Shiyu Wang
Zakir Hossain
Yan Zhao
Tao Han
Graphene
Field-Effect
Transistor
Biosensors
Graphene Field-Effect Transistor Biosensors
Shiyu Wang · Zakir Hossain · Yan Zhao · Tao Han
Graphene Field-Effect
Transistor Biosensors
Shiyu Wang
Division of Electronics and Informatics
Graduate School of Science
and Engineering
Gunma University
Kiryu, Gunma, Japan
Jihua Laboratory
Foshan, Guangdong, China
Zakir Hossain
GIAR
Gunma University
Kiryu, Gunma, Japan
Tao Han
First Affiliated Hospital of China
Medical University
Shenyang, China
Yan Zhao
Jihua Laboratory
Foshan, Guangdong, China
ISBN 978-981-16-1211-4
ISBN 978-981-16-1212-1 (eBook)
https://doi.org/10.1007/978-981-16-1212-1
© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature
Singapore Pte Ltd. 2021
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Preface
Coronavirus disease 2019 (COVID-19) is an emerging human infectious disease
associated with severe respiratory distress. Since a series of unexplained pneumonia
cases were reported in Wuhan City, Hubei Province, China in December 2019, the
number of infections has increased rapidly with human-to-human transmission. As
of October 13, 2020, more than 37745,000 COVID-19 cases have been confirmed
worldwide, and a conservative estimate has caused 1079963 deaths. As there is
currently no specific drug for COVID-19, large-scale and rapid early diagnosis will
often play a vital role in controlling the epidemic for this rapidly spreading epidemic.
Currently, the main detection methods include Nucleic Acid Detection (NAT),
which is a technique used to detect specific nucleic acid sequences, so it is usually
used to detect and identify specific viruses or bacteria. NAT needs to collect blood,
tissue, urine, etc., and detect whether it contains pathogens. The difference between
NAT and other tests is that it detects the genetic material (RNA or DNA) instead of
antigens or antibodies. The detection of genetic material can diagnose diseases early
because the detection of antigens and/or antibodies takes a while to begin to appear
in the blood or body fluids. Since the amount of genetic material collected is usually
small, many NATs include steps that can amplify genetic material, that is, copy a
large amount of genetic material. This NAT is called a Nucleic Acid Amplification
Test (NAAT). However, because the amplification step is necessary for the NATs, it
always takes several hours then gets the result. Thus the nucleic acid test is usually
unable to achieve large-scale rapid testing, which makes epidemic control a very
difficult problem. Therefore, there is an urgent need to develop a new type of sensor
that can perform large-scale rapid detection while having a certain sensitivity and
specificity, especially for large-scale epidemic diseases like COVID-19.
Graphene is a type of carbon. As the first two-dimensional material discovered in
the world, it is almost completely transparent. It is not only the thinnest but also the
strongest. It has excellent electrical and thermal conductivity. Initially, Profs. Geim
and Novoselov extracted graphene from graphite. They used tape to mechanically
peel off the graphite to obtain graphene. Although many people believed that this twodimensional crystal material could not exist stably at that time. Now, using the twodimensional material graphene, physicists can study the strange properties of matter
in the two-dimensional world. Graphene makes a series of new experimental ideas
v
vi
Preface
and designs possible, which brings many surprising new experimental phenomena
and exciting new application areas. Currently, graphene has already many novel
practical applications. Especially, graphene-based field-effect transistors biosensors,
due to their excellent electrical properties and two-dimensional size, are expected to
become ultra-sensitive biological and chemical-sensing platforms.
At present, various biological technologies such as avidin-biotin technology have
been diffusely applied in different types of ELISA (enzyme-linked immunosorbent assay) kits, polymer-based detection, and labeled immunosensors for detecting
distinct biomarkers related to different kinds of diseases (such as cancer and
influenza). Here we demonstrated these Graphene Field-Effect Transistors (GFET)
based on different biological technologies and illustrated its ultrasensitive detection
capability for the specific target biomolecule (such as virus, microbes, cells) in the
sub-pico molar (pM) range. Although the invention and development of the graphene
FET biosensor have only gone through 10 years, this novel rapid detection platform
has shown great potential for ultra-sensitive rapid detection, which is difficult to
achieve by traditional detection methods. Especially for large-scale epidemic detection and point-of-care testing, this new type of sensor platform is expected to exert
its unique advantages.
Generally speaking, this monograph is divided into 11 chapters. As the upper part,
Chaps. 1–4 mainly state the basic knowledge of graphene FET biosensors, including
graphene-related applications, graphene preparation, mathematical principles about
the graphene FET, fundamental of graphene FET biosensing, etc. Chapters 5–11, as
the lower part, mainly state the application of graphene FET biosensor combined with
various biotechnologies. In the lower part, not only previously existed technologies
are introduced but also inserted some of my personal ideas and conceives for the
first time. In addition, it discusses some related problems existing in graphene FET
biosensor and then introduces some improve methods about these problems. Finally,
it states the future application prospects.
Chapter 1 extensively introduces recent research related to the application of
graphene and its potential applications in various fields. Chapter 2 introduces the
electrical properties of graphene and provides the relevant electrical theoretical basis
for graphene FET sensors. Based on the above theoretical, I proposed two important inferences in the field of graphene FET sensing. At the end of this chapter, the
low-temperature characteristics of graphene are also briefly introduced. Chapter 3
systematically introduces the preparation method for graphene. At the same time,
some of my personal experiences with graphene preparation are also inserted in this
chapter. Chapter 4 introduces the fundamental of the biosensor based on graphene
FET and briefly demonstrates its current application in biological detection. Chapter 5
describes the graphene FET biosensor based on the avidin-biotin interaction and
systematically explains its preparation method and the expected detection effect.
Chapter 6 introduces the graphene FET biosensor based on antigen-antibody interaction, focusing on its application in biomarker detection. Chapter 7 discusses the
graphene FET biosensor based on base complementary pairing technology and
discusses the possibility of applying this technology to large-scale population detection of COVID-19. Chapter 8 introduces the graphene FET biosensor based on
Preface
vii
aptamer technology and compares its difference with the biosensor based on antigen–
antibody technology. Chapter 9 introduces the graphene biosensor based on ConA
technology, and based on the technical characteristics of ConA, two different detection methods are proposed: adsorption detection method and dissociation detection
method. Chapter 10 summarizes the current problems in the field of graphene FET
biosensing and briefly states some of the improved methods for these problems.
Chapter 11 summarizes and outlooks the research on graphene FET biosensors based
on various biotechnologies. Moreover, some aspects have been proposed, which need
to be improved and noted in the future.
Currently, the most direct problem facing clinical detection is that most of the
existing testing methods cannot achieve rapid testing, including PCR and ELISA,
especially in the context of the current COVID-19 pandemic. Based on the above
considerations, the GFET biosensor as a new type of biosensor that can achieve rapid
quantitative detection of specific biological molecules with ultra-high sensitivity
and specificity compared with traditional detection methods. To quickly provide
a potentially reliable basis for clinical diagnosis, it is expected to achieve rapid
screening for large-scale epidemics.
Therefore, the GFET biosensor, as an emerging sensing platform that has only
been invented for a decade, I hope that readers can grasp the basic knowledge and
future directions of graphene FET biosensors in general through this monograph. At
the same time, enjoying the fun of research.
Kiryu, Japan
Kiryu, Japan
Foshan, China
Shenyang, China
Shiyu Wang
Zakir Hossain
Yan Zhao
Tao Han
Acknowledgments
Special thanks to my parents and Miss Yuan Gu for their encouragement and supports.
Shiyu Wang
ix
Contents
1
Fundamental of Graphene . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.1 Graphene Conductive Ink . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.2 Graphene Supercapacitor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.3 Microbial Fuel Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.4 Graphene Flexible Sensing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.5 Graphene Nanogenerator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.6 Thermal Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.7 Biomedical Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.7.1 Drug Delivery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.7.2 Cell Imaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.7.3 DNA Sequencing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.7.4 Tumor Therapy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.7.5 Biological Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.7.6 Graphene Biosafety Research . . . . . . . . . . . . . . . . . . . . . . . .
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1
2
4
5
6
6
7
9
9
11
11
12
13
14
15
2
Graphene Electrical Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.1 Room Temperature Electrical Characteristics . . . . . . . . . . . . . . . . .
2.2 Low-Temperature Electrical Characteristics . . . . . . . . . . . . . . . . . .
2.2.1 Magic Angle Graphene . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.2.2 Moiré Pattern . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
21
22
27
27
27
28
3
Graphene Manufacture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.1 Mechanical Exfoliation Method . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2 Chemical Vapor Deposition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2.1 Pretreatment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2.2 CVD Graphene . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2.3 Transferring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.3 Epitaxial Growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.3.1 Epitaxial Graphene Preparation . . . . . . . . . . . . . . . . . . . . . .
3.3.2 Graphene Characterization . . . . . . . . . . . . . . . . . . . . . . . . . .
3.4 Other Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
29
29
30
31
31
33
37
37
37
38
xi
xii
4
5
Contents
3.4.1 Directly Synthesis on SiO2 . . . . . . . . . . . . . . . . . . . . . . . . . .
3.4.2 Reduced Graphene Oxide (R-GO) . . . . . . . . . . . . . . . . . . . .
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
38
39
40
Graphene Field-Effect Transistor Biosensor . . . . . . . . . . . . . . . . . . . . .
4.1 Electrical Double Layer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.1.1 Stern Model (1924) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.1.2 BDM Model (1963) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.2 Debye Length . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.3 Graphene Field-Effect Transistor . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.4 Graphene Field-Effect Transistor Biosensors . . . . . . . . . . . . . . . . .
4.5 Mechanism of the Graphene Field-Effect Transistor
Biosensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.6 Biological Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
45
47
48
49
50
51
52
60
61
64
Graphene FET Biosensor Based on the Avidin–Biotin
Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.2 Biotinylated Biomolecules Detection . . . . . . . . . . . . . . . . . . . . . . . .
5.2.1 Device Fabrication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.2.2 Graphene Modification . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.2.3 Quantitative Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.2.4 Specificity of the Sensor . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.2.5 Exogenous Biotin Interferences . . . . . . . . . . . . . . . . . . . . . .
5.2.6 Comparative Sensitivity and Practical Applicability . . . . .
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
69
70
72
72
77
78
80
80
81
82
Graphene FET Biosensor Based on the Antigen–Antibody
Interaction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.1 Tumor Marker . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.2 Other Biomarkers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
87
88
89
91
7
Graphene FET Biosensor Based on the Base Pair . . . . . . . . . . . . . . . .
7.1 COVID-19 Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
93
95
96
8
Graphene FET Biosensor Based on the Aptamer Technology . . . . . .
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
97
99
9
Graphene FET Biosensor Based on the Concanavalin A . . . . . . . . . .
9.1 Adsorption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
9.2 Dissociation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
101
103
103
105
6
Contents
10 Challenges and Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
10.1 Standardization of Transfer and Modification . . . . . . . . . . . . . . . . .
10.2 Signal Interference . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
10.3 Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
xiii
107
108
109
110
112
11 Conclusions and Future Works . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
11.1 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
11.2 Future Works . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
Chapter 1
Fundamental of Graphene
Abstract Graphene is the first two-dimensional material discovered in the world.
It has many excellent properties that traditional bulk-materials cannot match, such
as ultra-high mechanical strength, high thermal conductivity, electrical conductivity,
ultra-high specific surface area, stable chemical properties, etc. This makes graphene
have great application potential in many fields such as composite materials, conductive inks, nano power generation, anti-corrosion coatings, and biological applications. Although it has been less than 20 years since Andre Geim and Konstantin
Novoselov discovered graphene in 2004, a series of remarkable results have been
achieved in the related theories and practical applications of graphene around this
new two-dimensional material. This also indicates that scientists have paid great
attention to two-dimensional materials including graphene. This chapter introduces
the discovery history of graphene and the main application directions of graphene in
recent years.
Keywords Graphene · Supercapacitor · Conductive ink · Microbial fuel cells ·
Flexible sensing · Nanogenerator · Thermal applications · Biomedical applications
Graphene is the first two-dimensional material discovered in the world. It is an
allotrope of carbon and consists of single atomic layers arranged in a two-dimensional
honeycomb lattice [1, 2]. The name is the suffix of “graphite”, the suffix is -ene,
reflecting that the graphite allotrope of carbon is composed of stacked graphene
layers [3, 4].
Each carbon atom is connected to the three neighboring atoms through a σ bond
and contributes an electron to the conduction band in the entire graphene film. This is
the same type of bonding seen in carbon nanotubes and polycyclic aromatic hydrocarbons, and (partially) in fullerenes and glassy carbon [5, 6]. These conduction bands
make graphene a semimetal with unusual electronic properties that are best described
by theories for massless relativistic particles [1]. Charge carriers in graphene show
linear, rather than quadratic, dependence of energy on momentum, and field-effect
transistor s with graphene can be made that show bipolar conduction. Charge transport is ballistic over long distances; the material exhibits large quantum oscillations
and large and non-linear diamagnetism [7]. Graphene conducts heat and electricity
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021
S. Wang et al., Graphene Field-Effect Transistor Biosensors,
https://doi.org/10.1007/978-981-16-1212-1_1
1
2
1 Fundamental of Graphene
Fig. 1.1 The main application directions of graphene since its discovery
very efficiently along its plane. The material strongly absorbs light of all visible wavelengths [8, 9], which accounts for the black color of graphite; yet a single graphene
sheet is nearly transparent because of its extreme thinness. The material is also about
100 times stronger than would be the strongest steel of the same thickness [10, 11].
For decades, scientists have been working on graphene and graphene-related
applications. In fact, pencils and other graphite-related applications may have been
unknowingly produced in small quantities for hundreds of years. It was first observed
in an electron microscope in 1962, but it was only studied under the support of a metal
surface [3]. But graphene was rediscovered, separated, and identified by Andre Geim
and Konstantin Novoselov of the University of Manchester in 2004, [12] due to their
research they obtained the 2010 Nobel Prize in Physics. During the PhD research,
my major work is to focus on the research of the biological applications based on the
graphene FET. Developing a kind of ultrasensitive rapid detection method for specific
biomolecules, besides, we should also mention that graphene composite materials
have received more attention in recent years, such as graphene composite rubber and
graphene composite coatings.
The global market for graphene was $9 million in 2012 [13], with most of
the demand from research and development in semiconductor, electronics, electric batteries, and composites. In 2019, it was predicted to reach over $150 million
by 2021 [14]. Figure 1.1 lists the main application directions of graphene since
its discovery, and brief introduction about these main application directions is also
followed below this section.
1.1 Graphene Conductive Ink
Series of applications in the emerging field of printed electronics require a new set
of functional materials for development including flexible and large-area displays
[15], radio frequency identification tags, portable energy harvesting and storage [16,
1.1 Graphene Conductive Ink
3
17], biomedical and environmental sensor arrays [18, 19], and logic circuits [20].
To realize these novel technologies, functional materials must be integrated with
appropriate patterning technologies, such as spraying, inkjet, gravure, and flexographic printing [21, 22]. Since electrical conductors are the core components of
electronic devices as conductive materials, researchers have invested a lot of effort
in developing and manufacturing conductive materials. In the field of printable inks
[23], common conductive inks can be divided into three categories: precious metals,
conductive polymers, and carbon nanomaterials [24]. We focus on the development
of conductive inks based on carbon nanomaterials.
Because different types of conductive inks have unique properties suitable for
specific applications, for example, among noble metals, silver is the most common
printed conductor due to its high conductivity and oxidation resistance, and inks
based on silver nanoparticles or silver precursors have used for printing [25]. These
inks have the highest conductivity among printed materials. However, because silver
is relatively expensive [24], conductive polymers have also been developed for
printed electronics applications. These materials provide moderate conductivity at
low cost but are limited in terms of chemical and thermal stability. Carbon nanomaterials, including carbon nanotubes and graphene, provide a low-cost alternative with
excellent environmental stability and ideal electrical conductivity as well as unique
properties suitable for various applications [24].
Carbon nanomaterials provide many opportunities for printing and flexible electronics. The electrical properties produced by the sp2 bonding structure of fullerenes,
carbon nanotubes, and graphene are particularly promising and have been developed
in many applications from thin-film transistors (TFT) and electrochemical sensors
to supercapacitors and photovoltaic cells [26, 27]. Figure 1.2 shows the image of the
printable graphene conductive ink.
Fig. 1.2 The image of the
printable graphene
conductive ink
4
1 Fundamental of Graphene
1.2 Graphene Supercapacitor
Electric Double Layer Capacitor (EDLC), sometimes also called supercapacitors, is
a novel type of energy storage device. Graphene is used in the electrode material so
that graphene supercapacitors can store charge in an electric double layer formed by
physically adsorbing electrolyte ions to graphene electrodes. With excellent characteristics such as high power density and excellent cycle stability, they are hoping to be
used in applications including uninterruptible power supplies, high-power electronic
equipment, and electric and hybrid electric vehicles. However, for most practical
applications, due to the limited energy density of graphene supercapacitors, their
energy density is usually about 4–5 Wh/kg, which is an order of magnitude lower
than the energy density of batteries.
However, at present, because graphene has an ultra-high theoretical surface area
(2630 m2 g−1 ) and electrical conductivity, it has become the focus of research and
development of supercapacitor electrode materials. A variety of graphene-based
materials with different chemical structures and morphologies have been developed, such as chemically modified graphene, microwave expanded graphite oxide
(MEGO), and curved graphene, which are used as electrode materials for supercapacitors. Recently, it has been reported that graphene-derived materials have
an extremely high surface area of up to ~3100 m2 g−1 , which is prepared by
microwave irradiation of graphite oxide (GO) and then chemical activation with
potassium hydroxide (KOH) [28]. This activated microwave-expanded graphite
oxide (a-MEGO) has a large part of micropores and mesopores, which can provide
a large and accessible surface area to hold the charge, so it can improve specific
capacitance in interface and ionic liquid electrolytes, thereby obtaining a relatively
high weight energy density. Figure 1.3 shows the schematic diagram of the graphene
supercapacitor structure.
Fig. 1.3 The schematic diagram of the graphene supercapacitor structure
1.3 Microbial Fuel Cells
5
1.3 Microbial Fuel Cells
Microbial fuel cell (MFC) is a promising technology, currently, the technology is
mainly used for sewage treatment and power generation. It can use microorganisms
to convert chemical energy (in organic waste) into electrical energy, and the process
combines bioremediation with power generation. In MFC, organic compounds are
oxidized by bacteria along with the production of bacteria at the anode, and oxygen is
reduced at the cathode [29–32]. At present, it can be divided into a single chamber and
dual chamber. MFC is a relatively wide-ranging type of bioelectrochemical system
research and application, including various applications, such as power generation,
wastewater treatment, implantable medical equipment, energy recovery, and biosensors. Figure 1.4 shows an image of a dual-chamber microbial fuel cell. However, the
output of MFC is limited by low charge transfer efficiency and internal resistance
provided by the electrodes. At present, the power conversion efficiency of MFC is
still not high. The losses in the MFC system are evident from the voltage equation, V = E t − ηact − ηohmic − ηconc , where ηact , ηohmic and ηconc are voltage losses
due to the reaction kinetics, ohmic polarization, and mass transport, respectively
[33–36]. Reaction kinetics are predominantly dependent on the electrode reaction
rate. The properties of anode material such as accessible area for bacterial colonization, biocompatibility, and interfacial electron transfer resistance play a vital role in
influencing output power of MFC [37, 38]. Hence, the performance of MFC largely
depends on the anode material used [39, 40].
So far, carbon fiber materials including carbon cloth, carbon paper, and graphite
particles are the most studied anode materials for MFC. Among them, carbon cloth
is the most widely used [41, 42], but they have inherent shortcomings, such as low
electrical conductivity, biological phase poor tolerance, small surface area, and many
other deficiencies. Among carbon-based materials, graphene as an anode material
has attracted wide attention from researchers in recent years [43–46]. It has many
advantages such as excellent biocompatibility, chemical stability, excellent electrical
conductivity, high mechanical strength, and good elasticity. In addition, graphene
has a large specific surface area of 2630 m2 g−1 , and the carrier mobility is greater
than 200000 cm2 V−1 s−1 [47–49]. Using graphene to modify anodes is one of
Fig. 1.4 The image of the
double chamber microbial
fuel cell
6
1 Fundamental of Graphene
the most effective ways to improve anode performance [50]. In addition, graphene
provides a larger surface area for bacterial colonization, promotes the direct electron
transfer process, and improves the efficiency of electron transfer [51]. Zhang et al.
first explored graphene as an anode material for MFC. They report that the power
density of graphene-modified stainless steel is 2668 mW m−3 , which is 18 times
higher than SS (stainless steel) bare mesh [52]. In Xiao et al., it is reported that the
highest power density of the anode modified with wrinkled graphene is 3.6 W/m3 . In
addition, it was observed that the graphene modification increased the power density
and energy conversion by 2.7 times and 3 times, respectively [53].
1.4 Graphene Flexible Sensing
Because of the unique 2D properties of the graphene, lots of flexible sensing devices
have been developed based on graphene [54–56]. Graphene strain sensing is the
most significant flexible sensing application that has almost ready for commercial
manufacture [56]. In my opinion, the large-scale preparation of multilayer graphene
strain sensors through graphene ink is the main direction for the development of
graphene strain sensing in the future. The multilayer graphene is made onto the
surface of the flexible substrate by the print of the graphene ink. Then the strain
force makes the displacement between the interlayer of the graphene, which changes
the conductivity of the multilayer graphene. Because the printing of the multilayer
graphene by the graphene ink is not difficult processing (sometimes only need to
heat curing after screen printing), thus the graphene strain sensing device is easy
to be manufactured. At the same time, because graphene is thin enough that it can
be developed as the ultrathin strain sensing device, which can break through the
thickness level that traditional materials can not arrive. Thus as one of the most
promising graphene applications, the graphene flexible sensing is expected to be
applied as the ultrathin strain sensing platform. Figure 1.5 shows the image of the
graphene flexible sensing platform based on the graphene tape.
1.5 Graphene Nanogenerator
The triboelectric nanogenerator is an energy conversion and collection device that
can convert external mechanical energy into electrical energy through triboelectric effect and electrostatic induction. In 2012, this new type of nanogenerator was
demonstrated for the first time in the research team of Professor Wang Zhonglin of
Georgia Institute of Technology [57]. In simple terms, for this power generation unit,
in the internal circuit, a potential is generated due to the charge transfer between two
organic/inorganic thin films showing opposite tribopolarity due to triboelectricity. In
an external circuit, electrons are driven to flow between two electrodes attached to
1.5 Graphene Nanogenerator
7
Fig. 1.5 The image of the
graphene flexible sensing
platform based on the
graphene tape
the back of the film to balance the potential. In the past 10 years, triboelectric nanogenerators have made new developments. Combined with nanomaterials, focusing
on the triboelectric effect of the solid–liquid interface has become a research focus
in recent years.
Nature provides a huge amount of water energy in diverse forms, but very limited
part has been collected. Recently, great achievements have been made in carbon
nanomaterial-based energy harvesters, as they collect many rich forms of water
energy, such as flows, waves, raindrops, moisture, and evaporation, based on radically different principles from traditional electromagnetic generators. Recently, some
studies have reported that dropping or waving potential can be induced in graphene
when electrolyte droplets or waves move across the graphene surface [58, 59]. Such
electric potential is generated due to the moving electrical double layer (EDL)
boundary at the interface between graphene and electrolyte, where ions adsorption/desorption occurs and induces charge carriers to flow in graphene. These studies
indicated that there is charge transferring between the interface of the graphene and
water, which induce the electric potential. The electric potential generated from
the liquid flow on graphene has triggered great interest and shown its prospect in
harvesting mechanical water energy. Figure 1.6 shows the schematic image of the
graphene water–solid triboelectric nanogenerator.
