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Graphene-Based Artificial Intelligence Flexible Sensors

Hongji Jiang , Meili Wang , Zhiwei Lu , Shanghui Ye , Xiaochen Dong

Progress in Chemistry ›› 2022, Vol. 34 ›› Issue (5) : 1166 -1180.

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Progress in Chemistry ›› 2022, Vol. 34 ›› Issue (5) : 1166-1180 DOI: 10.7536/PC210513
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Graphene-Based Artificial Intelligence Flexible Sensors
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Abstract

Skin is the largest organ of the human body and can perceive and respond to complex environmental stimuli. As a 2D atomic layer of sp2-hybridized carbon arranged in a hexagonal network, graphene is regarded as a promising material for nanoelectronics owing to its high crystallinity and interesting semimetal electronic properties. In addition, graphene has extremely strong perception ability and high selectivity for different stimuli, and graphene-based materials have been widely used as key perceiving materials of artificial flexible sensors to imitate the flexibility and stretchability of human skin, which is one of the most promising wearable and sensing materials for potential commercialization. This paper first introduces the main working mechanisms of piezoresistive type, capacitive type, piezoelectric type and transistor type, as well as the key performance evaluation parameters such as sensitivity, detection range, response speed and so on of sensors. At the same time, the advantages and synthesis methods of graphene materials are also briefly summarized. In conjunction of our recent research works of graphene-based composite materials made up of graphene and polyaniline, Ag nanoparticles, carbon nanotubes, Ni(OH)2(Ⅱ) and quantum dots for flexible sensors, this paper then reviews the applications of graphene-based single function flexible sensors in detecting pressure, strain, temperature, humidity, chemical molecules, biomolecules, gas and other fields, as well as several graphene-based multifunctional flexible sensors. Finally, the future development of graphene-based flexible sensors is prospected.

Contents

1 Introduction

2 Flexible sensors

2.1 Flexible sensor features

2.2 The sensing mechanism of flexible sensors

2.3 Performance parameters of flexible sensors

3 Graphene

3.1 Synthesis of graphene-based materials

3.2 Sensing properties of graphene-based materials

4 Graphene-based single function flexible sensors

4.1 Graphene-based flexible pressure sensors

4.2 Graphene-based flexible strain sensors

4.3 Graphene-based flexible humidity sensors

4.4 Graphene-based flexible temperature sensors

4.5 Graphene-based other flexible sensors

5 Graphene-based multifunctional flexible sensors

5.1 Pressure/strain sensors

5.2 Pressure/humidity/temperature sensors

5.3 Strain/humidity/temperature sensors

5.4 Pressure/strain/humidity/temperature sensors

5.5 Graphene-based other multifunctional flexible sensors

6 Conclusion and prospect

Graphical abstract

Keywords

graphene / wearable / flexible sensor / single function / multifunction

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Hongji Jiang, Meili Wang, Zhiwei Lu, Shanghui Ye, Xiaochen Dong. Graphene-Based Artificial Intelligence Flexible Sensors. Progress in Chemistry, 2022, 34(5): 1166-1180 DOI:10.7536/PC210513

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1 Introduction

Skin is the largest organ of the human body, which has the characteristics of stretchability, mechanical flexibility and tactile sensing. Wearable smart sensors sense various stimuli such as pressure, strain, temperature and humidity by simulating the tactile sensing ability of human skin, and transmit the corresponding visual signals in time[1]. Wearable smart sensors can also monitor health status by detecting vital signs such as pulse, breathing and types of daily activities. The key to wearable sensors is that the sensors must be flexible and stretchable in order to fit irregularly shaped surfaces to sense various stimuli. In 2004, Geim and Novoselov first successfully obtained stable single-layer graphene by mechanical exfoliation, which attracted wide attention of researchers[2]. Graphene is a two-dimensional carbon nanomaterial with hexagonal honeycomb lattice composed of carbon atoms with sp2 hybrid orbitals, which has broad application prospects in flexible display, energy storage, photocatalytic activity and flexible sensors[3][4][5]. According to the geometry, graphene can be divided into graphene sheets, graphene ribbons and three-dimensional porous graphene[6,7]. Flexible sensors based on graphene and its derivatives have become a research hotspot because of their wearable, portable, low cost and high detection sensitivity.

2 Flexible transducer

2.1 Characteristics of Flexible Sensor

Compared with traditional inorganic semiconductor sensors, flexible sensors can fit the surface of irregular objects, adapt to different movements, withstand more stretching, bending and pressure, and have higher stability and reliability. Flexible sensors have great potential applications in health monitoring, motion detection and health care[8].

2.2 Working mechanism of flexible sensor

According to the different working mechanism, flexible sensors can be generally divided into four main sensing types, such as piezoresistive, capacitive, piezoelectric and transistor, as shown in Figure 1[9⇓~11].

2.2.1 Piezoresistive transducer

Piezoresistive sensor can convert the change of material resistance caused by external stimulation into electrical signal output, which has been widely studied because of its advantages of easy preparation, fast response, large sensing range and high sensitivity. The main factors affecting the resistance change of piezoresistive sensor are: (1) the change of the geometric structure of the sensitive element; (2) The change of semiconductor energy level structure; (3) The change of contact resistance between two materials; (4) The change of interparticle spacing in the composite[11,12].

