J. Mol. Sci. 2019, 20 (10), 2461.

44  Chapter 2  Graphene-Based Transduction Systems in Biosensors

17. Shu, H.; Chen, X.; Tao, X.; Ding, F. Edge Structural Stability and Kinetics of Graphene Chemical Vapor Deposition Growth. ACS Nano 2012, 6 (4), 3243–3250. 18. Yi, M.; Shen, Z. A Review on Mechanical Exfoliation for the Scalable Production of Graphene. J. Mater. Chem. A 2015, 3 (22), 11700–11715. 19. Young, R. J.; Kinloch, I. A.; Gong, L.; Novoselov, K. S. The Mechanics of Graphene Nanocomposites: a Review. Compos. Sci. Technol. 2012, 72 (12), 1459–1476. 20. Ritzert, N. L.; Rodriguez-Lopez, J.; Tan, C.; Abruna, H. D. Kinetics of Interfacial electron Transfer at Single-Layer Graphene Electrodes in Aqueous and Nonaqueous Solutions. Langmuir 2013, 29 (5), 1683–1694. 21. Fang, Y.; Wang, E. Electrochemical Biosensors on Platforms of Graphene. Chem. Commun. 2013, 49 (83), 9526–9539. 22. Valota, A. T.; Kinloch, I. A.; Novoselov, K. S.; Casiraghi, C.; Eckmann, A.; Hill, E. W.; Dryfe, R. A. Electrochemical Behavior of Monolayer and Bilayer Graphene. ACS Nano 2011, 5 (11), 8809–8815. 23. Wang, J. Electrochemical Glucose Biosensors. Chem. Rev. 2008, 108 (2), 814–825. 24. Shan, C.; Yang, H.; Song, J.; Han, D.; Ivaska, A.; Niu, L. Direct Electrochemistry of Glucose Oxidase and Biosensing for Glucose Based on Graphene. Anal. Chem. 2009, 81 (6), 2378–2382. 25. Wu, H.; Wang, J.; Kang, X.; Wang, C.; Wang, D.; Liu, J.; Aksay, I. A.; Lin, Y. Glucose Biosensor Based on Immobilization of Glucose Oxidase in Platinum Nanoparticles/Graphene/Chitosan Nanocomposite Film. Talanta 2009, 80 (1), 403–406. 26. Wang, Y.; Shao, Y.; Matson, D. W.; Li, J.; Lin, Y. Nitrogen-Doped Graphene and its Application in Electrochemical Biosensing. ACS Nano 2010, 4 (4), 1790–1798. 27. Jiang, Y.; Zhang, Q.; Li, F.; Niu, L. Glucose Oxidase and Graphene Bionanocomposite Bridged by Ionic Liquid Unit for Glucose Biosensing Application. Sens. Actuators B 2012, 161 (1), 728–733. 28. Yildiz, G.; Bolton-Warberg, M.; Awaja, F. Graphene and Graphene Oxide for BioSensing: General Properties and the Effects of Graphene Ripples. Acta Biomater. 2021, 131, 62–79. 29. Wang, J.; Wu, L.-H.; Lu, Z.; Li, R.; Sanchez, J. Mixed Ferrocene-Glucose OxidaseCarbon-Paste Electrode for Amperometric Determination of Glucose. Anal. Chim. Acta 1990, 228, 251–257. 30. Fang, Y.; Zhang, D.; Guo, Y.; Guo, Y.; Chen, Q. Simple One-Pot Preparation of Chitosan-Reduced Graphene Oxide-Au Nanoparticles Hybrids for Glucose Sensing. Sens. Actuators B 2015, 221, 265–272. 31. Jaiswal, N.; Pandey, C. M.; Solanki, S.; Tiwari, I.; Malhotra, B. D. An Impedimetric Biosensor Based on Electrophoretically Assembled ZnO Nanorods and Carboxylated Graphene Nanoflakes on an Indium Tin Oxide Electrode for Detection of the DNA of Escherichia coli O157: H7. Microsc. Acta 2020, 187 (1), 1–8. 32. Wang, J. Towards Genoelectronics: Electrochemical Biosensing of DNA Hybridization. Chem. A Eur. J. 1999, 5 (6), 1681–1685. 33. Bonanni, A. Advances on the Use of Graphene as a Label for Electrochemical Biosensors. ChemElectroChem 2020, 7 (20), 4177–4185. 34. Ambrosi, A.; Bonanni, A.; Sofer, Z.; Cross, J. S.; Pumera, M. Electrochemistry at Chemically Modified Graphenes. Chem. A Eur. J. 2011, 17 (38), 10763–10770. 35. Zhou, M.; Zhai, Y.; Dong, S. Electrochemical Sensing and Biosensing Platform Based on Chemically Reduced Graphene Oxide. Anal. Chem. 2009, 81 (14), 5603–5613. 36. Bonanni, A.; Chua, C. K.; Zhao, G.; Sofer, Z. K.; Pumera, M. Inherently Electroactive Graphene Oxide Nanoplatelets as Labels for Single Nucleotide Polymorphism Detection. ACS Nano 2012, 6 (10), 8546–8551.

Chapter 2  Graphene-Based Transduction Systems in Biosensors  45

37. Ambrosi, A.; Pumera, M. Stacked Graphene Nanofibers for Electrochemical Oxidation of DNA Bases. Phys. Chem. Chem. Phys. 2010, 12 (31), 8943–8947. 38. Khristunova, E.; Dorozhko, E.; Korotkova, E.; Kratochvil, B.; Vyskocil, V.; Barek, J. Label-Free Electrochemical Biosensors for the Determination of Flaviviruses: Dengue, Zika, and Japanese Encephalitis. Sensors 2020, 20 (16), 4600. 39. Shang, N. G.; Papakonstantinou, P.; McMullan, M.; Chu, M.; Stamboulis, A.; Potenza, A.; Dhesi, S. S.; Marchetto, H. Catalyst‐Free Efficient Growth, Orientation and Biosensing Properties Of Multilayer Graphene Nanoflake Films with Sharp Edge Planes. Adv. Funct. Mater. 2008, 18 (21), 3506–3514. 40. Demirkan, B.; Bozkurt, S.; Cellat, K.; Arıkan, K.; Yılmaz, M.; Şavk, A.; Çalımlı, M. H.; Nas, M. S.; Atalar, M. N.; Alma, M. H. Palladium Supported on Polypyrrole/ Reduced Graphene Oxide Nanoparticles for Simultaneous Biosensing Application of Ascorbic Acid, Dopamine, and Uric Acid. Sci. Rep. 2020, 10 (1), 1–10. 41. Zou, H. L.; Li, B. L.; Luo, H. Q.; Li, N. B. A Novel Electrochemical Biosensor Based on Hemin Functionalized Graphene Oxide Sheets for Simultaneous Determination of Ascorbic Acid, Dopamine and Uric Acid. Sens. Actuators B 2015, 207, 535–541. 42. Kim, Y.-R.; Bong, S.; Kang, Y.-J.; Yang, Y.; Mahajan, R. K.; Kim, J. S.; Kim, H. Electrochemical Detection of Dopamine in the Presence of Ascorbic Acid Using Graphene Modified Electrodes. Biosens. Bioelectron. 2010, 25 (10), 2366–2369. 43. Xu, L.; Wang, J. The Application of Graphene-Based Materials for the Removal of Heavy Metals and Radionuclides from Water and Wastewater. Crit. Rev. Environ. Sci. Technol. 2017, 47 (12), 1042–1105. 44. Zhao, W.; Fang, M.; Wu, F.; Wu, H.; Wang, L.; Chen, G. Preparation of Graphene by Exfoliation of Graphite Using Wet Ball Milling. J. Mater. Chem. 2010, 20 (28), 5817–5819. 45. Obraztsova, E. A.; Osadchy, A. V.; Obraztsova, E. D.; Lefrant, S.; Yaminsky, I. V. Statistical Analysis of Atomic Force Microscopy and Raman Spectroscopy Data for Estimation of Graphene Layer Numbers. Phys. Status Solidi B 2008, 245 (10), 2055–2059. 46. Xu, X.; Lv, X.; Tan, F.; Li, Y.; Geng, C.; Cui, B.; Fang, Y. Simultaneous Electrochemical Detection of Multiple Heavy-Metal Ions Based on Furfural/Reduced Graphene Oxide Composites. J. Electrochem. Soc. 2021, 168 (12), 126516. 47. Shan, C.; Yang, H.; Han, D.; Zhang, Q.; Ivaska, A.; Niu, L. Electrochemical Determination of NADH and Ethanol Based on Ionic Liquid-Functionalized Graphene. Biosens. Bioelectron. 2010, 25 (6), 1504–1508. 48. Guo, Y.; Jia, X.; Zhang, S. DNA Cycle Amplification Device on Magnetic Microbeads for Determination of Thrombin Based on Graphene Oxide Enhancing Signal-on Electrochemiluminescence. Chem. Commun. 2011, 47 (2), 725–727. 49. Jaiswal, N.; Pandey, C. M.; Soni, A.; Tiwari, I.; Rosillo-Lopez, M.; Salzmann, C. G.; Malhotra, B. D.; Sumana, G. Electrochemical Genosensor Based on Carboxylated Graphene for Detection of Water-Borne Pathogen. Sens. Actuators B 2018, 275, 312–321. 50. Pohanka, M. Overview of Piezoelectric Biosensors, Immunosensors and DNA Sensors and their Applications. Materials 2018, 11 (3), 448. 51. Chauhan, R.; Singh, J.; Solanki, P. R.; Manaka, T.; Iwamoto, M.; Basu, T.; Malhotra, B. Label-Free Piezoelectric Immunosensor Decorated with Gold Nanoparticles: Kinetic Analysis and Biosensing Application. Sens. Actuators B 2016, 222, 804–814. 52. Xu, Q.; Gao, X.; Zhao, S.; Liu, Y. N.; Zhang, D.; Zhou, K.; Khanbareh, H.; Chen, W.; Zhang, Y.; Bowen, C. Construction of Bio‐Piezoelectric Platforms: From Structures and Synthesis to Applications. Adv. Mater. 2021, 33 (27), 2008452. 53. Ma, J.; Li, T.; Chen, Y. H.; Lim, T. H.; Boey, F. Piezoelectric Materials for Biomedical Applications. In Key Engineering Materials; Trans Tech Publications, 2007; pp. 1117–1120.

46  Chapter 2  Graphene-Based Transduction Systems in Biosensors

54. Pohanka, M. The Piezoelectric Biosensors: Principles and Applications. Int. J. Electrochem. Sci 2017, 12, 496–506. 55. Sauerbrey, G. Verwendung von Schwingquarzen zur Wägung dünner Schichten und zur Mikrowägung. Zeitschrift für physik 1959, 155 (2), 206–222. 56. Pintea, J.; Dumitru, A.; Pîslaru, L. D.; Chirita, I. Piezoelectric Transducer for Fluid Viscosity Measurement. Electroteh. Electron. Autom. 2012, 60 (3), 63. 57. O’Sullivan, C. K.; Guilbault, G. G. Piezoelectric Immunosensors: Theory and Applications. In Biosensors and Their Applications; Yang, V. C., Ngo, T. T., Eds.; Springer: Boston, MA, 2000. https://doi.org/10.1007/978-1-4615-4181-3_9. 58. Zuo, B.; Li, S.; Guo, Z.; Zhang, J.; Chen, C. Piezoelectric Immunosensor for SARSAssociated Coronavirus in Sputum. Anal. Chem. 2004, 76 (13), 3536–3540. 59. Suleiman, A. A.; Guilbault, G. G. Recent Developments in Piezoelectric Immunosensors. A review. Analyst 1994, 119 (11), 2279–2282. 60. Muratsugu, M.; Ohta, F.; Miya, Y.; Hosokawa, T.; Kurosawa, S.; Kamo, N.; Ikeda, H. Quartz Crystal Microbalance for the Detection of Microgram Quantities of Human Serum Albumin: Relationship between the Frequency Change and the Mass of Protein Adsorbed. Anal. Chem. 1993, 65 (20), 2933–2937. 61. Deng, T.; Li, J.-S.; Wang, H.; Shen, G.-L.; Yu, R.-Q. Piezoelectric Immunoassay for Complement C4 Based on a Nafion-Modified Interface for Antibody Immobilization. J. Immunol. Methods 2005, 299 (1–2), 1–8. 62. Lim, H. J.; Saha, T.; Tey, B. T.; Tan, W. S.; Ooi, C. W. Quartz Crystal MicrobalanceBased Biosensors as Rapid Diagnostic Devices for Infectious Diseases. Biosens. Bioelectron. 2020, 168, 112513. 63. D’Aurelio, R.; Tothill, I. E.; Salbini, M.; Calò, F.; Mazzotta, E.; Malitesta, C.; Chianella, I. A Comparison of EIS and QCM NanoMIP-Based Sensors for Morphine. Nanomaterials 2021, 11 (12), 3360. 64. Lian, Y.; He, F.; Wang, H.; Tong, F. A New Aptamer/Graphene Interdigitated Gold Electrode Piezoelectric Sensor for Rapid and Specific Detection of Staphylococcus aureus. Biosens. Bioelectron. 2015, 65, 314–319. 65. Yogeswaran, N.; Hosseini, E. S.; Dahiya, R. Graphene-Based Low Voltage Field Effect Transistor Coupled with Biodegradable Piezoelectric Material Based Dynamic Pressure Sensor. ACS Appl. Mater. Interfaces 2020, 12 (48), 54035–54040. 66. Liu, Z.; Zhang, X.; Yan, X.; Chen, Y.; Tian, J. Nonlinear Optical Properties of Graphene-Based Materials. Chin. Sci. Bull. 2012, 57 (23), 2971–2982. 67. Zhu, S.; Song, Y.; Zhao, X.; Shao, J.; Zhang, J.; Yang, B. The Photoluminescence Mechanism in Carbon Dots (Graphene Quantum Dots, Carbon Nanodots, and Polymer Dots): Current State and Future Perspective. Nano Res. 2015, 8 (2), 355–381. 68. Nath, S.; Bandyopadhyay, A.; Datta, S.; Uddin, M. M.; Jana, D. Electronic and Optical Properties of Non-hexagonal Dirac Material S-Graphene Sheet and Nanoribbons. Physica E 2020, 120, 114087. 69. Chamoli, P.; Banerjee, S.; Raina, K. K.; et al. Characteristics of Graphene/Reduced Graphene Oxide. In Handbook of Nanocomposite Supercapacitor Materials I; Kar, K., Ed.; Springer Series in Materials Science, vol. 300; Springer: Cham, 2020; pp. 155–177. https://doi.org/10.1007/978-3-030-43009-2_5. 70. Rasheed, M.; Shihab, S.; Sabah, O. W. An Investigation of the Structural, Electrical and Optical Properties of Graphene-Oxide Thin Films Using Different Solvents. J. Phys. Conf. Ser. 2021, 012052. IOP Publishing. 71. Tiwari, S. K.; Sahoo, S.; Wang, N.; Huczko, A. Graphene Research and their Outputs: Status and Prospect. J. Sci. Adv. Mater. Devices 2020, 5 (1), 10–29. 72. Tse, W.-K.; MacDonald, A. Interaction Effects in the Optical Conductivity of Bilayer Graphene: Drude-Interband Coupling and Screening. Phys. Rev. B 2009, 80 (19), 195418.

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73. Xiao, Y.; Xu, W.; Peeters, F. Infrared to Terahertz Absorption Window in Mono-and Multi-Layer Graphene Systems. Opt. Commun. 2014, 328, 135–142. 74. Zhu, S.-E.; Yuan, S.; Janssen, G. Optical Transmittance of Multilayer Graphene. Europhys. Lett. 2014, 108 (1), 17007. 75. Mak, K. F.; Ju, L.; Wang, F.; Heinz, T. F. Optical Spectroscopy of Graphene: from the Far Infrared to the Ultraviolet. Solid State Commun. 2012, 152 (15), 1341–1349. 76. Chae, D.-H.; Utikal, T.; Weisenburger, S.; Giessen, H.; Klitzing, K. V.; Lippitz, M.; Smet, J. Excitonic Fano Resonance in Free-Standing Graphene. Nano Lett. 2011, 11 (3), 1379–1382. 77. Gao, X.-G.; Cheng, L.-X.; Jiang, W.-S.; Li, X.-K.; Xing, F. Graphene and its Derivatives-Based Optical Sensors. Front. Chem. 2021, 5. 78. Wu, L.; Chu, H.-S.; Koh, W. S.; Li, E.-P. Highly Sensitive Graphene Biosensors Based on Surface Plasmon Resonance. Opt. Express 2010, 18 (14), 14395–14400. 79. Marinova, V.; Lin, S. H.; Petrov, S.; Chen, M. S.; Lin, Y. H.; Hsu, K. Y. GrapheneBased Spatial Light Modulator Operating at near Infrared Spectral Range. Appl. Surf. Sci. 2019, 472, 2–9. 80. Fu, H.; Zhang, S.; Chen, H.; Weng, J. Graphene Enhances the Sensitivity of ­fiber-Optic Surface Plasmon Resonance Biosensor. IEEE Sens. J. 2015, 15 (10), 5478–5482. 81. Patel, S. K.; Parmar, J.; Kosta, Y. P.; Charola, S.; Zakaria, R. B.; Nguyen, T. K.; Dhasarathan, V. Graphene-Based Highly Sensitive Refractive Index Biosensors Using C-Shaped Metasurface. IEEE Sens. J. 2020, 20 (12), 6359–6366. 82. Balaji, A.; Zhang, J. Electrochemical and Optical Biosensors for Early-Stage cancer Diagnosis by Using Graphene and Graphene Oxide. Cancer Nanotechnol. 2017, 8 (1), 1–12. 83. Li, B.; Tan, H.; Jenkins, D.; Raghavan, V. S.; Rosa, B. G.; Güder, F.; Pan, G.; Yeatman, E.; Sharp, D. J. Clinical Detection of Neurodegenerative Blood Biomarkers Using Graphene Immunosensor. Carbon 2020, 168, 144–162. 84. Zhang, Q.; Zhang, D.; Lu, Y.; Yao, Y.; Li, S.; Liu, Q. Graphene Oxide-Based Optical Biosensor Functionalized with Peptides for Explosive Detection. Biosens. Bioelectron. 2015, 68, 494–499. 85. Xu, M.; Fujita, D.; Sagisaka, K.; Watanabe, E.; Hanagata, N. Production of Extended Single-Layer Graphene. ACS Nano 2011, 5 (2), 1522–1528. 86. Dash, J. N.; Jha, R. On the Performance of Graphene-Based D-Shaped Photonic Crystal Fibre Biosensor Using Surface Plasmon Resonance. Plasmonics 2015, 10 (5), 1123–1131. 87. Kumar, A.; Kumar, A.; Kushwaha, A. S.; Dubey, S. K.; Srivastava, S. A Comparative Study of Different Types of Sandwiched Structures of SPR Biosensor for Sensitive Detection of ssDNA. Photonics Nanostruct. Fundam. Appl. 2022, 48, 100984. 88. Chauhan, N.; Maekawa, T.; Kumar, D. N. S. Graphene-Based Biosensors— Accelerating Medical Diagnostics to New-Dimensions. J. Mater. Res. 2017, 32 (15), 2860–2882. 89. Morales‐Narváez, E.; Merkoçi, A. Graphene Oxide as an Optical Biosensing Platform: a Progress Report. Adv. Mater. 2019, 31 (6), 1805043. 90. Morales‐Narváez, E.; Baptista‐Pires, L.; Zamora‐Gálvez, A.; Merkoçi, A. Graphene‐Based Biosensors: Going Simple. Adv. Mater. 2017, 29 (7), 1604905.

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3

3.1 Introduction Successful isolation of single-layered graphene in 2004 has led to various developments in the emerging field of biosensing. Graphene is a single atomic carbon sheet of sp2 hybridized atoms wherein the atoms are organized in a honeycomb-like crystal structure. The high electrical conductivity, fast electron movement, and biocompatibility along with unique physiochemical properties and high surface area make graphene a suitable material for applications in health sector, environment, and energy.1–4 Graphene offers the advantage of a one-dimensional crystalline planar film. The stability of graphene film with high electron mobility of around 10,000–15,000 cm2 V−  1 s−  1 has enabled the use of graphene for advanced biosensing applications including graphene-based field effect transistor (GFET) biosensors.4 An exfoliated graphene layer, when deposited on silicon oxide, exhibits an upper limit of electron mobilities of 40,000–70,000 cm2 V−  1 s−  1.1–3,5 Thus, high electron conductivity with chemical and physical stability has made graphene a promising material for sensing applications.4,6 In a GFET, a graphene channel is placed between the two electrodes, and the electronic response is modulated with the gate contact (Fig.  3.1). The exposed surface of the graphene allows functionalization and facilitates coupling of the receptor biomolecules on the graphene channel for efficient binding of the target molecules. The GFET has been widely used for the development of biomedical devices, especially for point-of-care diagnostics, due to their low-cost manufacturing, high sensitivity, and large-scale scalability. Apart from this, GFET-based biosensing has additional advantages of fast and ­label-free detection along with high sample throughput. The GFET characteristics allow for its incorporation into an integrated miniaturized platform for the manufacture of portable devices, further making it fit for point-of-care devices. For the diagnosis of a particular disease with high sensitivity, the recognition of a target analyte with high accuracy and reproducibility is required. In this context, GFET can play an important role to Graphene Based Biomolecular Electronic Devices. https://doi.org/10.1016/B978-0-12-821541-8.00005-6 Copyright © 2023 Elsevier Inc. All rights reserved.

49

50  Chapter 3  Graphene in Field Effect Transistor-Based Biosensors

Fig. 3.1  Schematic representation of a graphene-based field effect transistor (GFET).