1.6 Thermal Applications
Due to the excellent thermal conductivity of graphene and its potential in thermal
management applications, heat transfer applications and thermal management applications related to graphene have become a booming research field. Under ideal conditions, the thermal conductivity of graphene at room temperature can reach the range
of 3000–5000 W/mK. Compared with the thermal conductivity of pyrolytic graphite
8
1 Fundamental of Graphene
Fig. 1.6 The schematic
image of the graphene
water–solid triboelectric
nanogenerator
at room temperature of about 2000 Wm−1 K−1 , its thermal conductivity is A further
improvement. However, some current studies suggest that the thermal conductivity
of graphene in practical applications may be slightly lower than this ideal value. For
free-suspended graphene samples, the in-plane thermal conductivity of graphene at
room temperature is about 2000–4000 Wm−1 K−1 [60, 61]. But this number is still
the highest among all known materials. Graphene is considered to be an excellent
thermal conductor. According to the size of the sample, some studies have found that
graphene has unlimited thermal conductivity, which runs counter to the micron-level
thermal conductivity (Fourier’s law). In computer simulations and experiments, the
researchers found that the larger the graphene segment, the more heat it transfers.
In theory, graphene can absorb an unlimited amount of heat. The thermal conductivity increases logarithmically, and the researchers believe that this may be due to
the stable bonding pattern and the two-dimensional material. Since graphene has
stronger tear resistance than steel, and is lighter in weight and flexible, its related
thermal conductivity applications may have great potential in the future.
Since graphene is the most thermally conductive found so far, and graphene has
high mechanical strength, light weight, and thinness, this means that it is a good
material for manufacturing attached or coated heat dissipation solutions, such as
heat sinks or heat dissipation films. This can be useful in both microelectronics (such
as making LED lighting more efficient and durable) and large applications (such as
thermally conductive foils for mobile devices). In addition, in the field of electric
vehicles, due to its super thermal conductivity, fire resistance, light weight, and other
characteristics, it can be used as a thermal conductive material to coat the surface of
the battery in the thermal management of the battery.
Temperature is an important factor affecting semiconductor components. An
increase in the operating temperature of the component will increase the power
of the component. For portable devices such as mobile phones, the increase in power
will lead to excessive battery loss. Therefore, the application of graphene thermal
film is beneficially extend the use time of portable devices. Huawei’s latest smartphones, for example, have adopted graphene-based thermal films [62]. Believe that
there are more and more different kinds of the graphene-based thermal films that will
1.6 Thermal Applications
9
Fig. 1.7 The image of the
graphene thermal tape used
on the surface of the
semiconductor chip
be applied in the future. Figure 1.7 shows the image of the graphene thermal tape
used on the surface of the semiconductor chip.
1.7 Biomedical Applications
As a new type of two-dimensional nanomaterial composed of carbon atoms,
graphene’s unique and excellent electrical, optical and mechanical properties, as
well as the broad application prospects resulting from it, have become a research
hotspot that has attracted much attention.
At present, the research on graphene and its derivatives is mainly concentrated in
its physical research field. The chemistry and material science research of graphene
have also developed rapidly, while the research work of graphene in the field of
biomedicine has just begun, but some of its recent highlight research has hinted
that graphene may have great potential in the biomedical field. This section briefly
describes the latest developments in graphene in the field of biomedicine, including
targeted drug delivery, cell imaging, DNA sequencing, tumor therapy, biological
detection, and graphene biosafety research as shown in Fig. 1.8.
1.7.1 Drug Delivery
Drug delivery is one of the prominent biomedical applications of graphene nanomaterials in the current scenario. The rapid growth in the graphene-based drug delivery
systems showed the potential of this nanomaterial in the future healthcare industry.
The unique monoatomic planar structure and associated properties such as large
surface area, chemical and mechanical stabilities, superb electrical conductivity,
10
1 Fundamental of Graphene
Fig. 1.8 The main biomedical applications based on the graphene
and good biocompatibility enabled the utility of these nanomaterials in medical
applications.
In 2008, Dai Hongjie’s research group [63] first reported the use of polyethylene
glycol (PEG) modified graphene oxide as a poorly soluble aromatic-containing anticancer drug carrier. They first oxidized graphite to obtain nanoscale graphene oxide
(NGO) with a size of less than 50 nm and then grafted biocompatible PEG onto NGO.
This graphene material has good biocompatibility and stability under physiological
conditions including serum. Then, the anticancer drug SN38 (camptothecin derivative) is adsorbed on the surface of the PEG-based NGO through physical effects such
as π–π stacking to form a graphene–drug complex. Graphene has a single atomic
layer thickness, and its two base surfaces can absorb drugs, so it has an ultra-high
drug loading rate unmatched by other nanomaterials. Studies have found that the
NGO-SN38 complex has good water solubility, indicating that it can be used as a
drug carrier to solubilize poorly soluble drugs, and the SN38 in the complex still
maintains a high degree of activity. In vitro experiments have found that NGO-SN38
can effectively kill colon tumor cells. More importantly, NGO-PEG as a drug carrier
has no obvious cytotoxicity and has good biological safety.
1.7 Biomedical Applications
11
1.7.2 Cell Imaging
Graphene quantum dots (GQD) have shown great potential in bioimaging applications due to their excellent biocompatibility, feasibility of surface functionalization,
physiological stability, low cytotoxicity, and adjustable fluorescence characteristics.
In addition, some of the fluorescent dyes connected with the graphene are also always
used for the cell image. In this section, cell imaging based on the graphene will be
briefly introduced.
Gao et al. proposed a GQD coated with polyethyleneimine (PEI) for in vitro
tumor cell imaging [64]. Depending on the molecular weight (MW) of the PEI,
the prepared GQD can show red, yellow, and blue emissions, making it possible to
perform multicolor imaging of U87 tumor cells in vitro. Besides, they claimed that
the reason for the multicolor emission is that the PEI coating not only determines the
core structure of the GQD but also changes the energy gap, leading to the multicolor
emission GQD.
Peng et al. [65] used PEG to connect fluorescent dyes with NGO to perform
intracellular imaging. Among them, the PEG molecule acts as a bridge, which can
prevent NGO from causing fluorescence quenching of the dye, effectively improves
the biocompatibility and stability of NGO, and enhances the absorption of materials
by cells. The research results show that the fluorescein-PEG-NGO (Fluo-G) structure
exhibits excellent pH-regulated fluorescence characteristics. More importantly, the
complex can be efficiently absorbed by cells and used as a fluorescent probe in cell
imaging Fluo-G emits green fluorescence when excited with blue light. At the same
time, at pH 4.6–8.0, the fluorescence density of Fluo-G increased with the increase
in pH value. Studies have found that, compared with active absorption, Fluo-G may
be more dependent on being absorbed by cells directly through the cell membrane.
In view of the high biocompatibility and carrying capacity of NGO, it is easy to
synthesize, and it is expected to be used for cell imaging.
1.7.3 DNA Sequencing
DNA is the blueprint of life because it encodes all genetic information. In many
genetic diseases, DNA sequencing is used as the gold standard for diagnosis.
Researchers have been conducting research to achieve genome sequencing at a low
cost while maintaining high precision and high throughput [66].
In principle, graphene is an ideal pore material for DNA sequencing. Its singleatom thickness of 0.35 nm is similar to DNA base spacing, and it can create graphene
nanopores with a diameter of only 1.0 nm (about the size of a DNA molecule).
Although most of the current research is still in the theoretical stage, it is one of the
most promising and revolutionary DNA sequencing technologies.
There are two main promising methods of the DNA sequencing based on the
graphene nanomaterial, containing the charge tunneling through graphene nanopores
12
1 Fundamental of Graphene
and in-plane charge transport within graphene nanoribbon containing a nanopore
[67]. For the charge tunneling, because different bases have different electronic
energy level structures, thus when each base passes through the nanopore gap,
different degrees of tunneling current will be generated. The idea is to measure
the conductance through two graphene-based electrodes and to monitor the current
change when DNA bases go through the nanopore. When different DNA bases fall
within the voltage range of the electrodes, a special and different current is noticed.
For the graphene nanoribbon in-plane detection where DNA bases modulate the
ionic current passing through graphene nanoribbon differently. This approach has an
advantage over the previous one since the current in the nanoribbons is larger. As a
potential rapid sequencing method, although more in-depth research is needed, the
rapid DNA sequencing based on graphene nanomaterials is worthy to be expected.
1.7.4 Tumor Therapy
Although tumor therapies based on the carbon nanomaterials have been intensively
studied in recent years, graphene has been rarely mentioned in this field. The research
of the tumor therapies based on the graphene may be still in the primary stage that
still needs to continuously research.
Currently, Liu Zhuang’s research team has reported for the first time the in vivo
behavior of nano-graphene sheets (NGS) coated with polyethylene glycol (PEG)
by fluorescent labeling [68]. Their results showed that based on in vivo fluorescence imaging, NGS tumor uptake was abnormally high in several xenograft tumor
mouse models. In contrast to PEGylated carbon nanotubes, PEGylated NGS exhibits
several interesting behaviors in vivo, including relatively low retention in the reticuloendothelial system and efficient passive tumor targeting. Then, they used the strong
light absorption of NGS in the near-infrared (NIR) region for in vivo photothermal
therapy. After intravenous administration of NGS and low-power NIR laser irradiation on the tumor, they achieved ultra-efficient tumor ablation. In addition, through
histology, blood chemistry, and whole blood plate analysis, no obvious side effects
of PEGylated NGS on injected mice were observed in its pilot toxicity study. This
research has opened the way for graphene nanosheets to be used for tumor ablation
through photothermal therapy.
Although more effort is needed to further understand the in vivo behavior and
long-term toxicology of this new nanomaterial, their work is the first success in using
carbon nanomaterials for effective in vivo photothermal therapy through intravenous
administration, which shows the promise of graphene in tumor treatment.
1.7 Biomedical Applications
13
1.7.5 Biological Detection
With its excellent physical and optical properties, graphene has become a novel
material for biosensors. At the same time, it is also biocompatible, very suitable
for clinical diagnosis or medical applications, and is relatively easy to manufacture,
with stable chemical properties. At present, the biological detection application of
graphene has attracted more and more attention. GFETs and graphene-enhanced
surface plasmon polaritons (SPPs) as the two of the most promising applications in
biological detection are widely researched in the world.
GFET is an improvement of the conventional silicon field-effect transistor (FET).
In the conventional FET, silicon material acts as a thin conductive channel, and its
conductivity can be adjusted by the gate voltage. GFET is performed in a similar
way, where the silicon in conventional FET is replaced by the graphene. Based on the
remarkable carrier mobility (15000 cm2 V−1 s−1 at room temperature) and atomicscale thickness, graphene creates a thinner, more sensitive channel area. Compared
with the bulk semiconductor materials, such as silicon, because most of the FET
channel materials are three-dimensional materials, which induces any charge carrier
changes at the interface of the channel do not always penetrate deeper into the device.
This phenomenon will greatly limit the response sensitivity of the FET. Especially
for applications that require high sensitivity, such as some special gas or biosensing
applications, but because the channel of GFET is graphene that is only one carbon
atom thick, the entire channel is directly exposed to any molecules in the nearby environment. In addition, stable chemical properties and easy large-scale preparation are
also reasons why graphene is more suitable as a channel material than other nanomaterials. Therefore, through the functionalization of graphene surfaces, GFETs have
become attractive devices for attaching specific biomolecules. Because graphene has
an extremely thin thickness (two-dimensional material), even the smallest concentration of attached molecules will change the channel conductivity, which makes
the GFET biosensor very suitable as a potential clinical diagnose platform for rapid
detection [69]. Especially in recent years, graphene FET biosensors have shown
the ultrasensitive rapid detection capabilities for COVID-19 [70]. Moreover, some
studies show that graphene FET biosensors combined with CRISPR technology
to develop CRISPR chips that can quickly identify DNA sequences [71]. These
outstanding studies have made people gradually pay attention to the related applications of graphene FET biosensors and hope that these novel technologies will be
widely used as soon as possible. Figure 1.9 shows the main detection targets for the
GFET biosensor.
In addition, graphene film materials can also be used in combination with surface
plasmon polarons (SPP) on metal films to enhance the performance of biosensors.
SPP-based sensors confine light waves to metal surfaces to make small-volume chemical and biological sensors. The sensing volume is given by a tightly enclosed surface
wave, which improves the sensitivity of optical detection. The main metals used in
SPP biosensors are gold (Au) and silver (Ag) because they have good surface wave
propagation characteristics. However, gold has poor adsorption performance,while
14
1 Fundamental of Graphene
Fig. 1.9 The main detection targets for the GFET biosensor
silver corrodes quickly. Note that the layer of graphene on the gold surface will
produce excellent adsorption [69].
1.7.6 Graphene Biosafety Research
For the biomedical applications of graphene, the safety of graphene is always a topic
that cannot be ignored. In the last section of this chapter, the safety of graphene will
be briefly discussed.
It is almost inevitable that any new material invention or discovery will usually
be accompanied by safety warnings from researchers in the field. The same is true
for graphene, especially once the concept of nano is mentioned [72]. Currently, the
toxicity of graphene is still under study. The literature published by Lalwani et al.
systematically elaborated on the detailed study of graphene toxicity. The various
mechanisms of graphene toxicity are demonstrated [73]. They claimed that the toxicity of graphene depends on a variety of complex factors, such as size, purity, shape,
production process, functional groups, and dispersion state [74]. Researchers at Stony
Brook University have shown that graphene nanomaterials such as nanoribbons,
nanosheets, and nanoonions are non-toxic at concentrations up to 50 μg/ml. These
graphene nanomaterials will not change the differentiation of human bone marrow
stem cells into osteoblasts (bone) or adipocytes (fat), which indicates that low-dose
graphene nanomaterials are safe for biomedical applications. This result enhances
the confidence in the low-dose application of graphene nanomaterials in vitro and
in vivo [75]. Researchers at Brown University found that multilayer 10 μm graphene
sheets can penetrate cell membranes in solution. It was observed that they initially
entered through sharp jagged points, but their specific physiological effects are still
unclear [76].
1.7 Biomedical Applications
15
Although significant results have been achieved regarding graphene biomedical
applications, the toxicity of graphene is still unclear, so I think that this kind of
potential risk should be vigilant before practical applications.
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Chapter 2
Graphene Electrical Characteristics
Abstract As one of the important characteristics of graphene, the electrical properties of graphene have been extensively studied and applied whether in the field
of low-temperature physics or the field of room temperature physics. In the field
of physics at room temperature, relying on graphene’s ultra-high carrier mobility,
ultra-high specific surface area (small size effect), and chemical stability, series of
graphene-based sensing applications such as magnetic, optical, biological, flexible
sensors have been reported. Starting from the classical theory, this chapter algebraically describes the electrical conductivity of graphene at room temperature and
the variables related to the electrical conductivity of graphene. These conclusions
provide a theoretical basis for the sensing application of graphene at room temperature. Besides, at the end of this chapter, a brief introduction is given to the hot spot
(magic-angle graphene) of graphene’s low-temperature physics in recent years.
Keywords Graphene · Room-temperature · Electrical characteristics ·
Magic-angle · Moiré pattern
Graphene electrical characteristics are the electrical properties of graphene, which
arise from the unique behavior of electrons in such a thin layer, that have led to
the breakthrough applicated cases for graphene in sensors and other fields. At the
same time, the superconductivity for this remarkable material has been more and
more focused in recent years. These excellent electrical applications are both inseparable from the corresponding mathematical models. In this chapter, the electrical
characteristics of graphene in room temperature will be illustrated with the mathematical formula at first. Some of the derivation processes are based on the work of
Wojtaszek [1], then introducing some enlightening conclusions about the graphene
sensing applications at room temperature from them. Finally, the superconductivity
of the magic angle graphene at low temperatures is briefly demonstrated.
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021
S. Wang et al., Graphene Field-Effect Transistor Biosensors,
https://doi.org/10.1007/978-981-16-1212-1_2
21
22
2 Graphene Electrical Characteristics
2.1 Room Temperature Electrical Characteristics
Generally speaking, the two types of charge carriers: electrons and holes that usually
describe the graphene electrical characteristics at the room temperature particularly
the work point is nearing the Dirac point. Based on the classical description for
the net electrostatic force, Fel = q E is used to describe the charge carrier drift,
because of the relationship between the electric field E and the drift velocity Vq
can also be depicted as Vq = μq E that the net electrostatic force Fel satisfies the
relation: Fq = q Vq /μq . At the same time, the moving charges around the graphene
also affect with the Lorentz force: FL = q(Vq × B). The net electrostatic force Fel
and the Lorentz force FL regulate the moving charges in the graphene at the room
temperature.
Based on these two principle relations, the traditional graphene electrical transfer
characters can be analyzed using an ambipolar conductor model as shown in Fig. 2.1.
When a voltage drop is applied in x direction, electrons and holes begin to move in
opposite directions along the same axis. Since the magnetic field is perpendicular to
its movement, the Lorentz force deflects the movement of the carriers to the same side
Fig. 2.1 The schematic diagram of the traditional graphene electrical transfer characters using an
ambipolar conductor model
2.1 Room Temperature Electrical Characteristics
23
of the graphene. Therefore, both holes and electrons are gathered based on the Lorentz
force (eV hxBz, eVexBz). When the density of carriers and their mobility are equal,
there is no potential drop in y direction (negative electrons compensate for positive
holes). However, when the density of different carriers or their mobility differs, it
will have an asymmetric distribution of the charge density across the graphene. This
establishes an electric field E y that prevents further charge migration, and thereby a
stable electric potential (Hall potential) is formed.
For any charge q in a magnetic field (since graphene is a two-dimensional plane,
we just only consider magnetic field with Z component B = (0, 0, B) in our experiment.), which moves in x and y direction as presented in Fig. 2.1, thus the charge q
motion equation can be obtained as follows:
q Vq
= Fnet,q = Fel + FL
μq
Here Fel = q E represents the electric force in this system. For the case of holes,
for which q = e, note that e represents the elementary charge (e ∼
= 1.602 × 10−19 C),
we obtain the following equations:
eVhx
= e(E x + Vhy B)
μh
eVhy
= e(E y − Vhx B)
μh
(For holes, their velocity and mobility are marked as “h”).
For the case of electrons, here q = −e, note that their moving direction is opposite
to the direction of the holes, thus we get:
eVex
= e(E x − Vey B)
μe
eVey
= e(E y − Vex B)
μe
(For electrons, their velocity and mobility are marked as “e”).
Reintegrate the velocity equations in the form of electrons and holes into a matrix
form:
E
1 μe B
Vex
= −μe x
·
Vey
Ey
−μe B 1
1 −μh B
Ex
Vhx
= μh
·
Vhy
Ey
μh B 1
24
2 Graphene Electrical Characteristics
After conversion, we can get the velocities expression as follows:
−μe
1 −μe B
Ex
=
2
Ey
1 + (μe B) μe B 1
μh
Vhx
Ex
1 μh B
=
·
Vhy
Ey
−μh B 1
1 + (μh B)2
Vex
Vey
Note that there is usually no current in the y direction during the actual experiment,
so:Jy = Jhy + Jey = epVhy + enVey = 0, where as p represents the concentration
of holes and n represents the concentration of electrons. Thus we can get: pVhy =
nVey . However, the current flowing in the direction x is not zero, it consists of two
components Jx = Jhx + Jey = epVhx + epVex . Combine this expression with the
definition of conductivity J = σ E, We can get the corresponding hole and electron
conductivity:
epμh
1 −μh B
.
1 + (μh B)2 μh B 1
enμe
∧
1 μe B
σe =
·
−μe B 1
1 + (μe B)2
∧
σh =
The total conductivity of a dual current-carrying system is the sum of hole conduc∧
∧
∧
tivity and electron conductivity (for uncoupled carriers) σ = σe + σh . In the experiment, because we usually measure resistivity instead of conductivity, we use the
∧
∧
tensor relationship to convert the equation: ρ = σ −1. For graphene, since electrons
and holes have equal mobility, we mark it as: μe = μh = μ. After reversing the total
tensor of conductivity, we can get:
1 + (μB)2
P=
eμ ( p + n)2 + (μB)2 ( p − n)2
∧
p + n −Bμ( p − n)
Bμ( p − n)
p+n
For expressing the vertical ρx x and horizontal resistivity ρx y clearly, we get:
eμ ( p + n)2 + (μB)2 ( p − n)2
( p − n) · 1 + (μB)2
·B
=− e ( p + n)2 + (μB)2 ( p − n)2
ρx x =
ρx y
( p + n) · 1 + (μB)2
From the last formula, we can derive the Hall coefficient R H , based on ρx y =
R H · B. In the two type model, R H is related as follows:
(n − p) · 1 + (μB)2
RH = e ( p + n)2 + (μB)2 ( p − n)2
2.1 Room Temperature Electrical Characteristics
25
But when we consider the conductive properties of graphene at room temperature,
we should replace this description with a simpler description. With the help of the
external gate voltage Vg , we can change the Fermi level of the system, from one
carrier type electron or hole transport to another carrier type (Drude system). In this
case, the resistivity equation should be simplified by adding an appropriate form of
carrier concentration. This leads us to the Drude model of graphene resistivity:
1. when Vg VDirac , p = 0, n = α Vg − VDirac
ρx x =
Note that
2.
1
ne
1
B
, ρx y =
= RH B
eμn
en
= RH
when Vg VDirac , n = 0, p = α VDirac − Vg
ρx x =
1
B
, ρx y =
= RH B
eμp
ep
1
Note that pe
= RH
According to the actual electrical experiment results, the ρx x , ρx y that can be
calculated. Applying the priviously formulas that have been mentioned, we can get
the mobility and the carrier concentration of the graphene, as follows:
1
enρx x
B
n=
eρx y
μ=
Based on the two of the above formulas, we can obtain some simple conclusions
as follows if ignoring the affected from temperature:
When Vg is far from the VDirac
1.
2.
ρx x is only regulated by the Vg , it is not affected by other factors.
ρx y is both regulated by the Vg and B.
These are two very important conclusions, which lay a simple mathematical model
for graphene-based electrical sensors. The relationship implied by these conclusions
is shown in Fig. 2.2.
26
2 Graphene Electrical Characteristics
Fig. 2.2 a The schematic diagram of the functional relationship implied by the conclusion 1. b The
schematic diagram of the functional relationship implied by the conclusion 2
Conclusion 1 implies that any variations from the Vg that can be monitored by the
current of the graphene. The Vg variations can be generated from chemical, biological,
and other complex effects. So theoretically speaking, based on the graphene ρx x
monitoring that has the enormous potential to develop a novel sensing platform.
Conclusion 2 implies that if Vg keeps constant, the graphene can be seen as a
novel 2D Hall device, it will also own the same broad application prospects with the
traditional Hall device in the future.
2.2 Low-Temperature Electrical Characteristics
27
2.2 Low-Temperature Electrical Characteristics
2.2.1 Magic Angle Graphene
Yuan et al. is the first group to reveal that the heterostructure composed of doublelayer graphene has tunable low-temperature superconductivity. They used doublelayer graphene and twisted one of the graphene layers to a certain angle relative
to the other [2, 3]. Experiments show that when this angle is close to the so-called
“magic” angle (1.1°, 0.5°, 0.24°) due to strong interlayer coupling, the electronic
band structure of the graphene becomes flat near zero Fermi energy. These flat band
structures induce the graphene to exhibit an insulating state when half-filled. They
also pointed out that the relative state in the half-filled state is similar to that of
Mott-type insulators, where the electrons are located in the superlattice, which may
be the possible cause of the graphene in the insulating state.
But the funny thing is when the graphene is at the “magic” angle, after electrostatic doping these graphenes that are originally in the relevant insulating state, a
tunable zero resistance state is observed, that is, it enters the superconducting state of
graphene. The critical temperature of the superconducting state is 1.7 K. In addition,
they also claimed that the temperature-carrier density phase diagram of the twisted
double-layer graphene is similar to the copper oxide (or cuprate) and also includes
the dome-shaped region corresponding to superconductivity.
Twisted double-layer graphene is the first known two-dimensional insulator–
superconductor switchable material that can be precisely tuned at low temperatures.
It opens up a whole new field of research, and it can be used as a new platform
for studying superconductivity theory and properties. In addition, the conversion
of superconductivity and insulation makes it possible to produce low-power semiconductor devices. In short, there are still many projects worthy of research and
exploration for the dramatic properties of twisted double-layer graphene and other
twisted two-dimensional materials in low-temperature environments.