2.2.2 Capacitive transducer

Capacitive sensors consist of two conductive layers separated by an elastomeric dielectric layer, based on a parallel plate capacitance, which is given by Equation 1:
C=(ε0·ε·A)/d
Where ε0, ε, d, and A are the vacuum permittivity, the elastomer permittivity, the distance, and the overlap area between two parallel plates, respectively. Capacitive sensor has the advantages of low power consumption, good stability and easy multi-point identification[13]. Most capacitive sensors have a dielectric layer sandwiched between two electrodes, and when pressure or strain is applied, the capacitance between the electrodes changes due to plate deformation, but because the change in parallel plate capacitance is relatively small, the sensitivity of such sensors tends to be low[13].

2.2.3 Piezoelectric transducer

The voltage produced by the material under the external mechanical stimulation is called the piezoelectric effect. The anisotropic crystal will produce a dipole moment under the external pressure, which will produce a macroscopic potential in the crystal[14]. Piezoelectric sensors convert dynamically changing pressure into measurable current, which can be used to detect dynamic pressure such as sound vibration or pulse beating in the field of wearable sensing, with the advantages of high sensitivity and fast response[11]. Compared with other piezoelectric materials, graphene has better flexibility and is more widely used in flexible piezoelectric sensing.

2.2.4 Transistor transducer

Compared with resistive and capacitive sensors, transistor sensors have the advantages of small signal crosstalk, high throughput sensing and miniaturization, and have obvious advantages in flexible sensing[15]. The typical organic field effect transistor is composed of source, drain, gate, semiconductor layer and dielectric layer. The unique current amplification function of the transistor enables the field effect transistor sensor to distinguish complex signals and become an ideal choice for sensing weak signals[16,17]. In addition, every component including gate electrode, dielectric layer, semiconductor layer, and drain/source electrode may be used as the active layer of the sensor, which provides more possibilities for the integration of multiple sensing functions[18,19][20]. The Fermi energy level can be adjusted by the gate voltage to generate two carriers of holes or electrons in the graphene with zero band gap, and the bipolar property not only enables the graphene to obtain a plurality of sensing signals, but also can adjust the sensitivity of the sensor in a large range[21][22,23].

2.3 Parameters for Evaluating the Performance of Flexible Sensors

The main parameters to evaluate the performance of flexible sensors are: (1) Sensitivity. Sensitivity is defined as the curve of the relative change of the output electrical signal with the applied stimulus. (2) detection limit. The detection limit refers to the range of variation of the stimulus that can be detected by the sensor. (3) Response time. Response time refers to the speed of stimulus response changes in the form of output signals, that is, response and recovery time. In the wearable flexible sensor, the sensor is required to respond immediately, detect and transmit signals in real time. (4) Mechanical properties. The sensor needs to have a long service life and good repeatability and stability in the long-term use process.

3 Graphene

3.1 Preparation of Graphene

The first challenge for the preparation of commercialized graphene-based sensors is the controllable preparation of high-quality graphene at low cost and large area. At present, there are mainly two preparation methods: top-down and bottom-up[24][25⇓~27]. Top-down methods include mechanical exfoliation, solution method, laser etching and carbon nanotube debonding[28,29]. The top-down method usually processes bulk graphite into thinner or smaller graphene sheets, which inevitably introduces defects during exfoliation. Solution method mainly includes solvent method, intercalation method and liquid phase ultrasonic method. The bottom-up approach includes epitaxial growth, chemical vapor deposition, and organic precursor synthesis, starting from carbon atoms to build or assemble large-sized graphene structures. The commonly used solution method for preparing graphene is the Hummer method as shown in Figure 2. Graphite flakes are oxidized into graphite oxide by strong acid and strong oxidant, and then graphene is prepared by reduction layering with hydrazine hydrate, ascorbic acid, ethylenediamine, sodium borohydride, etc[30][31⇓~33]. Different preparation methods of graphene have their own advantages and disadvantages, and the quality of graphene prepared is uneven, which leads to different sensing mechanisms.

3.2 Sensing properties of graphene.

The ideal graphene is composed of a single layer of carbon atoms, and each carbon atom exposed to the environment can act as an active site sensing stimulus. Graphene has many characteristics suitable for sensing, firstly, graphene has large specific surface area (2630 m2/g), high electron mobility (200 000 cm2/(V·s)), good conductivity, and can sense a variety of stimuli; Secondly, graphene is the thinnest two-dimensional material, which is light in weight, good in mechanical flexibility, easy to process, and compatible with large-area flexible solid supports, and is suitable for the preparation of flexible sensors[34⇓⇓⇓~38]. Finally, graphene composited with other functional materials can enhance the sensitivity and selectivity to specific analytes, and induce flexibility and stretchability to construct multifunctional graphene-based sensors[39⇓~41].

4 Graphene based single function flexible sensor

Graphene-based sensors are widely used in the fields of pressure, strain, temperature, humidity and chemical sensing[42][43,44][45,46][47,48][49]. Graphene-based flexible sensors can not only be used to detect human activities and monitor vital signs such as blood pressure and pulse, but also to detect temperature, humidity and chemical concentration, so as to achieve early diagnosis and prevention of diseases and achieve the purpose of monitoring human health (Figure 3)[50]. According to the different sensing functions, several graphene-based single-function flexible sensors are introduced below.