­ roduce an effective biosensing platform. The graphene materials p used in clinical diagnostics, especially in sensing platforms, provide a high surface area along with a Debye-Hükel screening effect, which allows the development of high performance bioelectronic devices. The FET-based biosensor (Bio-FET) with improved FET characteristics and structure modulations of the bio-receptor molecules are a special focus of researchers for the manufacturing of bioelectronic devices. We highlight the efforts undertaken to accelerate GFET development for bioelectronic applications, especially in the context of biosensors. As discussed in the previous chapter, biosensors are bioanalytical devices that recognize target bio-analytes through its bio-recognition layer which converts the biological response into detectable and measurable signals via a physio-chemical transducer. Basically, a biosensor is comprised of two main components: a bio-recognition element and a physical-chemical transducer.4–8 The biorecognition part of the biosensor recognizes and detects the bio-analytes and translates the biochemical response, such as concentration of the analytes, into an output signal whilst the transducer transduces the signal to the data device.4,5 BIO-FETs can also be used to detect and analyse the concentration of the bio-analytes and have wider applications in health, environment, and food sectors including toxicity level detection, cancer diagnostics, and food analysis. As a result, the Bio-FETs have emerged as advanced and promising biosensing devices.9–12 A Bio-FET is comprised of a semiconductor-based channel system connected to both drain and source electrodes, which assist in capturing the target analytes with high selectivity and efficient binding activity. The third electrode works as a gate for the application of the bias potential. The varied conductance of a Bio-FET channel due to the binding of target analytes is processed and read using an electrical measurement system. There are two types of FET systems, viz., n-type and p-type. In an n-type FET system, the electrons act as

Chapter 3  Graphene in Field Effect Transistor-Based Biosensors  51

primary charge carriers, whilst in a p-type FET system, the holes act as main charge carriers. In the former case, if the analytes are positively charged, the conductance is increased due to the accumulation of electrons on the surface of the sensing channels, whereas conductance is decreased if the negatively charged analytes are detected due to electron drainage from the surface of the sensing channels. In the latter case, viz., the p-type FET system, if the analytes are positively charged, conductance decreases owing to depletion in positive charge carriers, i.e. the holes at the sensing surface, whereas recognition of the negative charge carrier increases conductance due to accumulation of charge carriers (holes). The advanced field of nanotechnology allows for the integration of nanomaterials on the sensing elements of a biosensors, which could lead towards breakthrough applications using nanotransducers. The next section discusses the fabrication and application of Bio-FETs.

3.2  Graphene Bio-FET A Bio-FET is an FET wherein dielectric material is gated due to the changes in the surface potential with the binding of the charged biological molecules. The electrostatic interactions between the biomolecules and dielectric substrate of the FET gate alter the charge distribution of the semiconductor material present underneath. Herein, conductance of the FET channel changes due to these interactions, which leads to the detection of bio-analytes.7,13 There are two components in a Bio-FET: a bio-recognition component and an FET. Hence, the Bio-FET is an ion-sensitive FET (ISFET) that can be categorized as a metal oxide semiconductor FET (MOSFET); the major difference is that an ion-sensitive membrane has taken the place of a metal gate along with the electrolyte solution and reference electrode.7,13–15 The basic principle of all graphene-based biosensing devices is the alteration of the graphene’s electrical conductivity due to the binding or adsorption of biological entities on the graphene surface. Actually, the interactions and binding of the biomolecular species disturb the electron free flow in the graphene leading to a change in graphene conductance. As a result, the real-time monitoring of the analytes can possibly be conducted using a graphene-based conductive channel without using any labels. Furthermore, the graphene can be used as a gate electrode wherein binding of biomolecular species results in modulations of the FET due to electrostatic interactions and charge variations near the graphene surface (Fig. 3.2). Bio-FETs utilize nano-electronic materials such as carbon nanotubes (CNTs), silicon nanowires (SiNWs), and graphene for the development of desired sensors. This section focuses on low-cost, high-performance, reliable and scalable, GFET for biosensing applications. We describe

52  Chapter 3  Graphene in Field Effect Transistor-Based Biosensors

Fig. 3.2  Schematic representation of GFET-based DNA biosensing. Free electron flow takes place in the absence of a biomolecular entity on graphene surface, (a) whilst electron flow is perturbed when DNA binds on the graphene (b). Current output changes with a change in conductivity of the graphene due to biomolecular interactions on its surface as shown in (c) and (d).

the developments of GFET-based biosensor wherein the aim is to combine the existing concepts of biosensors based on ISFET and chemically modified FET (CHEMFET)15 and transfer it onto a graphene-based BioFET. Generally, graphene is used as a channel material and an extended gate for analyte detection whilst silicon is used as a substrate material. Graphene is known to exhibit a semiconductive nature with tuneable electrical conductivity. It is a zero-band gap semiconductor or semi-metal and could potentially be compared with and possibly substitute for conventionally used silicon semiconducting material.16 There are three basic processing steps involved when using graphene in a biosensing device, viz., (i) preparation of suitable substrate, (ii) selection of the type of graphene material, and (iii) fabrication of a graphene interactive surface through bio-functionalization (Fig. 3.3).

Substrate preparation The type of material used for deposition of the graphene layer significantly affects the surface characteristics of the graphene material.17 Hu et al. have shown that the electron mobilities vary in the graphene material depending on the selection of the substrate. A decrease in the electron mobilities has been observed in the order of SiO2 > Si3N4 > HfO2 > Al2O3 > TEOS-oxide.18 Herein, it was found that the substrate also influenced the graphene morphology, scattering of the charge carriers and doping in graphene. Furthermore, it has

Chapter 3  Graphene in Field Effect Transistor-Based Biosensors  53

Fig. 3.3  Graphene was deposited on Cu foil (A) by CVD method; subsequently, an ultrathin layer of poly(methyl methacrylate) (PMMA) was placed on graphene (B) to assist graphene transfer on the Si substrate. Cu foil was etched, and graphene was transferred onto the Si substrate (C). After its transfer, graphene was functionalized and bio-conjugated with desired biomolecules, e.g. antibodies (D).

been found that hexagonal boron nitride (h-BN) can perhaps act as a promising intermediate layer because it is atomically flat and deprived of charge traps as well as dangling bonds. However, h-BN, in the form of a single crystalline, can not be created over large areas, which limits their use on a mass scale. However, graphene with a high electron carrier mobility of up to 40,000 cm2 V−  1 s−  117 can be relatively generated on the large areas using a substrate of silicon. Silicon is the most widely used semiconducting material in the electronic industry. However, initially it was observed that a graphene layer deposited on a substrate of silicon showed inhomogeneous charge distribution with localized charge variations around ∼  20 nm along its length.19,20 The highest electron mobility of the graphene surface whilst deposited on the silicon substrate has been reported to be 10,000 cm2 V−  1 s−  1.18 Furthermore, the doping of the intercalated water molecules on the graphene surface could be prevented when using silicon dioxide modified with octadecyltrichlorosilane21 as the lifting object with graphene deposited on the substrate of silicon dioxide. Polymers can also be used as flexible substrates as they prevent variations and inhomogeneities in charge distribution.22 In this context, poly(methyl methacrylate) (PMMA)23 and polystyrene24 are the polymers that can be utilized as substrate materials. However, they also significantly affect graphene doping.

54  Chapter 3  Graphene in Field Effect Transistor-Based Biosensors

Graphene selection Amongst the various available types of graphene-based materials, graphene is selected depending on the type of application. For example, if the intrinsic and inherent property is to be analysed, then exfoliated graphene layers having high quality structural properties and high electronic mobilities can be used.24,25 For the fabrication of a biosensor, chemically modified graphene having a functionalized surface is preferred, so that the receptors can be easily mobilized for the target analysis, even with reduced electronic sensitivity. Chemical vapour deposition (CVD) is the most widely used method for the synthesis of graphene for biosensing applications. A chemical method to produce exfoliated graphene and reduced graphene oxide (rGO) can also be utilized for biosensor applications. It should be noted that 38% of patents cover methods relating to CVD techniques. The remaining 39% relate to exfoliation methods, and 23% pertain to pyrolysis and lithography, etc.26

Exfoliation and cleavage The method of exfoliation and cleavage for the synthesis of graphene includes a combination of multiple techniques and methods such as lithographic patterning, which has been used to produce highly oriented pyrolytic graphite (HOPG) along with the technique of oxygen plasma etching to prepare pillars. A thin lamellae can then be generated using adhesive tape or by manual rubbing. The leftover portions of few or mono-layered graphene can then be transferred by pressing the silicon surface against the graphene layers. Chemical intercalation is another example that can be used for graphene synthesis. It basically involves inclusion or insertion of a charged species (ion) or a molecule inside the compound having a multiple-layered structure in a reversible manner.27 Under suitable conditions of polar solvents, the layered structure of the graphene material can be efficiently separated. The solution-based method does not necessarily generate an individual defect-free isolated graphene layer. Further processing is required using an appropriate solvent28 or thermal method of heat shock and ultrasonication.29These methods can be used to generate small flakes of graphene material dispersed in solution with low yield and hence cannot be commercialized.

Chemically prepared graphene Mono-layered graphene can be produced in large quantities in the form of graphene oxide (GO) in a cost-effective manner and can be easily transferred onto various substrates. The most widely used chemical method for production of GO is Hummers’ method. In this

Chapter 3  Graphene in Field Effect Transistor-Based Biosensors  55

method, graphite is oxidized to GO by boiling in sulphuric acid and potassium permanganate. Moreover, GO is electrostatically repulsive in nature due to the presence of a negative charge on the surface and is highly hydrophilic. As a result, it is easily separated and exfoliated in a water solvent upon ultrasonication, comprising of mainly stable and dispersive mono-layered sheets.30 The GO-layered structure has a thickness of ~  0.34 nm formed due to sp3 hybridized carbon atoms that are arranged one above another with the presence of covalently bound oxygen atoms. GO sheets have various functional groups including hydroxyl and epoxy groups that are located on the basal plane whilst carbonyl and carboxyl groups are present on the edges of a sheet. The GO sheet size and its thickness vary depending on the degree of oxidation and due to undulation of the GO sheet caused by the creation of an elastic strain from functional groups of hydroxyl and epoxy.31 The oxidation yields a graphene surface with multiple functional groups that result in an interactive surface suitable for the synthesis of Bio-FET devices. The functional biological molecules can be easily attached and can efficiently detect the target analytes of DNA and proteins. Mohanty and Berry et al. first reported the use of GO to produce a graphene-based Bio-FET.32 There are certain disadvantages that mainly involve the resistance caused by the presence of oxygen molecules resulting in a manifold decrease of electrical conductivity. Also, the defects created in the lattice during the process of chemical oxidation further enhance the charge carriers resulting in overall enhancement of electronic noise.

Chemical vapour deposition CVD is preferred to produce graphene on a large scale. During this process, gases are used to form a thin film by reacting on the active surfaces with catalytic characteristics. Normally, a graphene film having a thickness of a single or few layers can be formed on a metallic surface such as cobalt,33 nickel, and copper34 and carbon gases of acetylene, methane, etc. At a very high temperature, the gases diffuse and are incorporated into these metallic surfaces. Yet at a lower temperature, graphene starts to form with the precipitation of the carbon gases. Furthermore, the rate of lowering the temperature along with the concentration and type of the carbon gases are used to control the layers of the graphene. The number of the graphene layers formed has been found to be dependent on these factors. With the formation of the graphene layers on the metallic substrate, the metallic surface can be removed by etching away the substrate with chemical processing methods. Once the underlying substrate is removed, graphene can then be easily transferred to an appropriate substrate. Subsequently, additional processing, e.g. electrical connections, can be made by i­nsertion of

56  Chapter 3  Graphene in Field Effect Transistor-Based Biosensors

metal electrodes. A more typical example includes the growth of methane gas at a temperature of 800–1000°C and atmospheric pressure of the mtorr.35 Moreover, a graphene layer with a single crystal domain can be fabricated by regulating the surface oxygen as previously reported with a centimetre-scale crystal domain.36 The number of the defects arising due to a CVD-grown graphene layer can be reduced by regulating the procedure. A multi-layered structure is obtained on the graphene surface grown by CVD with multiple weak points, specifically at grain boundaries; however, they have been found to minimally affect the performance of the synthesized material. In this context, Samsung produced a mono-layer graphene with wafer scale growth having a single crystal domain using the surface of hydrogen-terminated germanium.37 Herein, the germanium substrate can be used repeatedly for the growth of graphene due to its recyclable nature. The charge mobility of 10,620 cm2 V−  1 s−  1 has been reported for the carriers, in the case of backgated FETs, whilst using the surface of Si/SiO2.

3.2.1  Placement of graphene on suitable substrates Graphene and its oxidized derivatives have been found to be fragile by nature. Therefore, for its use as a transducer, graphene should be placed at an appropriate substrate that can provide the support and electrical contact to tune the sensitivity of the graphene material.

Exfoliated graphene Isolation of a single layer of graphene by the mechanical exfoliation method involves the repeated lifting of the graphene layer using adhesive tape. The single-layered graphene can be attained by lifting the last layer of graphene on the surface of the silicon chip. The spatial positioning of the mono-layered graphene film has been found to be difficult to attain, which results in random placement of the graphene layer. The electrical contacts can be made by e-beam lithography. However, the procedure does not seem to be suitable for mass production. Moreover, it is difficult to achieve an array of sensors using either mono or few layered graphene, and thus the process cannot be used for large-scale applications. However, the pristine graphene thus obtained could be easily observed through the microscope and can be used for laboratory purposes.

Reduced graphene oxide The oxidized derivatives of graphene, viz., GO are hydrophilic, and a colloidal suspension can thus be formed. The pristine graphene

Chapter 3  Graphene in Field Effect Transistor-Based Biosensors  57

g­ enerated by the exfoliation method cannot yield a large continuous film. However, GO can be used to form a thin film using the techniques of spin coating,38 dip coating,39 spray deposition,40 inkjet printing,41 or vacuum filtration.42 Different methods of deposition decide the thickness of the film thus generated. Nevertheless, the deposited GO film should have thickness of about 4 nm with the deposition of only a few layers without any pinholes in the fabricated film.

3.2.2  Fabrication of FET sensors After the fabrication and subsequent deposition of graphene at an appropriate surface, some standard photolithographic technique is required to devise the sensor. The electrical contacts can be made by depositing the metal on the graphene surface.43–45 Furthermore, methods like O2 plasma can be used to generate the patterns on the sheets of the graphene to create the individual FET.46 The surface of the electrode should be kept separated using dielectric substances44 and polymers46 that could act as a protective layer and perturb the aqueous solution interactions so that electrolysis can be prevented. Lithographic patterning, which is commonly used to fabricate FET devices, has the disadvantage of containing residual photoresist. Generally, this photoresist residue encompasses aromatic resins, which strongly interact with the surface of the graphene layer via π-π stacking.47 A polymer like PMMA can be deposited temporarily between the photoresist and graphene to reduce graphene stacking over the surface of residual photoresist, though it has been found that the PMMA also tends to produce the residual contamination. Inkjet printing has been used for the mass scale production of sensors as the technique provides a rapid and cost-effective means of producing FETs. The exfoliated graphene can be used to prepare the graphene ink for inkjet printing.41 More recently, inkjet printing has been preferred over general manufacturing methods to mask as well as deposit conductive channels and pathways because of the fast and cost-effective procedure involved.48 The CVD technique has been utilized to deposit graphene on thin patterned foil. In this method, the characteristics of the graphene can be translated on a random substrate. Electrical contact can be made through the inkjet printing of the silver nanoparticles followed by sintering at 180°C to obtain improved conductivity. Furthermore, the graphenebased FETs exhibit carrier mobilities of about 3300 cm2 V−  1 s−  1.

Non-covalent and covalent functionalization After designing and fabrication of the platform, the sensor needs to be modified by surface functionalization to bind with specific target entities. Bio-FET is an off-shoot of ISFET technology, which involves

58  Chapter 3  Graphene in Field Effect Transistor-Based Biosensors

altering the electrostatic field of the FET surface due to the electrostatic interactions of the charges’. This results in a change of the current. Further, this change in the current, measured through the transistor, gives the signal for the detection of the target analyte. The main issue regarding the employment of the pristine graphene as the transducer is its inertness, which results in inefficient binding. Therefore, functionalization is required for the efficient binding of the specific biomolecule to form an effective bio-­recognition layer. Moreover, the employed strategy should maintain the characteristic properties of the graphene whilst functionalizing the surface, thus balancing the electronic and chemical properties of the graphene to obtain enhanced sensor performance.

3.2.3  Non-covalent functionalization The chemical functionalization method involves covalent binding of the functional groups that disrupt the sp2 structure resulting change in the electrical properties of the graphene molecules. Thus, the non-covalent method of functionalization has also been employed for minimum disruption of graphene electronic behaviour. In the non-­ covalent functionalization method, the sensing of biomolecule (e.g. protein) is attached to some aromatic biomolecules having chemically active groups like 1-pyrenebutatonic acid, which could be easily attached to the graphene surface due to van der Waals force arising due to π-π aromatic interactions (Fig. 3.4).49,50 It has been found that ­single-stranded DNA can be attached to the graphene surface via

Fig. 3.4  Schematic illustration of non-covalent functionalization of graphene. Reprinted by permission from Mao, H. Y.; Lu, Y. H.; Lin, J. D.; Zhong, S.; Wee, A. T. S.; Chen, W., Manipulating the Electronic and Chemical Properties of Graphene Via Molecular Functionalization. Prog. Surf. Sci. 2013, 88 (2), 132–159. Copyright Elsevier Ltd., 2020.

Chapter 3  Graphene in Field Effect Transistor-Based Biosensors  59

sugar phosphate-containing bases, resulting in π-π stacking.51 Here, the chances of false positives exist due to non-specific binding. Another type of non-covalent interaction that can be utilized into Bio-FETs is to adsorb the nanoparticles and use them to anchor the sensor biomolecules.52 For example, the nanoparticles of gold can be adsorbed over the surface of the graphene and subsequently functionalized using thiol chemistry. It may be noted that gold nanoparticles can be reportedly aligned over the surface of graphene via π-π stacking for the fabrication of FET wherein graphene has been configured vertically to obtain an enhanced surface area.53 The method employed is the direct growth of graphene sheets on the surface of a sensor electrode in the vertical direction using the technique of CVD enhanced by direct current (DC) plasma. On the vertically aligned graphene sheets, gold nanoparticles bio-conjugated with antibodies were adhered. The immunological interactions of antibodies and antigens upon the bio-recognition resulted in a change of charge and conductivity at the FET gate. The observed change was measured and detected with high sensitivity with a detection limit of ~  2 ng/mL (13 pM). Dip-pen nanolithography can also be employed to fabricate membranes of phospholipids having different functional groups on the surface of graphene in a highly controlled manner. In this method, a graphene bilayer can be utilized for the fabrication of the device. This strategy takes care of the problems associated with bio-­ functionalization of the invasive surface compromising the conductivity of pristine graphene.22 In this method, the upper-most layer of graphene has been functionalized to bind with sensing molecules whilst the lower layers of the graphene sheet remain undisturbed and could be functionalized to act as a transduction layer. However, the alteration of the charge with the bio-electrochemical reactions in the upper graphene layers results in charge puddles, which cause measurable change in conductivity of the lower graphene layers. The strategy has been found to be highly efficient and effective to evolve a scheme related to unified chemical functionalization useful for various types of substrates including flexible and rigid.54 However, attachment that occurs through non-covalent interactions has led towards the possibility of desorption and dissociation of the probe biomolecules that are exposed to the graphene layer for the further interactions and non-specific binding of the biomolecules causing false positive results.22

Covalent attachment The performance of a biosensor having GO as a gate material has been reported to be improved over a wide range of pH and temperature by adhering sensing molecules on the electrode surface using

60  Chapter 3  Graphene in Field Effect Transistor-Based Biosensors

covalent crosslinking.32,44,55 GO flakes have the advantage of functional moieties of carboxyl and epoxide for the attachment of desired biomolecules. One of the effective methods for maintaining the bio-functionality of the surface is to bind ethylenediamine (EDA) to the functional groups of the epoxide prior to the chemical reduction. The amines are known to carry the chemical reduction process forward. Reduction is required to enhance the electrical conductivity of the graphene material as the process of graphene oxidation results in a manifold decrease in the graphene conductivity.44 CVD-grown graphene based on ammonia plasma at low energy was utilized to fabricate the DNA biosensor. In this approach, amine groups can be suitably used for the reduction purpose and further bio-functionalization.56 Diazonium salt mediated reaction is another example of covalent bonding based on bio-functionalization of the graphene for Bio-FETbased sensor production.57–59 For example, Kasry and colleagues60 utilized this strategy for the detection of streptavidin by binding with biotin.

Anti-biofouling As previously discussed, the principle behind the graphene-based Bio-FET system relies upon the binding of target molecules and subsequent changes in current values, which yield the FET response. However, a major challenge is to apply the biosensor for the practical applications such as real sample analysis of environmental samples of wastewater and clinical samples of saliva, blood samples, etc. This requires the use of strong anti-biofouling measures to minimize non-specific binding against a cadre of analytes including proteins, aptamers, DNA, and other biological materials.61 Recently, it has been reported that DNA molecules of a single-stranded type could be easily adsorbed on the surface of GO even though both DNA and GO are negatively charged biomolecules.62 The electrostatic repulsion can be overcome by allowing the adsorption of DNA on the GO surface in the buffer solution having a high concentration of salt. Herein, the force of attraction is mainly due to π-π bonding in addition to other types of forces including van der Waals force of attraction, hydrophobic interaction, and hydrogen bonding between DNA and GO.63 However, except for covalent bonding, other types of forces of attraction are reversible resulting in DNA desorption. For example, the adhered DNA molecules of a single-stranded type can be detached with the formation of duplex with the hybridization of its complimentary DNA strand. And relative to double-stranded DNA, single-stranded DNA can strongly adhere to GO biomolecules.64 Whilst detecting the whole cell, care should be taken to perform interference studies to minimize false results.

Chapter 3  Graphene in Field Effect Transistor-Based Biosensors  61

GO has been found to exhibit antimicrobial activities and has been studied extensively for detection of E. coli.65 Also, GO has been reported to disintegrate the bacterial cell by disrupting its cell wall and cell membrane. For example, in the case of dental pathogen P. gingivalis, it has been reported that GO increases the bacterial permeation, which results in leaching the intracellular contents.66 Much more progress is required to achieve a successful anti-­ biofouling strategy for the development of effective preventive measures for non-specific adhesion. Blocking agents such as bovine serum albumin (BSA) have been used for applications of biosensing protocols for inhibiting non-specific adhesion. BSA has also been used along with Tween-20 and fish gelatin to the segments of the bio-functionalized graphene surface that are not occupied.52,67 Furthermore, non-specific binding can be minimized by using a wash buffer such as sodium dodecyl sulphate (SDS) and BSA, which facilitate the removal of biomolecules that are bound non-specifically after the sample solution has been investigated.32,68,69 Even the aptamers have been found to show anti-biofouling properties. The aptamers as the capture molecules can be utilized for the bio-recognition of immunoglobulin E (IgE). Because of the negative charge present on their surface, aptamers prohibit the non-specific binding of the protein molecules.43,50

3.2.4  Some graphene-based FET biosensors There are a number of bio-recognition elements used in a biosensor, and their selection depends on the desired target of interest. DNA, antibodies, and peptides are some of the most commonly used modifying agents that provide specificity for the detection of a particular bio-analyte when immobilized on the sensor transducer. Table 3.1 depicts different graphene forms and their applications for the detection of a particular analyte.