2.2.2 Moiré Pattern
In fact, our group found through STM that moiré patterns can also be observed on
epitaxial graphene, as shown in Fig. 2.3. This result shows that the graphene epitaxially grown on SiC has a certain angle between each other, which makes epitaxial
graphene as a potential research platform for the study of the magic-angle graphene.
28
2 Graphene Electrical Characteristics
Fig. 2.3 Two-dimensional
STM image of the surface of
the graphene. The hexagonal
moiré presents on the surface
of the graphene, and the
moiré wavelength is about
1.6 nm
References
1. Wojtaszek, M.: Graphene: A Two Type Charge Carrier System, 81
2. Cao, Y., Fatemi, V., Fang, S., Watanabe, K., Taniguchi, T., Kaxiras, E., Jarillo-Herrero, P.:
Unconventional superconductivity in magic-angle graphene superlattices. Nature 556(7699),
43–50 (2018). https://doi.org/10.1038/nature26160
3. Cao, Y., Fatemi, V., Demir, A., Fang, S., Tomarken, S.L., Luo, J.Y., Sanchez-Yamagishi, J.D.,
Watanabe, K., Taniguchi, T., Kaxiras, E., Ashoori, R.C., Jarillo-Herrero, P.: Correlated insulator
behaviour at half-filling in magic-angle graphene superlattices. Nature 556(7699), 80–84 (2018).
https://doi.org/10.1038/nature26154
Chapter 3
Graphene Manufacture
Abstract Almost all application research based on graphene is inseparable from the
preparation of graphene. The preparation process of graphene is very important for
almost all graphene application research. Currently, preparation methods of graphene
can be roughly divided into five categories, namely, mechanical exfoliation, chemical vapor deposition, epitaxial growth, reduced graphene oxide, and direct synthesis.
In fact, the best choice of graphene preparation methods may be also different for
facing different types of applications. For graphene field-effect transistor biosensors,
graphene prepared by chemical vapor deposition is mainly used to make conductive
channels. Besides, mechanical exfoliation methods are also used in early experiments. Recently, reduced graphene oxide methods and epitaxial growth methods are
also reported to use as conductive channels. Since the preparation quality is directly
related to the conductive characteristics of the conductive channel, thus it affects
the performance of the sensor. Therefore, it is necessary to sufficiently introduce the
preparation method and the details about the preparation process.
Keywords Mechanical exfoliation · Chemical vapor deposition · Epitaxial
growth · Reduced graphene oxide · Direct synthesis
It is necessary to introduce the preparation method of graphene before formally
discussing the graphene field-effect transistor. Because the premise of any form of
electrical application requires the preparation of high-quality graphene films as a
sensor platform. In this chapter, the common methods of preparing graphene will be
introduced including mechanical exfoliation, chemical vapor deposition, epitaxial
growth, and other methods. Figure 3.1 shows the major methods for the graphene
preparation at present.
3.1 Mechanical Exfoliation Method
Mechanical exfoliation is a very old but very effective method of obtaining graphene,
and this method can even trace back to the era when graphene was discovered by
Professor Andre Geim and Professor Konstantin Novoselov in 2004 [1]. They used
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021
S. Wang et al., Graphene Field-Effect Transistor Biosensors,
https://doi.org/10.1007/978-981-16-1212-1_3
29
30
3 Graphene Manufacture
Fig. 3.1 The major methods for the graphene preparation at present
scotch tape to mechanically exfoliate the graphene from the graphite crystal and
then transferred the graphene onto a silicon substrate. Although most people at that
time still believed that thin crystalline materials like graphene could not exist stably.
Finally, they confirm the single-layer graphene by the AFM and integer quantum
Hall effect. Until now, much research on two-dimensional materials still uses this
method, such as black phosphorus, transition metal dichalcogenide [2–7].
It is known that graphite is composed of graphene stacked on each other [8].
Because the Van der Waals interaction forces between graphene are weak, it is easy
to peel off. When graphene is produced by this mechanical exfoliation method, highquality single-crystal samples of several to several tens of µm are obtained, which
is very useful for elucidating basic physical properties and verifying the operation
principle of the device using graphene. However, in order to use graphene for device
applications, large areas of wafer size (several inches), high-quality graphene is indispensable and currently impossible to achieve by mechanical exfoliation. Therefore,
there is a need to establish a method capable of using a large-area, high-quality
graphene manufacturing rather than mechanical exfoliation.
3.2 Chemical Vapor Deposition
Chemical vapor deposition (CVD) has been widely used in the industrial field as
one of the important thin film growth methods [9–14]. Since the advent of graphene,
much research has been conducted worldwide due to the prospect of high-quality and
large-area synthesis of large-area graphene [15, 16]. The principle is that the carbon
source gas is supplied onto a high-temperature metal catalyst, and the decomposed
growth precursor is polymerized to form graphene, but there are many parameters that
affect the growth, so the quality of the exfoliated sample has not reached. However,
3.2 Chemical Vapor Deposition
31
from the application point of view, it is important to develop low-cost synthesis
methods. Nowadays, CVD graphene has become one of the most important graphene
manufacturing methods. In this section, the CVD graphene manufacture method will
be reviewed at first. Then CVD graphene transfer methods will be simply illustrated.
The graphene chemical vapor deposition method is the method that can directly
synthesize the graphene on to the substrate. Since the binding energy of a hydrocarbon
gas such as methanol is relatively large, it is very difficult to grow graphene by
utilizing the principle of thermal decomposition. For the graphene biosensor, catalytic
CVD methods are mainly used. In this section, the commonly graphene chemical
vapor deposition method will be demonstrated.
In common, graphene film was synthesized on iridium [17], nickel [18] and copper
[19] film. For the poly layer, graphene synthesizes, the nickel or the copper–nickel
alloy is commonly used [20]. The copper film is commonly used to synthesize the
monolayer graphene [19]. That is because the copper and the nickel film have different
solubility to the carbon atom at high temperatures, thus induce the different number
of layers in copper and nickel film during the synthesizing process. The monolayer
graphene is commonly synthesized on copper foils using chemical vapor deposition
(There are some studies that also show that the Pt film can also synthesize the monolayer graphene in recent years [21]). We mainly introduce the monolayer graphene
synthesis on copper foil.
3.2.1 Pretreatment
Before chemical vapor deposition, it is usually necessary to heat the copper foil at
300° for 30 min in the atmosphere to form an oxide layer on the surface of the copper
foil. Because some studies have shown that the formation of an oxide layer on the
surface of copper foil helps to significantly decrease the graphene nucleation density
[22]. Therefore, this step is usually used as a pretreatment process of copper foil
before CVD synthesis, in order to synthesize graphene with higher quality.
After the pretreatment, it can be clearly observed that the color of the copper foil
becomes darker, which commonly indicates that the formation of an oxide layer on
the surface of the copper foil.
3.2.2 CVD Graphene
The chemical vapor deposition (CVD) method is a vacuum deposition method that
has been widely used to deposit high-performance and high-quality solid materials.
This process is usually used in semiconductor manufacturing processes to deposit
thin films [23]. Generally, the wafer (substrate) is first exposed to the atmosphere of
one or more volatile precursors, and then the precursors will react and/or decompose
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on the surface of the substrate to produce the desired deposits. Note that volatile byproducts are usually produced in the chemical vapor deposition process, but these
by-products will be discharged from the reaction chamber. At present, as an important
deposition method, CVD is widely used in semiconductor processing technology and
microfabrication technology to deposit various materials, including single crystal,
polycrystalline, epitaxial, and amorphous. These materials include silicon, various
high-k dielectrics, and others. In recent years, the formation of two-dimensional thin
films including molybdenum disulfide and graphene by chemical vapor deposition
has gradually become an important method for preparing two-dimensional materials.
In terms of the CVD synthesis of graphene, there are many different kinds of methods.
As far as the types of carbon sources are concerned, methane gas has been widely
used to produce graphene as the most commonly used carbon source. (In addition,
ethylene and pitch can also be used as carbon sources to synthesize graphene in the
gas phase.) However, it is far from enough to introduce only a carbon source into
the reaction chamber. During the preparation process, hydrogen gas is also required
to promote carbon deposition on the substrate. Because in the process of graphene
crystal growth, the role of methane is to provide a carbon source, and the role of
hydrogen is to provide H atoms to corrode amorphous C [24], but too many hydrogen
atoms will also corrode graphene, leading to the destruction of the integrity of the
graphene lattice [25]. Therefore, it is necessary to adjust the ratio of carbon source to
hydrogen to achieve the best synthesis effect. For substrate, metal film and alloy film
are usually used to deposit graphene, different kinds of metal film, and the percentage
of the alloy film also determine the quality and the thickness of the synthesized
graphene. In addition, temperature, pressure, reaction chamber materials, and other
complex factors also play an important role in graphene synthesis. In most CVD
synthetic graphene applications, low-pressure CVD (LPCVD) synthesis technology
with a pressure ranging from 1 to 1500 Pa is usually used [16, 26–28]. However,
some reports also use atmospheric pressure CVD (APCVD) synthesis technology
[29]. Low pressures are currently the more commonly used methods because they
help produce a more uniform deposition thickness on the substrate and avoid other
unnecessary reactions. The synthesis temperature is usually in the range of 800–
1050 °C, [16, 26–29], but note that although high-temperature environments can
speed up the reaction rate. However, attention should also be paid to the energy
consumption caused by high temperature, the tolerance of the materials in the reaction
chamber, and the potential hazards. In addition, it is usually required that hydrogen
and inert protective gas (such as argon) flow into the system together. Excessive
hydrogen concentration may increase the risk of explosion. In the application of
CVD synthetic graphene, a quartz tube is usually used as a reaction chamber [16,
26–29]. Because quartz has a high melting point and is chemically inert.
Finally, we talk about some details about CVD graphene using methane sources.
In Common, first the copper film is H2 annealing at the 1040 °C under 3% hydrogen
and 97% argon flow at 500 sccm for 40 min. Then the carbon atoms are adsorbed at
1040 °C under 3% hydrogen and 97% argon flow at 1500 sccm and 5% methane and
95% argon flow at 15 sccm for 55 min. Finally, the temperature is slowly decreased
to 700 °C under 3% hydrogen and 97% argon flow at 500 sccm for 40 min to
3.2 Chemical Vapor Deposition
33
Fig. 3.2 The schematic
diagram of the CVD
graphene synthesis process
synthesize graphene. In addition, during the initial heat process (50 min) and the
cooling process after synthesis (55 min), argon gas is required to protect against
oxidation (argon flow at 500 sccm). This process diagram is shown in Fig. 3.2. At
present, there are researchers using ethylene as a C source for graphene growth.
Compared with methane gas, ethylene is cheaper and has almost the same synthesis
quality [30, 31]. Generally speaking, growing graphene on copper foil using methane
as a C source has become a mature method for the continuous preparation of graphene
films. Figure 3.3 shows graphene grown on A4 paper size copper foil.
3.2.3 Transferring
Graphene synthesized by chemical vapor deposition has many uses, but for most
applications, it must be transferred from the metal film to other different substrates
[32–35]. In this section, we will demonstrate two of the most popular methods that
are transferring graphene from metal films to substrates based on electrochemical
transfer and etching methods. The first method is the electrochemical exfoliation
method, it can quickly exfoliate the CVD graphene from the metal film. The second
method is the etching transfer method. This method uses etchant to etch the metal
film, then transferring graphene to the substrate. Although it will take a long time,
the further higher quality of the continuous graphene can obtain compared with the
electrochemical exfoliation method. Thus the etching method is usually preferable.
For electrochemical transfer, a flexible polymer is coated on the graphene/metal
foil so that it can be used as the cathode in the water electrolysis cell. Generally,
NaOH is used as an electrolyte in an aqueous solution. Generate hydrogen bubbles
and squeeze them into the graphene–metal interface to mechanically delaminate the
graphene/polymer from the metal. The electrochemical bubble transfer of graphene
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Fig. 3.3 The graphene
grown on A4 paper size
copper foil through the CVD
method
has become a technology with high industrial potential due to its scalability, time
and cost-effectiveness, and environmental protection. However, graphene is often
damaged due to turbulence and direct H2 O and H + infiltration through the supporting
polymer to form bubbles [36].
If the experiment requires high-quality continuous graphene, it is recommended
to use the etching transfer method. Generally speaking, the etching method requires
spin-coating an auxiliary transfer layer on the graphene film. The more commonly
used ones include poly(methyl methacrylate) (PMMA). In addition, some research
also reported that rosin can also be used as an auxiliary transfer layer. Taking PMMA
as an example, the etching method is more complicated, but it can almost continuously
cover the surface of graphene and prepare high-quality graphene films. First, a layer
of PMMA is spin-coated onto graphene to serve as a support. An etchant is then used
to remove the metal film, and the PMMA/graphene stack is transferred to another
substrate. Finally, a solvent is used to remove PMMA to complete the graphene
transfer. At present, FeCl3 or ammonium persulfate is usually used as an etchant to
etch copper foil [37–40]. However, the etching time is long and the transfer process
requires a superb transfer method. Thus transferring graphene using the PMMA
method is not an easy procedure. Figure 3.4 shows the etching process of graphene
copper foil based on ammonium persulfate, which shows the relationship between
etching and time.
3.2 Chemical Vapor Deposition
35
Fig. 3.4 The etching process of graphene copper foil based on ammonium persulfate, a 0 h, b 1 h,
c 2 h, d over 3 h
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Finally, we talk about some experiences about the PMMA transfer method. First
of all, in general, the vibration of the device should be avoided as much as possible
during the transfer process, which may cause damage and wrinkles in the graphene
film. Second, during the graphene transfer process, the transfer should start along
the edge of the graphene first, and the substrate should first contact the edge of the
graphene, and then pull it out diagonally and should try to avoid repeated transferring.
Although the CVD method has been considered as the most potential synthesis
process for the larger areas of high-quality graphene, the high temperatures (around
1000 °C) also induce a series of problems such as the copper’s significant evaporation and thermal load. In sharp contrast, the synthesis of graphene by plasmaenhanced CVD (PECVD) can improve this problem by substantially shortening the
processing time and the prospect of lowering the substrate temperature. PECVD
method allows that the graphene can be synthesized at a lower temperature. It is
an important current research direction that is, hoping to, widely used to synthesize the high-quality graphene substrate. Figure 3.5 shows the image of the PECVD
equipment and the heat pretreatment (annealing) equipment.
Fig. 3.5 a The image of the PECVD equipment. b The image of the heat pretreatment (anneal)
equipment
3.3 Epitaxial Growth
37
3.3 Epitaxial Growth
Although the traditional graphene FET biosensor is made from chemical vapor deposition (CVD) graphene, this method has to bring the surface contamination during the
transfer step [41]. During the transfer step, for easier transferring the CVD graphene,
CVD graphene is covered an organic protection layer like PMMA. Although this
method made it easier to be transferred, this organic protection layer is too difficult
to remove, even by the H2 anneal. This contamination is a kind of craft defect in
actually.
In order to avoid this contamination from the transfer step, using the SiC substrate
to manufacture the graphene FET directly, it can make sure the surface clean during
the whole manufacturing step [42]. In this section, we briefly describe how to prepare
epitaxially grown graphene and how to characterize it.
3.3.1 Epitaxial Graphene Preparation
The SiC graphene was prepared by directly heating the 6H-SiC(0001) sample at
1350 °C for six cycles of 60 s under ultrahigh vacuum (UHV) condition (maximum
pressure 5.0 × 10−9 Torr). Thus the prepared SiC graphene on the Si-face of SiC
substrate usually contains one to three layers of graphene. The typical sample size
(cut from a 6H-SiC(0001) wafer) was about 10 mm × 10 mm. For making sure
the quality of the epitaxial graphene, the sample after preparation is examined by
scanning X-ray photoelectron spectroscopy (XPS).
3.3.2 Graphene Characterization
Graphene was directly manufactured onto the surface of the SiC substrate. Figure 3.6
shows the wide-range XPS spectra of the SiC graphene substrate. This XPS spectrum
shows only the peaks corresponding to C (C 1 s) and Si (Si 2 s and Si 2p). There are
no other peaks that exist in these XPS spectra. This result indicates that there are no
contaminants on the surface of the SiC graphene substrate. The high-resolution C
1 s peak of the SiC graphene substrate is shown in Fig. 3.7. It can be deconvoluted
into two parts as 283.6 and 284.7 eV. The 283.6 eV part represents the C atoms of
the SiC. The 284.7 eV part represents the C atoms of the graphene [43]. This result
confirms that the graphene exists on the surface of the SiC substrate and there are no
surface contaminants from other kinds of elements. Compared with the original SiC
substrate, after graphene is formed, the surface becomes dark, as shown in Fig. 3.8.
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Fig. 3.6 The wide-range XPS spectra of the SiC graphene substrate
Fig. 3.7 The high-resolution C 1 s peak of the SiC graphene substrate
3.4 Other Methods
3.4.1 Directly Synthesis on SiO2
Some recent new studies have shown that graphene can be directly synthesized on
SiO2 substrates by chemical vapor deposition [44, 45]. In fact, low-temperature
growth of graphene and transfer-free growth on the substrate have always been the
focus of graphene research, because they can better integrate with current semiconductor technology. Riteshkumar et al. reported a simple method to realize the growth
of transfer-free graphene on a Si (SiO2 /Si) substrate covered by SiO2 at 250 °C
[46]. The key to this method is the catalyst metal, which is not the same as growing
graphene by chemical vapor deposition. A 500 nm thick catalyst metal film was first
deposited onto a SiO2 /Si substrate coated with amorphous C (50 nm thick), then the
sample was annealed under vacuum at 250 °C. Finally, the catalyst metal film was
removed by chemical etching and measured. The Raman spectra showed that strong
G and 2D peaks, and small D peaks, these results confirm that the transfer-free growth
3.4 Other Methods
39
Fig. 3.8 After graphene is formed, the surface becomes dark compared with the original SiC
substrate
of multilayer graphene on SiO2 /Si substrate. Based on the optical microscope and
atomic force microscope, the average domain size of graphene is about 5 µm. Therefore, this method will open up a new way for the growth of non-transferred graphene
at low temperatures. Xu et al. proved that by using a chemical vapor deposition
system assembled with two different temperature regions, it is possible to directly
grow high-quality graphene films uniformly and continuously on a SiO2 substrate
[47]. The graphene growth process is started by nucleating the carbon precursor in
the high-temperature zone through the low-temperature zone. Most of the graphene
films synthesized by this method are single-layer graphene, and the multilayer area
accounts for only a small proportion of them, and its optical transmittance and electrical conductivity can be comparable to the transferred metal substrate graphene.
The method avoids the etching process of the metal substrate and the complicated
graphene transfer process, which is beneficial to combine graphene with the current
semiconductor process.
3.4.2 Reduced Graphene Oxide (R-GO)
Reduced graphene oxide (R-GO) is obtained by treating graphene oxide (GO) with
chemical, thermal, and other methods to reduce the oxygen content, while graphene
oxide (GO) is produced by graphite oxide, which can lead to increased interlayer
spacing and functionalization of the graphite base surface [48].
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The reduction step, as an important production step for reducing graphene oxide,
plays a decisive role in the quality of reduced graphene oxide. Compared with the
mechanical exfoliation method, the CVD method, reduced graphene oxide can be
expected to realize the mass production of graphene. In fact, in a large number of
industrial applications such as friction nanogenerators, energy storage, composite
materials, conductive inks, etc., a large amount of graphene is required for these
applications. R-GO is an effective method for the mass production of high-quality
graphene. Because it can relatively quickly and easily prepare sufficient quantities
of graphene to achieve the required quality level [49].
In terms of specific reduction steps, there are many methods to achieve reduction,
although they are all based on chemical, thermal, or electrochemical means. Some
of these technologies have been able to produce very high-quality R-GO (already
very similar to the original graphene in terms of its structure).
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reduced-graphene-oxide. Accessed Sep 29, 2020
Chapter 4
Graphene Field-Effect Transistor
Biosensor
Abstract As a new type of sensing platform, graphene field-effect transistor
biosensor has unique advantages for sensing applications such as magnetism, pressure, chemistry, and biology. Using graphene as a sensing channel, because any local
graphene conductance changes caused by magnetic force, pressure, chemical, and
biological, and other complex factors coupling will affect the conductance of the
entire graphene channel, thus this new type of sensing platform theoretically has
a high sensitivity. For the graphene field-effect transistor biosensor, the surface of
the graphene sensing channel directly contacts the test liquid, and then the electric signal (current Ids signal is usually used) is used to quickly and quantitatively
detect the concentration of specific molecules in the test liquid. This chapter first
introduces the unique electric double layer structure formed at the interface between
graphene and the liquid to be measured. After that, the basic structure and sensing
principle of graphene field-effect transistors are introduced, and then the relationship
between the adsorption of specific molecules and the change of current is proposed.
Finally, the main applications of current biosensors based on graphene field-effect
transistors are briefly introduced. This chapter first introduces the unique electric
double layer structure formed at the interface between graphene and the test liquid.
After that, the basic structure and sensing principle of graphene field-effect transistors are demonstrated. Then the relationship between the adsorption of specific
molecules and the variation of current Ids (the variation of current Ids and the concentration of specific molecules) is proposed. Finally, the main applications of graphene
field-effect transistor biosensors are briefly introduced.
Keywods Graphene · Electrical double layer · Field-effect transistor · Biosensor ·
Graphene FET
In the past few decades, fast and reliable sensing technology for biomolecules detection in medical diagnosis, healthcare, and lab on a chip has become a more and more
important central issue that had been widely studied, such as many optical methods
and other electrochemical sensors, which have been applied to the clinical diagnosis
in our daily life. Strictly speaking, the graphene field-effect transistor biosensor is
not a completely novel technology. As far as we know, Mohamed M. Atalla and
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021
S. Wang et al., Graphene Field-Effect Transistor Biosensors,
https://doi.org/10.1007/978-981-16-1212-1_4
45
46
4 Graphene Field-Effect Transistor Biosensor
Dawon Kahng invented MOSFET (Metal Oxide Semiconductor Field-Effect Transistor, or MOS transistor) in 1959 and proved it in 1960 [1]. Two years later, Leland
C. Clark and Champ Lyons first proposed the concept of biosensors in 1962 [2, 3].
The biosensor MOSFET (BioFET) was developed after 1970 and has been widely
used to measure chemical, biological, physical, and environmental parameters [4].
In 1970 Piet Bergveld invented the first BioFET, an ion-sensitive field-effect transistor (ISFET), for electrochemical and biological applications [5, 6]. In addition,
other early research on BioFET also includes P.F. Cox’s patented adsorption FET
(ADFET) in 1974. I. Lundstrom, M.S. Shivaraman, C.S. Svenson, and L. Lundkvist demonstrated hydrogen-sensitive MOSFETs in 1975 [4]. ISFET is a special
MOSFET with a certain distance from the gate [4]. The metal grid is replaced
by an ion-sensitive membrane, electrolyte solution, and reference electrode [7].
ISFET has been widely used in different kinds of biomedical applications, such as
blood biomarker detection, antibody detection, DNA hybridization detection,glucose
measurement, pH sensing, and genetic technology [7].
By the mid-1980s, other kinds of BioFETs had been developed, including the
gas sensor FET (GASFET), pressure sensor FET (PRESSFET), chemical fieldeffect transistor (ChemFET), immunologically modified FET (IMFET), and enzymemodified FET (ENFET) [4]. By the early 2000s, BioFETs such as the gene-modified
FET (GenFET), DNA field-effect transistor (DNAFET), and cell-potential BioFET
(CPFET) have also been reported [7].
Since 2004 K.S. Novoselov and coworkers find the new miracle material,
graphene, which brings lots of outstanding property, such as the large surface area,
atom-scale thickness, high carrier mobility [8]. This breakthrough opened the 2D
materials gate, and let the bioFET technology based on the 2D materials such as
graphene is possible. Graphene as the channel of the FET for the sensing application was also first demonstrated by K.S. Novoselov and his group in 2007 [9]. They
fabricated sensors made from graphene nanosheet and found that the conductivity
of the graphene is sensitive to gas molecule adsorption. This work pioneered the
introduction of 2D materials into FETs for the first time and predicted the other
potential applications of graphene-based FETs in chemical and biological sensing.