4.1 Graphene-based flexible pressure transducer

Graphene-based piezoresistive sensor is the most widely studied pressure sensor at present, and the resistance of graphene changes due to the deformation of the sensitive layer of the sensor under pressure. The deformation of a single graphene sheet and the contact between graphene sheets can cause resistance changes, in which the sharp change of contact resistance on the surface of the material is the key to obtain high sensing performance. The performance of piezoresistive pressure sensors can be improved by constructing porous structures, which is proved by the good pressure sensing ability of three-dimensional porous graphene structures such as foam, sponge, aerogel and hydrogel as flexible pressure sensors[51][52][53][42]. The three-dimensional network graphene ultrasensitive pressure sensor prepared by Lv et al. Has excellent compression characteristics, high stability and deformability, and the pressure sensitivity at low pressure is 229.8 kPa-1, which is the highest among piezoresistive graphene-based sensors at present[42]. Three-dimensional graphene porous structures with specific structures can also be constructed by template-directed self-assembly, such as the development of graphene-wrapped sponge composites with discontinuous microstructures using polyurethane templates. The change of contact area under compression causes a significant change in resistance, which improves the piezoresistive sensitivity of the material[51][52,54,55][52]. At present, most pressure sensors can not have high sensitivity and wide working range at the same time. Dong et al. Used graphene coating to prepare flexible pressure sensors with polyaniline nanowires wrapped in sponge.It combines the good conductivity of graphene, the large contact area of polyaniline nanowires and the excellent compression characteristics of sponge, which can not only monitor small physiological activities, but also be used to detect human movement in real time[54][54]. It has fast response (about 96 ms) in the working range of 0 ~ 27 kPa, adjustable sensitivity (0.042~0.152 kPa-1), good repeatability (about 9000 cycles) and stable signal waveform output. Similarly, the paper-based graphene pressure sensor reported by Tao et al. Also has high sensitivity in the pressure range of 0 – 20 kPa, and can achieve ultra-high sensitivity (17.2 kPa-1) at 0 – 2 kPa, which can be used to sense wrist pulse, speech, breathing and movement[50][50].
The piezoelectric effect of intrinsic graphene is limited by the lattice distortion, and the threshold deformation exceeding 20% will lead to the change of electronic energy band and conductivity[56]. Chen et al. Reported a piezoelectric-induced sensor based on a PbTiO3 nanowire/graphene heterojunction to achieve fast static pressure measurement, which has been used to monitor the human radial artery[56]. Researchers have also studied capacitive graphene-based pressure sensors, such as the capacitive sensor composed of single-layer graphene electrodes proposed by Pyo et al., which shows high mechanical flexibility and optical transparency, as well as high pressure sensitivity (6.55%kPa-1), fast response (about 70 ms) and high stability[57]. The graphene capacitive touch sensor proposed by Kang et al. Can perform multi-touch and three-dimensional sensing under high deformation, and has good extensibility and sensing ability when installed on deformable human body parts[58]. In order to solve the problem of low sensitivity of capacitive pressure sensor, it is found that the microstructure graphene electrode structure can not only greatly improve the sensitivity of capacitive pressure sensor, but also the sensitivity is adjustable[59].

4.2 Graphene-based flexible strain sensor

The sensitivity of the flexible sensor to strain can be expressed by the Gauge factor (GF) shown in Equation 2:
G F = ( R g - R 0 ) / R 0 ε = Δ R / R 0 ε
Where R0 is the resistance of the material in the initial state, Rε is the resistance of the material when the strain is applied, and ε is the deformation of the material. Under tensile strain, the structure of graphene will be partially deformed, resulting in a shift of the electronic energy band and a change in resistance, making graphene an excellent piezoresistive strain sensing material[60].
Graphene prepared by different methods has different morphologies, among which fibrous graphene has flexibility and biocompatibility, and can fit the human body well, such as the preparation of graphene core/polyvinyl chloride shell fiber by chemical vapor deposition or the assembly of graphene coating layer by layer on polyurethane[61][62]. Under tensile and bending strains, the graphene layer produces microcracks that are capable of enhancing the sensitivity of the material. The strain sensor with high GF can be fabricated by introducing defects to connect graphene sheets to form a conductive network[63]. Under the action of tensile and compressive strain, the deformation of a single graphene sheet will change its own resistivity, causing the resistance of the whole conductive network to change[63]. However, the strain response of the graphene network mainly depends on the contact resistance between adjacent graphene sheets[64]. As shown in Fig. 4, after applying tensile and compressive strain on the graphene film, the overlapping area between adjacent graphene layers will become smaller or larger, which will cause the resistance change[63]. The introduction of polymers containing appropriate functional groups can improve the mechanical properties of graphene strain sensors. The composite film prepared by Liang et al. By combining graphene oxide, γ-polyglutamic acid and calcium ions has a high ultimate stress (150 ± 51.0 MPa) and excellent Young's modulus (21.4 ± 8.7 GPa), which are 120% and 70% higher than those of pure graphene oxide film, respectively[65].
Graphene with three-dimensional network structures such as foam, hydrogel, aerogel, and sponge can also be used to fabricate high-performance stretchable strain sensors[66,67][68][69,70][71]. Pang et al. Fabricated a graphene aerogel strain sensor by hydroplastic foaming method, which can achieve high GF (about 2) and ultra-stable strain range (0% ~ 95%) at the same time[70]. Graphene foam-polydimethylsiloxane strain sensor fabricated by chemical vapor deposition is highly sensitive to bending or tensile deformation[72]. Studies have found that such sensors can be stretched to 30% of their original length and can monitor the bending of human fingers and elbow joint movements[73]. Graphene has also been used as a conductive nanofiller for elastic polymers, such as natural rubber and polyurethane, to form a conductive skeleton for nanocomposite sensors[74⇓~76]. Compared with carbon nanotubes, graphene has higher strain sensitivity, but its stretchability is not as good as that of carbon nanotubes[64]. Monolayer and multilayer graphene can only be stretched in a very limited range, which is not enough to withstand a wide range of deformation[77,78]. Dong et al. used a two-step chemical deposition method to organically combine three-dimensional graphene foam and carbon nanotubes to prepare an all-carbon synergistic permeable network stress-strain sensor as shown in Figure 5, which showed a significantly enhanced scalability range, from 6% of the inherent graphene to 85% of the synergistic permeable network and a high sensitivity with a GF of 35, and a stable response with almost no noise[79][79]. Wang et al. Reported a double-layer self-adhesive sensor with graphene and carbon nanotubes as the sensing layer and waterborne polyurethane as the dry adhesive layer, which can conform to the skin, has higher sensitivity and reliability, lower noise, and can detect motion in two perpendicular directions[80][80].