Genomic detection Bio-FET-based DNA detection has been considered as one of the most highly selective and sensitive biosensing strategies. Over the past few decades, DNA-based biosensing using graphene Bio-FETs have been carried out. A general strategy for the designing of a Bio-FET includes the construction of drain and source electrodes, whilst the gate is generally substituted by bio-recognition elements. For example, in the case of DNA biosensing, bio-recognition elements are the DNA probes of single stranded, which are covalently or non-covalently immobilized on the graphene surface for the analysis of target DNA.52,63,67 The target DNA has complementary DNA sequences, and with the hybridization on the platform of the graphene material, the

Single-layer graphene

Single-layer graphene

Graphene nanogrid-based FET coupled with artificial neural network.

Graphene synthesized by CVD on Cu foil and transferred on SiO2/ Si wafer:source and drain electrodes (Cr/Au) were deposited by photolithography. Graphene deposited on nanoporous SiO2 by electrophoretic deposition. Interdigitated metal electrodes of Al deposited on substrate by screen printing.

Wet chemical approach

Single-layer graphene

Liquid gated GFET with: Cr and Au act as source and drain electrodes.

CVD

Single-layer graphene

Liquid gated GFET, silver paste acts as source and drain electrode. rGO-based FET

CVD synthesized graphene sheets modified in multilayered graphene foam.

Synthesis route

Graphene foam

Graphene form

3D Liquid gated GFET; Ti and Au act as drain and source electrode.

FET material

Width and spacing between two electrodes were 60 μm.

[EMIM][BF4] ionic liquid was used for absorbing the ammonia gas.

CVD deposited graphene transferred on gold surface. rGO deposited on Silicon oxide.

Liquid gating of transistor is specified by electrolytic doublelayer capacitance.

Device fabrication

Transconductance and capacitive mode used for measuring current sensitivity and the shift in the peak frequency, respectively.

Gate voltage between graphene channel and electrode supported by ionic liquid.

Dirac point obtained at 10 V of gate voltage with electron mobility of 6 cm2 V−  1 s−  1

Capacitance generated at interface of liquid channel, electrostatically controlling channel conductivity at low gate voltages. Transferred film exhibit 125% enhanced sensing performance.

Description

Table 3.1  Some graphene-based FETs.

Hep-B surface antigen

Ammonia

Immunogl­ obulin E (IgE)

DNA hybridization



Analytes

Hep-B surface antigen measured in serum with the detection limit of 0.1 fM

Detection limit and dynamic range were 8.1 ng/mL and 104, respectively. Ammonia gas detected with shift in minimum gate voltage value of −  240 mV.

Sensitivity of DNA biosensing 1 pM (10−  12 M)



Output

74

73

72

71

70

Reference

GFET, interdigitated Au electrode, rGO was deposited using wet chemical approach, electroactive polymer (PABA) was deposited electrochemically to immobilize enzyme.

Single-layer graphene

Enzymatic (acetyl­ cholinesterase (AchE)) modified rGO FET biosensor

AchE immobilized on PABA. Acetylcholine presence was detected by change in Dirac point of AchE-PABA-GFET changes.

Enzymatic hydrolysis changes local pH value affected conductivity of GFET.

Neurotran­ smitter acetylcholine (Ach)

Detection limit 2.3 μM in range of 5 to 1000 μM and sensitivity of −  26.6 ± 0.7 μA/ Ach

75

64  Chapter 3  Graphene in Field Effect Transistor-Based Biosensors

current flow is perturbed due to changes in the charge present near the graphene surface, which results in the recognition of the DNA molecules with the electronic change. For biomolecular detection of DNA, an analytical model has been used for the liquid-gated GFET. Current and voltage measured through the sensor gate of the FET has been utilized to design an analytical model. The model is based on the use of particle swarm optimization (PSO) algorithm for evaluation of DNA concentration.76 PSO has been utilized as a target to find the iterative approximate values and solutions of the complicated minimization and maximization numeric problems.77 More recently, an advanced technique of DNA detection has been used wherein nanopores present on the CVD-grown graphene sheet are employed. DNA can be detected whilst passing through the nanopores.78 In device fabrication, CVD can be used to grow graphene on the SiNx. Graphene nanoribbon of the size 60 to 100 nm wide has been created using electron beam lithography (EBL) and reactive ion etching (RIE). The approach can be used to fabricate a dual sensor using a suitable ionic strength gradient. The results obtained can be correlated with DNA translocation events that can be detected by both the ionic pore current and graphene current changes.

Biomarker detection For clinical applications, screening is required on a large scale for multiplexed samples pertaining to preclinical diseases. Dopamine, prostate-specific antigens (PSA), immunoglobulin E, and ions such as calcium and potassium can be used as biomarkers to diagnose related specific diseases. For example, the biomarker PSA, which is a protein by nature, is released in males through the prostate glands and circulates in blood. The average value of the PSA in the blood is about 4.0 ng/mL, whilst an increased value of the PSA has been found to be an indicator of prostate cancer. In certain cases, even low values of PSA have been reported to be related with the disease.79 A highly sensitive sensor based on rGO and Bio-FET has been reported for the detection of the PSA/α1antichymotrypsin (ACT) levels in the sample.80 Recently, a biodevice has been developed based on the use of graphene nanoribbons with a size of 50 nm.81 The designed biosensor having immobilized antiPSA antibodies has been reported to show the sensitivity of about 0.4 pg/ mL for the PSA antigen. Besides this, the researchers have depicted that there is a twofold difference of sensitivity between the sensors designed with suspended graphene and unsuspended graphene when used in a graphene-based FET sensor. Dopamine, which is a type of catecholamine neurotransmitter, has been found to be released in the brain. This biomarker has been

Chapter 3  Graphene in Field Effect Transistor-Based Biosensors  65

considered to play a key role in controlling our body movement. It has been reported as a biomarker for diseases related to neural degeneration such as82 Parkinson’s disease83 and schizophrenia.84 Qiyuan et al. developed a procedure for large-scale production of the sensor using rGO pattering over the 1.5 cm-long flexible surface of polyethylene terephthalate (PET).85 In this study, the dopamine level was measured to be in the range of 1–60 mM. Pharmacology assays mainly involve the tracking of cellular activities, for example, for maintaining osmotic balance using potassium (K+) and calcium (Ca2  +) ions and nerve transmission. More recently, an ionophore of valinomycin (C54H90N6O18) has been used to design a BioFET gated by electrolytes. Valinomycin has been considered a type of dodecadepsipeptide, which can be synthesized using the Streptomyces strains. The designed sensor has been reported to show higher affinity for the potassium ions as compared to the other metallic ions belonging to the alkali metals.86 Herein, valinomycin has been incorporated in an ion-selective membrane formed using the combination of sodium tetraphenyl borate, polyvinyl chloride (PVC), and bis(2-ethylhexyl)sebacate. The mixture was prepared using tetrahydrofuran as a solvent. The solution thus formed can be used to prepare a spin-coated film over the surface of the GFET gate. In this manner, a barrier can be reportedly formed by spin coating that has not permitted the passage of potassium ions through the ionophores of valinomycin. The fabricated sensor can detect potassium ions with a detection range from 10 nM to mM.

Cellular detection The identification of the pathogenic microbes and their rapid detection is a demand of time due to the spread of deadly infectious diseases such as severe acute respiratory syndrome (SARS). Only a few techniques such as real-time polymer chain reaction (PCR) are available for effective bacterial detection whilst no gold standard technique exists for clinicians. The conventionally used standard culturing techniques have been found to be insufficient for multiple bacterial identification in the case of a polymicrobial infection as compared to the technique of real-time PCR.87 It may be noted that the RT-PCR has the main drawback of high complexity with low sensitivity and selectivity, whereas the graphene-based FET biosensor has emerged as an effective technique for bacterial identification with high sensitivity and selectivity.32 The principle behind the identification of any biological entity depends on its interaction with the graphene surface, which mainly involves electrostatic interactions. Generally, a negative charge is present on the bacterium such as Bacillus cereus whilst the positive charge can be created on the graphene surface by using aminated GO sheets. The electrostatic interactions further result in the change of graphene conductivity up to 42%.

66  Chapter 3  Graphene in Field Effect Transistor-Based Biosensors

CVD-grown graphene Bio-FET has been fabricated for the detection of E. coli, and its growth has been found to be correlated with a glucose concentration at high specificity and sensitivity. Herein, the anti-E. coli antibodies were immobilized on the surface of graphene to detect E. coil. In this study, glucose has been reported to affect the bacterial concentration by enhancing its metabolic activities.69 The designed Bio-FET exhibited sensitivity of 10 cfu/mL and is very less responsive for the controls. This Bio-FET has also been found to sense variations in the glucose concentration with the change in pH arising due to release of metabolic organic acids by bacteria. In another study, Bio-FET was designed using thermally grown rGO. Further electrostatic interactions were used to bind rGO with gold electrodes modified with 2-aminoethanethiol. These GO sheets can be further separated by ultrasonication. Subsequently, reduction of the GO sheets occurs by thermal annealing at a temperature of 400°C. Eventually, anti-E. coli antibodies were immobilized on the gold nanoparticles bonded to the rGO surface with a sensitivity of 10 cfu/ mL.88 However, this procedure results in the multilayering of GO sheets. Rotavirus can also be detected using Bio-FET-based biosensors. In this study, photolithography procedure was used to generate the patterned surface on the spin-coated GO sheets to develop the desired sensors. First, the graphene sheets were stabilized on the substrate of SiO2/Si by treating them with hexamethyldisilazane, which actually enhances the hydrophobicity of the surface. When GO was deposited on the surface, it was reduced by using a gaseous mixture of hydrogen and argon for about 5 h at a temperature range of 220–900°C. This type of designed sensor has a detection limit of 103 pfu using the spiked sample of faecal material.89

3.3  Bio-FET-based label-free detection mechanism The basic principle to detect biological molecules by a Bio-FETbased electrochemical sensor is shown in Fig. 3.5.90 The response is generated from the charge σ0 present at the surface of a sensing platform. The capacitances are present on both sides of the charged surface, and there is one ground signal. The actual capacitance of the system encompasses the parallel addition of the capacitance pertaining to the FET sensor (CFET) as well as a double-layer (CDL) sensor. CFET comprises the capacitances of depletion Cb and the gate oxide COX. The change in the measured potential at the surface of the sensing platform can be estimated by studying the relationship between σ0, CFET and CDL .

Chapter 3  Graphene in Field Effect Transistor-Based Biosensors  67

Fig. 3.5  Schematic depiction of the potential diagram across a generic nanowire biosensor, as well as the capacitive divider that is seen by the biomolecules. This generic diagram applies to all structures of interest. CDL, COX, and CNW represent the capacitances due to the diffuse layer in the electrolyte, the gate dielectric, and the mobile carriers in the nanowire, respectively. The blue and red potential diagrams correspond to the prebinding and postbinding states of the sensor; that is, the blue diagram has only charged receptors at the oxide surface, whereas the red curve has both charged receptors and charged analytes. The analytes cause a potential change ΔVE at the outer surface of the gate dielectric, which we consider to be the sensor’s sensitivity. The potential change is screened, and decays with distance into the nanowire and electrolyte regions. Adapted from Shoorideh, K.; Chui, C. O., On the Origin of Enhanced Sensitivity in Nanoscale FETBased Biosensors. Proc. Natl. Acad. Sci. 2014, 111 (14), 5111–5116.

In the next section, we are discussing the detection mechanisms for FET sensors such as direct and indirect biosensing.

3.3.1  Indirect detection of macromolecules The use of suitable labels and appropriate sensitive surfaces allowing electrochemical reactions have been proven to be an effective strategy in comparison to approaches based on intrinsic charges. Additionally, the former strategy also reduces the steps involved in screening desired biomolecules. Generally, the enzymes used as

68  Chapter 3  Graphene in Field Effect Transistor-Based Biosensors

l­ abels have been found to catalyse the reactions occurring at the electrochemical sensitive platforms. For example, in the electrochemical detection of the DNA, the working electrode can be of a gold material modified with ferrocenyl-alkanethiol that has been reported to show a wider dynamic range of detection. The labelling of ferrocenyl- alkanethiol has also been shown to have higher long-term drift as compared to the direct detection of the bio-analyte.91 Furthermore, another indirect approach of labelling and detection could be through bio-­ conjugation of enzymatic bodies to the secondary antibodies, which could specifically detect the desired antigen.91 Herein, the conjugated enzymes act as both label and participate in the redox reactions occurring at the sensing surface through electron transfer. However, the major challenge associated with highly specific and efficient sensing of the indirect detection method involves the complicated procedure of sample preparation and sophisticated measurement devices. Bio-recognition layer in an FET-based biosensor can be prepared directly by immobilizing the enzymes on an FET gate. Immobilization of the enzymes is possible through various binding techniques involving physical adsorption, chemical crosslinking, mixed physiochemical methods, and entrapping the enzymes inside the complex framework of the polymer chains.7 The first such enzymatic ISFET was developed by immobilizing penicillinase on the gate membrane of the FET biosensor. The immobilized enzyme of penicillinase accelerated the hydrolysis of penicillin if present in the sample into penicilloic acid. Then the generated protons alter pH of the gate, which can be measured to detect the analyte. An organic polymeric membrane that can allow efficient transfer of the electrons can be used as an alternative to that of pH-based enzymatic sensing. The use of an organic polymeric membrane permits direct detection of the target analyte by enzymatic reactions or only electrochemical reactions without using any redox mediators. Such systems facilitate towards the fabrication of independent autonomous biosensing devices.92,93

3.3.2  Direct detection of macromolecules Detection of oligonucleotides As compared to a protein macromolecule, the size of an oligonucleotide is much smaller. As a result, relatively, the Debye screening effect has been found to be less influencing for the detection of the oligonucleotides. Hence, the label-free detection technique of molecular diagnostics has been used for the past many years.94 For the construction of a DNA-FET, a specifically designed oligonucleotide probe can be immobilized on the transistor gate. Then the hybridization between the probe and complementary target DNA leads to the sensitive detection

Chapter 3  Graphene in Field Effect Transistor-Based Biosensors  69

of the desired bio-analyte. Because of the negative charge on the DNA molecular backbone, the hybridization causes a shift in the generated potential at the sensing transistor gate. Furthermore, a 0.34 nm length of DNA base provides sufficient space for binding of the probe resulting in hybridization. The charge exists even after hybridizing with target DNA that can be sensed by the gate surface with optimal concentration of the salt solution at high hybridization efficiency.95 The real sample has many molecules that can be taken as targets for detection. Therefore, for a practical application, a sensor is required that could efficiently sense multiple targets in a complex sample. In this context, the sensor using graphene-based FET has been found appropriate for the multiplexed type sensing. Herein, the sensing platform can be utilized to detect multiple targets with a single reaction conducted on the sensing element. The multiple targets can be detected by integrating multiple transistors arranged in an array wherein different DNA probes are immobilized. By using a lower concentration of salt solution, the electrostatic repulsion can be minimized between the target molecule and probe that could assist in the label-free detection.96 The immobilized probes on different transistors have been found to facilitate the transduction of the signal generated due to hybridization.97 However, the theoretical concepts have been found to be insufficient to explain the results attained via label-free detection. Moreover, the variation has been observed in the measured values of the gate potential after the DNA hybridization and the analysed empirical results. The basic principle behind such measurements needs to be established for effective l­abel-free detection.94,98

3.3.3  Detection of proteins The label-free and direct detection of the immunological reactions of antibodies-antigens has gained significant attention over the last decade. Generally, proteins carry some charge at the molecular surface at the wider range of pH levels. This is perhaps due to the presence of charges on the surface that may allow for the surface-charge sensing. However, the possibility of sensing by this method has not been fully established. The double-layer screening has mainly been found to be responsible for the failure of the previously mentioned approach.99 However, cases have been reported that have shown that label-free detection can be achieved even in cases where immunological complex formed over the longer distances than double layer.94 This could be due to the Donnan effect. It has been postulated that proteins, which are largely charged molecules, form a membrane at the surface of electrode. Besides

70  Chapter 3  Graphene in Field Effect Transistor-Based Biosensors

this, ions can easily pass through the membrane because of their smaller size and shuffling between the protein membrane layer and solution. Furthermore, the charge present on the bio-analyte creates a difference in the ion concentration at the interface of the solution and the protein membrane. This change of interfacial ion concentration leads to a change in the interfacial potential called the Donnan potential, which can be used to detect the target. In addition to this, pH values also shift due to the Donnan effect. Consequently, response has been generated due to both change in pH as well as Donnan potential. It has also been reported that a non-­Nernstian surface, which does not replenish the charges created due to binding of proteins, can be used for the target analysis by this approach.99

3.4  Challenges of using graphene in fabrication of FET-based sensing devices Graphene-based Bio-FET devices presently represent simple and highly sensitive cost-effective devices. However, there are certain problems associated with the mass production and commercialization of graphene-based biosensing devices including the production of the desired graphene material. The major challenges are the contamination of metallic and carbonaceous impurities during the processing and production of graphenebased materials. Difficulties also exist in the transfer of a fabricated graphene layer onto the surface of a substrate. Moreover, the uniform surface functionalization of graphene for efficient binding is required, which is also difficult to attain. Lacking of efficient anti-biofouling procedures and competent biochemical functionalization methods are some other major hurdles for sensor manufacturing. The practical application of biosensing devices mainly employ the sensing of real samples pertaining to environmental and clinical samples including the spiked buffers. The real samples of blood, serum, wastewater, and samples of tissue biopsies can be characterized. Further, carrier mobility of the graphene may be affected with the interactions of biological molecules. Efforts should be made for the configuration and designing of the biosensor. Efficiency of the graphene-based biosensor further depends on the selection of the substrate, chemical functionalization of the graphene surface, and orientation of the graphene layers. Discovery of new applications related to graphene as a material may indicate that graphene-based Bio-FETs perhaps hold promising potential to generate label-free and highly sensitive biosensing devices.

Chapter 3  Graphene in Field Effect Transistor-Based Biosensors  71

Over the past few decades, multiple attempts have been made for commercializing miniaturized and multiplexed biosensing devices. The production of sensors at a mass level mainly has been hindered due to the requirement of wet conditions that can perhaps be minimized via encapsulation. Many attempts have been made in encapsulation electronics, however, an aqueous storage medium is required, which is difficult to maintain during mass production.100 Furthermore, requirement of multiple sensors increases the overall cost of the device. Presence of multiple biological entities in real samples further increases the complexity for sensitive detection.101 Prior to detection of desired analytes using real samples, pretreatments at various level of processing are required. The variations in sample parameters such as of pH, temperature, and solvent ionic strength deviate the sensing results. Only a few sensors are available that can potentially detect the desired analytes directly in the patient samples such as amperometric sensor for the detection of blood glucose. Despite these challenges, point-of-care diagnostics is in the process of being commercialized soon. For example, a sepsis test is being commercially conducted by the DNAe using ISFET.102 Similarly, QuantuMDx has recently launched the Q-POCTM device, which is a portable pointof-care testing molecular diagnostic kit to rapidly analyse DNA and RNA in minutes. This device has recently been utilized for the diagnosis of SARS-CoV-2.103 Herein, the hybridization and detection of the target DNA can be conducted via fluorescence technology. Besides, another commercial body InSilixa has developed a sensing platform using the CMOS biochip to perform molecular diagnostic tests. The new facile detection strategies using FET-based biosensors have also been utilized for the detection of spike antigen proteins of SARS-CoV-2. The introduction of graphene in sensing platforms has been found to result in increased efficiency of the biosensing platform. The analytes can be efficiently detected even in a small sample size in an FET-based biosensor owning to being ultrasensitive with immediate response and low noise.104

Protocols for GFET device fabrications 1. Ameri et  al.70 reported the design the GFET using ionic liquid. Herein, first, graphene was deposited on Cu foam by CVD method, and then the assembly was immersed in FeCl3 solution to etch away the Cu foam. Titanium and gold metal electrodes deposited by shadow mask acted as drain and source, respectively. After fabrication of these electrodes and channel, ionic liquid was added on both the top of graphene channel and metal electrodes. Consequently, the ionic liquid gate was ready after removing the shadow masks from the electrodes.

72  Chapter 3  Graphene in Field Effect Transistor-Based Biosensors

2. Chen et  al.71 used ionic liquid-based FET for DNA biosensing where CVD-grown graphene film was transferred to a gold surface and compared with annealed PMMA-graphene. 3. Hasegawa et  al.72 configured rGO-FET based on the use of a ­bottom-contact electrode where drain and source electrodes were deposited on silicon oxide, which was thermally grown on a silicon substrate. 4. Inaba et al.73 reported on graphene synthesized by CVD on Cu foil and transferred to SiO2/Si wafer, whereas Cr/Au electrodes patterned by photolithography were used as source/drain electrodes. The length and width of graphene channel was 20 and 50 μm. Both channel and electrodes were covered by ionic liquid. Herein, ionic liquid acts as gas absorption unit and graphene acts as a sensing material. The sensitivity and gas absorbability largely depend on the type of cations and anions present in liquid, thus the performance of these types of GFETs depend on the selection of the ionic liquid. 5. Basu et al.74 have fabricated graphene nanogrid-based FET. Initially, nanoporous SiO2 substrate was synthesized by thermal oxidation of Si wafer at the temperature of 900°C. After that, graphene was deposited using electrophoretic deposition on nanoporous SiO2. Interdigited metal electrodes were synthesized on the graphenecoated nanoporous SiO2 using screen printing with aluminium, where the electrode width and gap was 60 μm. The measurement of Hep-B surface antigen in serum was estimated by transconductance and capacitance to evaluate current sensitivity and peak frequency shift, respectively. Finally, architecture of an artificial neural network was used to process the previously discussed parameters to determine the analyte of Hep-B surface antigen with a detection limit of 0.1 fM serum. 6. Fenoy et al. have postulated that the interdigitated electrodes were synthesized using Au material on glass surface; subsequently, the GFET was deposited on interdigitated electrodes by wet chemical approach. Furthermore, acetylcholinesterase (AchE) was immobilized to detect the presence of neurotransmitter acetylcholine (Ach). To immobilize the enzyme, the electroactive polymer layer poly(3-aminobenzylamine-co-aniline) (PABA) containing amino moiety was deposited on the graphene by voltammetric synthesis method. Herein, the Dirac point of the AchE-PABA-GFET changes towards more negative values with the change in pH caused by the enzyme-mediated hydrolysis occurring on the graphene. This resulted in a change of GFET conductivity. Thus, a signal transduction mechanism was used to constitute the transistor to detect Ach with a detection limit of 2.3 μM in the range of 5 to 1000 μM and sensitivity of −  26.6 ± 0.7 μA/Ach.