Then in 2009, Ohno et al. first demonstrate the bovine serum albumin sensing based
on the electrolyte-gated graphene FET sensor [10]. They demonstrate that through
interface adsorption, the protein concentration in the liquid pool can be detected
by the change of Ids. This is the first time that graphene FET sensor has been
used for protein detection. In the past 10 years, many kinds of linkers had been
reported for specific biomolecules detection such as nanoparticles, 1-pyrenebutyric
acid n-hydroxysuccinimide ester (PBASE), and tetrakis(4-carboxyphenyl)porphyrin
(TCPP) [11–13]. These linkers can bind the specific biomolecules to the interface
of the graphene such as the antibodies, aptamers, and DNA [14–20]. Based on these
properties from these biomolecules, the graphene FET biosensor can execute many
forms of specific detection and be given different designated functions. Linkers and
biomolecules modified into the surface of the graphene greatly enriched the application scope of the graphene FET biosensor. Nowadays, graphene FET biosensor has
become one of the most potentially promising technologies for rapid diagnosis and
4 Graphene Field-Effect Transistor Biosensor
47
MOSFET IS INVENTED IN 1960
Mohamed M. Atalla and Dawon Kahng
BioFET IS INVENTED IN 1970
Piet Bergveld
GRAPHENE IS DISCOVERED IN2004
K.S. Novoselov and coworkers
GRAPHENE FET BIOSENSOR IS INVENTED IN 2009
Ohno et al.
FUNCTIONALIZED GRAPHENE
FET BIOSENSOR UNTIL NOW
Fig. 4.1 The development history of graphene FET biosensors
real-time sensing. Relying on rapidity and real-time performance, graphene biosensors can complement traditional detection methods. Especially for the large-scale
detection of epidemic diseases such as COVID-19, graphene FET biosensors have
become the potentially promising detection method [21]. This development history
of graphene FET biosensors is depicted in Fig. 4.1.
However, there are also a series of non-ignorable problems, have to face, that
hinder its practical application, such as the transfer of the graphene, the merge of the
semiconductor craft, the quality of the graphene, and other complex problems. These
problems hinder the further practical applications for the graphene FET biosensors.
4.1 Electrical Double Layer
A double layer (DL, also called an electrical double layer, EDL) is a structure that
appears on the surface of an object when it is exposed to a fluid. The object might be
a solid particle, a gas bubble, a liquid droplet, or a porous body. The DL refers to two
parallel layers of charge surrounding the object. The first layer, the surface charge
(either positive or negative), consists of ions adsorbed onto the object due to chemical
interactions. The second layer is composed of ions attracted to the surface charge via
the Coulomb force, electrically screening the first layer. This second layer is loosely
associated with the object. It is made of free ions that move in the fluid under the
influence of electric attraction and thermal motion rather than being firmly anchored.
It is thus called the “diffuse layer”. A double layer (DL) sometimes it is also called an
electric double layer, (EDL) which is a specific structure that appears on the interface
between an object when it is exposed to the fluid. Objects can take many forms,
including solid particles, flat surfaces, porous bodies, and other complex shapes. In
48
4 Graphene Field-Effect Transistor Biosensor
simple terms, DL refers to two parallel charge layers formed around an object. The
first layer of surface charge (positive or negative) is the composition of ions adsorbed
on the object due to chemical interaction. The second layer is composed of ions that
are attracted to surface charges by Coulomb force and electrically shields the first
layer. The second layer is loosely associated with the object. It is often affected by
a series of complex factors such as liquid flow rate and vibration. Therefore, the
second layer is not firmly anchored to the interface, and therefore, it is called the
“diffusion layer”. In fact, in a broader sense, essentially after any two phases are in
contact (solid–liquid, solid–gas, liquid–gas), an electric double layer will be formed
at the interface of different phases. Note that even if different substances in the same
phase are in contact, the similar electric double layer phenomenon still exists. Here,
we mainly discuss the phenomenon of the electric double layer at the solid–liquid
interface.
The development of the (interfacial) double-layer can be traced back to 1853
[22]. Hermann von Helmholtz was the first to realize that penetrating a charged
electrode into an electrolyte solution would attract counter ions to its surface and
drive out the same ions in the charge. He also claimed that the double layer with
opposite polarity will be formed at the interface between the electrode and the
electrolyte. In 1853, he proved that the electric double layer (DL) is essentially a
molecular dielectric and stores electric charge electrostatically, then, it has undergone seven major improvements. They are Gouy–Chapman model (1910) [23], Stern
model (1924) [24], Grahame model (1947) [25], Bockris/Devanathan/Müller model
(BDM) (1963) [26], Trasatti/Buzzanca model (1971) [27], Conway model (1991)
[28], Marcus (1992) [29]. For the graphene bio-FET sensor, as relatively simple
models, the Stern model (1924) and the Bockris/Devanathan/Müller model (BDM)
(1963), can explain the phenomenon of biosensing very well. The Stern model (1924)
macroscopically summarizes the overall situation of the graphene electric double
layer, and the Bockris/Devanathan/Müller model microscopically explains the actual
distribution of ions on the interface.
4.1.1 Stern Model (1924)
Because the Gouy–Chapman model cannot describe the highly charged DLs. well. In
1924, Otto Stern proposed to combine the Helmholtz model with the Gouy–Chapman
model to form the Stern model. In Stern’s model, some ions adhere to the electrode
as suggested by Helmholtz, forming the internal Stern layer, while others form the
Gouy–Chapman diffusion layer at external [24].
The Stern layer illustrates the finite size of the ions, so the nearest approach
between the ions and the electrode is about the ion radius. However,the Stern model
still has its limitations, that is, it treats ions as point charges, assumes that allimportant interactions in the diffusion layer are Coulombic, and assumes that the
dielectric constant of the entire double layer is constant, and the fluid viscosity is a
constant plane. The schematic diagram of the Stern model is shown in Fig. 4.2.
4.1 Electrical Double Layer
49
Fig. 4.2 The schematic diagram of the stern model
4.1.2 BDM Model (1963)
J. O’M. Bockris, M. A. V. Devanathan and Klaus Müller first reported a two-layer
BDM model in 1963, which included the role of solvent in the interface [26]. They
proposed that the solvent attached molecules (such as water) should have a fixed
alignment with the electrode surface. The first layer of solvent molecules shows
a strong orientation to the electric field according to the charge. This orientation
has a great influence on the dielectric constant of the solvent that changes with the
field strength. The inner Helmholtz plane (IHP) passes through the centers of these
molecules. Particularly adsorbed, partially solvated ions appear in this layer. The
solvated ions of the electrolyte are outside the IHP. The centers of these ions pass
through the outer Helmholtz plane (OHP). The diffusion layer is a region other than
OHP. The schematic diagram of the BDM model is shown in Fig. 4.3.
When a voltage is applied to the capacitor, two layers of polarized ions are generated at the electrode interface. One layer is inside the solid electrode (on the surface of
the crystal grain in contact with the electrolyte). The other layer of opposite polarity
is formed by dissolved and solvated ions distributed in the electrolyte, which have
moved to the polarized electrode. The two layers of polarized ions are separated by a
single solvent molecule. The molecular monolayer forms the inner Helmholtz plane
(IHP). It adheres to the electrode surface by physical adsorption and separates the
oppositely polarized ions from each other to form a molecular dielectric.
The amount of charge in the electrode matches the magnitude of the countercharge
in the outer Helmholtz plane (OHP). This is the area where polarized electrolyte ions
are collected near the IHP. This separation of the two layers of polarized ions passing
through the double layer stores charges in the same way as a conventional capacitor.
The double-layer charge forms an electrostatic field in the molecular IHP layer of
solvent molecules, which corresponds to the strength of the applied voltage.
50
4 Graphene Field-Effect Transistor Biosensor
Fig. 4.3 Schematic representation of a double layer on an electrode (BMD) model. 1. Inner
Helmholtz plane, (IHP), 2. Outer Helmholtz plane (OHP), 3. Diffuse layer, 4. Solvated ions (cations),
5. Specifically adsorbed ions (redox ion, which contributes to the pseudocapacitance), 6. Molecules
of the electrolyte solvent
In the electrolyte, the thickness depends on the size of solvent molecules and the
movement and concentration of ions in the solvent. As described in the Debye length
below, the range is 0.1–10 nm. The sum of the thickness is the total thickness of the
double layer.
4.2 Debye Length
At room temperature (20 C), the Debye length can consider in water the relation
[30].
0.304
κ −1 (nm) = √
I (M)
where
κ −1 is expressed in nanometers (nm)
I is the ionic strength expressed in molar (M or mol/L).
4.2 Debye Length
51
Commonly speaking, for the contact between the metal electrode and the solution, the “thickness” of a charged layer in the metallic electrode, i.e., the average
extension perpendicular to the surface, is about 0.1 nm, and mainly depends on the
electron density because the atoms in solid electrodes are stationary. Because of the
unparalleled ultra-thin properties of graphene, changes from the charge layer will be
completely transferred to the channel material of graphene, which is unmatched by
traditional bulk materials. Thus graphene-based FET sensor has a significant sensing
level compared with the traditional bulk materials.
4.3 Graphene Field-Effect Transistor
The field-effect transistor (FET) is one kind of transistor that can use the electric
field to regulate the flow of current from the drain terminal to the source terminal.
Normally, FETs contain three different terminals: source, drain, and gate between
the source and drain terminal,the specific semiconductor channel is placed so that the
current flow through this channel can be regulated by the variation of gate voltage.
Generally speaking, because FET can control the source-to-drain current by changing
the gate voltage, thereby changing the conductivity between the drain and the source.
The graphene field-effect transistor (GFET) follows the typical structure of the FET
device and the semiconductor channel between the source and drain is replaced with
graphene to make a graphene field-effect transistor. Because the channel in the GFET
uses graphene, which is a lattice of carbon atoms with a thickness of only one atom,
therefore, any small changes that occur near the interface may be coupled with the
carrier concentration of the local graphene, which will significantly affect the entire
graphene channel, thus it has unprecedented sensitivity and can be used in various
applications, such as photosensitive, magnetic sensing, gas sensing, and biological
sensing. FETs control the flow of current by the application of a voltage to the
gate, which in turn alters the conductivity between the drain and source. Graphene
field-effect transistors (GFETs) take the typical FET device and insert a graphene
channel tens of microns in size between the source and drain. Being graphene, a
lattice of carbon atoms that is only one atom thick, the channels in GFETs have
unprecedented sensitivity, which can be exploited in a wide variety of applications
such as photosensing, magnetic sensing, gas sensing, and biosensing. Figure 4.4
shows the schematic of the typical graphene FET structure.
For the biomolecules detections, the graphene channel is directly exposed so that
it can sufficiently contact with the test solution to permit the binding and detection of biomolecules such as biomarker, nucleic, protein, virus, or other specific
biomolecules [31]. When these specific biomolecules bind onto the graphene channel,
these molecules will affect the double layer capacitance between the interface thus
change the carrier density in the graphene side inducing the variation of the graphene
conductivity. While the target biomolecules typically do not directly specifically
bind with the bare graphene surface, the corresponding antibodies can be used to
52
4 Graphene Field-Effect Transistor Biosensor
Fig. 4.4 shows the schematic of the typical graphene FET structure
modify the surface of the graphene. This processing gives the graphene surface the
ability to specifically bind target biomolecules. Thus it makes specific detection of
biomolecules possible.
4.4 Graphene Field-Effect Transistor Biosensors
Graphene field-effect transistor (FET) biosensor for protein detection can be traced
back to 2009, Ohno et al. first reported the electrolyte-gated graphene FET biosensor
for bovine serum albumin (BSA) concentrate detection [10]. They using the exfoliated graphene to make the channel of the FET, basing the physical adsorption between
the graphene and BSA, the concentration of the BSA can be quantitatively detected
by the current of the Ids. This work confirmed that protein rapid quantitive detection
is possible by the graphene FET biosensor. Almost after 10 years, although the structure of the graphene FET biosensor is not changing many crafts and manufacturing
details have changed. In this section, we will review this novel craft and manufacture
details.
In the earliest days, graphene FET biosensor s were made based on nanosheets
mechanically exfoliated from highly oriented pyrolytic graphite (HOPG) or natural
graphite [10]. The atomic-thick graphene nanosheets are obtained by mechanical
exfoliation to make the FET sensor channels, because high-quality single-layer
graphene films could not be prepared in large quantities at that time. It was not
until the CVD method of synthesizing graphene on copper foil was discovered and
widely put into use that the mechanical exfoliate method was then gradually replaced.
Up to now, graphene synthesized by CVD on the copper foil is still widely used in
the research of graphene FET sensors.
4.4 Graphene Field-Effect Transistor Biosensors
53
The field-effect transistor (FET) is a type of transistor that uses an electric field
to control the flow of current. For the normal FET, there are three terminals: source,
gate, and drain. FETs control the flow of current by the application of a voltage to the
gate, which in turn alters the conductivity between the drain and source. Normally,
FETs use electrons or holes as charge carriers in their operation, but not both. Many
different types of field-effect transistors exist. Graphene FET is one of the special
FETs. Because graphene is a zero-bandgap semiconductor, gate voltage regulation
cannot completely switch off the current from source to drain. Moreover, through
gate voltage regulation, the carrier type can also be changed from the hole area to the
electron area. For the graphene bio-FET sensor, not only the gate can regulate the
current but also the graphene interface can also regulate the current through binding
the specific molecules to the surface of graphene. When the target molecules are
bound onto the surface of the graphene, the charge distribution at the interface of
the graphene is regulated, this regulated principle is similar to the special gate for
the graphene bio-FET sensor. Therefore, the target molecule concentration can be
quantitively detected through observing the graphene FET biosensor current. The
schematic diagram of the traditional graphene FET biosensor is shown in Fig. 4.5.
The CVD graphene is transferred onto the SiO2 /Si substrate, and during the two
sides of the graphene, there are the source and drain terminals made from metal.
In some applications, for regulating the graphene conductivity better, the reference
electrode is used as the top gate into the electrolyte solution. These are the most basic
Metal terminal
SiO2
Si
modificaƟon
D
Fig. 4.5 The schematic diagram of the traditional graphene FET biosensor
S
54
4 Graphene Field-Effect Transistor Biosensor
Fig. 4.6 a The schematic diagram of the PBASE. b The schematic diagram of the TCPP
components of the graphene FET sensors. Moreover, in order to enable the graphene
FET sensor to achieve certain specific functions, the surface of the graphene usually
needs to be modified. For biosensing, the modification step is very important for
the sensitivity and specificity of the sensor. It is mainly divided into three steps: 1.
Modification of linkers 2. Modification of specific biomolecules 3. Blocking.
For the modification of the linkers, the most commonly used linker is PBASE and
AuNPs. Graphene is then chemically modified using 1-pyrenebutanoic acid succinimidyl ester (PBASE) through the Van der Waals force between the graphene and the
pyrene backbone of PBASE molecule. This interaction is usually called π-stacking
[32]. Then PBASE modified graphene is further modified with biomolecules through
the NHS ester reaction from N-hydroxysuccinimide ester group of PBASE. The
schematic diagram of the PBASE is shown in Fig. 4.6a. Otherwise, some studies show
that the tetrakis(4-carboxyphenyl)porphyrin (TCPP) was used as a linker for surface
modification of the graphene FET and the properties of the device were better than the
graphene FET device modified with the conventional linker 1-pyrenebutanoic acid
succinimidyl ester (PBASE) [13]. TCPP modification resulted in a higher density
of receptor immunoglobulin E (IgE) aptamer molecules on the graphene FET. This
study indicated that the TCPP may be a potential excellent linker than the PBASE.
The schematic diagram of the TCPP is shown in Fig. 4.6b. Graphene is decorated
with AuNPs, which is also a commonly used method for the modification of linkers
[11]. The biocompatibility and high surface energy of Au allow it to bind to a large
amount of protein without altering its activity and result in a more sensitive sensor.
For the modification of specific biomolecules, there are several different types
such as the antibody, nucleic acids, aptamer, and others. These different types of
modification methods both have a unique property that they can bind with other
specific biomolecules, such as the antibody can bind with its specified antigen, the
nucleic acids can bind its corresponding nucleic acid chain based on the complementary base pairs. Actually, the function of the graphene FET biosensor is determined
4.4 Graphene Field-Effect Transistor Biosensors
55
by the modified specific biomolecules. As far as antibody modification is concerned,
the antigen is specifically bound by the antibody and binds with high affinity to
form an antigen–antibody complex, thereby realizing the detection of the specific
antigen. Compared with aptamers, antibodies generally have higher affinity. Therefore, in some applications, graphene FET biosensors perhaps have higher sensitivity
after being modified with antibodies than with aptamers. But generally speaking,
aptamers usually have a simpler structure than antibodies thus aptamers are more
suitable for large-scale production, and the aptamers are not easily affected by temperature, humidity, and other factors. Therefore, graphene FET biosensors modified
with aptamers are more conducive to long-term storage. Moreover, aptamers have
an innate ability to bind to any molecule they are targeted at, including cancer cells
and bacteria. Thus, its application scale is wider than the antibodies theoretically. It
can be said that the two methods have advantages for each other.
Blocking is the last step of manufacturing processing. For the graphene FET
biosensor, because the previous processing can not cover the entire surface of the
graphene, the blocking processing can block the uncovered surface of the graphene
after biomolecules modification that is to prevent the non-specific bind occurred at the
uncovered area during the real-time detection. Because during real-time detection, the
uncovered surface of the graphene will bind the other biomolecules through simple
adsorption. It will induce the decrease the specificity during the real-time test. The
BSA solution is the most commonly used for blocking processing, but some of the
studies reported that the BSA solution may not the perfect blocking solution for the
graphene [33] and proposed that ethanolamine is more suitable for the graphene FET
biosensor [34]. Moreover, in some applications of the detection of nucleic acid, some
studies indicate that guanine blocking is a useful potential method for the graphene
surface [35].
The IV curve is the important characterization method for the graphene FET
biosensor. The IV Test-Setting of the bare graphene FET is shown in Fig. 4.7a.
The Vds is fixed at 0.1 V, 0.15 V, 0.20 V, 0.25 V, and 0.30 V respectively among
each IV-Test. The Vgs is connected to the back gate (Si/SiO2 substrate). The Vgs
is swept at the −50–50 V among each IV-Test. Based on the bare graphene FET
biosensor, the different Vds of the IV curve is shown in Fig. 4.7b. When the back
gate is connected to the negative voltage, due to the electric field effect, there are
fewer electrons on the graphene surface, and the Fermi level drops. At this time,
the Fermi level is in the valence band, and holes are the main carriers, dominating
the graphene conductivity. When the back gate voltage gradually increases, due to
the electric field effect, the electrons on the graphene surface gradually increase,
and the valence band is gradually filled. When the back gate voltage moves to 0,
the graphene Fermi level is still in the valence band, and holes still dominate the
graphene conductivity. When the gate voltage is further increased to around 20 V,
since graphene is a zero-bandgap semiconductor, the Fermi level is at the junction of
the valence band and the conduction band. Based on the quantum tunneling effect,
as well as the thermal effect, graphene can still conduct electricity at this time, and
a small number of holes and electrons in the same amount simultaneously dominate
56
4 Graphene Field-Effect Transistor Biosensor
Fig. 4.7 a The IV Test-Setting of the bare graphene FET in different Vgs and Vds. b The IV curve
of the bare graphene FET in different Vgs and Vds
4.4 Graphene Field-Effect Transistor Biosensors
57
the conductivity of graphene. At this time, graphene has the least total amount of
carriers and the lowest conductivity. The corresponding point at this time is usually
called the Dirac point, and the voltage corresponding to this point is usually called
the Dirac voltage of graphene. Note that when the graphene is in the region near its
Dirac point, holes and electrons simultaneously dominate the graphene conduction,
and the conductivity is the lowest at this time. When the back gate voltage is further
increased, the Fermi level of graphene is further upper. At this time, the Fermi level
has entered the conduction band, and electrons as the main carrier dominate the
conductive properties of graphene. In addition, the conduction state of the graphene
can be classified according to the types of the carrier, when the gate voltage is much
smaller than the voltage of the Dirac point, the graphene is in the P zone (hole area).
When the voltage is much greater than the voltage at the Dirac point, graphene is
in the N zone (elec. area). When the voltage is near the Dirac voltage, the graphene
is in the Dirac zone. Note that the slopes of the IV curves of the P and N zones are
in opposite directions and equal in magnitude. This result implies that the carrier
mobility (uelec. and uhole ) of holes and electrons is approximately equal. When the
back gate voltage is 0, the graphene is in the P zone. Most of the bare graphene FETs
made from the CVD graphene are the P-type (the Dirac point is on the right side of
the Vgs). It indicates that the hole plays the Maxine carriers on bare graphene, and
the conductivity of the graphene is regulated by Vgs and Vds at the same time, but
whether it is changing Vds and Vds, the position of Dirac point cannot be changed.
These results indicated that for the same graphene FET, the conductivity can be
regulated by the Vds and Vgs. But the regulation of the Vds and Vgs can not change
the position of the Dirac point.
The position of the Dirac point may be related to the inherent properties of the
interface graphene. Some of the studies reported that the changing of the Dirac
point position can be regulated by the doping, the interface capacity effect, and
other complex factors involved in the graphene interface [36–38]. In addition, we
should note during the actual test that the pH value of the test solution and the ion
concentration can also regulate the position of the Dirac point [10, 39].
For the GFET biosensor, the Dirac shift of graphene interface maintains high sensitivity for any modification and adsorption such as surface modification and molecules
adsorption. In the following discussion, we first introduce the Dirac shift caused by
graphene surface modification (AuNPs modification and PBASE modification) and
then discuss the Dirac shift caused by molecular adsorption.
Here I–V measurements are given for the clean and modified graphene. Vgs
(back-gate) is swept at −10–60 V, Vds is fixed at 0.1 V, and the source terminal is
grounded. A typical I–V curve for the clean and AuNP-modified graphene is shown in
Fig. 4.8a. A typical I–V curve for the clean and PBASE-modified graphene is shown
in Fig. 4.8b. For Fig. 4.8a, compared to the clean graphene, a large shift of the Dirac
point toward lower voltages is observed in the case of AuNP-modified graphene. This
shift in the Dirac point toward lower voltage indicates that the decoration of graphene
with AuNPs decreases the extent of P-doping characteristics. This phenomenon can
be attributed to differences in the work function between graphene and Au. The work
58
4 Graphene Field-Effect Transistor Biosensor
Fig. 4.8 a I–V curves for clean and AuNPs modified graphene. b I–V curves for clean and PBASE
modified graphene
function of graphene and Au is around 4.2 and 5.1 eV respectively. When the AuNPs
are deposited on the surface of the graphene, the work function difference induces the
electronic charge transfer from AuNPs to graphene. Note that the bare graphene is
strong P-doped. (Because of many complex factors such as surface organic residues.)
Figure 4.9 shows the details about the Dirac point shift after AuNPs modification.
For Fig. 4.8b, a typical I–V curve for clean and PBASE modified (modified for
4 h) graphene is shown. A large shift of the Dirac point towards higher voltages
is observed in the case of PBASE-modified graphene, this shift in the Dirac point
toward lower voltage indicates that the decoration of graphene with PBASE increases
the extent of P-doping characteristics. The possible reason is that pi–pi stacking fixes
part of the free electrons of graphene, which leads to further enhancement of P-doped.
This phenomenon has been observed and confirmed in many other published papers.
Figure 4.9 shows the details about the Dirac point shift after PBASE modification.
Besides, for molecular adsorption and binding, the Dirac shift of graphene will
also occur. For the graphene–gas interface, some specific graphene gas sensors can
be made based on the Dirac displacement produced by the interface adsorption and
binding. For the graphene–liquid interface, specific graphene liquid sensing devices
such as biosensors can also be fabricated based on the Dirac displacement generated
by the interface adsorption and binding. At present, the electrical changes caused by
the Dirac shift of graphene can be quickly and easily observed through a variety
of electrical methods, there have been a large number of related researches on
the sensing applications of graphene solid–liquid interface sensing and solid–gas
interface sensing, showing huge application potential.