4.3 Graphene-based flexible humidity sensor

Humidity sensing is to convert the number of water molecules in the environment into measurable signals for the purpose of detection[81]. As shown in Fig. 6 (a), Smith et al. Found that when the ambient humidity changes, the resistance of the graphene sensor also changes accordingly[47]. Fig. 6 (B) is a density functional theory simulation of the sensitivity of graphene devices to water molecules. Due to the interaction between the electrostatic dipole moment of water and the impurity band in the substrate, the electrostatic doping of the graphene layer makes the resistive graphene humidity sensor have a high humidity sensitivity[47]. When graphene is exposed to moisture, the band gap increases with the number of adsorbed water molecules, and the resistivity of graphene also increases[82]. The adsorption of water molecules on the defect sites of graphene will also lead to different changes in resistance[48].
The abundant oxygen-containing functional groups on the surface of graphene oxide provide a large number of humidity-responsive active sites, which are highly sensitive to proton conduction of water molecules. The graphene oxide humidity sensor senses by detecting capacitance or impedance signals according to the change of proton conductivity[83,84]. Bi et al. Constructed the graphene oxide-based humidity sensor shown in Fig. 7 (a) by depositing graphene oxide on micro-scale crossed electrodes, and found that the sensor showed ultra-high sensitivity in different humidity ranges[85]. As shown in fig. 7 (B), the adsorption of water molecules on the graphene oxide film is divided into two processes: the first layer of water molecules is attached to the graphene oxide film through two hydrogen bonds; From the second layer, water molecules are adsorbed by only one hydrogen bond[85]. A first layer of physical adsorption is formed at a low relative humidity, and water molecules are attached to oxidized groups and vacancies on the surface of the graphene oxide, so that the dielectric constant and the capacitance of the graphene oxide film are increased, and high sensitivity can be obtained; With the increase of relative humidity, multilayer physical adsorption occurs, and the number of water molecules adsorbed on the double hydrogen-bonded water layer increases, which enhances the proton conductivity of the membrane and leads to more sensitivity to water molecules at high relative humidity[85].
Reducing graphene oxide is beneficial to shorten the response/recovery time, and partially reduced graphene oxide also shows some capacitive behavior[86]. Lee et al. Prepared a flexible humidity sensor by compounding graphene on a polyurethane substrate, with a measurement humidity range of 10% ~ 70%, which can meet the requirements of monitoring human skin humidity and environmental humidity at the same time[87]. Kim et al. Used platinum modified nano-n-type doped graphene for humidity sensing[88]. Other carbon materials, such as carbon nanotubes, nanodiamonds, or fullerenes, can be introduced into the graphene oxide film as intercalation to expand the graphene oxide film and improve water molecule diffusion[89,90]. The introduction of hygroscopic or hydrophilic components, such as cellulose, protonated polyethyleneimine, polyethylene oxide, polyaniline, tin dioxide, and zinc oxide, or graphene films by direct mixing or layer-by-layer assembly can provide more active sites to adsorb water molecules and improve the humidity sensing performance[91,92][93][94][95][96].