Chapter 3  Graphene in Field Effect Transistor-Based Biosensors  73

References 1. Novoselov, K. S.; Geim, A. K.; Morozov, S. V.; Jiang, D.; Zhang, Y.; Dubonos, S. V.; Grigorieva, I. V.; Firsov, A. A. Electric Field Effect in Atomically Thin Carbon Films. Science 2004, 306 (5696), 666–669. 2. Novoselov, K. S.; Geim, A. K.; Morozov, S. V.; Jiang, D.; Katsnelson, M. I.; Grigorieva, I.; Dubonos, S.; Firsov, A. Two-Dimensional Gas of Massless Dirac Fermions in Graphene. Nature 2005, 438 (7065), 197–200. 3. Novoselov, K. S.; Jiang, D.; Schedin, F.; Booth, T.; Khotkevich, V.; Morozov, S.; Geim, A. K. Two-Dimensional Atomic Crystals. Proc. Natl. Acad. Sci. 2005, 102 (30), 10451–10453. 4. Wisitsoraat, A.; Tuantranont, A. Graphene-Based Chemical and Biosensors. In Applications of Nanomaterials in Sensors and Diagnostics; Springer, 2013; pp. 103–141. 5. Meyer, J. C.; Geim, A. K.; Katsnelson, M. I.; Novoselov, K. S.; Booth, T. J.; Roth, S. The Structure of Suspended Graphene Sheets. Nature 2007, 446 (7131), 60–63. 6. Dreyer, D. R.; Ruoff, R. S.; Bielawski, C. W. From Conception to Realization: an Historial Account of Graphene and some Perspectives for its Future. Angew. Chem. Int. Ed. 2010, 49 (49), 9336–9344. 7. Schöning, M. J.; Poghossian, A. Recent Advances in Biologically Sensitive FieldEffect Transistors (Bio-FETs). Analyst 2002, 127 (9), 1137–1151. 8. Burnett, T. L.; Yakimova, R.; Kazakova, O. Identification of Epitaxial Graphene Domains and Adsorbed Species in Ambient Conditions Using Quantified Topography Measurements. J. Appl. Phys. 2012, 112 (5), 054308. 9. Ying, H.; Fengying, S.; Feng, H.; Yanhong, W.; Xianru, X.; Xiaolei, T. Diagnostic Value of Quantification of Circulating Free DNA for Gall Bladder cancer Using a Chemiluminescence DNA Biosensor System Based on DNA G-Quadruplex/ Hemin Enzyme. Transl. Oncol. 2020, 14 (1), 100928. 10. Yang, Y.; Wang, Y.-Z.; Fang, Z.; Yu, Y.-Y.; Yong, Y.-C. Bioelectrochemical Biosensor for Water Toxicity Detection: Generation of Dual Signals for Electrochemical Assay Confirmation. Anal. Bioanal. Chem. 2018, 410 (4), 1231–1236. 11. O’Kennedy, R. Rapid Antibody-Based Technologies in Food Analysis, 15; Royal Society of Chemistry, 2019. 12. Saylan, Y.; Erdem, Ö.; Ünal, S.; Denizli, A. An Alternative Medical Diagnosis Method: Biosensors for Virus Detection. Biosensors 2019, 9 (2), 65. 13. Hossain, N. M.; Ashenafi, E.; Hossen, M.; Es-Sakhi, A.; Chowdhury, M. H. Multilayer Graphene Nanoribbon Based Bio-FET Sensor Design. In 2017 IEEE 60th International Midwest Symposium on Circuits and Systems (MWSCAS); IEEE, 2017; pp. 1402–1405. 14. Fakih, I.; Durnan, O.; Mahvash, F.; Napal, I.; Centeno, A.; Zurutuza, A.; Yargeau, V.; Szkopek, T. Selective Ion Sensing with High Resolution Large Area Graphene Field Effect Transistor Arrays. Nat. Commun. 2020, 11 (1), 1–12. 15. Kaisti, M. Detection Principles of Biological and Chemical FET Sensors. Biosens. Bioelectron. 2017, 98, 437–448. 16. Singh, V.; Joung, D.; Zhai, L.; Das, S.; Khondaker, S. I.; Seal, S. Graphene Based Materials: Past, Present and Future. Prog. Mater Sci. 2011, 56 (8), 1178–1271. 17. Dean, C. R.; Young, A. F.; Meric, I.; Lee, C.; Wang, L.; Sorgenfrei, S.; Watanabe, K.; Taniguchi, T.; Kim, P.; Shepard, K. L. Boron Nitride Substrates for High-Quality Graphene Electronics. Nat. Nanotechnol. 2010, 5 (10), 722–726. 18. Hu, Z.; Prasad Sinha, D.; Ung Lee, J.; Liehr, M. Substrate Dielectric Effects on Graphene Field Effect Transistors. J. Appl. Phys. 2014, 115 (19), 194507. 19. Martin, J.; Akerman, N.; Ulbricht, G.; Lohmann, T.; Smet, J. V.; Von Klitzing, K.; Yacoby, A. Observation of electron–Hole Puddles in Graphene Using a Scanning Single-electron Transistor. Nat. Phys. 2008, 4 (2), 144–148.

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20. Zhang, Y.; Brar, V. W.; Girit, C.; Zettl, A.; Crommie, M. F. Origin of Spatial Charge Inhomogeneity in Graphene. Nat. Phys. 2009, 5 (10), 722–726. 21. Chen, S.-Y.; Ho, P.-H.; Shiue, R.-J.; Chen, C.-W.; Wang, W.-H. Transport/ Magnetotransport of High-Performance Graphene Transistors on Organic Molecule-Functionalized Substrates. Nano Lett. 2012, 12 (2), 964–969. 22. Park, S. J.; Kwon, O. S.; Lee, S. H.; Song, H. S.; Park, T. H.; Jang, J. Ultrasensitive Flexible Graphene Based Field-Effect Transistor (FET)-Type Bioelectronic Nose. Nano Lett. 2012, 12 (10), 5082–5090. 23. Shin, D.-W.; Lee, H. M.; Yu, S. M.; Lim, K.-S.; Jung, J. H.; Kim, M.-K.; Kim, S.-W.; Han, J.-H.; Ruoff, R. S.; Yoo, J.-B. A Facile Route to Recover Intrinsic Graphene over Large Scale. ACS Nano 2012, 6 (9), 7781–7788. 24. Lee, W.-K.; Robinson, J. T.; Gunlycke, D.; Stine, R. R.; Tamanaha, C. R.; King, W. P.; Sheehan, P. E. Chemically Isolated Graphene Nanoribbons Reversibly Formed in Fluorographene Using Polymer Nanowire Masks. Nano Lett. 2011, 11 (12), 5461–5464. 25. Geim, A. K.; Novoselov, K. S. The Rise of Graphene. In Nanoscience and Technology: A Collection of Reviews from Nature Journals; World Scientific, 2010; pp. 11–19. 26. Sivudu, K. S.; Mahajan, Y. Mass Production of High Quality Graphene: An Analysis of Worldwide Patents; Nanowerk, 2012, June 28. 27. Kovtyukhova, N. I.; Wang, Y.; Berkdemir, A.; Cruz-Silva, R.; Terrones, M.; Crespi, V. H.; Mallouk, T. E. Non-oxidative Intercalation and Exfoliation of Graphite by Brønsted Acids. Nat. Chem. 2014, 6 (11), 957–963. 28. Nethravathi, C.; Rajamathi, M. Chemically Modified Graphene Sheets Produced by the Solvothermal Reduction of Colloidal Dispersions of Graphite Oxide. Carbon 2008, 46 (14), 1994–1998. 29. Jia, J.; Kan, C.-M.; Lin, X.; Shen, X.; Kim, J.-K. Effects of Processing and Material Parameters on Synthesis of Mono-Layer Ultralarge Graphene Oxide Sheets. Carbon 2014, 77, 244–254. 30. Li, D.; Müller, M. B.; Gilje, S.; Kaner, R. B.; Wallace, G. G. Processable Aqueous Dispersions of Graphene Nanosheets. Nat. Nanotechnol. 2008, 3 (2), 101–105. 31. Pan, S.; Aksay, I. A. Factors Controlling the Size of Graphene Oxide Sheets Produced Via the Graphite Oxide Route. ACS Nano 2011, 5 (5), 4073–4083. 32. Mohanty, N.; Berry, V. Graphene-Based Single-Bacterium Resolution Biodevice and DNA Transistor: Interfacing Graphene Derivatives with Nanoscale and Microscale Biocomponents. Nano Lett. 2008, 8 (12), 4469–4476. 33. Kim, E.; An, H.; Jang, H.; Cho, W. J.; Lee, N.; Lee, W. G.; Jung, J. Growth of Few‐ Layer Graphene on a Thin Cobalt Film on a Si/SiO2 Substrate. Chem. Vap. Depos. 2011, 17 (1–3), 9–14. 34. Losurdo, M.; Giangregorio, M. M.; Capezzuto, P.; Bruno, G. Graphene CVD Growth on Copper and Nickel: Role of Hydrogen in Kinetics and Structure. Phys. Chem. Chem. Phys. 2011, 13 (46), 20836–20843. 35. Batzill, M. The Surface Science of Graphene: Metal Interfaces, CVD Synthesis, Nanoribbons, Chemical Modifications, and Defects. Surf. Sci. Rep. 2012, 67 (3– 4), 83–115. 36. Hao, Y.; Bharathi, M.; Wang, L.; Liu, Y.; Chen, H.; Nie, S.; Wang, X.; Chou, H.; Tan, C.; Fallahazad, B. The Role of Surface Oxygen in the Growth of Large SingleCrystal Graphene on Copper. Science 2013, 342 (6159), 720–723. 37. Lee, J.-H.; Lee, E. K.; Joo, W.-J.; Jang, Y.; Kim, B.-S.; Lim, J. Y.; Choi, S.-H.; Ahn, S. J.; Ahn, J. R.; Park, M.-H. Wafer-Scale Growth of Single-Crystal Mono-Layer Graphene on Reusable Hydrogen-Terminated Germanium. Science 2014, 344 (6181), 286–289. 38. Robinson, J. T.; Perkins, F. K.; Snow, E. S.; Wei, Z.; Sheehan, P. E. Reduced Graphene Oxide Molecular Sensors. Nano Lett. 2008, 8 (10), 3137–3140.

Chapter 3  Graphene in Field Effect Transistor-Based Biosensors  75

39. Wang, X.; Zhi, L.; Müllen, K. Transparent, Conductive Graphene Electrodes for Dye-Sensitized Solar Cells. Nano Lett. 2008, 8 (1), 323–327. 40. Gilje, S.; Han, S.; Wang, M.; Wang, K. L.; Kaner, R. B. A Chemical Route to Graphene for Device Applications. Nano Lett. 2007, 7 (11), 3394–3398. 41. Dua, V.; Surwade, S. P.; Ammu, S.; Agnihotra, S. R.; Jain, S.; Roberts, K. E.; Park, S.; Ruoff, R. S.; Manohar, S. K. All‐organic vapor sensor using inkjet‐printed reduced graphene oxide. Angew. Chem. Int. Ed. 2010, 49 (12), 2154–2157. 42. Eda, G.; Fanchini, G.; Chhowalla, M. Large-Area Ultrathin Films of Reduced Graphene Oxide as a Transparent and Flexible Electronic Material. Nat. Nanotechnol. 2008, 3 (5), 270–274. 43. Ohno, Y.; Maehashi, K.; Matsumoto, K. Label-Free Biosensors Based on Aptamer-Modified Graphene Field-Effect Transistors. J. Am. Chem. Soc. 2010, 132 (51), 18012–18013. 44. Stine, R.; Robinson, J. T.; Sheehan, P. E.; Tamanaha, C. R. Real‐Time DNA Detection Using Reduced Graphene Oxide Field Effect Transistors. Adv. Mater. 2010, 22 (46), 5297–5300. 45. Dankerl, M.; Hauf, M. V.; Lippert, A.; Hess, L. H.; Birner, S.; Sharp, I. D.; Mahmood, A.; Mallet, P.; Veuillen, J. Y.; Stutzmann, M. Graphene Solution‐Gated Field‐Effect Transistor Array for Sensing Applications. Adv. Funct. Mater. 2010, 20 (18), 3117–3124. 46. Dong, X.; Shi, Y.; Huang, W.; Chen, P.; Li, L. J. Electrical Detection of DNA Hybridization with Single‐Base Specificity Using Transistors Based on CVD‐ Grown Graphene Sheets. Adv. Mater. 2010, 22 (14), 1649–1653. 47. Wang, Q. H.; Hersam, M. C. Room-Temperature Molecular-Resolution Characterization of Self-Assembled Organic Mono-Layers on Epitaxial Graphene. Nat. Chem. 2009, 1 (3), 206. 48. Hurch, S.; Nolan, H.; Hallam, T.; Berner, N. C.; McEvoy, N.; Duesberg, G. S. InkjetDefined Field-Effect Transistors from Chemical Vapour Deposited Graphene. Carbon 2014, 71, 332–337. 49. Huang, Y.; Dong, X.; Shi, Y.; Li, C. M.; Li, L.-J.; Chen, P. Nanoelectronic Biosensors Based on CVD Grown Graphene. Nanoscale 2010, 2 (8), 1485–1488. 50. Ohno, Y.; Maehashi, K.; Inoue, K.; Matsumoto, K. Label-Free Aptamer-Based Immunoglobulin Sensors Using Graphene Field-Effect Transistors. Jpn. J. Appl. Phys. 2011, 50 (7R), 070120. 51. Akca, S.; Foroughi, A.; Frochtzwajg, D.; Postma, H. W. C. Competing Interactions in DNA Assembly on Graphene. PLoS One 2011, 6 (4), e18442. 52. Mao, S.; Lu, G.; Yu, K.; Bo, Z.; Chen, J. Specific Protein Detection Using Thermally Reduced Graphene Oxide Sheet Decorated with Gold Nanoparticle‐Antibody Conjugates. Adv. Mater. 2010, 22 (32), 3521–3526. 53. Mao, S.; Yu, K.; Chang, J.; Steeber, D. A.; Ocola, L. E.; Chen, J. Direct Growth of Vertically-Oriented Graphene for Field-Effect Transistor Biosensor. Sci. Rep. 2013, 3 (1), 1–6. 54. Mulvaney, S. P.; Stine, R.; Long, N. C.; Tamanaha, C. R.; Sheehan, P. E. Graphene Veils: A Versatile Surface Chemistry for Sensors. Biotechniques 2014, 57 (1), 21–30. 55. Kurkina, T.; Sundaram, S.; Sundaram, R. S.; Re, F.; Masserini, M.; Kern, K.; Balasubramanian, K. Self-Assembled Electrical Biodetector Based on Reduced Graphene Oxide. ACS Nano 2012, 6 (6), 5514–5520. 56. Baraket, M.; Stine, R.; Lee, W. K.; Robinson, J. T.; Tamanaha, C. R.; Sheehan, P. E.; Walton, S. G. Aminated Graphene for DNA Attachment Produced Via Plasma Functionalization. Appl. Phys. Lett. 2012, 100 (23), 233123. 57. Bekyarova, E.; Itkis, M. E.; Ramesh, P.; Berger, C.; Sprinkle, M.; de Heer, W. A.; Haddon, R. C. Chemical Modification of Epitaxial Graphene: Spontaneous Grafting of Aryl Groups. J. Am. Chem. Soc. 2009, 131 (4), 1336–1337.

76  Chapter 3  Graphene in Field Effect Transistor-Based Biosensors

58. Farmer, D. B.; Golizadeh-Mojarad, R.; Perebeinos, V.; Lin, Y.-M.; Tulevski, G. S.; Tsang, J. C.; Avouris, P. Chemical Doping and electron− Hole Conduction Asymmetry in Graphene Devices. Nano Lett. 2009, 9 (1), 388–392. 59. Lomeda, J. R.; Doyle, C. D.; Kosynkin, D. V.; Hwang, W.-F.; Tour, J. M. Diazonium Functionalization of Surfactant-Wrapped Chemically Converted Graphene Sheets. J. Am. Chem. Soc. 2008, 130 (48), 16201–16206. 60. Kasry, A.; Afzali, A. A.; Oida, S.; Han, S.-J.; Menges, B.; Tulevski, G. S. Detection of Biomolecules Via Benign Surface Modification of Graphene. Chem. Mater. 2011, 23 (22), 4879–4881. 61. Blaszykowski, C.; Sheikh, S.; Thompson, M. Surface Chemistry to Minimize Fouling from Blood-Based Fluids. Chem. Soc. Rev. 2012, 41 (17), 5599–5612. 62. Liu, B.; Sun, Z.; Zhang, X.; Liu, J. Mechanisms of DNA Sensing on Graphene Oxide. Anal. Chem. 2013, 85 (16), 7987–7993. 63. Yan, L.; Zheng, Y. B.; Zhao, F.; Li, S.; Gao, X.; Xu, B.; Weiss, P. S.; Zhao, Y. Chemistry and Physics of a Single Atomic Layer: Strategies and Challenges for Functionalization of Graphene and Graphene-Based Materials. Chem. Soc. Rev. 2012, 41 (1), 97–114. 64. Park, J. S.; Goo, N.-I.; Kim, D.-E. Mechanism of DNA Adsorption and Desorption on Graphene Oxide. Langmuir 2014, 30 (42), 12587–12595. 65. Hu, W.; Peng, C.; Luo, W.; Lv, M.; Li, X.; Li, D.; Huang, Q.; Fan, C. Graphene-Based Antibacterial Paper. ACS Nano 2010, 4 (7), 4317–4323. 66. He, J.; Zhu, X.; Qi, Z.; Wang, C.; Mao, X.; Zhu, C.; He, Z.; Li, M.; Tang, Z. Killing Dental Pathogens Using Antibacterial Graphene Oxide. ACS Appl. Mater. Interfaces 2015, 7 (9), 5605–5611. 67. Mao, S.; Yu, K.; Lu, G.; Chen, J. Highly Sensitive Protein Sensor Based on Thermally-Reduced Graphene Oxide Field-Effect Transistor. Nano Res. 2011, 4 (10), 921. 68. Guo, S.; Dong, S. Graphene and its Derivative-Based Sensing Materials for Analytical Devices. J. Mater. Chem. 2011, 21 (46), 18503–18516. 69. Huang, Y.; Dong, X.; Liu, Y.; Li, L.-J.; Chen, P. Graphene-Based Biosensors for Detection of bacteria and their Metabolic Activities. J. Mater. Chem. 2011, 21 (33), 12358–12362. 70. Ameri, S. K.; Singh, P. K.; Sonkusale, S. R. Liquid Gated Three Dimensional Graphene Network Transistor. Carbon 2014, 79, 572–577. 71. Chen, T.-Y.; Loan, P. T. K.; Hsu, C.-L.; Lee, Y.-H.; Wang, J. T.-W.; Wei, K.-H.; Lin, C.T.; Li, L.-J. Label-Free Detection of DNA Hybridization Using Transistors Based on CVD Grown Graphene. Biosens. Bioelectron. 2013, 41, 103–109. 72. Hasegawa, M.; Hirayama, Y.; Ohno, Y.; Maehashi, K.; Matsumoto, K. Characterization of Reduced Graphene Oxide Field-Effect Transistor and its Application to Biosensor. Jpn. J. Appl. Phys. 2014, 53 (5S1), 05FD05. 73. Inaba, A.; Yoo, K.; Takei, Y.; Matsumoto, K.; Shimoyama, I. Ammonia Gas Sensing Using a Graphene Field–Effect Transistor Gated by Ionic Liquid. Sens. Actuators B 2014, 195, 15–21. 74. Basu, J.; Samanta, N.; Jana, S.; RoyChaudhuri, C. Towards Reliability Enhancement of Graphene FET Biosensor in Complex Analyte: Artificial Neural Network Approach. Microelectron. Reliab. 2018, 91, 154–159. 75. Fenoy, G. E.; Marmisollé, W. A.; Azzaroni, O.; Knoll, W. Acetylcholine Biosensor Based on the Electrochemical Functionalization of Graphene Field-Effect Transistors. Biosens. Bioelectron. 2020, 148, 111796. 76. Karimi, H.; Yusof, R.; Rahmani, R.; Hosseinpour, H.; Ahmadi, M. T. Development of Solution-Gated Graphene Transistor Model for Biosensors. Nanoscale Res. Lett. 2014, 9 (1), 71. 77. Kennedy, J.; Eberhart, R. Particle Swarm Optimization. In Proceedings of ICNN’95International Conference on Neural Networks; IEEE, 1995; pp. 1942–1948.