4.4 Graphene Field-Effect Transistor Biosensors
59
Fig. 4.9 The details about the Dirac point shift after AuNPs modification and PBASE modification
60
4 Graphene Field-Effect Transistor Biosensor
4.5 Mechanism of the Graphene Field-Effect Transistor
Biosensors
When the target molecule is bound to the graphene interface, although two main
mechanisms (direct charge transfer and electrostatic field effect) can both adjust
the conductive properties of graphene, the electrostatic field effect plays a leading
role in most GFET biosensor applications. Taking antigen–antibody interaction as
an example, because the detection object is usually a biological molecule such as
an antigen, which is not the conductor. Moreover, its charge is difficult to cross the
antibody linker or the electrolyte double layer through direct charge transport then
affecting the conductive properties of graphene. Thus the main mechanism is the
electrostatic field effect of the electrolyte double layer. In the following sections,
we will discuss based on this mechanism. In most biosensing applications, it is
necessary to introduce receptor–ligand interaction as a tool to specifically recognize
biomolecules. In order to identify specific ligands to be detected, the receptor needs
to be modified on the graphene surface at first.
For the specific biomolecules (ligand), the charges of the specific biomolecules
could affect the charge distribution at the interface double layer between the graphene
and the PBS solution to achieve the effect of regulating the conductivity of the
graphene. The observation of the variation for the current Ids indicates that the
specific biomolecules (ligand) in the solution bind onto the surface of the graphene
leads to an interface capacitance variation at the double layer, thus changing the
graphene carrier density (hole density). Based on σ = neu (σ represents the conductivity of the graphene, e represents the unit carrier charge, u represents the carrier
mobility) that has mentioned mathematical formula in Chap. 2 and Ohm’s law, the
current Ids for the graphene FET biosensor can be demonstrated in I = U ∗ σ (U
represents the voltage between the interdigital electrode. U is 0.1 V during the realtime test.). Hence I = U ∗ neu (e is a constant, when the work point is far from
the Dirac point, u can also be assumed to be constant [40]), thus current Ids and
carrier concentration can be approximated as a linear relationship.
Commonly based on the real-time current Ids variations upon addition of the
different concentrations of specific biomolecule (ligand) solutions during the actual
experiments, current change I and the concentration of the specific biomolecule
(ligand) in solution C can be estimated using the Langmuir adsorption model I =
(C*I max )/(C + Kd ), K d represents the dissociation constant, I max represents the
maximum of the current change [41]. The corresponding Langmuir adsorption model
has the potential to be used as the calibration curve for the quantitative detection of
specific biomolecule (ligand) in a given sample. Note that the theoretical dissociation
constant of the receptor–ligand interaction may be less than the estimated value. This
difference in Kd value, which is in agreement with previous reports, is thought to be
caused by binding of the receptor to the substrate surface [42–44], and the affinity
of receptor–ligand interaction may also be affected when receptor is modified onto
the linkers. In addition, the Langmuir adsorption model indicates that the current
4.5 Mechanism of the Graphene Field-Effect Transistor Biosensors
61
Ids and the concentration of the specific biomolecule (ligand) in the solution can be
approximated as a non-linear relationship.
Based on the mathematical model in Chap. 2 mentioned, we have known that
current Ids and carrier density can be approximated as a linear relationship. Based
on the actual experiments previously described, current Ids and the concentration
of the specific biomolecule (ligand) in the solution can be approximated as a nonlinear relationship. Hence there must have a potential non-linear relationship between
the concentration of the specific biomolecule (ligand) and carrier density. As we
know that the surface adsorption phenomenon follows the Hill–Langmuir equation
m
given by θ = K dC+C m where θ represents the percentage of the surface cover [45].
C represents the concentration of the adsorbates. K d represents the dissociation
constant, which represents the dissociation strength between the specific biomolecule
(ligand) and the surface of the substrate. m represents the Hill coefficient. The m > 1
represents positively cooperative binding, i.e., if the specific molecule binds on the
substrate, its affinity for other specific molecules increases. The m < 1 represents a
negatively cooperative binding, i.e., if the specific molecule binds on the substrate, its
affinity for other specific molecules decreases, and m = 1 represents non-cooperative
(completely independent) binding, i.e., the substrate affinity for a particular molecule
does not depend on the already bonded molecules. If assume that the change quantity
of the carrier density on graphene (n) is S when the specific biomolecule (ligand)
is saturated adsorption (θ = 1) and then assumed that the relationship between
n and θ can be simply approximated to a linear relationship n = S · θ . Thus
m
the analytical expression of I will be given by I = U · S KdC+Cm eμ. When
m = 1, this analytical expression I = U · S KdC+C eμ can be unified with the
I = (C*Imax )/(C + K d ), which is proposed by professor Yasuhide Ohno in 2009
[10]. The latter has been succeeded widely used for electrochemical biosensor nonlinear fitting. This result indicates that the relationship between the change quantity
of the carrier density on graphene (n) and the percentage of the surface cover
(θ ) can be simply approximated to a linear relationship n = S · θ . In addition,
the potential non-linear relationship between the concentration of the biotinylated
biomolecules (C) and the change
of the carrier density on graphene (n)
quantity
Cm
can be approximated to n = S Kd +Cm based on the Hill–Langmuir equation.
4.6 Biological Applications
In this section, the applications of the graphene FET biosensor will be reviewed. At
present, not only the protein, the nucleic acid target can be detected, but also the
living cell, virus, and other target detection are also reported based on the graphene
FET biosensor [8, 46–57]. These representative works will be listed as follows.
For the protein target, it is the most common target for precise disease diagnosis.
Many of the cancer biomarkers consist of protein, such as prostate-specific antigen
62
4 Graphene Field-Effect Transistor Biosensor
(PSA), carcinoembryonic antigen (CEA). The rapid detection of the cancer biomarker
has become the potential application to the graphene FET biosensor field. Lin Zhou
et al. demonstrated that label-free GFET biosensor based on antibody-modified [52].
Antibodies targeting carcinoembryonic antigen (Anti-CEA) were bond onto the
surface of graphene using non-covalent modification. The bifunctional molecule,
PBASE, which is composed of pyrene and a reactive succinimide ester group, interacts with graphene non-covalently via π-stacking. The succinimide ester group reacts
with the amine group to initiate antibody surface immobilization, which was verified
by Atomic Force Microscopy, X-ray Photoelectron Spectroscopy, and Electrochemical Impedance Spectroscopy. The resulting anti-CEA modified GFET sufficiently
monitored the reaction between CEA protein and anti-CEA in real-time with high
specificity, which revealed selective electrical detection of CEA with a limit of detection (LOD) of less than 100 pg/ml. The dissociation constant between anti-CEA and
CEA protein was assessed to be 6.35 × 10−11 M, indicating the high sensitivity and
affinity of anti-CEA-GFET. In addition,Kim et al. report reduced graphene oxide
field-effect transistor (R-GO FET) biosensor for label-free ultrasensitive detection
of a prostate cancer biomarker, prostate-specific antigen/α1-antichymotrypsin (PSAACT) complex [58]. This R-GO channel in the R-GO FET was manufactured by the
reduction of graphene oxide nanosheets networked by a self-assembly process.
Immunoreaction between PSA-ACT and PSA monoclonal antibodies on the RGO channel surface induced a sensitive linear response on the shift of the gate voltage,
Vg, min. They also reported that R-GO FET can detect antibody–antigen interactions
at the fM level, and its dynamic range exceeds Vg by 6 orders of magnitude. For
the pH 6.2 and pH 7.4 analyte solutions, high association constants of 3.2 nM−1
and 4.2 nM−1 were obtained, respectively. In addition, they also confirmed that the
R-GO FET biosensor also showed high specificity for other cancer biomarkers in
PBS buffer and human serum.
In addition, Kim et al. reported a biosensor based on reduced graphene oxide fieldeffect transistor (R-GO FET) for the detection of prostate cancer biomarkers, namely
prostate-specific antigen/α1-antichymotrypsin (PSA-ACT) complex. The label-free
ultra-sensitive detection [58]. The R-GO channel in this device is formed by reducing
graphene oxide nanosheets that form a network through a self-assembly process.
The immune response based on the PSA-ACT complex on the surface of the RGO channel and the PSA monoclonal antibody caused a linear response in the shift
of the gate voltage Vg, min, in which the smallest conductivity appeared. R-GO
FET can detect protein–protein interactions at the droplet level, and its dynamic
range exceeds 6 orders of magnitude of Vg, and the minimum displacement is the
sensitivity parameter. For the pH 6.2 and pH 7.4 analyte solutions, high association
constants of 3.2 nM-1 and 4.2 nM-1 were obtained, respectively. The R-GO FET
biosensor shows high specificity for other cancer biomarkers in phosphate buffer and
human serum.
mRNA is one kind of nucleic acid target, which plays an important role in disease
diagnosis. Tian et al. used graphene field-effect transistor (GFET) biosensors modified with PNA and DNA probes for ultra-sensitive detection of specific RNA [59].
Compared with the DNA probe modified GFET sensor, the detection limit (LOD) of
4.6 Biological Applications
63
the PNA probe modified GFET sensor is reduced to 0.1 aM, which is three orders
of magnitude lower. At the same time, they observed an excellent linear electrical
response to RNA concentrations in a broad range from 0.1 aM to 1 pM for PNA
probe-modified GFET and from 100 aM to 1 pM for DNA probe-modified GFET,
respectively. They also claimed that both PNA and DNA probe-modified GFETs have
great potential in the rapid quantitative detection of specific RNA. Compared with the
DNA probe modified GFET biosensor, the PNA probe modified GFET sensor significantly reduces the detection time and speeds up the detection. In addition, the electrical response of the PNA probe-modified GFET biosensor to non-complementary
RNA is almost negligible, showing that the sensor is highly specific for the detection
of specific RNA. In addition, they also proved that the GFET sensor can also be
applied to detect RNA in human serum, making it a promising method for detecting
RNA in biomedical research and early clinical diagnosis in the future.
For real-time live-cell monitoring, Priscilla et al. developed a graphene transistor
array integrated with a micro-flow cytometer for “flow capture-release” sensing of
malaria-infected red blood cells at the single-cell level [60]. They demonstrate that red
blood cells infected with malaria cause highly sensitive capacitive coupling changes
in the conductivity of graphene. Together with the characteristic conductance dwell
time, specific microscopic information about the disease state can be obtained.
For virus detection, Chen et al. have developed a reduced graphene oxide fieldeffect transistor (R-GO FET) biosensor for real-time detection of Ebola virus antigens [61]. Their biosensor takes advantage of the excellent semiconductor properties
of graphene-based materials (R-GO) and can rapidly conduct high-sensitivity and
specific detection for the Ebola glycoprotein. Ebola glycoprotein diluted with PBS
buffer, human serum, and plasma was used to assess the feasibility of clinical application of this biosensor. These results indicate that their R-GO FET biosensor can
successfully rapidly detect the Ebola virus and it is promising for Ebola virus clinical
diagnosis in the future.
In addition, Zhen Wang et al. develop a •OH FET sensor with a graphene channel
functionalized by metal ion indicators for the free radical detection, and they claim
that at the electrolyte/graphene interface, highly reactive •OH cuts the cysteamine to
release the metal ions, resulting in surface charge de-doping and a current response.
By this inner-cutting strategy, the •OH is selectively detected with a concentration
down to 10−9 M [62].
In the past decade, GFETs based on various interactions have been extensively
studied as shown in Fig. 4.10, including antigen–antibody, base pair, aptamer technology, concanavalin A, and avidin–biotin. Based on the significant advantages of
biosensing, that is, the electronic properties of graphene are highly susceptible to a
series of interface effects such as electrostatic force generated by long-range charge
scatterers and local dielectric environment changes. This makes graphene extremely
sensitive to the surface charge density at its interface. In my opinion, based on these
properties, it will further apply widely in the future. Next sections, I will, respectively, introduce the prospects and developing directions based on my experience for
the variety bio-interaction combined GFET.
64
4 Graphene Field-Effect Transistor Biosensor
Fig. 4.10 The research about GFET combing with various bio-interaction in the past decade
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org/10.1038/s41598-017-11387-7
Chapter 5
Graphene FET Biosensor Based
on the Avidin–Biotin Technology
Abstract Avidin-biotin interaction is the strongest known protein-ligand interaction and is widely used in the field of biomedicine, including immunochromatography and various biological detection technologies. Because avidin or streptavidin
can specifically bind to four biotinylated molecules efficiently and quickly, and the
biotinylated molecules will not change their inherent characteristics. At present, this
avidin-biotin interaction has been widely used in the field of biomedical detection to
amplify biological signals for specific molecules. Combined with the graphene fieldeffect transistor biosensor, using the avidin-biotin interaction, the concentration of
specific molecules in the test solution is expected to be amplified by the biotin-avidin
interaction, which helps to increase the limit of detection for the biosensor. Besides,
based on the avidin-biotin interaction, the graphene field-effect transistor biosensor
is expected to rapidly quantitative detect free biotin and biotinylated molecules.
This chapter mainly introduces the graphene field-effect transistor biosensor from
the perspectives of device preparation, surface modification, sensitivity, and specificity, and discusses the possible situations that the sensor may encounter in actual
detection.
Keywords Avidin · Biotin · Graphene FET · Avidin-biotin interaction
Avidin–biotin technology is widely used in different types of ELISA (enzyme-linked
immunosorbent assay) kits, polymer-based detection and labeled immunosensor s for
the detection of different bio-markers linked to different diseases such as cancer and
influenza. In this section, we introduced the employing avidin-biotin technology in
the graphene FET biosensor and demonstrated the specific detection of the biotinylated biomolecule in the sub-pico molar (pM) range. The sensing performance of
graphene FET biosensor was characterized by the real-time two-terminal electrical
current measurement upon injection of analyte solution into a silicone pool preattached onto the graphene channel. Since the Avidin–biotin technology has strong
affinity and specificity, any biotinylated biomolecules are hopping for rapid detecting
with ultra-low concentration level through this sensing platform. Thus the present
graphene FET biosensor is expected to be a breakthrough in biomedical analysis. It
can be used as a potential common platform for the rapid and point of care detection
of different biomolecules and biomarkers linked to different diseases.
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021
S. Wang et al., Graphene Field-Effect Transistor Biosensors,
https://doi.org/10.1007/978-981-16-1212-1_5
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5 Graphene FET Biosensor Based …
5.1 Background
The strong interaction between avidin and biotin has been widely exploited in many
applications such as protein and nucleic acid detection, immobilization, and purification methods [1–3]. Avidin produced in the oviducts of reptiles, birds, and amphibians is a tetrameric biotin-binding protein and deposited in the egg white. Some
research reported that Dimeric members of the avidin family are also found in some
bacteria [4]. The avidin makes up approximately 0.05% of total protein (approximately 1800 μg per egg) in chicken egg white. Avidin contains four identical subunits
(homotetramer), each of which can specifically bind biotin (vitamin B7, vitamin H)
with high affinity [5]. Biotin involves in a wide range of metabolic processes, both
in humans and other organisms, primarily related to the utilization of fats, carbohydrates, and amino acids [6]. Because of its small size, biotin is a useful label for many
proteins and nucleotides without changing the original properties of the proteins or
nucleotides. The process of labeling a protein or nucleotide with biotin is known
as biotinylation. It is also important that biotin protein ligases can attach biotin to
specific lysine residues in vitro or in living cells [7]. The interaction between avidin
and biotin is known as the most specific and strongest non-covalent interaction (Kd =
10−15 M) between a protein and ligand [5]. The exceptionally strong affinity of avidin
for biotin arises from hydrophobic interactions of biotin and aromatic amino acids
arranged in the binding pocket of avidin and a multiple hydrogen bonding between
heteroatoms in the ureido ring of biotin and asparagine, serine, tyrosine, and threonine residues in avidin [7]. Due to the strong interaction, avidin–biotin complex
is robust and stable against temperature, pH, harsh organic solvents and denaturing
reagents. For the unique properties of avidin–biotin system, it has been used in many
enzyme-linked immunosorbent assay (ELISA) for the purpose of different types of
medical applications such as cancer diagnosis [8–11]. In addition, the other fantastic
applications such as labeled immunosensors [12], polymer-based detection systems
[13] are also based on the avidin–biotin system.
To date, most of the biomolecule and biomarker detections are based on the
ELISA, where the quantitative detection is achieved through the measurement of
intensity of transmitted light by spectrophotometry. Experimentally, the specific
conjugation of biomolecules is realized in terms of optical signals, which are then
converted into electrical signals by spectrophotometry for quantitative reading. The
direct conversion of biological conjugation into electrical signals is of great significance in clinical diagnosis, especially for the development of simple, easy to use and
low-cost sensing devices. The direct electrochemical detection methods possess not
only the advantages of simplicity, fast responses, and ease of use but also promising
for miniaturization of the diagnostics instruments into low-cost microscale dimensions [14]. Of course, the present status of ELISA detection methods in medical
diagnosis is unshakeable because of its widespread application and commercialization of the kits. Hence other methods of biomolecules detection including field-effect
transistor (FET)-based sensor might not immediately be the alternative to the ELISA
but to the complementary to ELISA as an initial screening method for dealing with
large-scale epidemic situation.
5.1 Background
71
Biosensors are comprised of mainly two components. A bio-recognition molecule
or receptor such as antibody or antigen (or capture molecule) determines the specificity, and a signal transducer such as graphene determines the sensitivity of the
sensor [15]. The extremely high carrier mobility (200,000 cm2 V−1 s−1 ), ambipolar
transfer characteristics [16, 17], physical flexibility and robustness in ambient conditions make the graphene the most ideal material for different types of ultra-sensitive
graphene field-effect transistor (GFET) sensors including biosensor. Because of the
compatibility, sensitivity, and the advancement of the state of art nanofabrication
technique, GFET sensor has drawn much attention as the most promising approach
to point-of-care medical diagnostics for rapid, sensitive, specific, low-cost detection and quantification of biomarkers [8]. To date, a number of studies have been
reported on the potential applications of GFET in biosensors [18–30]. The detection
of biomolecules including cancer marker s and RNA s by GFET biosensors has been
reported using various types of acceptor/receptor design [18–26]. Ohno et al. have
reported the electrolyte gated GFET for pH and protein detection [27]. The aptamermodified GFET has been reported for label-free detection of immunoglobulin (IgE)
protein [20]. Recently, GFET has been shown to detect ethanol at ppb level. Deana
et al. have reported the label free sensing of exosomes using functionalized graphenebased FET [28]. Seo et al. have reported the rapid detection of COVID-19 causative
virus (SARS-CoV-2) using GFET [31]. Aerosol-jet-printed graphene-based sensors
were used for label-free cytokine monitoring in serum and food safety [32, 33].
Because of the easy attachment of avidin on solid surface, avidin immobilized on
graphene can be utilized as a prove to detect biotin and biotinylated protein in the
form of electrical signal allowing the real-time point of care diagnosis.
As a common linker of the graphene FET biosensor, PBASE is usually used to
chemically modify the surface of the graphene through the Van der Waals force
between the graphene and the pyrene backbone of the PBASE molecule. Then
PBASE modified graphene is further modified with avidin through the NHS ester
reaction between the lysine residue of avidin and N-hydroxysuccinimide ester group
of PBASE. Otherwise, graphene sheets decorated with metal nanoparticles (MNPs)
such as gold nanoparticles (AuNPs) are excellent materials for biosensors platforms
because of the bio-compatibility of AuNPs and the further enhancement of the carrier
mobility of the graphene [34, 35]. Recently, AuNPs decorated reduced graphene
oxide FET has been reported for the label-free detection of miRNA using peptide
nucleic acid as bio-recognition molecule [36, 37]. Those studies reported to date
utilize a surface-immobilized recognition probe to selectively interact with a biological analyte in solution, i.e., the GFET device is designed for the detection of a
specific biological analyte. Indeed, the binding capability of the bio-recognition
molecule limits the application of the sensor, i.e., if the bio-recognition molecule
can be tailored to bind different biomolecules with high specificity, then the same
sensing platform can be used for different target analytes. It is thus of great importance to develop a universal point of care sensing platform that can be used for a
wide range of detection purposes simply by labeling or linking the biomolecule to
be detected.
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5 Graphene FET Biosensor Based …
5.2 Biotinylated Biomolecules Detection
In biochemistry, biotinylation is the process of covalent bonding of biotin to nucleic
acids, proteins, or other molecules. The process of biotinylation is specific and rapid,
and due to the small size of biotin (molecular weight = 244.31 g/mol), the process
of biotin is unlikely to interfere with the original function of the modified molecule.
Biotin can bind to streptavidin and avidin with high affinity, rapid opening rate, and
high specificity. This interaction is usually used in many fields of biotechnology
to separate and detect target biotinylated molecules. The combination of biotin and
avidin has certain resistance to extreme pH, heat, and proteolysis, which allows this
interaction to quickly capture biotinylated molecules in various complex environments with high specificity, thereby detecting target biomolecules. In this section,
the graphene FET biosensor based on avidin–biotin technology will be explained.
5.2.1 Device Fabrication
The commercially available SiO2 /Si wafer (4-inch 285 nm) was cut into the desired
size (typically 1 cm × 1 cm). Then the cut SiO2 /Si was used as the substrate platform
for the fabrication of interdigital electrode. For the fabrication of the interdigital
electrodes, the commercially available shadow mask was carefully attached to the
SiO2 /Si surface. As the electrode materials, chromium (Cr) and gold (Au) were used.
The subsequent deposition of Cr and Au with desired thickness was achieved by the
electron beam vacuum evaporation deposition technique. Figure 5.1 shows the fullscale optical image of the interdigital electrodes fabricated on a SiO2 /Si substrate
after electrode deposition.
Transferring graphene onto the interdigital electrodes is a crucial step for the
fabrication of the sensor device. For transferring the graphene on the interdigital
electrodes, a thin layer of PMMA was deposited on the graphene on copper foil
Fig. 5.1 The full-scale
optical image of the
interdigital electrodes
fabricated on a SiO2 /Si
substrate
5.2 Biotinylated Biomolecules Detection
73
using PMMA in acetone solution. The deposition of PMMA solution was done
using a spin coater followed by 5 min of heating at 90 °C to evaporate the acetone
solvent. Then this PMMA/graphene on the copper foil was cut into 5 mm × 5 mm
size so that the interdigital electrodes can be fully covered. For etching of the copper
foil, the cut PMMA/graphene on copper foil was placed on ammonium peroxodisulfate aqueous solution until the copper fully is fully dissolved. This etching process
lefts the PMMA/graphene film floating on the surface of the solution. Then the
PMMA/graphene film was carefully transferred on the ultra-pure water, held for
30 min for removal of ammonium peroxodisulfate adhered to the film. Then the
clean PMMA/graphene film was transferred onto the surface of the interdigitated
electrode supported on SiO2 /Si substrate. The transferred PMMA/graphene film on
the interdigital electrodes was then dried in air for 30 min at room temperature
and then heated at 60 °C for 30 min in an oven. Finally, the PMMA attached with
graphene was removed with boiling acetone and isopropyl alcohol (IPA), which left
the graphene attached to the interdigital electrodes [38].
For the preparation of GFET, it is inseparable from semiconductor technology.
First, a specific electrode shape needs to be prepared by photolithography on the
substrate. If the small channel size (less than 1 micron) of the graphene FET is
required, electron beam lithography or maskless photolithography can be used.
Figure 5.2 shows electron beam lithography equipment and maskless lithography
equipment, they can produce the nano-scale size of the channel, but it takes a long
time. These equipment are very suitable for GFET research in nano-level applications. Ordinary UV mask lithography technology is sufficient for most current
applications, particularly some of the GFET applications are not the severe requirements in the size of the channel. Figure 5.3 shows a typical UV mask lithography
platform. After the specific electrode shape is prepared by photolithography, it needs
to be deposited to prepare the metal electrode. At present, there are many deposition methods such as thermal evaporation, sputtering, and electron beam evaporation. In order to ensure the uniformity and adhesion of the coating, electron beam
Fig. 5.2 a The image of the electron beam lithography equipment. b The image of the maskless
lithography equipment
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5 Graphene FET Biosensor Based …
Fig. 5.3 The image of the typical UV mask lithography platform
evaporation is recommended. In addition, in order to better remove the photoresist, it is recommended to use high-pressure jet lift-off equipment. Figure 5.4 shows
the electron beam evaporation equipment and high-pressure jet lift-off equipment.