4.4 Graphene-based flexible temperature sensor

Skin is not only capable of sensing mechanical stimuli, but temperature sensing is also an important aspect of tactile perception. As a wearable sensing device, it is also necessary to detect diseases such as fever, heatstroke and infection, and continuously monitor the temperature change of the human body to indicate the physiological state of the human body.
Temperature sensors can be prepared by thermistor, thermoelectric effect or optical means, among which thermistor is the most common. According to the increase or decrease of resistance with temperature, it can be divided into positive temperature coefficient and negative temperature coefficient. Graphene has positive temperature coefficient, and its resistance increases with temperature. Trung et al. Developed a flexible field effect transistor temperature sensor as shown in Figure 8A by reducing graphene oxide on a polymer substrate[97]. The sensor has a high temperature response capability in the temperature range of 30 ~ 80 ℃, and can detect a small temperature change of 0.1 ℃. However, such sensors are limited by the stretching ability of graphene, and the temperature response ability is still relatively poor. To solve this problem, Yang et al. Reported a wearable temperature sensor constructed by graphene nanosheets vertically on a polydimethylsiloxane substrate as shown in Figure 8B. The positive temperature coefficient of the sensor is three times higher than that of conventional similar products[45]. During the heating process as shown in fig. 8C, the polydimethylsiloxane substrate expands radially, and longer conductive channels are formed between the graphene nanowalls; After cooling, the conductive channel returns to its original state, which has fast response, recovery speed and stability, and can monitor the body temperature in real time[45].

4.5 Other Single Function Graphene Based Flexible Sensors

The adsorption of a single chemical or biomolecule on the surface of graphene can locally deform and cause charge or energy transfer to change the electronic and optical properties of graphene, which makes it play an important role in the field of chemical and biological sensing[98]. Therefore, the application range of graphene in single-function flexible sensors is also gradually expanding[98].

4.5.1 Graphene-based flexible chemical sensor

Electrochemical sensing of small biomolecules such as dopamine, ascorbic acid and uric acid by graphene is also one of its important applications[99]. Papakonstantinou et al. Were the first to use graphene for electrochemical sensing, and they grew multilayer graphene on a silica substrate to obtain a sheet film with excellent performance in detecting dopamine, ascorbic acid, and uric acid[100]. Graphene electrochemical sensors can also be used to detect heavy metal ions, ethanol industrial compounds, hydrogen peroxide and pH[101,102][103][104⇓~106][107]. The three-dimensional graphene-carbon nanotube hybrid prepared by Dong et al. Through chemical vapor deposition has high sensitivity of 470.7 mA·L·mol-1·cm-2 and low detection limit of 20 nmol·L-1 for electrochemical detection of dopamine[104]; After the modification of peroxidase and Nafion, the detection of hydrogen peroxide has high sensitivity (137.9 mA·L·mol-1·cm-2), low detection limit (1μmol·L-1) and wide linear detection range (10μmol·L-1~1 mmol·L-1). The hydrogen peroxide membrane sensor prepared by Xu et al. Using graphene composite chitosan containing hemoglobin molecules had a detection limit of 0.51μmol·L-1 and a linear range of 6.5~230μmol·L-1[105]. Compared with enzyme-based biosensors, non-enzymatic hydrogen peroxide sensors using metal nanoparticles, metal oxides or alloys as electrocatalysts have higher stability, stronger flexibility and lower cost[106]. The non-enzymatic hydrogen peroxide sensor prepared by Dong et al. Using silver modified graphene has fast amperometric sensing, low detection limit, wide linear response range and perfect selectivity for non-enzymatic hydrogen peroxide detection[106]. de Ohno et al. Studied the pH sensing ability of mechanically exfoliated graphene, which can measure the pH change of solution with a detection limit of 0.025[107]. Fig. 9 shows the preparation process of polydiacetylene/graphene composite film, the molecular structure formed by self-assembly, and the photos after exposure to different organic vapors. The sensor is sensitive to organic vapors such as methanol, chloroform, tetrahydrofuran and N, N-dimethylformamide with a concentration of 0.01%, and has different color changes when interacting with different volatile organic compounds[108]. Bisphenol A is one of the most harmful industrial chemicals to the environment and human health.Zou et al. Developed a β-cyclodextrin functionalized graphene/platinum nanoparticle electrochemical sensor to detect bisphenol A, and the oxidation peak current of bisphenol A increased linearly with the detection concentration in the range of 50 nmol·L-1~80μmol·L-1, with a detection limit of 15 nmol·L-1[109]. The sensor has high sensitivity, good stability and wide linear range.

4.5.2 Graphene-based flexible biosensor

Graphene-based flexible sensors can also detect human biomarkers such as glucose, lactate, sodium and calcium, and the simple and rapid determination of glucose is of great significance in the diagnosis of diabetes[110⇓~112][113,114]. The current response of the glucose biosensor prepared by the titanium dioxide/graphene composite changed linearly under the condition of glucose concentration of 0~8 mmol·L-1, and the highest sensitivity was about 6.2 mA·L·mmol-1·cm2[113]. Most glucose biosensors use glucose oxidase to catalyze glucose into gluconic acid and hydrogen peroxide to identify glucose molecules quickly and accurately.However, the enzyme activity is easily affected by temperature, pH and humidity. At present, the development of non-enzymatic glucose sensors using metal nanoparticles, metal oxides or alloys as electrocatalysts has attracted wide attention[114]. Dong et al. Used nickel (II) hydroxide/three-dimensional graphene foam composite to prepare a non-enzymatic glucose electrochemical electrode. Due to the synergistic effect of the high electrocatalytic activity of nickel (II) hydroxide nanosheets and the high conductivity and large specific surface area of three-dimensional graphene,The fabricated sensor has a high sensitivity of 2.65 mA·L·mmol-1·cm-2, a low detection limit of 0.34μmol·L-1, and excellent selectivity with a linear response range of 1μmol·L-1~1.17 mmol·L-1[114].
The mixture of protein and graphene oxide can maintain structural integrity and biological activity, which indicates the potential application of graphene oxide/protein complex in biosensors[115]. It is reported that the stacked graphene nanofibers have obvious oxidation reactions to adenine, guanine, cytosine and thymine, and can be used for direct label-free sensitive detection related to influenza A[116]. The graphene field effect transistor biosensor as shown in Fig. 10 maintained a highly consistent sensitive detection of the representative inflammatory cytokine IFN-γ in undiluted human sweat under different conditions, with a detection range of 0.015~250 nmol·L-1 and a detection limit as low as 740 fmol · L-1 [117]. Liquid controlled transistor fabricated by chemical vapor deposition growth of graphene film can be used for DNA sensing.Graphene transistor immobilized with probe DNA is sensitive to complementary DNA as low as 0.01 nmol·L-1 and has the ability to distinguish single group mismatch.The upper limit of detection can be increased from 10 nmol·L-1 to 500 nmol · L by modifying graphene with gold nanoparticles-1[118].