Chapter 3  Graphene in Field Effect Transistor-Based Biosensors  77

78. Traversi, F.; Raillon, C.; Benameur, S.; Liu, K.; Khlybov, S.; Tosun, M.; Krasnozhon, D.; Kis, A.; Radenovic, A. Detecting the Translocation of DNA through a Nanopore Using Graphene Nanoribbons. Nat. Nanotechnol. 2013, 8 (12), 939–945. 79. Thompson, I. M.; Pauler, D. K.; Goodman, P. J.; Tangen, C. M.; Lucia, M. S.; Parnes, H. L.; Minasian, L. M.; Ford, L. G.; Lippman, S. M.; Crawford, E. D. Prevalence of Prostate cancer among Men with a Prostate-Specific Antigen Level≤ 4.0 ng per Milliliter. N. Engl. J. Med. 2004, 350 (22), 2239–2246. 80. Kim, D.-J.; Sohn, I. Y.; Jung, J.-H.; Yoon, O. J.; Lee, N.-E.; Park, J.-S. Reduced Graphene Oxide Field-Effect Transistor for Label-Free Femtomolar Protein Detection. Biosens. Bioelectron. 2013, 41, 621–626. 81. Zhang, B.; Cui, T. Suspended Graphene Nanoribbon Ion-Sensitive Field-Effect Transistors Formed by Shrink Lithography for pH/cancer Biomarker Sensing. J. Microelectromech. Syst. 2013, 22 (5), 1140–1146. 82. Schultz, W. Multiple Reward Signals in the Brain. Nat. Rev. Neurosci. 2000, 1 (3), 199–207. 83. Kim, J.-H.; Auerbach, J. M.; Rodríguez-Gómez, J. A.; Velasco, I.; Gavin, D.; Lumelsky, N.; Lee, S.-H.; Nguyen, J.; Sánchez-Pernaute, R.; Bankiewicz, K. Dopamine Neurons Derived from Embryonic Stem Cells Function in an Animal Model of Parkinson’s Disease. Nature 2002, 418 (6893), 50–56. 84. Howes, O. D.; Kambeitz, J.; Kim, E.; Stahl, D.; Slifstein, M.; Abi-Dargham, A.; Kapur, S. The Nature of Dopamine Dysfunction in Schizophrenia and What this Means for Treatment: meta-Analysis of Imaging Studies. Arch. Gen. Psychiatry 2012, 69 (8), 776–786. 85. He, Q.; Sudibya, H. G.; Yin, Z.; Wu, S.; Li, H.; Boey, F.; Huang, W.; Chen, P.; Zhang, H. Centimeter-Long and Large-Scale Micropatterns of Reduced Graphene Oxide Films: Fabrication and Sensing Applications. ACS Nano 2010, 4 (6), 3201–3208. 86. Maehashi, K.; Sofue, Y.; Okamoto, S.; Ohno, Y.; Inoue, K.; Matsumoto, K. Selective Ion Sensors Based on Ionophore-Modified Graphene Field-Effect Transistors. Sens. Actuators B 2013, 187, 45–49. 87. Rhoads, D. D.; Wolcott, R. D.; Sun, Y.; Dowd, S. E. Comparison of Culture and Molecular Identification of bacteria in Chronic Wounds. Int. J. Mol. Sci. 2012, 13 (3), 2535–2550. 88. Chang, J.; Mao, S.; Zhang, Y.; Cui, S.; Zhou, G.; Wu, X.; Yang, C.-H.; Chen, J. Ultrasonic-Assisted Self-Assembly of Mono-Layer Graphene Oxide for Rapid Detection of Escherichia coli bacteria. Nanoscale 2013, 5 (9), 3620–3626. 89. Liu, F.; Kim, Y. H.; Cheon, D. S.; Seo, T. S. Micropatterned Reduced Graphene Oxide Based Field-Effect Transistor for Real-Time Virus Detection. Sens. Actuators B 2013, 186, 252–257. 90. Shoorideh, K.; Chui, C. O. On the Origin of Enhanced Sensitivity in Nanoscale FET-Based Biosensors. Proc. Natl. Acad. Sci. 2014, 111 (14), 5111–5116. 91. Nakazato, K. Potentiometric, Amperometric, and Impedimetric CMOS Biosensor Array. In State of the Art in Biosensors-General Aspects; InTech, 2013; pp. 163–177. 92. Purvis, D.; Leonardova, O.; Farmakovsky, D.; Cherkasov, V. An ultrasensitive and Stable Potentiometric Immunosensor. Biosens. Bioelectron. 2003, 18 (11), 1385–1390. 93. Dhand, C.; Das, M.; Datta, M.; Malhotra, B. Recent Advances in Polyaniline Based Biosensors. Biosens. Bioelectron. 2011, 26 (6), 2811–2821. 94. Poghossian, A.; Schöning, M. J. Label‐Free Sensing of Biomolecules with Field‐ Effect Devices for Clinical Applications. Electroanalysis 2014, 26 (6), 1197–1213. 95. Shen, N.-M.; Liu, Z.; Lee, C.; Minch, B. A.; Kan, E.-C. Charge-Based Chemical Sensors: A Neuromorphic Approach with Chemoreceptive Neuron MOS (C/spl nu/MOS) Transistors. IEEE Trans. Electron Devices 2003, 50 (10), 2171–2178.

78  Chapter 3  Graphene in Field Effect Transistor-Based Biosensors

96. Goda, T.; Singi, A. B.; Maeda, Y.; Matsumoto, A.; Torimura, M.; Aoki, H.; Miyahara, Y. Label-Free Potentiometry for Detecting DNA Hybridization Using Peptide Nucleic Acid and DNA Probes. Sensors 2013, 13 (2), 2267–2278. 97. Liu, Y.; Dutton, R. W. Effects of Charge Screening and Surface Properties on Signal Transduction in Field Effect Nanowire Biosensors. J. Appl. Phys. 2009, 106 (1), 014701. 98. Poghossian, A.; Cherstvy, A.; Ingebrandt, S.; Offenhäusser, A.; Schöning, M. J. Possibilities and Limitations of Label-Free Detection of DNA Hybridization with Field-Effect-Based Devices. Sens. Actuators B 2005, 111, 470–480. 99. Schasfoort, R. B.; Bergveld, P.; Kooyman, R.; Greve, J. Possibilities and Limitations of Direct Detection of Protein Charges by Means of an Immunological FieldEffect Transistor. Anal. Chim. Acta 1990, 238, 323–329. 100. Huang, W.; Diallo, A. K.; Dailey, J. L.; Besar, K.; Katz, H. E. Electrochemical Processes and Mechanistic Aspects of Field-Effect Sensors for Biomolecules. J. Mater. Chem. C 2015, 3 (25), 6445–6470. 101. Wei, F.; Lillehoj, P. B.; Ho, C.-M. DNA Diagnostics: Nanotechnology-Enhanced Electrochemical Detection of Nucleic Acids. Pediatr. Res. 2010, 67 (5), 458–468. 102. Reddy, B.; Hassan, U.; Seymour, C.; Angus, D.; Isbell, T.; White, K.; Weir, W.; Yeh, L.; Vincent, A.; Bashir, R. Point-of-Care Sensors for the Management of Sepsis. Nat. Biomed. Eng. 2018, 2 (9), 640–648. 103. Cui, Y.; Lieber, C. M. Functional Nanoscale Electronic Devices Assembled Using Silicon Nanowire Building Blocks. Science 2001, 291 (5505), 851–853. 104. Sengupta, J.; Hussain, C. M. Graphene-Based Field-Effect Transistor Biosensors for the Rapid Detection and Analysis of Viruses: A Perspective in View of COVID-19. Carbon Trends 2020, 2, 100011.

Graphene-Based Biosensors for Detection of Protein and Nucleic Acid

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4.1 Introduction After the isolation of a two-dimensional (2D) graphene sheet in 2004 by Andre Geim and Konstantin Novoselov by mechanical exfoliation,1 graphene-related research has aroused special interest in the scientific and industrial world. The unique physiochemical and electronic properties, along with its anticipated biocompatibility, make graphene a suitable material for various bioelectronic applications.2,3 The planar surface of graphene, comprises of hexagonally arranged sp2-hybridized carbon atoms with long range conjugations, facilitates the interactions of pristine graphene with the biomolecules.4 Therefore, graphene has emerged as a suitable material for fabrication of highly sensitive and selective biosensors.5,6 A biosensor is an analytical device that can be used for the detection of desired bio-analytes. It consists of a ­physico-chemical detector coupled with a biological component. These physico-­chemical detectors can be optical, electrical, magnetic, and piezo-electric types.7 Nucleic acid (DNA, RNA, aptamers, etc.), proteins (antibodies, enzymes, peptides, etc.), the whole biological cell, microbes, and other such biomolecules can be utilized as biorecognition elements in a biosensor. In a typical biosensor, biological information obtained due to interaction of the desired analyte is converted into an electronic format. This conversion may be rapidly made through graphene-mediated fast electron transport attributing high electron mobility of graphene.8 Furthermore, graphene has a high specific surface area along with conjugated bonds that enable it for the pi-pi interactions with biomolecules having aromatic rings. These interactions provide the possibility of bonding with a variety of biomolecules without disturbing the graphene’s electronic network. As a result, graphene can be conjugated with biomolecules of DNA, RNA, antibodies, aptamers, receptors, enzymes, etc. to obtain low detection limits and high efficiency.4,8 Graphene Based Biomolecular Electronic Devices. https://doi.org/10.1016/B978-0-12-821541-8.00010-X Copyright © 2023 Elsevier Inc. All rights reserved.

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The derivatives of graphene oxide (GO) and reduced graphene oxide (rGO) can be produced by oxidation of exfoliated graphene and its subsequent reduction. The oxidized form of graphene is more stable in an aqueous solution with the presence of abundant functional groups including carboxyl, hydroxyl, epoxy groups, etc. on the surface, which further enhance the interaction ability.9,10 As a result, GO and rGO surfaces have been found to be more interactive and suitable for synthesizing bio-conjugated surfaces as the presence of oxygen-­containing groups prompts the linkers to bond with a variety of ligands, which is useful for biosensing applications. Furthermore, in addition to having good conductivity, rGO has multiple unique properties such as an ability to form film on a large area with a functionalized and active surface, tailorable properties of conductivity, hydrophilicity, solubility, and dispersion depending on the method employed to reduce GO. These properties of rGO make it an attractive candidate to be used as a transducer for fabrication of a new generation of biological sensors. 11,12 The main aim of a biosensor is to obtain the signal of biological molecules instantly with higher sensitivity in a cost-effective manner. With the exploration of graphene derivatives and composites, the use of graphene in biosensors is increasing to obtain enhanced performance of these bioelectronic devices.13 Graphene is considered to be an effective component to trigger biosensor’s efficiency owing to its high and differential affinity toward its different forms.13 Over the past few decades, the successful preparation of single- or few-layered graphene on a large scale with the optimization of isolation techniques has led to many breakthroughs. Also, various new findings have been reported related to graphene material. As a result, the sensitivity of graphene-based biosensors to detect a desired analyte has increased manifold.13 Further, commercialization and large-scale production of graphene-based biosensors depend upon the cost of raw materials.14 The planar mono-layer or few-layered graphene may give rise to high-performance bioelectronic devices whilst a multi-layered graphitic substance possibly could be used for highly cost-effective and relatively low-performing biosensing devices. GO or rGO layers can be used for the fabrication of composites, conductive paints, etc., and could also be utilized for the fabrication of sensing platforms. Nevertheless, multiple methods of graphene synthesis are already available in the literature for the desired shape, dimension, and of specific quality. Herein, we discuss the role of graphene toward detection of nucleic acids such as ssDNA, peptide nucleic acid (PNA), aptamers, and proteins for application of graphene-based biosensors in the healthcare sector including point of care (POC) testing and ­lab-on-a-chip devices.

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4.2  Graphene-based biosensors for nucleic acid detection 4.2.1 Introduction Nucleic acids store genetic information relating to living organisms and enable sequence-specific identification. Their analysis is beneficial to diagnose infectious diseases, for gene therapy, for bacterial monitoring, etc. The recent emergence of nucleic acid-based devices has led to much interest in the detection and monitoring of various clinical parameters of disease, gaining special focus in effective clinical diagnostics.15 The physico-chemical properties of graphene can be further improved by modifying its surface, which increases its ability to interact and conjugate, resulting in enhanced sensitivity and selectivity of nucleic acid-based biomolecular analysis.4 Further, there is a demand for rapid DNA detection by targeting specific DNA sequences for early disease diagnosis. The synthetic probes (aptamers and PNAs) can be potentially utilized to fabricate rapid testing kits.16 Due to their low cost and flexibility, they are evolving as reliable and faster tools in the medical diagnostics market. Much advancement has been predicted toward the development of highly sensitive and precise biosensors that can detect multi-analytes to reduce time and cost.5,6 More effective recognition has recently been realized with the use of nucleic acid as a probe.17 These probes that could potentially target specific DNA sequences are being designed with advancements in the field of biotechnology using sophisticated microarray systems and different hybridization techniques.18 The probe used in a nucleic ­acid-based biosensor is an oligonucleotide, which could be DNA, RNA, PNA, or an aptamer of DNA or RNA. Herein, the recognition of DNA or RNA occurs due to the hybridization of the probe with the target of ­single-stranded nucleic acid sequences based on Chargaff’s rules of base pairing. The complimentary sequence of DNA or RNA binds with each other, i.e. adenine (A) binds specifically with thymine (T) whilst guanine (G) binds with cytosine (C) through hydrogen bonds.19,20 These DNA-based sensors can be used to detect the presence of pathogenic microorganisms, genetic polymorphisms, detection of point mutations, that is, single nucleotide polymorphism (SNP), etc. and have been recently commercialized.21 DNA-based biosensors have an advantage over immunosensor and enzymatic biosensors. Herein, the target biomolecules of DNA could be easily amplified by a polymer chain reaction (PCR) technique resulting in augmentation of the detection signal. Moreover, DNA with the desired sequences can be synthesized by thermal annealing of the DNA duplex to form a reusable

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Fig. 4.1  Pictorial representation of nucleic acid (PNA, aptamer, RNA, DNA) biosensors using graphene as a sensing platform.

and stable bio-recognition layer in a biosensor analytical device. As a result, amongst all other types of nucleic acid-based biosensors, DNAbased biosensors are the preferred biosensing tool (Fig. 4.1).21

4.2.2  Graphene-based aptamer biosensors Aptamers are oligonucleotides or peptide molecules that are known to bind with a specific target molecule. Aptamer-based detection is different from that of DNA-based hybridization because aptamers are known to fit the desired target structure, resulting in increased interaction with the analyte. The versatility of binding with a variety of biomolecules including biological cells, toxins, peptides, proteins, carbohydrates is assigned to the ability of aptamers to attain both a single-stranded loop structure and helical structure. Contrary to the complementary sequence binding, the aptamers interact with analytes like ligand-receptor interactions and ­antigen-antibody interactions. A pool of large random sequences can be used to form the desired aptamers.22 The combination of aptamers with graphene for creating bio-functional nanocomposites may result in improved sensitivity and selectivity of the fabricated biosensors due to the unique molecular recognition and biocompatibility of aptamers.23 Because of the various characteristic properties, graphene can also be used to enhance the performance of an aptasensor. The high surface area, owing to its 2D nanostructure, provides a flat and adequate surface to bind with many biomolecules (Fig. 4.2) resulting in enhanced biosensor sensitivity.24,25 Therefore, graphene has a promising application to be used for in  vivo biosensing systems with its promising biocompatibility at low dose as it exhibits dose-dependent ­cytotoxicity.26 Also, compared to antigen-antibody system-based biosensors, the a­ptamer-target aptasensors have shown several advantages like higher affinity, lower price, easier fabrication, higher sensitivity, and wider sensing application of analytes.27

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Fig. 4.2  Schematic of applications of graphene-based aptasensors.23 Reproduced with permission from Wang, L.; Wu, A.; Wei, G. Graphene-Based Aptasensors: From Molecule–Interface Interactions to Sensor Design and Biomedical Diagnostics. Analyst 2018, 143 (7), 1526–1543.

Graphene has perpendicular p-orbitals with delocalized electrons that form a pi electron system whilst aptamers are short chains of oligonucleotides of ssDNA having aromatic rings. As a result, aptamers can easily interact with graphene through a pi-pi electron system. These interactions play a pivotal role in direct binding of aptamers to the graphene surface to design graphene-based sensor units for the detection of a variety of biomolecules including DNA, proteins, metallic ions, cancer biomarkers, etc. These biosensors have been reported to exhibit high sensitivity and selectivity for desired targets.4,25 Ohno et  al. fabricated a label-free biosensor based on an ­aptamer-modified graphene field effect transistor (GFET) (Fig. 4.3).28 The aptamer of nearly 3 nm length was designed for immunoglobulin E (IgE) and absorbed on the surface of graphene; atomic force microscopy (AFM) was used to visualize the immobilization. The GFET having immobilized aptamers was able to detect the IgE protein by selective electrical detection. The dissociation constant was found to

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Fig. 4.3  (A) AFM image of a GFET with a bare graphene channel. (B) AFM image of the GFET with an aptamer-modified graphene channel.28 Reproduced with permission from Ohno, Y.; Maehashi, K.; Matsumoto, K. Label-Free Biosensors Based on Aptamer-Modified Graphene Field-Effect Transistors. J. Am. Chem. Soc. 2010, 132 (51), 18012–18013.

be approximately 47 nM measured by variation in drain current.28 The non-covalent interactions between graphene materials and ssDNA aptamers play important roles in the construction of high-performance aptasensors. We believe that the mechanistic understating of interactions between graphene and aptamers could give rise to graphenebased aptasensors with improved sensitivity, specificity, and stability.

4.2.3  Graphene-based DNA (deoxyribonucleic acid) biosensors DNA-based biosensors have been extensively employed for wider applications because, unlike immunosensors29 and enzymatic biosensors,30 these biosensors have an advantage of regeneration of nucleotide recognition layer for the multiple detection usages.31,32 Graphene relies on excellent physical and chemical properties and has shown great potential in biosensors for the detection of single-base mutations and gene sequencing,33 which can be used for the diagnosis of several genetic diseases.31 Electrochemical methods are well-suited for DNA hybridization detection because electrochemical reactions can directly give an electronic signal. As a result, there is no need for signal transduction equipment.34 Furthermore, gene chips with DNA biosensors have attracted major interest due to their potential for providing rapid specific information related to a particular gene in a cost-effective manner as compared to

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traditional hybridization. Advancements in technology like Sequential Evolution of Ligands by Exponential Enrichment (SELEX), which is an in  vitro technique for the evaluation of an appropriate target-specific probe from a large collection of oligonucleotides through an iterative process of selection and S-adenosyl methionine (SAM), can be utilized to develop better detection methods (both direct and indirect detection).35 One of the key steps in sensor design is to immobilize probe sequences.34 Both GO and rGO exhibit different functional groups on their surface that determine their performance level to interact and immobilize ssDNA as a probe.36 Thus, biosensors having different sensitivity levels could be designed by immobilizing ssDNA on the surface of a working electrode like glassy carbon electrode (GCE) modified with GO, chemically reduced GO (CrGO), or electrochemically reduced GO (ErGO).37 By measuring the electrochemical response of the modified electrode, the detection level of the target DNA can be found.38 In the context of mode by which oxygen level of the graphene surface has been modified, the highest detection limit has been reported for ErGO. For example, Bonanni et al. have reported the detection limit for the target sequences of wild type to be 250 pm, 3 nm, 100 nm, and 800 nm for ErGO, CrGO, GO, and graphite oxide, respectively.39 Further, measurement of florescence quenching is another potential biosensing method that can be used for the detection of DNA. Xu et al. designed the GO-based biosensor for the detection of single-base mutation in the target DNA based on the technique of florescence quenching. The technique was developed to detect SNP involving ­single-base extension reaction. The dsDNA and dGTP tagged with fluorescent dye (dGTP-F1) exhibited different binding efficiency on the GO surface. Herein, dGTP-F1 was attached to the probe by a single-base extension reaction to bind with mutant target DNA. As a result, only the mutant target exhibited florescence upon hybridization with the probe and not the wild DNA. Moreover, the efficiency of dsDNA binding was low compared to dGTO-F1. Consequently, the methodology was found to be rapid, selective, and simple for the identification of SNP in the target DNA. The detection limit of the target mutant DNA obtained as about 3 nM whilst the reported linear range was 3 to 50 nM. Moreover, this biosensing technique was postulated to be highly selective for a target as the biosensor was able to detect the target even if its concentration was nine times lower than that of the wild type DNA.40 Another approach for label-free detection of nucleic acid of RNA type is based on field effect transistor (FET) wherein graphene can be used as an electric channel called a GFET biosensor. The GFET-based biosensors are a more miniaturized, rapid, cost-effective method of sensing and can be utilized to measure RNA with high performance relative to the traditional method of RNA detection. The minimum detection limit of RNA can be 0.1 fM in the case of the GFET-based biosensor. Along with high sensitivity, GFET-based biosensor has been found

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to exhibit high selectivity for target RNA from non-­complementary RNA. Thus, high sensitivity, selectivity with high precision, and rapid analysis of the analyte have been obtained using the GFET-based biosensor, and it has emerged as a new feasible strategy for biosensing of RNA.41 Chen et al. have recently designed a GFET for detecting the bacteria Escherichia coli using a single layer of GO, which was self-­ assembled using ultrasonicaion.42 Furthermore, biosensing efficiency can be improved by understanding the mechanism of DNA and graphene interactions by using simulation studies as well as experimental studies. To experimentally study the adsorption level of DNA to the graphene surface, various techniques such as surface force apparatus, AFM, fluorescent dye labelling, calorimetry, and AFM-based force spectroscopy have been utilized to evaluate associated absorption or desorption energy.43 Akca et al. have used the AFM technique to study the assembly of ssDNA at the graphene surface and have shown that different nucleotides exhibit different behaviours. Adenine and cytosine bases were adsorbed to form a film on the graphene surface whilst thymine and guanine form a network on the graphene.44 Along with practical exploration (Fig.  4.4), nowadays, simulation studies pertaining to biomolecular interactions have been developed as a promising tool to fabricate stable bioconjugates for improved sensing. Zhao et al. reported on interactions between dsDNA and graphene surface in aqueous solution using molecular dynamic simulations. Pi-pi interactions were found to be the primary driving force for the stacking of DNA on the graphene wherein the base pairs present at the edge of the DNA interact with the rings of carbon atoms. Moreover, a different possibility of DNA self-assembly route was observed including the presence of DNA helices on graphene and the possibility of DNA parallel presence to the graphene surface in the case of deformed ending base pairs. The hydrophobic interactions involving pi stacking were found to be primarily responsible for such interactions driving toward self-assembly of DNA on the surface of graphene.46 Chen et al. have shown by molecular dynamic simulation studies using dsDNA segments of 8 and 12 base pairs that DNA segments could assemble on the GO surface perpendicularly with their ending base pairs. Stacking by pi-pi and electrostatic interactions between DNA base pairs and graphene allow contact with high binding affinity.47 Sun et al. have investigated that both types of DNA, i.e. ssDNA and dsDNA, can interact on the GO surface. However, compared to dsDNA, ssDNA could be easily absorbed on the graphene in aqueous solution. The observed difference was due to the limited pi-pi interactions in the case of long dsDNA.48 Furthermore, Hughes et al. analysed the adsorption of four nucleosides to the graphene surface in aqueous solution using both experimental as well as simulation study of molecular dynamics.49

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Fig. 4.4  (A) Patterning of DNA origami structures on graphene-based substrates. Spin-cast GO films are lithographically patterned and chemically modified by reduction or N doping. DNA origami structures were assembled on patterned graphene-based films from buffer solution (RIE = reactive ion etching). (B) A rectangular DNA origami assembly (2 nm thick, 70–90 nm2) obtained from the 7249 bp M13 ssDNA template and 226 small ssDNA staples. (C) AFM image and height profile of DNA origami structures on GO flakes. The red solid line shows the boundary of a single GO flake. The inset highlights one DNA origami structure to reveal its cross-sectional dimensions and rectangular shape.45 Reproduced with the permission from Yun, J. M.; Kim, K. N.; Kim, J. Y.; Shin, D. O.; Lee, W. J.; Lee, S. H.; Lieberman, M.; Kim, S. O. DNA Origami Nanopatterning on Chemically Modified Graphene. Angew. Chem. Int. Ed. 2012, 51 (4), 912–915.