After the photoresist is removed, annealing (inert gas protection) is required in usual
to release the stress on the interface between the electrode and the substrate. The
thermal annealing equipment is the same as shown in Fig. 5.5b. Although photolithography provides higher manufacturing accuracy and better uniformity; however, the
photolithography process is complicated, so if the requirements for the channel are
at the 100 μm level, the substrate can be directly covered with the shadow mask then
used to deposit the electrode. As a simple method, it can both avoid the photoresist
contaminates the surface of the substrate and simplify the processing, particularly, the
absolute cleanliness of the substrate surface is very important for two-dimensional
material such as graphene, their properties are very easy to be affected with the
substrate. Our sample is manufactured with this method.
The commercially available SiO2 /Si wafer (4-inch 285 nm) was cut into the desired
size (typically 1 cm × 1 cm) by the dicing saw equipment shown in Fig. 5.5a. The
cut SiO2 /Si shown in Fig. 5.5b was used as the substrate platform for the fabrication
of the interdigital electrode. For the fabrication of the interdigital electrodes, the
commercially available shadow mask was carefully attached to the SiO2 /Si surface.
As the electrode materials, chromium (Cr) and gold (Au) were used. The subsequent
deposition of Cr and Au with desired thickness was achieved by the electron beam
5.2 Biotinylated Biomolecules Detection
75
Fig. 5.4 a The image of electron beam evaporation equipment. b The image of the high-pressure
jet lift-off equipment
Fig. 5.5 a The image of the dicing saw equipment. b The image of the cut SiO2 /Si wafer
76
5 Graphene FET Biosensor Based …
Fig. 5.6 a The full-scale optical image of the interdigital electrodes fabricated on a SiO2 /Si
substrate. b The amplified optical image of the interdigital electrodes fabricated on a SiO2/Si
substrate. The electrode width and the electrode gap are both 200 microns
vacuum evaporation deposition technique. Figure 5.6 shows the full-scale optical
image of the interdigital electrodes fabricated on a SiO2 /Si substrate after electrode
deposition.
Because our GFET device uses CVD graphene to make the channel, transferring
of CVD graphene onto the interdigital electrodes is a crucial step for the fabrication
of the GFET. For transferring the graphene on the interdigital electrodes, a thin layer
of PMMA was deposited on the graphene on copper foil using PMMA in acetone
solution. The deposition of PMMA solution was done using a spin coater followed by
5 min of heating at 90 °C to evaporate the acetone solvent. Then this PMMA/graphene
on the copper foil was cut into 5 mm × 5 mm size so that the interdigital electrodes can
be fully covered. For etching of the copper foil, the cut PMMA/graphene on copper
foil was placed on ammonium peroxodisulfate aqueous solution until the copper fully
is fully dissolved. This etching process lefts the PMMA/graphene film floating on the
surface of the solution. Then the PMMA/graphene film was carefully transferred on
the ultra-pure water, held for 30 min for the removal of ammonium peroxodisulfate
adhered to the film. Then the clean PMMA/graphene film was transferred onto the
surface of the interdigitated electrode supported on SiO2 /Si substrate. The transferred
PMMA/graphene film on the interdigital electrodes was then dried in air for 30 min at
room temperature and then heated at 60 °C for 30 min in an oven. Finally, the PMMA
attached with graphene was removed with boiling acetone and isopropyl alcohol
(IPA), which left the graphene attached to the interdigital electrodes [38]. Note that
some reports have shown that hydrogen annealing can better remove residual organic
matter on the graphene surface, but this may destroy the integrity of the graphene
surface. Figure 5.7 shows the processing flow of the GFET chip fabrication.
5.2 Biotinylated Biomolecules Detection
77
PMMA
Graphene
Copper film
Etching soluƟon
PMMA
e
Graphene
Water
SiO2 (285 nm)
Cr/Au (25 nm/50 nm)
e
Graphene
Si
E-BEAM evaporaƟon
PMMA
Graphene transfer
Graphene
PMMA removing
Fig. 5.7 The processing flow of the GFET chip fabrication
5.2.2 Graphene Modification
Graphene modification is the key bridge step connected with the GFET chip fabrication and the actual detection. The graphene surface functionalized by the modification process enables the GFET to achieve specific functions. Therefore, the graphene
surface modification of GFET is a very important process.
For the nanoparticle modification shown in Fig. 5.8a, the transferred graphene on
SiO2 /Si substrate was directly immersed into the as-prepared AuNPs solution during
the AuNP synthesis at room temperature. The AuNPs were synthesized by the reduction of 1 mM HAuCl4 solution by slow addition of sodium borohydride (NaBH4).
Thus homogeneous decoration of AuNPs (25–70 nm) on graphene transferred on
SiO2 /Si substrate was obtained. To facilitate the real-time measurement upon the
addition of liquid analytes, a pre-designed liquid pool made with a silicone sheet
was fixed on the top of the AuNPs decorated graphene. There are many methods for
the characterization of gold nanoparticles on graphene, for the microscopy methods
such as atomic force microscope (AFM) and scanning electron microscope (SEM),
and for the chemical detection methods such as X-ray photoelectron spectroscopy
(XPS) [38].
For the PBASE modification shown in Fig. 5.8b, the surface modification with
PBASE is optimized by incubating the graphene on interdigital electrodes device in
the dry dimethylformamide (DMF) solution of 50 mM PBASE for 4 h at room temperature individually. Then the PBASE modified graphene is washed with methanol
three times and dried with rotary pump. Then a pre-designed liquid pool made with
silicone sheet is constructed on the top of the PBASE modified graphene so that
78
5 Graphene FET Biosensor Based …
Fig. 5.8 a The image of AuNPs surface-modified processing. b The image of PBASE surfacemodified processing
the desired bio-solution to be tested can be injected into this test pool [38]. After
PBASE is modified onto the surface of the graphene, the PBASE modification can
usually be characterized by observing the increase of the D (1350 cm−1 ) and D’ band
(1620 cm−1 ) peaks of the Raman spectrum [38].
The avidin was immobilized on modified graphene by injecting 100 μl of 1 mg/ml
avidin-PBS solution into the pool, and holding for 1 h at room temperature. Then the
device is washed with 100 μl PBS three times. To prevent the non-specific binding
of the residual surface regions (regions unmodified by avidin) to other molecules,
which may affect the signal during actual testing of the sensor device, the remaining
unmodified surface regions of the graphene were blocked by injecting 100 μl of
0.01 mg/ml BSA-PBS solution into the pool and holding for 1 h at room temperature
followed by washing with 100 μl PBS three times. For the nanoparticle modification,
the schematic image of the biotin ylated molecules capturing is shown in Fig. 5.9.
5.2.3 Quantitative Detection
For the quantitative detection, the biotin ylated biomolecule solution to be tested is
prepared to add into the test pool. Figure 5.10 shows the optical image for the GFET
biosensor during the real-time detection. During this processing, the current value
5.2 Biotinylated Biomolecules Detection
79
Fig. 5.9 The schematic image of the biotin ylated molecules capturing
Fig. 5.10 The optical image for the graphene FET biosensor during the real-time detection
of the Ids is monitored the whole time. Note that for avoiding the interference of
the current Ids signal, the top-gate (reference electrode) is not recommended. It is
observed that based on the concentration of biotinylated biomolecule solution, the
stable current value Ids gradually varies. In common, the current Ids value quickly
remains stable, the response time is less than 1 min. In addition, when the test
solution is added to the pool, there will be a significant characteristic that occurs a
quick sharp current alter, then gradually return to a stable. Note that the spikes in
Ids vs time curve upon addition of the solutions are the signature of an interfacial
capacitance that previously mentioned, it is disrupted by the fresh solution added and
80
5 Graphene FET Biosensor Based …
then recovers with time. Hence by monitoring the sharp current drops upon addition
of the test solution and subsequent recovery to stable Ids, the limit of detection for
biotinylated biomolecule can be estimated to the concentration of pM level. Based
on the avidin–biotin technology, the value of detection limit is lower than that of the
reported value in the case of pristine GFET biosensor [38].
5.2.4 Specificity of the Sensor
One of the key challenges in the practical applicability of a biosensor is the specific
detection of the target molecule or marker. Avidin is a glycoprotein that contains
four identical subunits of 16,400 Daltons each, giving an intact molecular weight
of approximately 66,000 [39]. Each subunit contains one binding site for biotin.
The tetrameric protein is highly basic, having a pI of about 10. Tryptophan and
lysine residues in each subunit are known to be involved in forming the binding
pocket [40]. Once the biotin is bound to avidin, the avidin–biotin complex became
much robust against breakdown. A minimum of 6–8 M guanidine at pH 1.5 is required
for inducing complete dissociation of the avidin–biotin complex [41, 42]. Such robust
nature of avidin–biotin complex against any denaturing agent makes the complex a
very useful in bioconjugate chemistry. Even biotinylated molecules and avidin can
also bind together and make the complex under extreme conditions. It can be said that
the specificity of the avidin–biotin interaction is similar to that of antibody–antigen
or receptor-ligand recognition, but with much higher affinity. Indeed, the specific
binding of biotinylated molecules with avidin cannot be prevented by variations in
buffer salt, pH, the presence of denaturants or detergents, and extremes of temperature
[43]. Because of the high pI and carbohydrate content, natural avidin has tendency
to bind nonspecifically with components other than biotin, hence, it shows some
disadvantages to using for sensing purposes. However, this disadvantage of tendency
to non-specific binding has been eliminated in the chemically modified avidin, such
as NeutrAvidin used in the present study, through deglycosylation and reducing its
pI through covalent modification of charged residues. Hence the present avidinimmobilized graphene FET platform is expected to exhibit high specificity.
5.2.5 Exogenous Biotin Interferences
In the case of blood sample analysis, one of the main disadvantages of the avidinbiotin technology is the interference of exogenous biotin present in the blood serum,
which can range from 0.12 to 0.36 nM [6]. Indeed, normal intake of biotin from
various foods and milk poses little effect on the avidin/biotin-based immunoassays.
However, overconsumption of biotin (daily doses 100–300 mg) can significantly
affect the avidin–biotin-based immunoassays. Biotin interferences have been noted
in immunoassays designed for thyroid markers, drugs, hormones, cancer marker s,
5.2 Biotinylated Biomolecules Detection
81
the biomarker for cardiac function (β-human chorionic gonadotropin), etc [44]. Since
the sensitivity of the present graphene FET platform lies in the pM range, the lowering
or removal of biotin content in the target sample should be considered before testing
the blood sample. There are different methods that can be used for lowering or preremoving the biotin from the blood serum. For example, biotin can be removed from
blood serum by interacting the serum with avidin/streptavidin immobilized on an
insoluble matrix such as magnetic particles, polymers (e.g. agarose beads), silica,
etc [45].
5.2.6 Comparative Sensitivity and Practical Applicability
To date, a number of studies have reported on the utilization of avidin–biotin interaction in sensing technology [46–50]. The detection limits ranged from 2 pM to
84 nM have been reported using various detection methods such as competitive
immunoassay, electrochemical, cyclic voltammetry, and immunoaffinity chromatography as listed in Table 5.1. The graphene FET biosensor based on avidin–biotin
technology presented here shows the highest sensitivity and the minimum time
requirement for real-time detection.
Similar to the biotin-avidin system used in the different types of conventional
ELISA kits [51–53], the present graphene FET biosensor is expected to be utilized
for the detection of antigen-antibody, hormone-receptor, nucleic acid system in body
fluid, tissue and cell, and other bioactive macromolecules through the judicious
Table 5.1 Avidin–biotin technology used in different biosensors. The limit of detection and time
required for data acquisition compared to the present study are indicated
Platform
Material
Method
Limit of
detection
Time
References
Beads and gold
nanoparticles
Anti-biotin antibody
Competitive
immunoassay
2 pM
15 min
[46]
Boron-doped
diamond
electrode
Captavidin
Electrochemical
sensing
1 nM
10 min
[48]
Boron-doped
diamond
electrode
Streptavidin
Electrochemical
sensing
5 nM
10 min
[47]
Electrochemical
magneto
biosensor
Streptavidin
Cyclic
voltammetry
84 nM
40 min
[49]
Sepharose beads
Anti-biotin antibody
Immunoaffinity
chromatographic
41 pM
30 min
[50]
Graphene FET
biosensor
Streptavidin
(neutravidin)
Current Ids
0.4 pM
real-time monitor
1 min
[38]
82
5 Graphene FET Biosensor Based …
choice of biotinylation. As the common sensing platform, because of the avidin’s
strong affinity for biotinylated macromolecule with high specificity, the different
biotinylated proteins, nucleotides, etc., can be quantitatively detected by monitoring
the current (Ids) response upon injection on to the device.
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Chapter 6
Graphene FET Biosensor Based
on the Antigen–Antibody Interaction
Abstract Antigen-antibody interaction is the most commonly used tool in biomedical detection and has the most extensive applications. generally speaking, antigens
include proteins, bacteria, viruses, and many other targets. These targets can specifically bind to specific antibodies. for biomedical detection, neither hematological
testing nor histological testing can easily conduct without antigen-antibody interaction. The graphene field-effect transistor biosensor combined with antigen-antibody
interaction is the earliest research field for graphene biosensing. This chapter first
introduces the progress that has been made in recent years in the field of graphene
field-effect transistor combined with antigen-antibody interaction. Then the implementation methods and future prospects of graphene field-effect transistor combined
with antigen-antibody interaction to detect specific biomarkers including cancer
markers are mainly introduced.
Keywords Graphene FET · Antigen-antibody interaction · Tumor marker ·
Biomarker
Antigen–antibody interaction (antigen-antibody reaction) as a kind of significant
immunic interaction is one of the most significant fundamental reactions in our body.
It can protect the human body from complex external factors such as pathogens
or chemical toxins. The antigen in the blood has specificity and high affinity and
combines with the antibody to form an antigen–antibody complex. The complex is
then transported to the cell system to destroy or inactivate it [1]. For the different
kinds of antigen, there are also different types of the specific antibody to bind its
corresponding antigen. Because antigens are bound to antibodies through several
weak and non-covalent interactions and their combination, such as hydrogen bonds,
electrostatic interactions, hydrophobic interactions, and Van der Waals forces. Therefore, the specificity of binding depends on the specific chemical composition of each
antibody. The epitope is located in the variable region of the polypeptide chain and
is recognized by the paratope of the antibody. This variable domain is highly variable and contains a unique amino acid sequence within each antibody. Currently, the
antigen–antibody interaction has been widely used in quantification of the antibody
for the purposes of the clinical diagnosis.
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021
S. Wang et al., Graphene Field-Effect Transistor Biosensors,
https://doi.org/10.1007/978-981-16-1212-1_6
87
88
6 Graphene FET Biosensor Based …
Fig. 6.1 The schematic image of the graphene FET biosensor based on the antigen–antibody
interaction
Because the antigen–antibody interaction has been widely applied to the traditional diagnosis approaches, combined with the antigen–antibody interaction technology has been deeply researched for the field of the Graphene FET biosensor.
Generally speaking, the antigen should be placed on the surface of the graphene
first. Then, based on the antigen–antibody interaction, the functionalized graphene
can bind the specific antigens to the graphene surface. Finally, the concentration of a
specific antibody can be quantified by the graphene FET based on the principle of the
electrical double layer. Commonly, the binding methods for binding antibodies to
the surface of the graphene include covalent and non-covalent methods. The covalent
binding includes PBASE and TCPP, and for the non-covalent methods, the AuNPs
decoration method is also used. The schematic image of the graphene FET biosensor
based on the antigen–antibody interaction is shown in Fig. 6.1.
Because antibodies are biomolecules composed of proteins, they are easily
affected by temperature and other complex environmental factors. Therefore, after
modification on the surface of graphene, it is difficult to maintain the original affinity
with the antigen. Current studies have shown that after surface modification, the
affinity is likely to decrease. At the same time, biosensor s made from antigens
are extremely susceptible to the influence of time and temperature. Excessive time,
extremely low or extremely high temperatures will cause the antibody to lose activity,
thereby losing its affinity for the antigen. But antigen–antibody technology, as the
most mature biometric tool so far, seems to be the easiest to be combined with GFET.
Most of the existing diagnostic methods based on antigen–antibody technology can
be transplanted to the graphene FET biosensing platform, which makes GFET based
on antigen–antibody technology a promising research direction.
6.1 Tumor Marker
For cancer diagnosis, developing a novel platform for rapid quantitative detection is
as important as finding more efficient cancer marker s for specific cancers. Graphene
FET biosensor as a novel type of detection platform, most of these researches
6.1 Tumor Marker
89
focused on the quantification of the tumor marker. In the traditional clinical diagnosis of cancer, the quantification method of the tumor marker has been an important
diagnosis factor during the whole clinical processing.
Currently, several tumor markers have been used to identify in oncology to help
detect or diagnose the presence of cancer, each of which may indicate a specific
disease course. Elevated levels of tumor markers may indicate the presence of cancer;
however, there may be other reasons for elevated levels (such as false-positive values),
such as alpha-fetoprotein (AFP) for the germ cell tumor, hepatocellular carcinoma,
prostate-specific antigen (PSA) for prostate cancer [2]. Based on the GFET, the
concentration of these specific tumor markers is hopefully to rapid qualification.
Currently, many of the researchers have shown that the GFET based on the
antigen–antibody interaction has huge applied potential in tumor marker qualification. Dae Hoon Kim et al. developed a biosensor that uses G-FET to detect
alpha-fetoprotein (AFP) in phosphate-buffered brine (PBS) solution. Furthermore,
this anti-AFP immobilized G-FET biosensor can detect AFP at a concentration of
0.1 ng mL−1 in PBS [3]. As a self-protective layer of graphene, the nano-DBSA film
has a certain protective effect, which can prevent surface pollution caused by lithography processing. Lin Zhou et al. made a GFET sensor composed of nano-DBSA
film immobilized anti-cancer embryonic antigen monoclonal antibody (anti-CEA
mAb) on EDC and Sulfo-NHS-activated graphene channels. This modified GFET
biosensor showed good specificity and high sensitivity to target matter (CEA) at
an ultra-low concentration of 337.58 fg mL−1 [4]. Based on the immune reaction
of PSA-ACT complex with PSA monoclonal antibody on the surface of reduced
graphene oxide (R-GO) channel, Duck-Jin Kim et al. obtained high binding constants
of 3.2 nM−1 and 4.2 nM−1 in analytical solutions at pH 6.2 and pH 7.4, respectively.
The reduced graphene oxide field-effect transistor (R-GO FET) biosensor demonstrated high specificity of cancer biomarkers in phosphate-buffered saline solutions
and human serum. The R-GO FET biosensor has certain application value and high
sensitivity in detecting prostate-specific antigen/α1-antichymotrypsin (PSA-ACT)
complex and unlabeled prostate cancer biomarkers [5].
6.2 Other Biomarkers
Not only the tumor marker-related researches have been reported but also some of the
biomarker-related researches based on the antigen–antibody interaction. Yong-Min
Lei et al. reported the platinum nanoparticles (PtNPs)-decorated reduced graphene
oxide (R-GO) field-effect transistor (FET) biosensor coupled with a microfilter
system for label-free and highly sensitive detection of brain natriuretic peptide (BNP)
in whole blood about the heart failure diagnosis. Their biosensors can achieve a lower
detection limit of 100 fM. The rGO FET sensor is cast from rGO onto a prefabricated
FET chip and then modified with PTNPs on the graphene surface. After anti-BNP was
combined with the surface of PTNPs, the FET biosensor immobilized by anti-BNP
could successfully detect BNP [6]. Nur Nasyifa Mohd Maidin et al. reported the role
90
6 Graphene FET Biosensor Based …
Table 6.1 The main researches about the biomarker
Target
Disease
Platform
Sensitivity
References
Alpha-fetoprotein (AFP)
Cancer
Graphene FET
0.1 ng mL−1
[3]
Carcinoembryonic antigen (CEA) Cancer
Graphene FET
mL−1
[4]
Prostate-specific
antigen/α1-antichymotrypsin
(PSA-ACT)
Cancer
Reduced
100 fg mL−1
graphene oxide
FET
[5]
Brain natriuretic peptide (BNP)
Heart
failure
Reduced
100 fM
graphene oxide
FET
[6]
Cortisol hormone
Stress
Graphene FET
Amyloid-β (Aβ) and tau protein
Alzheimer’s Reduced
10−1 pg mL−1 [8]
disease
graphene oxide
FET
337 fg
10 pg mL−1
[7]
of graphene-based electrolytic gate field-effect transistors (EGFET) in the detection
of cortisol hormones. Cortisol antibody was immobilized on the graphene surface for
specific and sensitive detection of cortisol target hormone and ethanolamine was used
to prevent non-specific binding. They also claimed that the 10 pg mL−1 of the cortisol
can be detected by their biosensors [7]. Dongsung Park et al. demonstrated hypersensitivity and multiplexing of R-GO FETs for biomarkers of Alzheimer’s disease (AD)
(Aβ1-42 and T-Tau) in the biological fluid. Furthermore, based on antigen–antibody
interactions, they proposed a broad log-linear range for the detection of lower fM
levels in 10−1 –105 pg mL−1 and a fM level limit of detection in biofluids (human
plasma and artificial cerebrospinal fluid) and phosphate buffer saline (PBS) [8].
In summary, based on the antigen-antibody interaction, the FET biosensor can be
used to rapidly detect the specific biomarker with ultrasensitive. Table 6.1 listed the
main research using the antigen–antibody interaction about the biomarker detection
based on the GFET. Such as previously mentioned, the Debye length determines
the active length of the electric field effect from the target biomolecules. Thus, we
hoping that the target biomolecules can more close to the graphene channel so that
the maximize the electric field effect of a single target molecule. But for the antigen–
antibody interaction, the bulk of the antibody (nm level) modified on the graphene
channel is relatively large compared with the Debye length in the test solution.
Therefore, this may cause the antigen to be far away from the graphene channel when
the antibody binds to the antigen, which makes the detection effect unsatisfactory.
Currently, using the antigen-binding fragment (Fab) instead of the antibody to bind
the surface of the graphene perhaps will become an available approach. It is a region
on an antibody that binds to antigens. Compared with the whole antibody, the bulk
of Fab has a small size that will bring more ideal detection effect. In addition, if only
from the perspective of the Debye length in the solution, the ion concentration in
the solution to be tested can be reduced to make the Debye length longer. However,
the concentration of the target molecule may decrease as the solution is diluted
during the actual test process. Therefore, finding the best adaptation point between
6.2 Other Biomarkers
91
Fig. 6.2 The schematic image of the compound nanosensor of the graphene and nanowire
the dilution of the solution and the concentration of the target biomolecule to be
tested may be the focus of future research. Finally, some compound nanosensors
made from a variety of nanomaterials are also hopeful to improve this problem. Here
I propose a new preliminary idea for the first time that the compound nanosensor
of the graphene and nanowire. The schematic image is shown in Fig. 6.2, place
the nanowire on top of graphene, and prepare electrodes only on both ends of the
nanowire. Nanowire s are used as the sensing part, and graphene is used as the
capturing part of specific biomolecules. When graphene captures a specific molecule
because the target molecule is closer to the upper nanowire, a more ideal detection
effect may be achieved, and because there is no hard link between the nanowire and
the graphene interface, the water molecules in the solution will penetrate then form an
insulating layer at the interface (modified graphene and nanowires are hydrophilic),
so that the graphene will hardly affect the electrical properties of nanowires.