4.5.3 Graphene-based flexible gas sensor

Ideal graphene has a strong gas adsorption ability, and mechanically exfoliated graphene can even sense the adsorption of a single gas molecule[119,120]. The structural design and optimization of graphene can obtain better adsorption gas and detection sensitivity[121,122]. Theoretical studies have shown that the adsorption of different gas molecules on the graphene surface will introduce doping States[123,124]. Common gas molecules such as ammonia, carbon monoxide and ethanol molecules act as electron donors for graphene, while other molecules such as nitrogen dioxide, water, oxygen and iodine act as electron acceptors[119]. If the residual oxygen-containing groups on the surface of graphene are electron-withdrawing, the adsorption of reducing gases will lead to the depletion of holes in the valence band, thus reducing the conductivity of graphene. On the contrary, the adsorption of oxidizing gases leads to an increase in the hole concentration and conductivity of graphene[125,126]. In addition, modification of graphene with functional groups containing lone pair electrons (such as ethylenediamine or sulfonate) can selectively adsorb electron-withdrawing gases[127]. The nitrogen dioxide sensor prepared by silver nanoparticles modified sulfonated graphene has high sensitivity and fast response and recovery characteristics in the concentration range of 0. 5 ~ 50 ppm, and the sensitivity is 74. 6% after exposure to 50 ppm nitrogen dioxide, the response time is 12 s, and the recovery time is 20 s, which is completely opposite to the effect of exposure to ammonia[128].
Different kinds of gas molecules can be adsorbed on the surface of graphene, which affects its electronic structure, resulting in the inability of graphene-based gas sensors to selectively identify specific gas molecules, which will certainly limit their practical application. It is found that the selectivity of gas molecules can be improved by compounding graphene with other functional materials. For example, conductive polymers (such as polyaniline, polypyrrole, and polythiophene) have strong electrochemical or acid-base interactions with various gases, and the adsorption of oxidizing or reducing gas molecules can cause doping or de-doping of graphene-conductive polymer composite components, which can enhance the sensitivity of the material to specific gas molecules[129⇓~131]. Graphene decorated with palladium or platinum noble metal nanoparticles exhibits significant sensitivity to hydrogen molecules[132,133]. Metal oxide nanoparticles such as zinc oxide, tin dioxide, and tungsten trioxide, as n-type semiconductors, can form p-n heterojunctions with p-type graphene, which contributes to electron transfer and enables the composite to detect gases at low temperatures[134⇓~136].

5 Graphene based multifunctional flexible sensor

In order to meet the needs of commercialization, graphene-based flexible sensors are needed to improve the sensing performance and achieve multi-functional sensing. Several graphene-based multifunctional flexible sensors are described below.

5.1 Pressure/strain transducer

Most graphene-based pressure/strain sensors are piezoresistive sensors, and the use of graphene foam for the preparation of stretchable flexible pressure/strain sensors has attracted much attention[70]. Graphene mechanical sensors with high elastic foam structure can have both pressure and strain sensing characteristics, and show high sensitivity and adjustable measurement range under different thicknesses[137].
Commonly used pressure/strain flexible sensors are composed of conductive materials and flexible polymer substrates with excellent mechanical properties[138,139]. Pang et al. demonstrated a mechanical sensor using porous graphene network combined with polydimethylsiloxane as shown in Fig. 11, which can realize pressure and strain sensing at the same time, and can identify States including walking, finger bending and wrist blood pressure, showing a pressure sensing range of up to 2000 kPa and a strain sensitivity of GF up to 8.5[140]. The stretchable and ultrasensitive strain sensor prepared from graphene and polydimethylsiloxane composite elastomer also shows a wide detection range (about 50%) and high sensitivity (GF about 630). It shows high selectivity under bending of 180 °, twisting of 90 °, external temperature of 30 ~ 63.5 ℃ and tensile strain caused by different downward pressures[69].