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As previously mentioned, in addition to disease diagnostics, biosensing has been found to be significant to study genome sequencing in evaluating the risk factors associated with genetic diseases such as cancer, obesity, diabetes mellitus, etc.31,50 In this context, the Sanger method is the most widely used method for genome sequencing and has been recently employed for the sequencing of the human genome in a collaborative human genome project.51 Nevertheless, researchers are interested to find more rapid and cost-effective genome sequencing methods for customized and personal medicinal therapy. These personalized therapies are likely to be beneficial for individual genotypes. Therefore, there is an urgent need to develop rapid DNA ­biosensor-based sequencing methods.52 More recently, nanopores have emerged as a novel method of DNA sequencing and for the identification of the other macromolecules. The nanopores can be of biological origin or a fabricated solid-state type. Postma et al. have reported the use of graphene nanogap for identification of the bases in the nucleotide chain. Herein, graphene was proposed to be used as a membrane as well as an electrode material. The mechanism behind the identification of a nucleotide base involves the intrinsic high conductive nature of a single atom-thick graphene layer. There is a difference in localized electron densities of each type of base, which could yield a signal in the form of tunnelling current variation. The base sequence of the ssDNA can be identified by measuring the transverse conductance of the DNA. This conductance can be evaluated based on the change in nucleotide position and orientation whilst the individual nucleotide base continuously translocated through the nanopore of the graphene membrane accomplishing the third-­generation base sequencing of the target DNA.53,54

4.2.4  Graphene-based PNA (peptide nucleic acid) biosensors PNAs are a synthetic combination of nucleobases and peptide chain components. In a DNA molecule, nucleobases are attached to the backbone of a deoxyribose phosphate chain, whilst in the case of a PNA, the nucleobases are linked to the polyamide chain. This replacement of deoxyribose phosphate sugar reduces electrostatic repulsion and assists in effective hybridization. As a result, PNAs have shown remarkable affinity along with high specificity toward target complementary DNA or RNA.55 Moreover, PNAs have unique chemical and physical stabilities. As a result, PNAs have been widely employed in diagnostics and molecular biology-based research assays. It has been used as an efficacious probe for DNA hybridization techniques, in antisense and anticancer drug therapy, in in situ labelling and detecting genetic mutations, and in modifying PCR-based reactions. More recently, PNAs

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have been proposed as an effective substitute for the oligonucleotide probe in DNA-based biosensors. Even the presence of single-base mutation and ultra-low concentration of the target DNA or RNA can be detected using the PNAs as a recognition layer in the genosensor.56 Tian et al. recently proposed that the designed GFET using PNA as a probe could effectively detect RNA with a lower limit of detection (LOD) of 0.1 aM, which is a threefold lower value than the LOD of GFET based on DNA as a probe. Moreover, a broad range of target RNA detection with a linear electric response from 0.1 aM to 1 pM has been reported in the case of PNA-based GFET whilst DNA probe based on GFET exhibited 100 aM to 1 pM linear range.57 In another study, the diagnosis of the Brugada syndrome, which is an inherited cardiac disorder, was attempted using a biosensor based on a hybrid transducer. The designing part involved a matrix of porous silicon on which nanosheets of GO were covalently attached. The PNA was used as a bio-probe whilst the SCN5A gene was used as a target DNA for the detection of Brugada syndrome in this label-free optical biosensor. The signals associated with the reflectance of porous silicon and photoluminescence of GO were used for monitoring and detection of a disease.58 Zaid et al. have proposed a highly sensitive electrochemical biosensor based on the use of a PNA probe for the detection of Mycobacterium tuberculosis. GO functionalized with NH2 groups were conjugated with quantum dots of CdS. The sensing platform was designed using a screen-printed carbon electrode modified with the electrodeposition of quantum dots conjugated with GO. The designed PNA probe was later immobilized on the sensing platform through EDC/ NHS-mediated chemical crosslinking. The electrochemical signals were recorded using differential pulse voltammetry (DPV) whereas methylene blue was used as an electrochemical indicator. Herein, the designed biosensor was able to detect the target DNA with an LOD of 8.948 × 10− 13 M and a linear detection range of 1 × 10− 11 to 1 × 10− 7 M.59 The PNA-based biosensor showed high sensitivity and selectivity as compared to the DNA-based biosensor for the detection of complimentary DNA or RNA because of the strong binding and quenching capability of the PNA and GO framework. As a result, the PNA has emerged as a new navigator for detecting target nucleic acids.60

4.3  Graphene-based biosensors for protein detection 4.3.1 Introduction The past decade has seen new findings related to the various enhanced physical properties of graphene. As a result, parallelly, many graphene-based biosensors have been developed for effective and

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selective detection of protein biomarkers, enzymes, and immunosensors.61 Protein is the basic structural element of living beings that is made of amino acid units. This biological macromolecule assists in the repair, regeneration, regulation, maintenance, and growth of the biological systems. There are many protein-based biomarkers that are reported to act as indicators of many diseases and/or early damaged biological states or conditions.62 Therefore, biosensing of protein biomarkers has been used as a detectable and measurable parameter to diagnose the stage of a disease.63 An example of the detection of chronic diseases based on a protein marker is prostate cancer, which is the sixth most commonly occurring cancer type. It is responsible for 10% of all cancer fatalities in the world.64,65 A biosensor can play a significant role in the diagnosis of prostate cancer by detecting protein biomarkers in serum or blood. The fatality can be minimized by early diagnosis, hence, a highly sensitive biosensor capable of identifying the associated markers at a very low concentration is required to diagnose cancer at an early stage.66 In this context, graphene could be potentially used to improve the sensitivity of the biosensor due to its high catalytic ability.67 It could be utilized to modify the sensor platform to develop novel bio-interfaces as well as enhancing the generated signal by utilizing a graphene-based material as the catalyst.64

4.3.2  Graphene-based immunosensors Biosensors based on immunological reactions are called immunosensors. In an immunosensor, the released B lymphocyte antibodies specifically bind with the target antigens of bacteria, toxins, or viruses.29,68,69 There are five types of antibodies based on their physiological functions and their bio-chemical structure, viz., IgG, IgM, IgA, IgE, and IgD.70 These are actually protein structures having four polypeptide chains bound together with disulphide bonds that look like a “Y”-shaped structure.71 An antibody consists of two domains, viz., the variable and constant regions. The variable part specifically recognizes the antigen whilst the constant domain contributes toward the activation of the complement system and assists in binding with Fc receptors. With its particular structure and specificity, immunoglobulins enable efficient biorecognition with high binding affinity. As a result, immunosensors have emerged as an excellent medical diagnostic tool.68 Further, modification of the functional groups presents on the surface of GO is required for specific binding of the desired antibodies on the GO sheets using a variety of methods. Some methods include chemical crosslinking by ethyl(dimethylaminopropyl)carbodiimide/N-hydroxysuccinimide (EDC/NHS), electrostatic interactions, or interacting and bonding by 1-indolebutyric acid succinimide ester (PASE).72,73 Amongst these methods, chemical crosslinking with the

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functionalization by EDC and NHS is one of the most effective methods for bioconjugation on the graphene surface through amide formation based on the interactions of COOH and NH2 groups.73 In immunological reactions, the carboxyl group present at the GO surface and the primary amine group present on the edges of the antibody’s polypeptide chains bind together through an amide group. The signal generated by the binding of antigen and antibodies reactions can be detected through electrochemical signals.73,74 An electrochemical method measures the change in current that occurs at the interface of the electrolyte and electrode surface. The decreased or enhanced current is because of the antigen and antibody interactions and the resulting conformational changes in the recognition layer of the biosensor. The working electrode senses the electric signals with the measurements of current, impedance, or potential.75 Over the past few decades, efforts have been made to enhance the performance of electrochemical sensors by using graphene as the sensing platform.75 The irreversibility of antibodies-antigens reactions and low binding affinity have major shortcomings in these biosensing devices; however, early diagnosis with the detection of analytes could be advantageous for managing chronic diseases such as cancer, diabetes, stroke, cardiovascular diseases, arthritis,76 oral and periodontal diseases, etc.77,78 Today, globally, the outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have raised an alarming situation due to its very high spread rate. Rapid and effective detection strategies for COVID-19 in nasopharyngeal swab and clinical sera are in high demand. In this context, graphene-based biosensing devices using FET and microfluidic systems could play an important role as a supportive and supplementary method to the standard method of reverse ­transcription-polymerase chain reaction (RT-PCR)-based detection, since the mutations occurring in the viral genome required alterations in the probe and primer sequences for the target RNA in the case of the RT-PCR method. Ali et  al. utilized a microfluidic system for the detection of COVID-19 antibodies based on the rapid diagnosis method of electrochemical immunosensing. Herein, three-dimensional electrodes were fabricated using 3D nanoprinting. The COVID-19 viral antigens were immobilized on the printed electrodes decorated with rGO. The modified electrode was then positioned in the microfluidic chip system, and viral antigens were immobilized. The resistance generated upon binding of COVID-19 antibodies with immobilized antigens was detected using impedance spectroscopy. Furthermore, the signals were readable on a smartphone interfaced with the biosensing device. LOD of receptor-binding-domain (RBD) and SARS-CoV-2 spike S1 protein were 16.9 × 10− 15 and 2.8 × 10− 15, respectively. Moreover, the sensing

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platform could be ­regenerated using low pH chemistry.79 TorrenteRodríguez et al. utilized a laser-etched graphene surface for biosensing of multiple analytes of C-reactive proteins, IgM and IgG antibodies, and SARS-CoV-2 antigen. The system was designed as a portable integrated miniaturized device and interfaced with smart devices through a Bluetooth wireless system. The system was termed SARS-CoV-2 RapidPlex. There were four working electrodes while one counter electrode made of graphene material and one reference electrode of Ag/ Agcl. All the electrodes were fabricated using the technique of laser engraving on a polymeric substrate. Furthermore, the working electrode of graphene was functionalized using 1-pyrenebutyric acid (PBA), which was conjugated on the graphene surface through pi-pi stacking and hydrophobic interactions. This additional surface allowed the immobilization of the capturing receptors. This graphene-based, multiplex, immunosensing system was postulated to have promising potential for telemedicine diagnostics at low-cost monitoring.80 Seo et al. proposed a GFET biosensor for the detection of COVID-19. Herein, the sensor platform was fabricated by immobilizing the antibodies against spike proteins of SARS-CoV-2. The designed FET biosensor enabled the label-free detection of spike proteins at a concentration of 100 fg/mL in a medium of clinical transport and 1 fg/mL in a solution of phosphate buffer saline (PBS) with no prior sample treatment. Additionally, the designed biosensor was able to detect the SARS-CoV-2 antigen in real samples of human nasopharyngeal swab with a LOD of 2.42 × 102 copies/mL and 2.42 × 102 copies/mL in the cultured media of COVID-19.81 Yakoh et  al. demonstrated the detection of COVID-19 in a serological sample using POC testing. The electrodes (working, counter, and closing electrodes) were screen printed to design an electrochemical paper-based analytical device for diagnosing COVID-19 (COVID-19 ePAD). The test region present on a working electrode was impregnated with GO nanoparticles. The captured antibodies containing a receptor-binding domain (RBD) of SARS-CoV-2 spike protein was then immobilized on GO surface by EDC-NHS crosslinking. The response generated due to formation of immunocomplex with SARS-CoV-2 antibodies present in sample specimen was recorded using a squarewave voltammetry (SWV) technique. The designed ePAD depicted a response time of 30 min with a detection limit of 1 ng/mL of SARS-CoV-2 antibodies, which was proposed to be threefold higher than the previously reported lateral flow assays.82,83

4.3.3  Graphene-based enzyme biosensors Enzymes are proteins; their supramolecular structure and presence of cofactors make them highly selective biocatalysts for their substrate. They participate in biochemical reactions such as metabolic

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reactions occurring in biological systems. Even the isomers L and R are forms of a substrate that could be distinguished and differentially catalysed by a biocatalyst. High selectivity, specificity, and convenience make the enzymes suitable for use in the biosensing applications.84–86 Nevertheless, the enzymes are sensitive biological agents, and their catalytical activity are affected by changes in surrounding pH, temperature, ionic conductivity of the solution, polar nature of solvent, and presence of chemical inhibitors. Therefore, in the context of enzymatic biosensors, maintenance of enzymatic stability is highly challenging as a change in pH and temperature may denature the enzymes, which can adversely affect their catalytic power and decrease the sensing ability of the biosensor.78,87 Over the past few years, many advancements have been made in the field of bioengineering to further improve the enzymes’ stability and specificity. Multiple techniques of recombinant technology can be used for genetic modifications of the genes responsible for expressing the desired enzymatic proteins.88 Initially, enzymatic electrochemical biosensor stability was found to be improved by genetic manipulation of the thermophilic enzymes. Later, site-directed mutagenesis was used to enhance enzyme stability and catalytic activity of the various sensitive enzymes.89,90 Apart from improving the enzyme’s biocatalytic activity and stability by genetic modifications, another potent approach could be the upgradation and refinement of the sensing platform. Graphene could be used in the sensing platform to enhance the stability of the immobilized enzymes under the variant conditions of pH, temperature, ionic strength, and polarity of the solvent. Moreover, the immobilized enzymes can directly and efficiently transfer the electrons to the improved graphene-based electrode material78,90,91 depending on the method employed for enzyme immobilization on graphene. Enzyme entrapment, adsorption of the enzymes, or attachment through covalent crosslinking92 are some of the most widely used enzyme immobilization methods; the choice of method depends on the desired application. Zhang et al. recently reported that, only with the surface modification of GO, direct enzyme immobilization can be achieved even without the use of any crosslinking agents.93 Hereby, the immobilized enzymes observed through the AFM depicted that, on a modified GO surface, the enzymes were able to maintain their natural structural state with improved stability and response time.93,94 Further, the working of enzymatic electrochemical biosensors uses the biocatalyst activity to catalyse the target analyte86 and the inhibition of the enzyme activity due to the target analyte.95 The catalysis or inhibition of the enzymatic actions both produce a change in the electric signal that could be detected with the help of a transducer and analyser. The analytes can be quantified with the intensity of the generated electric signals.86

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The benefit of using enzymes is the specificity and easily detectable signal, as the reaction products can generate an electrochemical signal for the measurement of the analyte. Diabetes is one such disease where self-monitoring is essential, and the glucometer is a useful device for monitoring the glucose level in the blood of diabetic patients.96 Graphene-based biosensing has been used for observing the regulatory reactions related to glucose metabolism and extensively applied for monitoring the glucose level.97 Glucose oxidase can be immobilized on the graphene surface by chemical crosslinking agents. Furthermore, fast response has been reported for the detection of glucose with the use of a composite of gold nanoparticles and nafion decorated with graphene nanoparticles.98 Many other enzyme-based biosensing devices like urea sensors have also been developed.99 In the case of enzymatic biosensors, enzymatic reactions occur at the electrochemical sensor platform by the immobilized enzymes and generate electrochemical signals through direct electron transport system. The monitoring systems of enzymatic biosensors are continuously improving over the past two decades. For example, the glucometer has been improved to achieve more accuracy and reliability for glucose level detection. However, there are many associated challenges including the operator handling, environmental effect, high cost, etc.100 Recently, the US Food and Drug Administration (FDA) has given more precise and stringent standards for the commercialization of the glucometer, and producers have to follow the international standards with a margin error of 20%.101,102

4.4  Advanced applications of graphene-based biosensors 4.4.1 Introduction Nowadays, the advanced technique of lab-on-a-chip, wherein miniaturization and integration of the various biosensing components including biorecognition layer, processing, and analysis tools occur at the same platform, give rise to POC testing. POC devices have been designed with the infusion of advanced sophisticated techniques of microfluidics, 3D printing, etc., for the early diagnosis and real time monitoring of disease prognosis.67,103,104These POC diagnostics have emerged as a promising solution for managing complexities associated with home and hospital settings in this contemporary world. The detection and monitoring of chronic diseases have become easier with the help of POC diagnostics.103 Approval of biosensing equipment has been obtained due to their high sensitivity, specificity, high throughput processing, and capability for multiple detection. In disease diagnostics, biosensing devices have emerged as promising tools for the multiple detection using new fabrication techniques. Over the past

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few decades, efforts have been made for improving the sensing and expanding the range of analytes to be detected. The accuracy, precision, and LOD have been continuously improving with the help of new innovations and techniques. Furthermore, efforts are being made to provide cost-effective, high-performance, and user-friendly biosensing devices that could be accessed globally by a large population in remote areas with a vast community.105,106

4.4.2  Graphene-based biosensors in microfluidic chips Biosensors and microfluidic chips are bioanalytical devices that have a sensitive biorecognition element and a physico-chemical transducer to detect target analytes in solution. In a biosensor device, the receptor biomolecules act as biorecognition elements that can be incorporated on a transducer to detect a single or multiple analytes that act as ligands. In a microfluidic chip, there is high throughput processing and precise and regulated fluid flow that enhance the transport and mixing of different reagents and solutions. The additional advantage of the microfluidic chip is that less volume of sample is required with low reagent volume. In contrast to a biosensor device, the microfluidic chip can be used both for the preparation of the sample and the detection of the analytes with high sensitivity due to high surface area to volume ratios.107 Apart from the receptor-ligand biorecognition, the microfluidic system detects the presence of any pathogens or biomarkers by observing a change in mass or dielectric charge.108 In these systems, the fluid flows in channels depending on the applied pressure and electroosmosis on the chip. Any transduction system, viz., electrochemical, optical, or mechanical can be used to detect the analyte for the applications of POC testing.109,110 More recently, microfluidic devices have emerged as promising tools to evaluate and analyse biomarkers and biomolecules whilst also indicating the biophysiological conditions of tissue regeneration. It has been observed that direct cell culture on a microfluidic platform promotes enhanced cellular adhesion and growth and proliferation due to precise and controlled flow rate of media. The dynamic conditions enhance the cellular metabolic rate whilst the sensing element allows the detection of engineered tissue progression with the monitoring of metabolites. Thus, the system generates signals with the growth of the tissue toward in vitro organogenesis due to the release of specific biomolecules in the media. Thus, multiple analytes need to be monitored to know the functionality of the engineered construct. The integration of a POC device with microfluidic cell culture platform may allow the evaluation of the analytes along with in vitro cell culture. However, incorporation of multiple functional devices for clinical applications is a challenge

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for lab-on-a-chip devices. For integration, miniaturization is required such as pumping systems, this, however, increases the overall cost of the microfluidic device. Moreover, there is difficulty in detecting the complex real sample due to complexity in analysis of multiple data generated with an unknown value of actual biomolecular transport.111,112 The combination of graphene-based advanced biosensing techniques with microfluidics may resolve some of the shortcomings and may result in the cost effective POC devices .

4.4.3  Graphene-based biosensors for point-of-care diagnostics Graphene-based diagnostic devices of POC types have emerged as accessible, reliable, cost-effective, and efficient devices in healthcare systems for the detection and monitoring of various diseases. POC diagnostics offer precise and fast test response at the patient site without the help of costly, sophisticated, and specialized instruments.113 Molecular diagnostics with portable, user-friendly, and low-cost POC devices is the other main advantage. Different materials like glass, paper, silicon, polydimethyl-siloxane (PDMS), thermoplastic polymers, etc. can be used to fabricate the microfluidic channels to be used in POC devices. Graphene can be used to construct the test region of the electrode due to its intrinsic tuneable properties. Easy bioconjugation with high conductivity attribute the high-performance potency of the electrodes. The graphene nanostructures can also be used as efficient transducing elements in biosensing devices due to their high stability in adverse conditions of pH, temperature, and solvent conditions along with electric properties and other physico-chemical characteristics. More work is required prior to commercialization of these biosensors, which could enable stable, accurate, sensitive, personalized, and minimally invasive devices with easy monitoring and early detection.103,114–116 Moreover, as described earlier, the POC devices based on a graphene sensing element could provide a suitable platform for performing molecular biology reactions to monitor the cellular growth and proliferation. Microfluidics can further assist in controlling the flow rate and quantity, which can help in the separation of multiple analytes present in a complex sample, as a result, different reagents can be controlled to differentially detect the analytes with high sensitivity and selectivity.112

4.4.4  Graphene-based biosensors in integrated lab-on-a-chip Graphene can be used to develop lab-on-a-chip with the fabrication of high-performance, miniaturized, functional ­components.67,103 In a graphene-based lab-on-a-chip device, various tests can be per-

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formed using a single drop of blood. The designed microchannels embedded within the chip could enable analysis of biomacromolecules (antibodies, antigens, DNA, RNA, aptamers, etc.). These devices can be used any place without the intrusion of an external factor.79,117

4.5 Protocols Biosensing devices are emerging as complementary tools to the standard RT-PCR method and help in making therapeutic decisions as mutations occurring in the viral genome limit the flexibility of scaling up the RT-PCR technique.5,118 Currently, because of graphene antiviral119 and antibacterial properties,120 graphene-based biosensor has emerged as a promising tool for the detection of many viral diseases including SARS-CoV-2. Some of the protocols pertaining to the detection of viral diseases using graphene-based biosensors are described as follows: ( 1) Afsahi et al. proposed a biosensor using liquid-gated FET based on the graphene channel system. Herein, graphene was deposited by a CVD method on a copper foil and then transferred to silicon wafers using a bubbling transfer method. Polyethylene glycol (PEG) and immobilized antibodies form the dielectric system. Sensing was conducted by placing the designed biosensor chip into an electronic reader; the graphene channel has source-drain voltage across them whilst gate voltage was applied between the drain electrode and applied liquid. The biosensor chip was able to detect the antigens of Zika virus, i.e. ZIKV NS1 at a concentration as low as 450 pM in the serological samples using monoclonal antibodies immobilized on pristine graphene. The antigen level was demonstrated with a measured percentage change in capacitance.121 ( 2) Joshi et  al. used indium tin oxide (ITO)/glass electrode modified with thermally reduced GO (TrGO) flakes; the presence of ­phenolic-OH moiety on the TrGO surface facilitated its interaction to the ITO surface, resulting in stability of the system. The TrGO was drop cast on the electrode surface and then the antibodies were immobilized for the detection of influenza virus H1N1 antigens using the technique of impedance spectroscopy. Biosensing was able to detect plaque-forming units in PBS and saliva with an LOD of 26 and 33, respectively.122 (3) Huang et  al. designed the electrochemical immunosensor by modifying a gold (Au) electrode by a nanocomposite of graphene and Au nanoparticles. The detection of influenza virus H7 (AIV H7) was performed by immobilizing H7-monoclonal

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antibodies (MAbs) on silver nanoparticle-graphene as trace labels. The designed biosensor exhibited LOD of 1.6 pg/mL with 1.6 × 10− 3 to 16 ng/mL dynamic working range.123 ( 4) Chen et al. developed an rGO-based FET biosensor owing to semiconductor characteristics of graphene for the detection of Ebola virus. Silicon wafer was used to pattern the Au electrodes on the surface. The test region was modified by chemically adsorbing GO at the concentration of 0.1 mg/mL on the electrode surface. The attached GO was then thermally annealed in the presence of argon gas; under an applied temperature of 400°C, the GO was reduced to rGO. To passivate the surface, Al2O3 of approximate thickness of 3 nm was deposited by atomic layer deposition followed by gold deposition by sputtering. Finally, the Ebola virus antibodies at a concentration of 0.2 μg/μL in PBS were immobilized to detect the glycoprotein of the Ebola virus in human plasma, serum, and PBS buffer.124 ( 5) Samavati et al. designed a probe using Au and fiber Bragg grating modified with GO nanoparticles. The probe was able to detect the COVID-19 virus in the saliva of six patients of an average age of 58.5 years old. The infection was detected by measuring changes in the wavelength of light with the insertion of a probe in the patients’ saliva.125

4.6 Conclusions Applications of graphene-based biosensors face many challenges. For example, the precise size of graphene’s dimension and its thickness are difficult to control. Graphene is easy to aggregate, which leads to the thickening of slice layers, and the layers can even turn into graphite. As a result, it is very important to develop new control and regulation systems for the synthesis of graphene. Moreover, converting graphene to GO usually leads to disruption of the electron transport properties of graphene. More focus is required to modulate the surface chemistry whilst converting the graphene to GO and rGO. These studies will help us understand graphene more clearly and encourage us to promote the development of graphene-based nucleic acid and protein biosensors. Furthermore, graphene has been reported for antimicrobial efficacy120 and antiviral activity.119 As a result, graphene-based modified advanced sensor platforms could be developed to generate wearable flexible sensor arrays on textile and clothing to detect and reduce the risk of deadly and infectious diseases like COVID-19.