References
1. Antigen-Antibody Interaction. Wikipedia (2020)
2. Tumor Marker. Wikipedia (2020)
3. Kim, D.H., Oh, H.G., Park, W.H., Jeon, D.C., Lim, K.M., Kim, H.J., Jang, B.K., Song, K.S.:
Detection of Alpha-fetoprotein in hepatocellular carcinoma patient plasma with graphene fieldeffect transistor. Sensors 18(11), 4032 (2018). https://doi.org/10.3390/s18114032
4. Zhou, L., Wang, K., Sun, H., Zhao, S., Chen, X., Qian, D., Mao, H., Zhao, J.: Novel graphene
biosensor based on the functionalization of multifunctional nano-bovine serum albumin for the
highly sensitive detection of cancer biomarkers. Nano-Micro Lett. 11(1), 20 (2019). https://doi.
org/10.1007/s40820-019-0250-8
5. 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. 41, 621–
626 (2013). https://doi.org/10.1016/j.bios.2012.09.040
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6 Graphene FET Biosensor Based …
6. Lei, Y.-M., Xiao, M.-M., Li, Y.-T., Xu, L., Zhang, H., Zhang, Z.-Y., Zhang, G.-J.: Detection of
heart failure-related biomarker in whole blood with graphene field effect transistor biosensor.
Biosens. Bioelectron. 91, 1–7 (2017). https://doi.org/10.1016/j.bios.2016.12.018
7. Maidin, N.N.M., Rahim, R.A., Halim, N.H.A., Abidin, A.S.Z., Ahmad, N.A., Lockman, Z.:
Interaction of graphene electrolyte gate field-effect transistor for detection of cortisol biomarker.
AIP Conf. Proc. 2045(1), 020022 (2018). https://doi.org/10.1063/1.5080835
8. Park, D., Kim, J.H., Kim, H.J., Lee, D., Lee, D.S., Yoon, D.S., Hwang, K.S.: Multiplexed
femtomolar detection of alzheimer’s disease biomarkers in biofluids using a reduced graphene
oxide field-effect transistor. Biosens. Bioelectron. 167, 112505 (2020). https://doi.org/10.1016/
j.bios.2020.112505
Chapter 7
Graphene FET Biosensor Based
on the Base Pair
Abstract The rapid quantitative detection of DNA/RNA fragments occupies an
important position in biomedical detection. Relying on the principle of base complementary pairing, any specific target (DNA/RNA) can be efficiently identified. At
present, based on complementary base pairing the biomedical detection methods
such as PCRs and NATs have been widely used in practical clinical detection applications. For example, many special miRNA/mRNA have been found that can be used
as tumor markers. Referred to the quantitative detection result of the specific tumor
markers, it has great reference value for predicting the cancer stage of the patient and
for evaluating the prognosis. In addition, the rapid quantitative detection of viruses
and other foreign DNA and RNA is also helpful to provide a rapid diagnosis basis for
influenza, Ebola virus, and other epidemics. For graphene field-effect transistors, due
to their excellent characteristics of rapid response, the target DNA/RNA in the sample
to be tested is expected to be quickly quantitatively detected. This provides a new
platform for rapid quantitative detection of DNA/RNA. This chapter first introduces
classic cases of graphene field-effect transistors combined with base complementary
pairing principles to detect specific DNA/RNA. Finally, a novel biosensing scheme
is proposed based on the graphene field-effect transistor to rapidly quantitive detect
COVID-19 RNA fragments.
Keywords DNA · RNA · Base pair · COVID-19 · Graphene FET
Base pairs (BPs) are the basic building blocks of the DNA/RNA double helix, the
folded structures that make up DNA and RNA. BP consists of two bases bonded
by hydrogen bonds, including thymine (T), cytosine (C), adenine (A), guanine (G),
and uracil (U). It is the basic unit of double-stranded nucleic acid [1]. Based on
the specific hydrogen bonding patterns, (guanine-cytosine, adenine-thymine, and
adenine-uracil) allow the double-stranded nucleic acids to tightly bind together and
maintain a regular helical structure.
At present, the nucleic acid test (NAT) has become the widest applied approach for
the early diagnosis of a disease based on base-pairing technology [2]. It is different
from antigen/antibody detection because the antigens/antibodies generally require a
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021
S. Wang et al., Graphene Field-Effect Transistor Biosensors,
https://doi.org/10.1007/978-981-16-1212-1_7
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7 Graphene FET Biosensor Based …
Table 7.1 The recent main researches about the nucleic acid detection
Target
Linker
Probe
Platform
Sensitivity
References
DNA
PBASE
DNA
Graphene FET
10 pM
[3]
DNA/RNA
PBASE
DNA
Crumpled graphene FET
600 zM
[4]
miRNA
AuNPs
PNA
R-GO FET
10 fM
[5]
further long time for them to start appearing in the bloodstream. Thus through the
detection of a particular nucleic acid sequence, it is to rapidly identify a virus or
bacteria in humans. Currently, most nucleic acid detection techniques rely on the
specificity of base pairing to capture complementary strands of DNA or RNA target
molecules through single-stranded probes or primers. Therefore, the design of probe
chain is of great significance to improve the specificity and sensitivity of nucleic acid
detection.
Recent researches have reported some works about graphene FET biosensor based
on the base pair for DNA/RNA detection. Shicai Xu et al. demonstrated that the timeand concentration-dependent DNA hybridization kinetics could be accurately and
sensitively measured by pattering graphene single crystal regions into multiple channels based on base pairs with DNA detection limits of 10 pM [3]. Michael Taeyoung
Hwang et al. used FETs with morphed graphene monolayer with millimeter-scale
channels to detect nucleic acids and demonstrated that they could detect ultrahigh
sensitivity of 600 zM and 20 aM, 18 and 600 nucleic acid molecules, respectively,
in the buffer and human serum samples [4]. Besides, Bingjie Cai et al. claimed that
reduced graphene oxide (R-GO) suspension was poured onto the sensor surface, and
then gold nanoparticles (AuNPs) were modified onto the surface of R-GO. Then
fixing the polypeptide nucleic acid (PNA) probe on the surface of AuNPs, PNAmiRNA hybridization was conducted for detection. It was found that the developed
FET biosensor could reach a detection limit as low as 10 fM. Based on AuNPs
modified GFET biosensors, their devices can be used to detect miRNAs with high
sensitivity, selectivity, and no labeling [5]. All of these fantastic works with highly
sensitive and selective have shown that GFET biosensor based on base pair for the
detection of the nucleic acid may have huge potential for the actual clinical diagnosis
in near future. Table 7.1 listed the recent works about the nucleic acid detection.
Generally speaking, for the detection of the nucleic acid based on the graphene
FET, the probe nucleic acid chain should be linked onto the surface of the graphene
at first. The commonly linker contains the PBASE and AuNPs. Some of the works
reported that using the Xeno nucleic acids (XNA) instead of the probe nucleic acid
may be a better approach because generally, the XNA is more stable than traditional nucleic acids. Finally, through the base-pairing principle, the specific nucleic
acids could be bound onto the surface of the graphene, thus conduct quantification
detection.
7.1 COVID-19 Detection
95
7.1 COVID-19 Detection
Since 2019, the COVID-19 has widely spread induced the global pandemic. For the
COVID-19 detection based on the graphene FET, Giwan Seo et al. demonstrated that
SARS-CoV-2 in clinical samples can be detected by a novel GFET biosensor. Their
sensor is coated with specific antibodies against SARS-CoV-2 spines on graphene
sheets of FET, and their instrument can detect SARS-CoV-2 spike protein in phosphate buffer saline at a concentration of 1 fg/mL and in a clinical transport medium
of 100 fg/mL [6]. However, there are no related works reported the nucleic acid s test
for the COVID-19 based on the graphene FET biosensor until now. Here, I propose
a new scheme for detecting specific partial sequences of COVID-19 nucleic acid as
follows.
As we all know, COVID-19 is an RNA virus. The current traditional detection
method is to detect specific fragments of COVID-19 in human blood/saliva through
nucleic acid test ing. However, nucleic acid detection usually requires amplification,
which may require longer time and more specialized equipment. The application
of graphene FET biosensor for ultra-sensitive nucleic acid fragment detection for
COVID-19 is expected to break the time limit of traditional detection methods and
bring the possibility of large-scale census.
Generally speaking, the specific probe-DNA is modified onto the surface of
the graphene at first which is to activate the surface of the graphene. Then the
remaining parts of the graphene surface should be blocked. Basically, the BSA and
the ethanolamine are always used for this processing. Finally, based on the principle
Fig. 7.1 The schematic image of the whole processing for the COVID-19 nucleic acid detection
96
7 Graphene FET Biosensor Based …
of the base-pairing, the target RNA sequence of the COVID-19 could be rapidly quantitively detected. The schematic image of the whole processing is shown in Fig. 7.1.
In addition, because the design of probe strands is very important for detection. Here
I give a potential probe sequence (AAGGATCAGTGCCAAGCTCGTCGCC) that
can be used in the design. It corresponds to the 701–725 of the original sequence of
the COVID-19.
References
1. Base Pair. Wikipedia (2020)
2. Nucleic Acid Test. Wikipedia (2020)
3. Xu, S., Zhan, J., Man, B., Jiang, S., Yue, W., Gao, S., Guo, C., Liu, H., Li, Z., Wang, J., Zhou,
Y.: Real-time reliable determination of binding kinetics of DNA hybridization using a multichannel graphene biosensor. Nature Commun. 8(1), 14902 (2017). https://doi.org/10.1038/nco
mms14902
4. Hwang, M.T., Heiranian, M., Kim, Y., You, S., Leem, J., Taqieddin, A., Faramarzi, V., Jing,
Y., Park, I., van der Zande, A.M., Nam, S., Aluru, N.R., Bashir, R.: Ultrasensitive detection of
nucleic acids using deformed graphene channel field effect biosensors. Nature Commun. 11(1),
1543 (2020). https://doi.org/10.1038/s41467-020-15330-9
5. Cai, B., Huang, L., Zhang, H., Sun, Z., Zhang, Z., Zhang, G.-J.: Gold nanoparticles-decorated
graphene field-effect transistor biosensor for Femtomolar MicroRNA detection. Biosens.
Bioelectron. 74, 329–334 (2015). https://doi.org/10.1016/j.bios.2015.06.068
6. 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., Kim, S.-J., Lee, J.-O., Kim, B.T., Park, E.C., Kim, S.I.: Rapid detection of COVID-19
causative virus (SARS-CoV-2) in human nasopharyngeal swab specimens using field-effect
transistor-based biosensor. ACS Nano 14(4), 5135–5142 (2020). https://doi.org/10.1021/acs
nano.0c02823
Chapter 8
Graphene FET Biosensor Based
on the Aptamer Technology
Abstract Aptamer technology is an emerging technology in biomedical testing. It
can be divided into nucleic acid aptamers and protein aptamers. This chapter mainly
focuses on aptamers in aptamer technology. Based on SELEX technology, specific
nucleic acid strands are screened out to target different targets (binding objects).
This makes the aptamer technology broadly adaptable to almost all foreign objects,
especially some targets which is still no corresponding antibody. Similarly, with
the antigen-antibody technogy,the designated nucleic acid chain screened by the
SELEX technology can bind the specific target with high-sensitivity and specificity.
It may have a wider application prospect in the biomedical testing field compared
with antigen-antibody technology. Besides, compared with antibodies composed of
amino acids, aptamers composed of nucleic acids are more stable, which enables
biosensing devices based on this technology to have milder storage and transportation
conditions, thus facilitates future practical applications. This chapter briefly describes
the graphene field-effect transistor biosensor based on aptamer technology, including
its specific implementation and preparation methods.
Keywords Aptamer · Graphene FET · Biosensor
Aptamers are oligonucleotides or peptide molecules that can bind to specific target
molecules. Here, we mainly discuss nucleic acid aptamers. This kind of aptamers
usually consists of short oligonucleotide chains [1]. An aptamer is a nucleic acid
(next-generation antibody simulator) that can produce antibodies against a specific
target through in vitro selection or other similar methods (from small entities (such as
heavy metal ions) to large entities (such as cells)) [2], especially suitable for targets
for which there is no specific antibody.
At the molecular level, aptamers bind to homologous targets through various noncovalent interactions, such as hydrophobicity, electrostatic interaction, and induced
fitting. Aptamers are of great value in biotechnology and detection applications
because they have molecular recognition properties equivalent to ordinary antibodies,
are easy to prepare and store, and are not easily affected by other environmental
factors. In addition, compared to antibodies made of amino acids, aptamers (aptamer
nucleic acids) are made of oligonucleotides (DNA, RNA, XNA), so theoretically
they are not easy to lose their activity.
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021
S. Wang et al., Graphene Field-Effect Transistor Biosensors,
https://doi.org/10.1007/978-981-16-1212-1_8
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8 Graphene FET Biosensor Based on the Aptamer Technology
Table 8.1 The main researches about the Graphene FET biosensor based on the aptamer technology
Target
Linker
Probe
Platform
Sensitivity
References
Immunoglobulin PBASE
E
DNA-aptamer Graphene 47 nM
FET
[3]
Escherichia coli
The pyrene tag (pyrene
phosphoramidite)
DNA-aptamer Graphene 100 CFU mL−1 [4]
FET
Hg2+
1,5-diaminonaphthalene DNA-aptamer Graphene 40 pM
(DAN) through Schiff
FET
base reaction
[5]
As of 2020, the graphene FET biosensor based on aptamer technology has been
researched for 10 years. Yasuhide Ohno et al. first reported this technology in
2010. They demonstrated an unlabeled immunosensor based on an aptamer-modified
GFET. Atomic force microscopy confirmed that immunoglobulin E (IgE) aptamers
with a height of about 3 nm have been successfully immobilized on the surface of
graphene. The aptamer-modified GFET can selectively detect IgE protein electrically.
According to the dependence of the drain current change on the IgE concentration,
the disintegration constant is estimated to be 47 nM, which indicates that GFET has
a good affinity and may be used in biosensors [3]. They demonstrated that a labelfree immunosensor based on an aptamer-modified graphene field-effect transistor
(G-FET). Immunoglobulin E (IgE) aptamers with an approximate height of 3 nm
were successfully immobilized on a graphene surface, as confirmed by atomic force
microscopy. The aptamer-modified G-FET showed selective electrical detection of
IgE protein. From the dependence of the drain current variation on the IgE concentration, the dissociation constant was estimated to be 47 nM, indicating good affinity
and the potential for G-FETs to be used in biological sensors [3]. Guangfu Wu et al.
reported that based on graphene FET biosensor with the aid of pyrene-tagged DNA
aptamers, which exhibit excellent selectivity, affinity, and stability for Escherichia
coli (E. coli) detection. It is the first time that the change of the carrier density in
the probe-modified graphene due to the attachment of E. coli is discussed theoretically and also verified experimentally. They confirmed the low detection limit of
100 CFU mL−1 for E. coli detection [4]. JiaWei Tu et al. reported a GFET array
biosensor (6 × 6 GFETs on chip) and applied it to the quantitative detection of Hg2+
based on single-stranded DNA (ssDNA) aptamer. The biosensor shows excellent
selectivity to Hg2+ in mixed solutions containing a variety of metal ions. The results
show that the biosensor has a lower detection limit (40 pM), a wider detection range
(100 pM–100 nM) and a shorter response time (less than 1 s) [5]. These pioneering
studies are listed in Table 8.1.
In principle, the graphene FET combined with aptamer technology is similar to
the antigen–antibody interaction that has been demonstrated in the previous section.
Figure 8.1 shows the schematic image of the graphene FET biosensor based on
aptamer technology. Here we mainly discuss the aptamer surface-modified method
on graphene. The most common method is to carry out amination or thiolation at
the end of aptamer, after which they can be combined with commonly used linker s
8 Graphene FET Biosensor Based on the Aptamer Technology
99
Fig. 8.1 The schematic image of the graphene FET biosensor based on aptamer technology
PBASE or AuNPs in graphene FET. In addition, there are many link methods, such
as the previously mentioned Schiff base reaction [5].
Because compared to antibodies, aptamer has a smaller volume, which makes
the distance between the object and the graphene interface closer, which may bring
better detection results. In addition, it can be used to specifically identify the test
objects in which there is no related specific antibody through SELEX technology.
This makes aptamer possible to have a wider range of applications than antibodies.
References
1. Aptamer. Wikipedia (2020)
2. Kaur, H., Shorie, M.: Nanomaterial based aptasensors for clinical and environmental diagnostic
applications. Nanoscale Adv. 1(6), 2123–2138 (2019). https://doi.org/10.1039/C9NA00153K
3. Ohno, Y., Maehashi, K., Matsumoto, K.: Label-free biosensors based on aptamer-modified
graphene field-effect transistors. J. Am. Chem. Soc. 132(51), 18012–18013 (2010). https://doi.
org/10.1021/ja108127r
4. Wu, G., Dai, Z., Tang, X., Lin, Z., Lo, P.K., Meyyappan, M., Lai, K.W.C.: Graphene fieldeffect transistors for the sensitive and selective detection of escherichia coli using pyrene-tagged
dna aptamer. Adv. Healthcare Mater. 6(19), 1700736 (2017). https://doi.org/10.1002/adhm.201
700736
5. Tu, J., Gan, Y., Liang, T., Hu, Q., Wang, Q., Ren, T., Sun, Q., Wan, H., Wang, P.: Graphene FET
array biosensor based on SsDNA aptamer for ultrasensitive Hg2 + detection in environmental
pollutants. front. Chem., 6 (2018). https://doi.org/10.3389/fchem.2018.00333
Chapter 9
Graphene FET Biosensor Based
on the Concanavalin A
Abstract Concanavalin A (ConA) is a particular protein that can specifically bind to
various sugars, glycoproteins, and some structures of glycolipids (mainly internal and
non-reducing terminal α-D-mannosyl and α-D-glucosyl groups). Unlike the other
biological interactions mentioned above, ConA protein only specifically adsorbs
target with glycosyl groups such as monosaccharides, glycans, glycoproteins, cell
surface with glycosyl groups, etc. This allows the interaction between ConA and
targets (with glycosyl groups) to be described separately as a special type of biological interaction. In actual biomedical clinical detection applications, glycoproteins,
cell surfaces, microbial surfaces, virus surfaces, etc., all contain glycosyl groups,
which makes it possible to use ConA protein for specific detection. This chapter
introduces the graphene field-effect transistor biosensor combined with ConA for
rapid detection of targets contained glycosyl groups. Then discusses two different
detection modes that are adsorption mode detection and dissociation mode detection. Unlike the biological interactions described previously, ConA protein has a
wide range of glycosyl group binding ability, which makes it possible to use ConA
in many glycosyl group-containing targets. But at the same time, it should be noted
that the binding of ConA to targets is not one-to-one, so competitive adsorption issues
should be considered in practical applications.
Keywords Concanavalin A · ConA · Glycosyl group · Monosaccharides ·
Glycans · Glycoproteins · Graphene FET
Concanavalin A (ConA) is a lectin (carbohydrate-binding protein), a member of the
legume lectin family, and is extracted from Jack bean (Canavalia ensiformis). Because
ConA can specifically bind to various sugars, glycoproteins, and some structures
of glycolipids (mainly internal and non-reducing terminal α-D-mannosyl and α-Dglucosyl groups). Therefore, ConA has great potential for efficient recognition of
sugars, glycoproteins, and glycolipids [1, 2]. Note that ConA needs to bind with
metal ions (Mn2+ and a Ca2+ ) to obtain affinity for sugars.
ConA has been considered that it is a useful tool applied in the solid-phase
immobilization of glycoenzymes, especially these difficult to immobilize by
traditional covalent coupling. Based on the ConA coupling matrix, this type of
enzyme can be immobilized efficiently, but the ConA coupling matrix will not lose
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021
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https://doi.org/10.1007/978-981-16-1212-1_9
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9 Graphene FET Biosensor Based on the Concanavalin A
the activity and/or stability of the enzyme. In addition, this kind of non-covalent
coupling mechanism can be easily dissociated by competing with other sugars or at
acidic pH. Based on the above advantages, many of the reports have demonstrated
that ConA can interact with diverse receptors containing mannose carbohydrates,
particularly rhodopsin, insulin-receptor, immunoglobulins. In addition, many of
the cells and microbes have been proved that can interact with the ConA through
surface immunoglobulins, such as cancerous cells, muscle cells, B-lymphocytes,
Escherichia coli, and Bacillus subtilis [3].
Because of its extensive binding capabilities, some studies have already applied
it for the graphene biosensor at present. Xiaojian Li et al. reported that an electrochemiluminescence (ECL) biosensor was developed for the detection of Con A,
and they claimed that under the optimization of determination conditions, a linear
response range for Con A from 0.5 pg mL−1 to 100 ng mL−1 was obtained, and the
detection limit was calculated to be 0.18 pg mL−1 (S/N = 3) [4]. Juanjuan Zhang
et al. reported that they designed a highly sensitive ECL biosensor for the detection
of ConA based on glucose oxidase (GOx) as a recognition element by carbohydrate–lectin biospecific interaction, and poly(ethylenimine) (PEI) reduced graphene
and hollow gold nanoparticles (HAuNPs) as supporting matrix and signal amplifier.
They found a linear relationship between ECL signal strength and the logarithm of
ConA concentration, with a linear range of 1.0–20 ng/mL and a detection limit of
0.31 ng/mL (signal to noise ratio =3) [5]. Besides, Chun-Fang Huang et al. claimed
that based on ConA as a model protein, they developed a novel surface plasmon
resonance (SPR) sensor for sensitive detection ConA. Their SPR sensor successfully
fulfilled the sensitive detection of ConA in the range of 1.0–20.0 μg mL−1 with a
detection limit of 0.39 μg mL−1 [6].
Although many of the ConA detection-related researches have been reported;
however, it may be difficult if the ConA is fixed to detect biomolecules with glycome
groups. Since many of the biomolecules are both containing glycome, thus how to
maintain the high specificity for the target biomolecules that is the difficult point
during the real detection. Thus for glycome biomolecule detection with the graphene
FET biosensor based on the ConA, the specificity should be noted. In addition, the
affinity of the ConA should be activated through the metal ions; however, some of
the reports have shown that the metal ions will also disturb the signal of the graphene
FET biosensing. It is a disturbing factor during target biomolecule detection. Thus the
introduced volume and concentration of the metal ions solution should be severely
controlled.
At present, there is almost no related research on ConA-based graphene FET
biosensing technology. The following will list my vision for the future application of
graphene FET based on ConA technology. My vision can be divided into two types:
adsorption and dissociation, and they will be described as follows, respectively.
9.1 Adsorption
103
9.1 Adsorption
Generally speaking, the adsorption method is that fixes ConA on the surface of
the graphene FET biosensor at first then relies on the adsorption capacity of ConA
for glycome-based molecules, microorganisms, cells, etc. for specific detection. The
immobilization of ConA on the graphene surface includes covalent bonding and noncovalent bonding. Among them, covalent bonding may be an ideal fixing method for
the adsorption method, because if a non-covalent bonding method is used for fixing,
there may be a risk that ConA binds to the target molecule and breaks off the graphene
surface during the test. The immobilization of ConA on the graphene surface includes
covalent bonding and non-covalent bonding. Among them, covalent bonding may
be an ideal fixing approach for the adsorption method, because if a non-covalent
bonding method is used for fixing, there may be a risk during the test that the target
molecule bind to the ConA then separates from the surface. For covalent bonding,
there are lots of approaches such as N-Hydroxysuccinimide (NHS) ester that has
been usually applied as a linker, so that ConA can be bound to the graphene surface.
Because this kind of structure can firmly fix ConA on the surface of graphene so that
we can expect that the quantitative detection of glycome-containing biomolecules,
microbes, and cells is possible through this structure in the near future. The schematic
image of the adsorption approach is shown in Fig. 9.1.
9.2 Dissociation
In general, for the dissociation method, it is first necessary to immobilize ConA
molecules on the graphene surface in a non-covalent manner. For example, first,
modify the chitosan onto the surface of graphene, and then rely on the electrostatic
effect and glycosyl binding effect between chitosan and ConA molecules, ConA
molecules can be immobilized on chitosan in a non-covalent manner. Later, when
the target molecule with glycosyl groups is added, the target molecule will occur
the competitive adsorption with the ConA-chitosan complex, resulting in a certain
dissociation of the ConA-chitosan complex. The original non-covalently modified
ConA molecules will partly dissociate from the graphene chitosan surface due to
the addition of target molecules with glycosyl groups. Because the dissociation ratio
is related to the concentration of the target molecule and the affinity of the target
molecule for the ConA molecule, thus it is possible to quantify the concentration of
the target molecule based on the graphene FET biosensor. The schematic image of
the dissociation approach is shown in Fig. 9.2.