5.2 Pressure/humidity/temperature sensor

Most temperature and humidity sensors are rigid, and the preparation of flexible sensors that can detect both temperature and humidity is still an unsolved problem. Wang et al. Proposed a multi-tactile sensor composed of hydrophobic film and graphene/polydimethylsiloxane sponge, which can synchronously detect pressure, temperature and humidity[141]. The high temperature detection resolution and pressure sensing sensitivity of the device are 1 K and 15.22 kPa-1, respectively, with a response time of 74 ms and a high stability after 3000 cycles. Ho et al. Reported a fully transparent multifunctional electronic skin sensor matrix with graphene deposited on polydimethylsiloxane by chemical vapor deposition and sprayed with graphene as shown in fig. 12, which has the function of triple sensing of pressure, temperature and humidity[142]. The most important thing is that each sensor is only sensitive to the external stimulus of its target and is not disturbed by the other two stimuli[142].

5.3 Strain/humidity/temperature sensor

The adoption of versatile graphene derivatives in wearable sensing devices paves the way for the realization of multifunctional sensors. The flexible temperature and humidity sensor constructed by chemical vapor deposition of graphene microstrips shows ultra-sensitivity, and the deformation range is 2% ~ 30%. The substrate, the aspect ratio of graphene microstrip and the oxygen plasma treatment time have a great influence on the sensitivity of temperature sensing, and the network structure of the material and the humidity sensitivity of cellulose acetate and cellulose butyrate ensure the good performance of humidity sensing[143]. Zhang et al. Reported a multifunctional electronic tattoo prepared with a mixture of silk and graphene, with an increase in GF from 34 to 470 at a high strain of 70% – 90%, a sensitivity of about 2.09%℃-1 in the temperature range of 20 – 50 ° C, and a rapid and stable humidity sensing in the humidity range of 11.3% – 85.1%, which can be used to detect the activity of human skin and monitor vital States such as electrocardiogram, respiration, and body temperature[144].

5.4 Pressure/strain/humidity/temperature sensor

Graphene has obvious response to pressure, strain, temperature, humidity and other stimuli, and the response to the four stimuli can be achieved by doping other functional materials to design and optimize the sensing function of graphene. Chen et al. Prepared a cellulose/graphene composite membrane, which can sense and detect the resistance changes caused by different stimuli such as pressure, strain, temperature, humidity and liquid[145]. Liu et al. Reported a multi-modal sensor composed of graphene/carbon black/cellulose as shown in Fig. 13, which uses the current response of multiple stimuli such as pressure and temperature, pressure and strain, and strain and humidity to achieve sensing[146]. The sensor has a sensitivity of 0.59%kPa-1, 0.09%kPa-1 in the pressure range of 0 – 50 kPa, 50 – 250 kPa, and a GF of 14.6, 1.8 in compression and tension, respectively, and can monitor the strain behavior such as finger and elbow bending. The sensor is also sensitive to temperature and humidity, and the sensitivity is 0.6%℃-1 when the temperature increases from 20 ℃ to 60 ℃. The humidity sensing property of cellulose also enhances the humidity sensing performance of the sensor, and the current is rapidly reduced from about 2.86 mA to 2.63 mA during the blowing process of 0.6 s, which has the ability of real-time response.

5.5 Other graphene-based multifunctional flexible sensors

In addition to the above graphene-based multifunctional flexible sensors, graphene-based flexible sensors also play an important sensing role in other fields by combining graphene with other materials and increasingly advanced device preparation technologies. Among them, the stability of graphene-based flexible sensors is also an important indicator. Sensitivity to stimuli and stability seem to be contradictory, but this is not the case. The stimulus can be natural or from the human body, and the stability mainly depends on whether the performance of the sensor can be maintained for a long time or completely reversible. Generally, the stability is indirectly characterized by the number of cycles, and even disposable degradable sensors are needed in certain fields, so the stability depends on the use and the type of stimulus. Qu et al. Prepared a multimodal graphene-based flexible sensor based on graphite-carbon nitride wrapped graphene double helix fiber structure, and the sensing performance of the sensor for humidity, temperature and mechanical motion remained basically unchanged after more than 1000 cycles[147]. Due to the limited space of this article, it is impossible for us to cover all aspects. Readers who are interested in this aspect can refer to [1, 148, 149] for more in-depth understanding.