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References 1. Novoselov, K. S.; Geim, A. K.; Morozov, S. V.; Jiang, D.; Zhang, Y.; Dubonos, S. V.; Grigorieva, I. V.; Firsov, A. A. Electric Field Effect in Atomically Thin Carbon Films. Science 2004, 306 (5696), 666–669. 2. Guan, S.; Wang, J.; Fang, Y. Transparent Graphene Bioelectronics as a New Tool for Multimodal Neural Interfaces. Nano Today 2019, 26, 13–15. 3. Nara, S.; Kandpal, R.; Jaiswal, V.; Augustine, S.; Wahie, S.; Sharma, J. G.; Takeuchi, R.; Takenaka, S.; Malhotra, B. D. Exploring Providencia rettgeri for Application to EcoFriendly Paper Based Microbial Fuel Cell. Biosens. Bioelectron. 2020, 165, 112323. 4. Georgakilas, V.; Otyepka, M.; Bourlinos, A. B.; Chandra, V.; Kim, N.; Kemp, K. C.; Hobza, P.; Zboril, R.; Kim, K. S. Functionalization of Graphene: Covalent and Non-covalent Approaches, Derivatives and Applications. Chem. Rev. 2012, 112 (11), 6156–6214. 5. Janegitz, B. C.; Silva, T. A.; Wong, A.; Ribovski, L.; Vicentini, F. C.; Sotomayor, M. D. P. T.; Fatibello-Filho, O. The Application of Graphene for In Vitro and In Vivo Electrochemical Biosensing. Biosens. Bioelectron. 2017, 89, 224–233. 6. Kumar, S.; Kumar, S.; Srivastava, S.; Yadav, B. K.; Lee, S. H.; Sharma, J. G.; Doval, D. C.; Malhotra, B. D. Reduced Graphene Oxide Modified Smart Conducting Paper for cancer Biosensor. Biosens. Bioelectron. 2015, 73, 114–122. 7. Bai, Y.; Xu, T.; Zhang, X. Graphene-Based Biosensors for Detection of Biomarkers. Micromachines 2020, 11 (1), 60. 8. Ando, T. The Electronic Properties of Graphene and Carbon Nanotubes. NPG Asia Mater. 2009, 1 (1), 17–21. 9. Zaaba, N.; Foo, K.; Hashim, U.; Tan, S.; Liu, W.-W.; Voon, C. Synthesis of Graphene Oxide Using Modified Hummers Method: Solvent Influence. Procedia Eng. 2017, 184, 469–477. 10. Silva, R. A.; Souza, M. L.; Bloisi, G. D.; Corio, P.; Petri, D. F. Bioconjugation of Lipase and Cholesterol Oxidase with Graphene or Graphene Oxide. J. Nanopart. Res. 2015, 17 (4), 1–12. 11. Robinson, J. T.; Perkins, F. K.; Snow, E. S.; Wei, Z.; Sheehan, P. E. Reduced Graphene Oxide Molecular Sensors. Nano Lett. 2008, 8 (10), 3137–3140. 12. Lu, X.; Miodek, A.; Munief, W.-M.; Jolly, P.; Pachauri, V.; Chen, X.; Estrela, P.; Ingebrandt, S. Reduced Graphene-Oxide Transducers for Biosensing Applications beyond the Debye-Screening Limit. Biosens. Bioelectron. 2019, 130, 352–359. 13. Peña-Bahamonde, J.; Nguyen, H. N.; Fanourakis, S. K.; Rodrigues, D. F. Recent Advances in Graphene-Based Biosensor Technology with Applications in Life Sciences. J. Nanobiotechnol. 2018, 16 (1), 1–17. 14. Goldsmith, B. R.; Locascio, L.; Gao, Y.; Lerner, M.; Walker, A.; Lerner, J.; Kyaw, J.; Shue, A.; Afsahi, S.; Pan, D. Digital Biosensing by Foundry-Fabricated Graphene Sensors. Sci. Rep. 2019, 9 (1), 1–10. 15. Hwang, M. T.; Heiranian, M.; Kim, Y.; You, S.; Leem, J.; Taqieddin, A.; Faramarzi, V.; Jing, Y.; Park, I.; Van Der Zande, A. M. Ultrasensitive Detection of Nucleic Acids Using Deformed Graphene Channel Field Effect Biosensors. Nat. Commun. 2020, 11 (1), 1–11. 16. Tan, Y.; Li, Y.; Tang, F. Nucleic Acid Aptamer: a Novel Potential Diagnostic and Therapeutic Tool for Leukemia. Onco. Targets. Ther. 2019, 12, 10597. 17. Sohrabi, N.; Valizadeh, A.; Farkhani, S. M.; Akbarzadeh, A. Basics of DNA Biosensors and cancer Diagnosis. Artif. Cells Nanomed. Biotechnol. 2016, 44 (2), 654–663. 18. Liu, F.; Jenssen, T.-K.; Trimarchi, J.; Punzo, C.; Cepko, C. L.; Ohno-Machado, L.; Hovig, E.; Kuo, W. P. Comparison of Hybridization-Based and Sequencing-Based Gene Expression Technologies on Biological Replicates. BMC Genomics 2007, 8 (1), 1–14.

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19. Davis, F.; Higson, S. Biosensors for DNA and RNA Detection and Characterization. In Biosensors for Medical Applications; Elsevier, 2012; pp. 163–190. 20. Liang, H.; Zhang, X.-B.; Lv, Y.; Gong, L.; Wang, R.; Zhu, X.; Yang, R.; Tan, W. Functional DNA-Containing Nanomaterials: Cellular Applications in Biosensing, Imaging, and Targeted Therapy. Acc. Chem. Res. 2014, 47 (6), 1891–1901. 21. Teles, F.; Fonseca, L. Trends in DNA Biosensors. Talanta 2008, 77 (2), 606–623. 22. Zhang, Q.; Hao, T.; Hu, D.; Guo, Z.; Wang, S.; Hu, Y. RNA Aptamer-Driven ECL Biosensing for Tracing Histone Acetylation Based on Nano-Prism Substrate and Cascade DNA Amplification Strategy. Electrochim. Acta 2020, 356, 136828. 23. Wang, L.; Wu, A.; Wei, G. Graphene-Based Aptasensors: from Molecule–Interface Interactions to Sensor Design and Biomedical Diagnostics. Analyst 2018, 143 (7), 1526–1543. 24. Shekari, Z.; Zare, H. R.; Falahati, A. Dual Assaying of Breast cancer Biomarkers by Using a Sandwich–Type Electrochemical Aptasensor Based on a Gold Nanoparticles–3D Graphene Hydrogel Nanocomposite and Redox Probes Labeled Aptamers. Sens. Actuators B 2021, 129515. 25. Wu, Y.; Su, H.; Yang, J.; Wang, Z.; Li, D.; Sun, H.; Guo, X.; Yin, S. Photoelectrochemical Immunosensor for Sensitive Detection of Alpha-Fetoprotein Based on a Graphene Honeycomb Film. J. Colloid Interface Sci. 2020, 580, 583–591. 26. Kudr, J.; Zhao, L.; Nguyen, E. P.; Arola, H.; Nevanen, T. K.; Adam, V.; Zitka, O.; Merkoçi, A. Inkjet-Printed Electrochemically Reduced Graphene Oxide Microelectrode as a Platform for HT-2 Mycotoxin Immunoenzymatic Biosensing. Biosens. Bioelectron. 2020, 156, 112109. 27. Zhang, G.; Liu, Z.; Fan, L.; Han, Y.; Guo, Y. A Novel Dual Signal and Label-Free Electrochemical Aptasensor for Mucin 1 Based on Hemin/Graphene@ PdPtNPs. Biosens. Bioelectron. 2021, 173, 112785. 28. Ohno, Y.; Maehashi, K.; Matsumoto, K. Label-Free Biosensors Based on Aptamer-Modified Graphene Field-Effect Transistors. J. Am. Chem. Soc. 2010, 132 (51), 18012–18013. 29. Nara, S.; Malhotra, B. D. Applications of Immuno-electrochemical Detection Strategies for Food Analysis. In Rapid Antibody-based Technologies in Food Analysis; Royal Society of Chemistry (RSC), 2019; pp. 154–174. 30. Krishnan, S. K.; Singh, E.; Singh, P.; Meyyappan, M.; Nalwa, H. S. A Review on Graphene-Based Nanocomposites for Electrochemical and Fluorescent Biosensors. RSC Adv. 2019, 9 (16), 8778–8881. 31. Wang, J. Survey and Summary: from DNA Biosensors to Gene Chips. Nucleic Acids Res. 2000, 28 (16), 3011–3016. 32. Mujica, M. L.; Zhang, Y.; Gutiérrez, F.; Bedioui, F.; Rivas, G. Non-amplified Impedimetric Genosensor for Quantification of miRNA-21 Based on the Use of Reduced Graphene Oxide Modified with Chitosan. Microchem. J. 2021, 160, 105596. 33. Han, J.; Wu, J.; Du, J. Fluorescent DNA Biosensor for Single-Base Mismatch Detection Assisted by Cationic Comb-Type Copolymer. Molecules 2019, 24 (3), 575. 34. Mohammadi, S.; Khoeini, F.; Esmailpour, M.; Esmailpour, A.; AkbariMoghanjoughi, M. Tunable Transport Properties in Graphene-DNA and Silicene-DNA by Controlling the Thickness of Nanopores. Chem. Phys. 2021, 541, 111048. 35. Burke, D. H.; Gold, L. RNA Aptamers to the Adenosine Moiety of S-Adenosyl Methionine: Structural Inferences from Variations on a Theme and the Reproducibility of SELEX. Nucleic Acids Res. 1997, 25 (10), 2020–2024. 36. Liu, L.; Zhai, J.; Zhu, C.; Han, L.; Ren, W.; Dong, S. One-Step Synthesis of Functional pNR/rGO Composite as a Building Block for Enhanced Ascorbic Acid Biosensing. Anal. Chim. Acta 2017, 981, 34–40.

Chapter 4  Graphene-Based Biosensors for Detection  101

37. Ni, S.; Qiao, L.; Shen, Z.; Gao, Y.; Liu, G. Physical Absorption Vs Covalent Binding of Graphene Oxide on Glassy Carbon Electrode toward a Robust Aptasensor for Ratiometric Electrochemical Detection of Vascular Endothelial Growth Factor (VEGF) in Serum. Electrochim. Acta 2020, 331, 135321. 38. Zinoubi, K.; Chrouda, A.; Soltane, R.; Al‐Ghamdi, Y. O.; Garallah Almalki, S.; Osman, G.; Barhoumi, H.; Jaffrezic Renault, N. Highly Sensitive Impedimetric Biosensor Based on Thermolysin Immobilized on a GCE Modified with AuNP‐Decorated Graphene for the Detection of Ochratoxin A. Electroanalysis 2021, 33 (1), 136–145. 39. Bonanni, A.; Ambrosi, A.; Pumera, M. Nucleic Acid Functionalized Graphene for Biosensing. Chem. A Eur. J. 2012, 18 (6), 1668–1673. 40. Xu, H.; Yang, Q.; Li, F.; Tang, L.; Gao, S.; Jiang, B.; Zhao, X.; Wang, L.; Fan, C. A Graphene-Based Platform for Fluorescent Detection of SNPs. Analyst 2013, 138 (9), 2678–2682. 41. Tian, M.; Xu, S.; Zhang, J.; Wang, X.; Li, Z.; Liu, H.; Song, R.; Yu, Z.; Wang, J. RNA Detection Based on Graphene Field-Effect Transistor Biosensor. Adv. Condens. Matter Phys. 2018, 2018. 42. Chen, S. L.; Hung, C.-S.; Xu, J.; Reigstad, C. S.; Magrini, V.; Sabo, A.; Blasiar, D.; Bieri, T.; Meyer, R. R.; Ozersky, P. Identification of Genes Subject to Positive Selection in Uropathogenic Strains of Escherichia coli: A Comparative Genomics Approach. Proc. Natl. Acad. Sci. 2006, 103 (15), 5977–5982. 43. Shen, G.-B.; Kan, Y.-J.; Chen, M.-H.; Chen, Y.-F. Study of ss-DNA Adsorption and Nano-Mechanical Properties on Mica Substrate with Surface Forces Apparatus. Chin. J. Mech. Eng. 2018, 31 (1), 1–8. 44. Akca, S.; Foroughi, A.; Frochtzwajg, D.; Postma, H. W. C. Competing Interactions in DNA Assembly on Graphene. PLoS One 2011, 6 (4), e18442. 45. Yun, J. M.; Kim, K. N.; Kim, J. Y.; Shin, D. O.; Lee, W. J.; Lee, S. H.; Lieberman, M.; Kim, S. O. DNA Origami Nanopatterning on Chemically Modified Graphene. Angew. Chem. Int. Ed. 2012, 51 (4), 912–915. 46. Zhao, X. Self-Assembly of DNA Segments on Graphene and Carbon Nanotube Arrays in Aqueous Solution: a Molecular Simulation Study. J. Phys. Chem. C 2011, 115 (14), 6181–6189. 47. Chen, J.; Chen, L.; Wang, Y.; Chen, S. Molecular Dynamics Simulations of the Adsorption of DNA Segments onto Graphene Oxide. J. Phys. D Appl. Phys. 2014, 47 (50), 505401. 48. Sun, W.; Qi, X.; Zhang, Y.; Yang, H.; Gao, H.; Chen, Y.; Sun, Z. Electrochemical DNA Biosensor for the Detection of Listeria monocytogenes with Dendritic Nanogold and Electrochemical Reduced Graphene Modified Carbon Ionic Liquid Electrode. Electrochim. Acta 2012, 85, 145–151. 49. Hughes, Z. E.; Tomásio, S. M.; Walsh, T. R. Efficient Simulations of the Aqueous Bio-Interface of Graphitic Nanostructures with a Polarisable Model. Nanoscale 2014, 6 (10), 5438–5448. 50. Soganci, K.; Bingol, H.; Zor, E. Simply Patterned Reduced Graphene Oxide as an Effective Biosensor Platform for Glucose Determination. J. Electroanal. Chem. 2020, 114801. 51. Chial, H. DNA Sequencing Technologies key to the Human Genome Project. Nat. Educ. 2008, 1 (1). 52. Wu, Y.; Yang, J.; Zheng, Z.; Li, Z.; Lu, F.; Chen, Y.; Gao, W. Three-Dimensional TriSNSs-Layered Electrodeposited Reduced Graphene Oxide for ECL Biosensing of DNA. Talanta 2018, 188, 58–65. 53. Prasongkit, J.; Grigoriev, A.; Pathak, B.; Ahuja, R.; Scheicher, R. H. Transverse Conductance of DNA Nucleotides in a Graphene Nanogap from First Principles. Nano Lett. 2011, 11 (5), 1941–1945. 54. Postma, H. W. C. Rapid Sequencing of Individual DNA Molecules in Graphene Nanogaps. Nano Lett. 2010, 10 (2), 420–425.

102  Chapter 4  Graphene-Based Biosensors for Detection

55. Wang, J. PNA Biosensors for Nucleic Acid Detection. Curr. Issues Mol. Biol. 1999, 1, 117–122. 56. Pellestor, F.; Paulasova, P. The Peptide Nucleic Acids (PNAs), Powerful Tools for Molecular Genetics and Cytogenetics. Eur. J. Hum. Genet. 2004, 12 (9), 694–700. 57. Tian, M.; Qiao, M.; Shen, C.; Meng, F.; Frank, L. A.; Krasitskaya, V. V.; Wang, T.; Zhang, X.; Song, R.; Li, Y. Highly-Sensitive Graphene Field Effect Transistor Biosensor Using PNA and DNA Probes for RNA Detection. Appl. Surf. Sci. 2020, 527, 146839. 58. Moretta, R.; Terracciano, M.; Borbone, N.; Oliviero, G.; Schiattarella, C.; Piccialli, G.; Falanga, A. P.; Marzano, M.; Dardano, P.; De Stefano, L. PNA-Based Graphene Oxide/Porous Silicon Hybrid Biosensor: toward a Label-Free Optical Assay for Brugada Syndrome. Nanomaterials 2020, 10 (11), 2233. 59. Zaid, M. H. M.; Abdullah, J.; Yusof, N. A.; Sulaiman, Y.; Wasoh, H.; Noh, M. F. M.; Issa, R. PNA Biosensor Based on Reduced Graphene Oxide/Water Soluble Quantum Dots for the Detection of Mycobacterium tuberculosis. Sens. Actuators B 2017, 241, 1024–1034. 60. Park, J. S.; Baek, A.; Park, I.-S.; Jun, B.-H.; Kim, D.-E. A Graphene Oxide-Based Platform for the Assay of RNA Synthesis by RNA Polymerase Using a Fluorescent Peptide Nucleic Acid Probe. Chem. Commun. 2013, 49 (80), 9203–9205. 61. Pumera, M. Graphene in Biosensing. Mater. Today 2011, 14 (7–8), 308–315. 62. Sandil, D.; Srivastava, S.; Malhotra, B.; Sharma, S.; Puri, N. K. Biofunctionalized Tungsten Trioxide-Reduced Graphene Oxide Nanocomposites for Sensitive Electrochemical Immunosensing of Cardiac Biomarker. J. Alloys Compd. 2018, 763, 102–110. 63. Stepanenko, O. V.; Verkhusha, V. V.; Kuznetsova, I. M.; Uversky, V. N.; Turoverov, K. Fluorescent Proteins as Biomarkers and Biosensors: Throwing Color Lights on Molecular and Cellular Processes. Curr. Protein Pept. Sci. 2008, 9 (4), 338–369. 64. Xu, L.; Wen, Y.; Pandit, S.; Mokkapati, V. R.; Mijakovic, I.; Li, Y.; Ding, M.; Ren, S.; Li, W.; Liu, G. Graphene-Based Biosensors for the Detection of Prostate cancer Protein Biomarkers: a Review. BMC Chem. 2019, 13 (1), 1–12. 65. Healy, D. A.; Hayes, C. J.; Leonard, P.; McKenna, L.; O’Kennedy, R. Biosensor Developments: Application to Prostate-Specific Antigen Detection. Trends Biotechnol. 2007, 25 (3), 125–131. 66. Chornokur, G.; Arya, S. K.; Phelan, C.; Tanner, R.; Bhansali, S. Impedance-Based Miniaturized Biosensor for Ultrasensitive and Fast Prostate-Specific Antigen Detection. J. Sens. 2011, 2011. 67. Singh, N.; Ali, M. A.; Rai, P.; Ghori, I.; Sharma, A.; Malhotra, B.; John, R. DualModality Microfluidic Biosensor Based on Nanoengineered Mesoporous Graphene Hydrogels. Lab Chip 2020, 20 (4), 760–777. 68. Kanai, Y.; Ohmuro-Matsuyama, Y.; Tanioku, M.; Ushiba, S.; Ono, T.; Inoue, K.; Kitaguchi, T.; Kimura, M.; Ueda, H.; Matsumoto, K. Graphene Field Effect Transistor-Based Immunosensor for Ultrasensitive Noncompetitive Detection of Small Antigens. ACS Sensors 2020, 5 (1), 24–28. 69. Nie, S.; Wang, Z.; Moscoso-Castro, M.; D'Souza, P.; Lei, C.; Xu, J.; Gu, J. Biology Drives the Discovery of Bispecific Antibodies as Innovative Therapeutics. Antib. Ther. 2020, 3 (1), 18–62. 70. Williams, A. F.; Barclay, A. N. The Immunoglobulin Superfamily—Domains for Cell Surface Recognition. Annu. Rev. Immunol. 1988, 6 (1), 381–405. 71. Harpaz, Y.; Chothia, C. Many of the Immunoglobulin Superfamily Domains in Cell Adhesion Molecules and Surface Receptors Belong to a New Structural Set which Is Close to that Containing Variable Domains. J. Mol. Biol. 1994, 238 (4), 528–539. 72. Wang, C.-F.; Sun, X.-Y.; Su, M.; Wang, Y.-P.; Lv, Y.-K. Electrochemical Biosensors Based on Antibody, Nucleic Acid and Enzyme Functionalized Graphene for the Detection of Disease-Related Biomolecules. Analyst 2020, 145 (5), 1550–1562.