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9 Graphene FET Biosensor Based on the Concanavalin A
Fig. 9.1 a The schematic image of the adsorption approach before target binding. b The schematic
image of the adsorption approach after target binding
Comparing these two methods, we can find that the adsorption method binds the
target molecules in the test solution to the graphene surface at first, and then changes
the electric double layer capacitance through the binding of the target molecules,
thereby changing the Ids of the graphene FET. But for the dissociation method is
to occur, the competitive adsorption between the target molecule in the test solution
and the ConA that has been non-covalently bound onto the graphene in previous,
so that the ConA is partly separated from the graphene surface into the solution.
After the ConA is separated from the graphene surface, this processing will change
the original electric double layer capacitance, which in turn changes the Ids of the
graphene FET.
For the adsorption method, it is more necessary to consider whether the adsorption
of the target molecule is sufficient to change the electric double-layer capacitance,
which depends on the isoelectric point (pI) of the target molecule, and a series of
complex factors. For the dissociation method, we need to intentionally focus on the
affinity of the target molecule with ConA. In short, based on my experience, I think
9.2 Dissociation
105
Fig. 9.2 a The schematic image of the dissociation approach before target molecules introduced.
b The schematic image of the dissociation approach after target molecules introduced
the adsorption method may be more suitable for biomacromolecules, microbes, and
cells. But for the dissociation method, I think it is more suitable for micromolecules,
such as oligosaccharides.
References
1. Liener, I.: The Lectins: Properties, Functions, and Applications in Biology and Medicine.
Elsevier (2012)
2. Sumner, J.B., Gralën, N., Eriksson-Quensel, I.-B.: The molecular weights of urease, canavalin,
concanavalin a and concanavalin B. Science 87(2261), 395–396 (1938). https://doi.org/10.1126/
science.87.2261.395
3. Concanavalin A. Wikipedia (2020)
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9 Graphene FET Biosensor Based on the Concanavalin A
4. Li, X., Wang, Y., Shi, L., Ma, H., Zhang, Y., Du, B., Wu, D., Wei, Q.: A novel ECL biosensor for
the detection of concanavalin a based on glucose functionalized NiCo2 S4 nanoparticles-grown
on carboxylic graphene as quenching probe. Biosensors Bioelectron. 96, 113–120 (2017). https://
doi.org/10.1016/j.bios.2017.04.050
5. Zhang, J., Chen, S., Ruo, Y., Zhong, X., Wu, X.: An ultrasensitive Electrochemiluminescent
biosensor for the detection of concanavalin a based on poly(Ethylenimine) reduced graphene
oxide and hollow gold nanoparticles. Anal. Bioanal. Chem. 407(2), 447–453 (2015). https://doi.
org/10.1007/s00216-014-8290-x
6. Huang, C.-F., Yao, G.-H., Liang, R.-P., Qiu, J.-D.: Graphene oxide and dextran capped gold
nanoparticles based surface plasmon resonance sensor for sensitive detection of concanavalin a.
Biosens. Bioelectron. 50, 305–310 (2013). https://doi.org/10.1016/j.bios.2013.07.002
Chapter 10
Challenges and Outlook
Abstract Since the graphene field-effect transistor biosensor was reported in 2009,
it has been widely developed around various biological interactions. Series exciting
research results are reported gradually in the past decade, which also indicate that
its great potential for practical clinical testing applications. However, there are still
many problems that need to be improved, such as how to improve the quality of
the graphene film, and how to standardize the graphene transfer and the surface
modification process. In addition, from the perspective of industrialization, how to
reduce signal disturbance, how to integrate with semiconductor technology and a
series of engineering problems also need time to solve. This chapter focuses on
the current problems facing industrialization, including graphene quality problems,
standardization problems, etc., and proposes improvement suggestions.
Keywords Graphene FET · Graphene transfer · Surface modification ·
Standardization · Signal interference
Although, the graphene FET biosensor shows much fantastic potential application
expects at present. At the same time, there are also lots of challenges. Such as integration with semiconductor technology, the standardization of transfer and modification,
and the signal of the graphene FET biosensor are easy to be interfered by the ultraviolet and other factors. In this section, these challenges will be illustrated respectively,
and at the end of this section, the outlook of the graphene FET biosensor and the
potential application in the future will also be demonstrated based on my opinion.
To our knowledge, when showing their readings of the source-drain current, which
is used as the biosensor signal, it is evident that there are substantially different current
levels in the experiences. The origin factors of differences have lots of aspects. For
the CVD graphene, it is polycrystalline not like the exfoliated graphene from the
graphite. The exfoliated graphene from the graphite is almost monocrystalline but
the CVD graphene is polycrystalline. Because of the irregular grain boundaries, the
conductivity of each part of the graphene on the channel is both different, so for the
channel material itself, it is impossible to guarantee two graphene FET with the same
conductivity. Figure 10.1a shows the optical image for the CVD graphene on copper
foil. It shows the micron-scale grain boundaries of CVD graphene. Figure 10.1b
shows the SEM image of the CVD graphene on copper foil. It shows that there are
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021
S. Wang et al., Graphene Field-Effect Transistor Biosensors,
https://doi.org/10.1007/978-981-16-1212-1_10
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108
10 Challenges and Outlook
Fi. 10.1 a The optical image of the CVD graphene on copper foil. b The SEM image of the CVD
graphene on copper foil
randomly distributed multilayer graphene island core structures with darker colors
inside the grain boundaries. It will also interrupt the conductivity of the graphene
FET biosensor.
However, as far as the current level of technology is concerned, it is still very
difficult to grow single-crystal graphene comparable to silicon wafer level. It is
conceivable that if graphene as a new type of two-dimensional material is further
widely used in several sensing applications, the core problem is how to prepare
high-quality monocrystalline graphene in my opinion. At present, some studies have
shown the method of preparing single-crystal graphene films by the CVD method [1].
They report that the growth of millimeter-sized hexagonal single-crystal graphene
and graphene films joined from such grains on Pt by ambient-pressure chemical vapor
deposition. I believe that the problem of CVD preparation of large-size single-crystal
graphene will be solved in the future.
10.1 Standardization of Transfer and Modification
Graphene transfer is the most difficult processing during the graphene FET manufacture. The graphene film has to transfer to the substrate from the liquid solution, it is
so thin that is very easy to be destroyed during the transfer processing. The transfer of
CVD graphene first requires spin-coating a layer of PMMA film on the surface of the
graphene copper foil, then etch the copper foil with the oxidant, and finally transfer
the graphene to the substrate in the solution. This series of complicated steps are
difficult to full automation. At present, the transfer steps of graphene are basically
done manually, which brings great difficulties to the standardization of graphene
10.1 Standardization of Transfer and Modification
109
FET biosensor. Therefore, it is easy to cause graphene to form wrinkles and creases
on the substrate during the graphene transfer process. The surface defects caused by
these subtle wrinkles and creases made the difference in conductivity between CVD
graphene FET sensors, which is also the reason for the conductivity difference. Otherwise, modification processing is also the main reason for the conductivity difference.
But at present, the modification steps of ELISA and other biological applications of
immunohistochemistry can be well standardized to narrow the differences between
individuals. So I think that with the gradual deepening of the application of graphene
FET biosensor, the standardization of the process will be well resolved, including
the use of more advanced automatic analyzers.
In addition, the adhesion between the electrode and the substrate is also an aspect
that needs attention (during the GFET biosensor test in solution, low adhesion may
cause the electrode to fall off). For example, if epitaxial graphene is used as a
substrate, the low adhesion between the interdigital electrode and the substrate may
cause the electrode of the GFET biosensor to fall during the test (strong hydrophilicity
of the electrode material). The current ideal improvement plan is to first deposit
electrodes on the substrate (to ensure strong adhesion between the electrodes and the
substrate), and then transfer the CVD graphene to the electrodes. However, the thickness of the deposited electrode should be controlled as thin as possible so that the
graphene can better adhere to the surface of the electrode and the substrate through
Van der Waals force. When using epitaxial graphene as the substrate, the specific
hydrophobic layer can be deposited on the surface of the electrode to shield the
electrode from its strong hydrophilicity.
10.2 Signal Interference
The signal interference of graphene biosensing is multifaceted. The most common
one is the electric signal jitter caused by vibration. In addition, since graphene is
almost transparent, if the substrate is SiO2 /Si, then electromagnetic radiation such
as ultraviolet rays can easily pass through the insulating layer to cause a similar gate
effect on the Si layer, which affects the conductivity of graphene [2]. Note that if
the linker with the fluorescent effects such as PBASE is used as the linker, it may
also absorb electromagnetic radiation such as ultraviolet rays, thereby affecting the
biosensing signal. Therefore, the sensor should try to avoid using it under strong
electromagnetic radiation.
From the perspective of the device structure, it is recommended to use only
the back-gate grounding method for real-time testing. Because in the real-time test
process, the change of the current Ids in the ideal state is only determined by the
number of molecules adsorbed on the graphene channel. If the gate is given to the
voltage, any small fluctuations in the gate voltage will affect the current Ids during
the real-time test. In addition, if the reference electrode is introduced as the top gate,
any small mechanical vibration and many other complex factors will significantly
110
10 Challenges and Outlook
disturb the current Ids during the real-time test. Meanwhile, the reference electrode
will introduce new ions in the test solution. Thus, according to my experience, for
real-time testing, the back-gate grounding method is recommended.
10.3 Outlook
Compared with traditional clinical detection methods, although GFET biosensor
cannot detect single nucleic acid molecules such as PCR through amplification in
terms of sensitivity, its sensitivity to specific targets can currently reach the sub-fM
level, which is close to that of ELISA. But in terms of detection speed, because GFET
biosensor can directly convert biological signals into current signals, and relying on
the super-large contact surface between the graphene channel and the solution to
be tested, the detection of GFET biosensor can accomplish within 1 min. This is
unmatched by traditional methods (even the rapid ELISA technique usually requires
more than 1 h).
At present, as a credible technology in clinical detection, the position of traditional
detection methods (such as ELISA and PCR) in medicine is unshakable. We proposed
the novel GFET biosensor that is not intended to alternative these traditional detection
methods but to complement each other based on the advantage of rapid detection
which traditional detection methods do not possess. At the same time, this novel
GFET biosensor also has a certain sensitivity and selectivity. Because this sensor
has a huge potential to perform rapid detection, it may be more suitable as a kind of
the initial screening method, thereby quickly introducing a preliminary diagnostic
opinion from the test results of the GFET biosensor. Then according to the positive
or negative detected result, further traditional detection methods such as ELISA and
PCR are gradually considered. This may be useful for large-scale epidemic diseases
such as COVID-19 (Tables 10.1, 10.2, 10.3 and 10.4).
Although graphene FET biosensors still have some thorny issues at present,
compared with traditional bulk materials, 2D materials, especially graphene, have
shown excellent performance in biosensing and other applications, so I think
graphene in the future FET biosensors are promising, but further research is still
needed. For example, how to manufacture GFET biosensors in large-scale industrial
production, and how to integrate with the existing semiconductor technology (Based
on system-on-a-chip technology, GFET biosensors should be further integrated with
the analog-digital converter and microprocessor).
The research of graphene applications has received more and more attention
worldwide, and many research centers have been established in the past two decades.
The main locations of these research centers are concentrated in China and the United
States. Finally, these major graphene research centers will be introduced.
10.3 Outlook
111
Table 10.1 The main research center in China
China
Shenyang Institute of Metal Science
Cheng Huiming group
http://www.imr.cas.cn/
Central South University
Liu Yanping group
http://www.yplab.cn/
Harbin Institute of Technology
Key laboratory of Micro-systems and
Micro-structures Manufacturing
http://mmme.hit.edu.cn/
Shanghai Institute of Microsystem and
Information Technology
Mao Hongju group
http://english.sim.cas.cn/
Xiamen University
Graphene Industry and Engineering Research
Institute of Xiamen University
https://gieri-en.xmu.edu.cn/en/
Fudan University
Wei Dacheng group
http://www.weigroupfudan.com/
Table 10.2 The main research center in Japan
Japan
Osaka University
Kobayashi Yoshihiro group
http://www.ap.eng.osaka-u.ac.jp/nanomaterial/
index.html
Nagoya University
Ohno Yutaka group
https://nanoflex.jp/public-j/member_ohno.html
Tokyo University of Agriculture and
Technology
Maehashi Kenzo group
http://web.tuat.ac.jp/~maehashi/index.html
Saitama University
Oeno Keiji group
http://surface-www.chem.saitama-u.ac.jp/wiki/
National Institute of Advanced Industrial
Science and Technology (AIST), Tsukuba
Nanomaterials Research Institute
https://unit.aist.go.jp/nmri/index_en.html
National Institute for Materials Science
(NIMS)
Advanced Low-Dimensional Nanomaterials
Group
https://www.nims.go.jp/1Dnanomaterials/eng
lish/index.html
112
10 Challenges and Outlook
Table 10.3 The main research center in the United States
United States
Massachusetts Institute of Technology
Jarillo-Herrero Group
http://jarilloherrero.mit.edu/
Harvard University
Charles M. Lieber group
http://cml.harvard.edu/
Columbia University
Qiao Lin group
https://biomems.me.columbia.edu/
University of California, Los Angeles
Duan Xiangfeng group
http://xduan.chem.ucla.edu/
University of Michigan
MICROTECHNOLOGY LAB
https://www.egr.msu.edu/mems/
University of Pennsylvania
Charlie Johnson Group
http://nanophys.seas.upenn.edu/
Table 10.4 The main research center in other countries
Other countries
University of Manchester
The University of Manchester National Graphene
Institute
https://www.graphene.manchester.ac.uk/
University of Cambridge
Cambridge Graphene Centre
https://www.graphene.cam.ac.uk/
University of Oxford
Nanostructured Materials Group
Department of Materials
http://nsm.materials.ox.ac.uk/Main/HomePage
Vienna University of Technology
Thomas Mueller group
https://www.graphenelabs.at/home
The National University of Singapore
The Graphene Research Centre (GRC)
https://graphene.nus.edu.sg/
Nanyang Technological University
Liu group
https://www.ntu.edu.sg/home/z.liu/index.html
References
1. Gao, L., Ren, W., Xu, H., Jin, L., Wang, Z., Ma, T., Ma, L.-P., Zhang, Z., Fu, Q., Peng, L.-M.,
Bao, X., Cheng, H.-M.: Repeated growth and bubbling transfer of graphene with millimetre-size
single-crystal grains using platinum. Nature Commun. 3(1), 699 (2012). https://doi.org/10.1038/
ncomms1702
2. Iqbal, M.Z., Siddique, S., Anwar, N.: Influence of electron beam and ultraviolet irradiations on
graphene field effect transistors. Optical Mater. 72, 496–500 (2017). https://doi.org/10.1016/j.
optmat.2017.06.039
Chapter 11
Conclusions and Future Works
Abstract Compared with other traditional clinical detection methods, the core
advantage of graphene field-effect transistor biosensor is its unparalleled testing
speed. At the same time, it can also maintain high sensitivity and specificity. From
the perspective of future applications, the graphene field-effect transistor biosensor
may be more suitable as a preliminary rapid detection solution. Large-scale prescreening can be conducted so that it can rapidly provide preliminary diagnostic
results. As a novel rapid quantitative detection platform, it can make up for the shortcomings of traditional detection methods in large-scale rapid detection. Believe that
with the gradual deepening of the research of graphene field-effect transistor biosensors, its potential value in the field of biological detection will become more and
more outstanding in the future.
Keywords Graphene · Graphene FET · Biosensor · Rapid detection
11.1 Conclusions
Based on excellent electrical properties, chemically stability, and compatibility
with different organic macromolecules, graphene has become an ideal platform
for binding receptor molecules and biosensor sensors. With the development of
advanced nanofabrication equipment, GFET biosensors have become the most potential biosensing and biological detection technology for rapid, low-cost, and ultrasensitive quantification of biomolecules. Although the invention and development
of the graphene FET biosensor have only gone through 10 years, it has sufficiently
merged with multiple biological technologies, and many different types of graphene
FET biosensors have been developed. Current research has shown that based on
graphene FET biosensors, virus es, bacteria, cells, and many different types of
biomolecules can be ultrasensitive rapid quantitative detection. Its detection limit
has approached the fM level, and through a series of blocking methods, the graphene
FET biosensor has shown ultra-high specificity, and compared with traditional detection methods, it can perform rapid quantification, thereby providing a potential basis
for rapid judgment for clinical diagnosis. This is unmatched by traditional detection
methods. In particular, it provides a potentially effective procedure for large-scale
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021
S. Wang et al., Graphene Field-Effect Transistor Biosensors,
https://doi.org/10.1007/978-981-16-1212-1_11
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11 Conclusions and Future Works
investigations of epidemics in the population. All these exciting results indicated the
great prospects of this technology in biosensing applications.
Here I would like to emphasize again that compared with traditional clinical
detection methods, such as ELISA and PCR, the key advantage of GFET biosensors
lies in the rapid detection and the high sensitivity. From the perspective of detection
speed, GFET biosensors can quickly respond to the concentration of the test solution
within 1 min, because GFET biosensors can directly convert biological signals into
electrical signals. However, traditional detection methods such as PCR and ELISA,
even the rapid detection procedure also takes 1 h. GFET biosensor has unparalleled
rapid detection performance (1 min < < 1 h). From the perspective of detection sensitivity, although the current GFET biosensor cannot perform single molecular-level
detection like PCR, its detection sensitivity is close to the detection accuracy of
ELISA (sub-pM-level) and is expected to be further improved in the future. Besides,
it may not require complex detection equipment, which makes it highly portable. As
a novel biosensing platform, the GFET biosensor is a good complementary detection method for traditional clinical detection methods. As an emerging biosensing
platform, it may be more suitable for rapid screening of large-scale epidemics and is
expected to complement the current traditional clinical detection methods that cannot
achieve large-scale rapid detection.
11.2 Future Works
Although this novel sensor has great potential in the clinical application field, there
are still some problems that need to be solved before it is put into practical application.
For example, the safety of graphene nanomaterials has not yet been clarified, and how
the graphene FET biosensor can be fused with current semiconductor technology for
large-scale preparation. In addition, it may be necessary to develop special signal
acquisition and analysis equipment for graphene FET biosensors. But these problems
will not substantially affect the sensing applications of graphene FET biosensor, and
there are some signs that these problems are gradually improving. So I believe that
the prospect of graphene biosensors is worthy of being expected.
Furthermore, in order to improve the detection effect, avoiding the noise signal,
and the standardization of graphene transfer and graphene modification should be
noted. These experimental details may also affect the detection results.
Index
A
Adsorption detection, vii
Alpha-fetoprotein, 89, 90
Amyloid-β (Aβ) and tau protein, 90
Antibody, 54, 62, 71, 80, 81, 87–90, 93, 98,
99
Antigen, 54, 61, 71, 80, 81, 87–90, 93, 98
Antigen-antibody interaction, vi, 87–90, 98
Aptamer, 46, 54, 71, 97–99
Aptamer technology, 98, 99
Atomic Force Microscope (AFM), 30, 77
AuNPs, 54, 71, 77, 88, 94, 99, 102
Avidin, 69–71, 78, 80, 81
Avidin-biotin technology, 69, 80, 81
Chemical vapor deposition, 30
Chitosan, 103
ConA-chitosan complex, 103
Cortisol hormone, 90
COVID-19, 47, 71, 95, 96
COVID-19 detection, 95
D
Debye length, 50, 90
Diffuse Layer (DL), 7, 47, 48, 50
Dirac point, 22, 57, 60
Dissociation detection, vii
DNA, 9, 11, 46, 94, 95, 97, 98
DNA sequencing, 9, 11
Double layer, 7, 47, 50, 51, 60, 88, 104
Drug delivery, 9
B
Base pair, 54, 93, 94
BDM model, 49
BioFETs, 46
Biological detection, 13
Biomedical applications, 9
Biosensor, 31, 37, 45–47, 52–55, 60–62, 69,
71, 78–81, 88–90, 93–95, 98, 99, 102,
103, 107, 109, 114
Biotin, 69–71, 78–81
Blocking, 55, 113
Bovine Serum Albumin (BSA), 46, 52, 55,
78, 95
Brain natriuretic peptide, 89, 90
E
Early diagnosis, 93
Electrical Double Layer (EDL), 7, 47
Electrical theoretical basis, vi
Electrochemiluminescence, 102
ELISA, 69, 70, 81, 109
Epitaxial growth, 37
Escherichia coli, 98, 102
Etching transfer method, 33
Ethanolamine, 55, 90, 95
C
Cancer marker, 71, 80, 88
Carcinoembryonic antigen, 62, 90
Cell imaging, 11
F
Field-effect transistor, 1, 29, 45, 46, 51–53,
60, 62, 71, 98
Free radical detection, 63
© The Editor(s) (if applicable) and The Author(s), under exclusive license
to Springer Nature Singapore Pte Ltd. 2021
S. Wang et al., Graphene Field-Effect Transistor Biosensors,
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116
G
Glucose oxidase, 102
Gold nanoparticles, 71, 77, 81, 102
Graphene, 1, 2, 6, 7, 9–12, 14, 15, 21, 22,
24–39, 45–48, 51–55, 57, 60–63, 69,
71, 72, 77–81, 88–91, 94, 95, 98, 99,
102–104, 107, 108, 114
Graphene biosafety, 14
Graphene conductive ink, 2
Graphene electrical characteristics, 21
Graphene FET biosensor, 37, 46, 47, 52–55,
60–62, 69, 71, 78, 79, 81, 88, 95, 98,
99, 102, 103, 107–109, 114
Graphene field-effect transistor, 29, 45, 62,
71, 98
Graphene flexible sensing, 6
Graphene manufacture, 29
Graphene nanogenerator, 6
Graphene supercapacitor, 4
Guanine blocking, 55
H
Hall device, 26
Helmholtz plane, 50
Hill-Langmuir equation, 61
I
Immunoglobulin E, 98
Interface capacitance, 60
Isoelectric point, 104
L
Labeled immunosensor, 69, 70
Langmuir adsorption model, 60
Large-scale census, 95
Large-scale epidemic detection, vi
Limit of detection, 62, 80, 81
Linker, 46, 54, 60, 71, 94, 98, 103
Low-temperature electrical characteristics,
27
M
Mechanical exfoliation method, 29
Metal ions, 63, 101, 102
Microbes, 102, 103, 105
Microbial fuel cells, 5
MiRNA, 71, 94
Moiré pattern, 27
Monocrystalline, 107, 108
Index
N
Nanoscale graphene oxide, 10
Nanowire, 91
N-Hydroxysuccinimide (NHS) ester, 103
Non-covalent interaction, 70
Nucleic acid, 54, 55, 61, 70, 71, 81, 93–95,
97
Nucleic acid sequence, 94
Nucleic Acid Test (NAT), 93, 95
O
Oligonucleotides, 97
P
PBASE, 46, 54, 62, 71, 88, 94, 98, 99
Percentage of the surface cover, 61
Point-of-care testing, vi
Polycrystalline, 107
Polymer-based detection, 69, 70
Polypeptide nucleic acid (PNA), 94
Poly(methyl methacrylate) (PMMA), 36, 37,
72, 108
Preparation method, 29
Probe sequence, 96
Prostate specific antigen/α1-antichymotrypsin,
90
R
Raman spectrum, 78
Reduced Graphene Oxide (RGO), 39, 89
RNA, 71, 94–97
RNA virus, 95
Room-temperature electrical characteristics,
22
S
SARS-CoV-2, 71
Scanning Electron Microscope (SEM), 77,
107, 108
Schiff base reaction, 98, 99
SELEX technology, 99
Sensing platform, 6, 26, 69, 71, 82, 88
SiC, 27, 37–39
Signal interference, 109
Stacking, 10, 54, 62
Standardization of transfer and modification,
108
Stern model, 48
Surface modification, 54, 77, 88
Index
T
Target RNA sequence, 96
Tetrakis(4-carboxyphenyl)porphyrin
(TCPP), 46, 54, 88
Thermal applications, 7
Tumer therapy, 12
117
V
Vibration, 36
Virus, 61, 71, 94, 95, 113
X
Xeno nucleic acids (XNA), 94, 97
X-ray Photoelectron Spectroscopy (XPS),
37, 38, 77