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73. Fischer, M. J. Amine Coupling Through EDC/NHS: A Practical Approach. In Surface Plasmon Resonance; Springer, 2010; pp. 55–73. 74. Srivastava, S.; Abraham, S.; Singh, C.; Ali, M. A.; Srivastava, A.; Sumana, G.; Malhotra, B. D. Protein Conjugated Carboxylated Gold@ Reduced Graphene Oxide for Aflatoxin B 1 Detection. RSC Adv. 2015, 5 (7), 5406–5414. 75. Taniselass, S.; Arshad, M. M.; Gopinath, S. C. Graphene-Based Electrochemical Biosensors for Monitoring Noncommunicable Disease Biomarkers. Biosens. Bioelectron. 2019, 130, 276–292. 76. Morais, A. L.; Rijo, P.; Hernán, B.; Nicolai, M. Biomolecules and Electrochemical Tools in Chronic Non-Communicable Disease Surveillance: a Systematic Review. Biosensors 2020, 10 (9), 121. 77. Steigmann, L.; Maekawa, S.; Sima, C.; Travan, S.; Wang, C.-W.; Giannobile, W. V. Biosensor and Lab-on-a-Chip Biomarker-Identifying Technologies for Oral and Periodontal Diseases. Front. Pharmacol. 2020, 11, 1663. 78. Chaubey, A.; Malhotra, B. Mediated Biosensors. Biosens. Bioelectron. 2002, 17 (6–7), 441–456. 79. Ali, M. A.; Hu, C.; Jahan, S.; Yuan, B.; Saleh, M. S.; Ju, E.; Gao, S. J.; Panat, R. Sensing of COVID‐19 Antibodies in Seconds via Aerosol Jet Nanoprinted Reduced‐Graphene‐Oxide‐Coated 3D Electrodes. Adv. Mater. 2020, 2006647. 80. Torrente-Rodríguez, R. M.; Lukas, H.; Tu, J.; Min, J.; Yang, Y.; Xu, C.; Rossiter, H. B.; Gao, W. SARS-CoV-2 RapidPlex: A Graphene-Based Multiplexed Telemedicine Platform for Rapid and Low-Cost COVID-19 Diagnosis and Monitoring. Matter 2020, 3 (6), 1981–1998. 81. Seo, G.; Lee, G.; Kim, M. J.; Baek, S.-H.; Choi, M.; Ku, K. B.; Lee, C.-S.; Jun, S.; Park, D.; Kim, H. G. Rapid Detection of COVID-19 Causative Virus (SARS-CoV-2) in Human Nasopharyngeal Swab Specimens Using Field-Effect Transistor-Based Biosensor. ACS Nano 2020, 14 (4), 5135–5142. 82. Liu, X.; Wang, J.; Xu, X.; Liao, G.; Chen, Y.; Hu, C.-H. Patterns of IgG and IgM Antibody Response in COVID-19 Patients. Emerg. Microbes Infect. 2020, 9 (1), 1269–1274. 83. Yakoh, A.; Pimpitak, U.; Rengpipat, S.; Hirankarn, N.; Chailapakul, O.; Chaiyo, S. Based Electrochemical Biosensor for Diagnosing COVID-19: Detection of SARSCoV-2 Antibodies and Antigen. Biosens. Bioelectron. 2021, 176, 112912. 84. Nguyen, H. H.; Lee, S. H.; Lee, U. J.; Fermin, C. D.; Kim, M. Immobilized Enzymes in Biosensor Applications. Materials 2019, 12 (1), 121. 85. Shao, Y.; Wang, J.; Wu, H.; Liu, J.; Aksay, I. A.; Lin, Y. Graphene Based Electrochemical Sensors and Biosensors: a Review. Electroanalysis 2010, 22 (10), 1027–1036. 86. Jiang, B.; Zhou, K.; Wang, C.; Sun, Q.; Yin, G.; Tai, Z.; Wilson, K.; Zhao, J.; Zhang, L. Label-Free Glucose Biosensor Based on Enzymatic Graphene OxideFunctionalized Tilted fiber Grating. Sens. Actuators B 2018, 254, 1033–1039. 87. Rocchitta, G.; Spanu, A.; Babudieri, S.; Latte, G.; Madeddu, G.; Galleri, G.; Nuvoli, S.; Bagella, P.; Demartis, M. I.; Fiore, V. Enzyme Biosensors for Biomedical Applications: Strategies for Safeguarding Analytical Performances in Biological Fluids. Sensors 2016, 16 (6), 780. 88. Chen, L.-Q.; Zhang, X.-E.; Xie, W.-H.; Zhou, Y.-F.; Zhang, Z.-P.; Cass, A. E. Genetic Modification of Glucose Oxidase for Improving Performance of an Amperometric Glucose Biosensor. Biosens. Bioelectron. 2002, 17 (10), 851–857. 89. Olshefsky, A.; Shehata, L.; Kuldell, N. Site-Directed Mutagenesis to Improve Sensitivity of a Synthetic Two-Component Signaling System. PLoS One 2016, 11 (1), e0147494. 90. Paternolli, C.; Antonini, M.; Ghisellini, P.; Nicolini, C. Recombinant Cytochrome P450 Immobilization for Biosensor Applications. Langmuir 2004, 20 (26), 11706–11712.

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91. Armetta, J.; Berthome, R.; Cros, A.; Pophillat, C.; Colombo, B. M.; Pandi, A.; Grigoras, I. Biosensor-Based Enzyme Engineering Approach Applied to Psicose Biosynthesis. Synth. Biol. 2019, 4 (1), ysz028. 92. Mohamad, N. R.; Marzuki, N. H. C.; Buang, N. A.; Huyop, F.; Wahab, R. A. An Overview of Technologies for Immobilization of Enzymes and Surface Analysis Techniques for Immobilized Enzymes. Biotechnol. Biotechnol. Equip. 2015, 29 (2), 205–220. 93. Zhang, J.; Zhang, F.; Yang, H.; Huang, X.; Liu, H.; Zhang, J.; Guo, S. Graphene Oxide as a Matrix for Enzyme Immobilization. Langmuir 2010, 26 (9), 6083–6085. 94. Marcuello, C.; De Miguel, R.; Gómez-Moreno, C.; Martinez-Julvez, M.; Lostao, A. An Efficient Method for Enzyme Immobilization Evidenced by Atomic Force Microscopy. Protein Eng. Des. Sel. 2012, 25 (11), 715–723. 95. Ashrafi, A. M.; Sýs, M.; Sedláčková, E.; Shaaban Farag, A.; Adam, V.; Přibyl, J.; Richtera, L. Application of the Enzymatic Electrochemical Biosensors for Monitoring Non-competitive Inhibition of Enzyme Activity by Heavy Metals. Sensors 2019, 19 (13), 2939. 96. Luong, A.-D.; Roy, I.; Malhotra, B. D.; Luong, J. H. Analytical and Biosensing Platforms for Insulin: A Review. Sens. Actuators Rep. 2021, 100028. 97. Slaughter, G.; Kulkarni, T. Detection of Human Plasma Glucose Using a SelfPowered Glucose Biosensor. Energies 2019, 12 (5), 825. 98. Saini, D.; Chauhan, R.; Solanki, P. R.; Basu, T. Gold-Nanoparticle Decorated Graphene-Nanostructured Polyaniline Nanocomposite-Based Bienzymatic Platform for Cholesterol Sensing. Int. Sch. Res. Notices 2012, 2012. 99. Fritea, L.; Tertis, M.; Sandulescu, R.; Cristea, C. Enzyme–Graphene Platforms for Electrochemical Biosensor Design with Biomedical Applications. Methods Enzymol. 2018, 609, 293–333. 100. Malhotra, B. D.; Chaubey, A. Biosensors for Clinical Diagnostics Industry. Sens. Actuators B 2003, 91 (1–3), 117–127. 101. Walsh, J.; Roberts, R.; Vigersky, R. A.; Schwartz, F. New Criteria for Assessing the Accuracy of Blood Glucose Monitors Meeting, October 28, 2011; SAGE Publications, 2012. 102. Klonoff, D. C. Point-of-Care Blood Glucose Meter Accuracy in the Hospital Setting. Diabetes Spectr. 2014, 27 (3), 174–179. 103. Pandey, C. M.; Augustine, S.; Kumar, S.; Kumar, S.; Nara, S.; Srivastava, S.; Malhotra, B. D. Microfluidics Based Point‐of‐Care Diagnostics. Biotechnol. J. 2018, 13 (1), 1700047. 104. Marzo, A. M. L.; Mayorga-Martinez, C. C.; Pumera, M. 3D-Printed Graphene Direct electron Transfer Enzyme Biosensors. Biosens. Bioelectron. 2020, 151, 111980. 105. Wang, H.; Wu, X.; Dong, P.; Wang, C.; Wang, J.; Liu, Y.; Chen, J. Electrochemical Biosensor Based on Interdigitated Electrodes for Determination of Thyroid Stimulating Hormone. Int. J. Electrochem. Sci. 2014, 9 (1), 12. 106. Pinyou, P.; Conzuelo, F.; Sliozberg, K.; Vivekananthan, J.; Contin, A.; Pöller, S.; Plumeré, N.; Schuhmann, W. Coupling of an Enzymatic Biofuel Cell to an Electrochemical Cell for Self-Powered Glucose Sensing with Optical Readout. Bioelectrochemistry 2015, 106, 22–27. 107. Luka, G.; Ahmadi, A.; Najjaran, H.; Alocilja, E.; DeRosa, M.; Wolthers, K.; Malki, A.; Aziz, H.; Althani, A.; Hoorfar, M. Microfluidics Integrated Biosensors: a Leading Technology toward Lab-on-a-Chip and Sensing Applications. Sensors 2015, 15 (12), 30011–30031. 108. Wei, Z.; Huang, J.; Li, J.; Xu, G.; Ju, Z.; Liu, X.; Ni, X. A High-Sensitivity Microfluidic Sensor Based on a Substrate Integrated Waveguide Re-Entrant Cavity for Complex Permittivity Measurement of Liquids. Sensors 2018, 18 (11), 4005.

Chapter 4  Graphene-Based Biosensors for Detection  105

109. Konwar, A. N.; Borse, V. Current Status of Point-of-Care Diagnostic Devices in the Indian Healthcare System with an Update on COVID-19 Pandemic. Sens. Int. 2020, 100015. 110. Bauer, M.; Wunderlich, L.; Weinzierl, F.; Lei, Y.; Duerkop, A.; Alshareef, H. N.; Baeumner, A. J. Electrochemical Multi-Analyte Point-of-Care Perspiration Sensors Using on-Chip Three-Dimensional Graphene Electrodes. Anal. Bioanal. Chem. 2020, 1–15. 111. Shin, Y. C.; Kang, S. H.; Lee, J. H.; Kim, B.; Hong, S. W.; Han, D.-W. ThreeDimensional Graphene Oxide-Coated Polyurethane Foams Beneficial to Myogenesis. J. Biomater. Sci. Polym. Ed. 2018, 29 (7–9), 762–774. 112. Hashemzadeh, H.; Allahverdi, A.; Sedghi, M.; Vaezi, Z.; Tohidi Moghadam, T.; Rothbauer, M.; Fischer, M. B.; Ertl, P.; Naderi-Manesh, H. PDMS Nano-Modified Scaffolds for Improvement of Stem Cells Proliferation and Differentiation in Microfluidic Platform. Nanomaterials 2020, 10 (4), 668. 113. Oshin, O.; Kireev, D.; Akinwande, D.; Adetiba, E.; Idachaba, F.; Atayero, A. Advancing PoC Devices for Early Disease Detection using Graphene-based Sensors. J. Phys. Conf. Ser. 2019, 032031. IOP Publishing. 114. Thangamuthu, M.; Hsieh, K. Y.; Kumar, P. V.; Chen, G.-Y. Graphene-and Graphene Oxide-Based Nanocomposite Platforms for Electrochemical Biosensing Applications. Int. J. Mol. Sci. 2019, 20 (12), 2975. 115. Viswanathan, S.; Narayanan, T. N.; Aran, K.; Fink, K. D.; Paredes, J.; Ajayan, P. M.; Filipek, S.; Miszta, P.; Tekin, H. C.; Inci, F. Graphene–Protein Field Effect Biosensors: Glucose Sensing. Mater. Today 2015, 18 (9), 513–522. 116. Kiechle, F. L.; Holland, C. A. Point-of-Care Testing and Molecular Diagnostics: Miniaturization Required. Clin. Lab. Med. 2009, 29 (3), 555–560. 117. Jaiswal, N.; Pandey, C. M.; Soni, A.; Tiwari, I.; Rosillo-Lopez, M.; Salzmann, C. G.; Malhotra, B. D.; Sumana, G. Electrochemical Genosensor Based on Carboxylated Graphene for Detection of Water-Borne Pathogen. Sens. Actuators B 2018, 275, 312–321. 118. Morales-Narváez, E.; Dincer, C. The Impact of Biosensing in a Pandemic Outbreak: COVID-19. Biosens. Bioelectron. 2020, 163, 112274. 119. Ye, S.; Shao, K.; Li, Z.; Guo, N.; Zuo, Y.; Li, Q.; Lu, Z.; Chen, L.; He, Q.; Han, H. Antiviral Activity of Graphene Oxide: How Sharp Edged Structure and Charge Matter. ACS Appl. Mater. Interfaces 2015, 7 (38), 21571–21579. 120. Al-Thani, R. F.; Patan, N. K.; Al-Maadeed, M. A. Graphene Oxide as Antimicrobial Against Two Gram-Positive and Two Gram-Negative Bacteria in Addition to One Fungus. Online J. Biol. Sci. 2014, 14, 230–239. 121. Afsahi, S.; Lerner, M. B.; Goldstein, J. M.; Lee, J.; Tang, X.; Bagarozzi, D. A., Jr.; Pan, D.; Locascio, L.; Walker, A.; Barron, F. Novel Graphene-Based Biosensor for Early Detection of Zika Virus Infection. Biosens. Bioelectron. 2018, 100, 85–88. 122. Joshi, S. R.; Sharma, A.; Kim, G.-H.; Jang, J. Low Cost Synthesis of Reduced Graphene Oxide Using Biopolymer for Influenza Virus Sensor. Mater. Sci. Eng. C 2020, 108, 110465. 123. Huang, J.; Xie, Z.; Xie, Z.; Luo, S.; Xie, L.; Huang, L.; Fan, Q.; Zhang, Y.; Wang, S.; Zeng, T. Silver Nanoparticles Coated Graphene Electrochemical Sensor for the Ultrasensitive Analysis of Avian Influenza Virus H7. Anal. Chim. Acta 2016, 913, 121–127. 124. Chen, Y.; Ren, R.; Pu, H.; Guo, X.; Chang, J.; Zhou, G.; Mao, S.; Kron, M.; Chen, J. Field-Effect Transistor Biosensor for Rapid Detection of Ebola Antigen. Sci. Rep. 2017, 7 (1), 1–8. 125. Samavati, A.; Samavati, Z.; Velashjerdi, M.; Ismail, A. F.; Othman, M.; Abdullah, M. S.; Bolurian, M.; Bolurian, M. Sustainable and Fast Saliva-Based COVID-19 Virus Diagnosis Kit Using a Novel GO-Decorated Au/FBG Sensor. Chem. Eng. J. 2020, 127655.

Graphene-Based Wearable Biosensors

5

5.1 Introduction Small portable electronic devices containing a sensing element within or over the body like bioimplants, tattoos, gloves, textiles, etc. are called wearable biosensors.1 These are biosensing devices that enable non-invasive monitoring through chemical analysis of biological fluids. Wearable technology has emerged as an alternative to biomedical devices in which in vivo biosensing is used in contrary to external blood sample testing. The wearable flexible biosensing technology is basically a conversion of sophisticated and bulky biomedical devices to an individual self-centred system.2 These are known to generate reactions and two-way feedback between patients and physicians for health management and can also be utilized for food safety and sports purposes.3 Initially, the technology of wearable sensors was developed only for generating physical sensors to monitor body movements and other related vital signs of body activity, for example, calories burned during body movements, heart rate, etc.4 Nowadays, more sophisticated wearable biosensors based on the development of new body attachments are produced. These are in high demand because of their easy wearability and simplicity.5 The new technologies developed with the exploration of new materials and software interfaces have enabled the wearable biosensors to become more user friendly by translating the monitored physiological information into the digital form6 (Fig. 5.1).7 Further, wearable biosensors can be classified broadly into three categories based on the human dynamic studies8: biophysical sensors, wearable motion state sensors, and biochemical sensors. Biophysical sensors can be used to measure electrophysiological signals, which are electrical signals generated by nerve cells, these are monitored and recorded by some implanted microelectrodes and then amplified to measure signals9 (more details are given in Section 5.3.1). To conduct real-time monitoring of physical parameters of the human body including sleep, the manner in which a person walks, muscle r­ igidity, and so Graphene Based Biomolecular Electronic Devices. https://doi.org/10.1016/B978-0-12-821541-8.00002-0 Copyright © 2023 Elsevier Inc. All rights reserved.

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108  Chapter 5  Graphene-Based Wearable Biosensors

Fig. 5.1  Ultra-flexible graphene field effect transistor (GFET) biosensor. (A) Schematic of the GFET biosensor fabricated on an ultrathin film. Photograph of the flexible device conformably attached onto the (B) human wrist and (C) artificial eyeball. (D) Stretchable biosensor can be stretched with activity of the human body. Reproduced with permission from Wang, Z.; Hao, Z.; Yu, S.; Huang, C.; Pan, Y.; Zhao, X. A Wearable and Deformable GrapheneBased Affinity Nanosensor for Monitoring of Cytokines in Biofluids. Nanomaterials 2020, 10 (8), 1503.

on where information is collected for the longer duration, motion state sensors are commonly used. The incorporation of techniques like microfluidics and lab-on-a-chip have enabled the simultaneous measurement and processing of a trace amount of samples.10 Here, connection with the physical body is required, such as with the skin, to measure parameters such as blood pressure, temperature, heart rate, etc.11 The wearable biochemical biosensors can dynamically monitor the bimolecular markers present in biological fluids such as interstitial fluids, sweat, saliva, tears, etc. for the presence of bacteria, metabolites, hormones, etc.12 These may be potentially useful for certain chronic diseases such as diabetes, which is caused by improper release of the insulin hormone resulting in reduced absorption of glucose from the blood. In diabetes, regular blood glucose monitoring is mandatory to maintain a stable glycaemic condition in blood with oral medication. The wearable biochemical biosensors work with the ability to ­recognize

Chapter 5  Graphene-Based Wearable Biosensors  109

and analyse analytes in non-invasive biofluids with the correlation of the concentration in a blood sample. Herein, the response given to the patient becomes useful for the diagnosis and treatment of ailment complications.13 Nevertheless, for clinical trials and acceptance, enough validation studies with critical evaluation are further required. There are many sectors involved in wearable sensing technology, and these mainly include the field of material science involving new innovations and advancements of material research, software technology with wireless communication systems, and identification of new biomarkers.12,14 Nowadays, in the context of materials, graphenebased flexible biosensors are gathering special interest owing to their interesting electric and mechanical properties enabling the monitoring of real-time parameters of physiological conditions with the ability to conform to a non-planar body surface. Moreover, the wireless flexible sensors are being developed to measure various other physical parameters like strain and pressure, which could correlate various biophysical characteristics and associated abnormalities.1 Some of the graphene-based wearable biosensing devices are given in Table 5.1. More details related to the design and applications of graphenebased flexible and stretchable electronic materials as wearable biosensors are described below.

5.2  Graphene-based flexible and stretchable materials Some of the superior properties of graphene allow its integration into various materials with stretchable and ductile characteristics, and thus can be used to develop wearable bioelectronic devices at a scalable level. The high mechanical strength of about 1 TPa Young’s modulus and fracture strain of about 25% make graphene a suitable material for non-planar body surfaces. Graphene has excellent electrical properties along with high electron mobility that enable high performance of the bioelectronic device. Furthermore, the piezoresistive sensitivity, along with good optical properties, contribute to the fabrication of transparent graphene electrodes for flexible devices1,25–28 (Fig. 5.2).29 However, the development of sensing tools that include stretching and flexible actuators depends largely on the production of new advanced materials and their structural design.30

5.2.1  Bio-integrated devices There are various well-established methods and techniques for fabricating graphene-based hybrid materials with desirable properties of body attachment and biosensing for developing bio-integrated devices.31

Field effect transistor (FET)-based flexible biosensor Graphene nanosensor printed on silk film

Flexible electrochemical biosensor

Photoelectrochemical biosensor with stable performance in bending condition

Electrochemical biosensor designed by immobilizing chitosan-glucose oxidase on electrode Flexible biosensor for the molecular recognition of DNA, lysozyme, Rhodamine 6 G

Electrochemical biosensor with capacitive characteristics

1.

3.

4.

5.

7.

6.

2.

Type

S. no.

Prussian blue/reduced graphene oxidebased designing of biosensor by screen printing technique

Aptamer-functionalized graphene as a conducting channel Silk bio-resorption result in direct transfer of graphene nanosensor on tooth enamel or tissue Graphene paper laden with nanoparticles of Au@Pt core-shell as a substrate for cell culture Flexible microelectrode sensor of graphene fibre formed by graphene sheets intercalated with nanoparticles of TiO2 Porous laser-induced graphene (LIG) and electrodeposited Pt nanoparticles-based electrode; surface modified with acetic acid treatment 3D graphene-based nanohybrids with silver nanoflowers

Graphene form

To detect glucose with the sensitivity of 4.622 μA mM−  1 and LOD >300 nM; dynamic linear range up to 2.1 mM Simulation study (VASP and COMSOL) indicated improved electromagnetic intensity by vertical coupling on nanohybrid layer To detect hydrogen peroxide and ascorbic acid

To detect urea with detection range of 0.01 to 1500 μM and lower limit of detection (LOD) of 1 nM

For real-time monitoring of nitric oxide (NO) secreted by cells

To monitor cytokines in biological fluids To detect pathogenic bacteria

Analyte

Table 5.1  Some of the graphene-based wearable biosensors.

20

19

18

17

16

15

7

References

8.

9.

10.

11.

12.

Flexible electrochemical biosensor with multi-sensing element; Pt@ Pd nanoparticles electrodeposited to detect glucose and polyaniline (PANI) was coated on the surface for pH detection Wearable enzyme-free glucose biosensor

LIG based electrode with spray coating of PEDOT:PSS; surface modified with Pt@Pd nanoparticles/PANI

Wireless pressure sensor to detect changes in frequency due to capacitance variation with physical movements Sensing platform fabricated using layer by layer deposition of material by vacuum filtration to form touch sensor Dual-functional wearable strain sensors and switches

Dielectric sponge of graphene/ polydimethylsiloxane (PDMS) composite

3D porous LIG with Co3O4 nanoparticles impregnated within structure was used for electrode formation

Hybrid material comprised of gold nanoparticles sandwiched between the sheets of graphene Hybrid material of graphene foam and PDMS composite

Glucose detection with linear range of 10 μM to 9.2 mM, sensitivity of 247.3 μA mM−  1 cm−  2, and a LOD of 3 μM; pH assessment with the sensitivity of 75.06 mV/pH with the linear range of pH 4 to 7 Glucose sensitivity of 214 μA mM−  1 cm−  2, linear range of detection of 1 μM to 9 mM, LOD of 0.41 μM, rapid response time of 0.49 s. Different sensitivity of 2.2 MHz kPa−  1, 230 kHz kPa−  1 and 37.5 kHz kPa−  1 observed for low-, medium-, and high-pressure ranges Rapid response time of   50 nm have shown high performance as compared to electrodes having mesoporous structure with the pore size of 2 to 50 nm and also as compared to a microporous structure which has a porosity of