6 Conclusion and prospect

Large area controllable preparation of graphene is still a key in the future development of graphene-based flexible sensors. In order to obtain high-performance graphene-based flexible sensors, the high performance of graphene must be guaranteed, and the modification, assembly and preparation of materials are still the focus of attention in the future. It is also a great challenge for state-of-the-art graphene-based flexible sensors to have high sensitivity, wide detection range and good mechanical properties at the same time. In the future, the sensitivity of graphene can be improved by optimizing the morphology and structure of graphene. In addition, the sensing performance of graphene sensors can also be optimized by developing new flexible and stretchable substrate materials, combining with organic materials, and developing and utilizing new materials.
Graphene sensors may not be able to distinguish each stimulus under a variety of stimuli, which also hinders the wide application of graphene-based multifunctional sensors. At present, most of the studies can only achieve one or several functions at the same time, so it is urgent to study a new strategy to integrate the multiple sensing functions of graphene. It will be an inevitable trend for future research to combine a variety of different sensing mechanisms to construct new graphene-based multifunctional sensors. According to the specific application objectives, the application of graphene flexible sensors in real life also requires the following special functions:
(1) Self-repairing function. As a wearable device, flexible sensors will inevitably be subjected to long-term repeated mechanical action, so there will be wear and tear in the use process, which will seriously affect the stability and repeatability of the sensor. Therefore, it is particularly important for the practical application of sensors to have the self-repairing ability similar to human skin.
(2) Self-powered function. Flexible wearable sensors need power supply and input system to provide energy and command information in order to detect human motion state or body signals and feed back these stimulation signals in time. However, due to the huge size of traditional batteries, they can not be bent or stretched, and are difficult to be applied to wearable devices. Therefore, there is an urgent need to develop sensor-compatible flexible energy storage devices that continuously supply power while withstanding mechanical strain[150].
(3) Self-cleaning function. The self-cleaning function mainly depends on the excellent hydrophobic properties of the material surface, which can resist the potential pollution of the surrounding environment, thus avoiding the degradation and failure of the performance. Therefore, self-cleaning can be achieved by building a superhydrophobic surface on the flexible sensor to overcome the contamination problem.
(4) Degradable function. The wide application of smart devices will inevitably lead to various environmental pollution problems, and how to effectively solve the electronic pollution is also a major challenge, so the development of degradable flexible sensing devices has become a new hot spot. To avoid electronic pollution, researchers have developed paper-based graphene flexible sensors that degrade naturally without polluting the environment and can be recycled[151].
In the future, graphene sensors are expected to be combined with modern digital equipment to transmit data in real time using wireless communication to ensure the reliability and high performance of the equipment. It will not be a dream to connect graphene-based flexible sensors with skin-connected smart devices to achieve real-time detection of limb activity and real-time monitoring of human physiological signals, and to achieve Avatar-style human-computer interaction. In addition, due to the high cost of wearable flexible sensors, they are mainly used in the medical field. Large-scale production also requires the development of new low-cost technologies for early commercialization.

References

Publishing order | Descend order by publishing year | Descend order by cited within
[1]

Miao P, Wang J, Zhang C C, Sun M Y, Cheng S S, Liu H. Nano Micro Lett., 2019, 11(1): 1.
[2]

Novoselov K S, Geim A K, Morozov S V, Jiang D, Zhang Y, Dubonos S V, Grigorieva I V, Firsov A A. Science, 2004, 306(5696): 666.
[3]

Geim A K. Science, 2009, 324(5934): 1530.
[4]

Huang H J, Zhang J, Jiang L, Zang Z G. J. Alloys Compd., 2017, 718: 112.
[5]

Huo Q S, Jin J Q, Wang X Q, Lu S W, Zhang Y W, Ma J C, Wang S. Mater. Res. Express, 2019, 6(7): 075613.
[6]

Le K, Wang Z, Wang F L, Wang Q, Shao Q, Murugadoss V, Wu S D, Liu W, Liu J R, Gao Q, Guo Z H. Dalton Trans., 2019, 48(16): 5193.
[7]

Huang X S, Yin R, Qian L, Zhao W, Liu H, Liu C T, Fan J C, Hou H, Zhang J X, Guo Z H. Ceram. Int., 2019, 45(14): 17784.
[8]

Zheng Q B, Lee J H, Shen X, Chen X D, Kim J K. Mater. Today, 2020, 36: 158.
[9]

Zang Y P, Zhang F J, Di C A, Zhu D B. Mater. Horiz., 2015, 2(2): 140.
[10]

Shin S H, Ji S, Choi S, Pyo K H, An B W, Park J, Kim J, Kim J Y, Lee K S, Kwon S Y, Heo J, Park B G, Park J U. Nat. Commun., 2017, 8(1): 1.
[11]

Cai Y C, Huang W, Dong X C. Chin Sci Bull, 2017, 62(7): 635.
[12]

(蔡依晨, 黄维, 董晓臣. 科学通报, 2017, 62(7): 635.
[13]

Xu M X. Doctoral Dissertation of University of Science and Technology Beijing, 2018.
[14]

(徐旻轩. 北京科技大学博士论文, 2018.).
[15]

Hammock M L, Chortos A, Tee B C K, Tok J B H, Bao Z N. Adv. Mater., 2013, 25(42): 5997.
[16]

Wang Z L. Adv. Mater., 2012, 24(34): 4632.
[17]

Zhao S, Zhu R. Acta Chim. Sinica, 2019, 77(12): 1250.
[18]

Li L Q, Gao P, Baumgarten M, Müllen K, Lu N, Fuchs H, Chi L F. Adv. Mater., 2013, 25(25): 3419.
[19]

Ren X C, Pei K, Peng B Y, Zhang Z C, Wang Z R, Wang X Y, Chan P K L. Adv. Mater., 2016, 28(24): 4832.
[20]

Kang B S, Kim J, Jang S, Ren F, Johnson J W, Therrien R J, Rajagopal P, Roberts J C, Piner E L, Linthicum K J, Chu S N G, Baik K, Gila B P, Abernathy C R, Pearton S J. Appl. Phys. Lett., 2005, 86(25): 253502.
[21]

Sun Q J, Kim D H, Park S S, Lee N Y, Zhang Y, Lee J H, Cho K, Cho J H. Adv. Mater., 2014, 26(27): 4735.
[22]

Lin P, Yan F. Adv. Mater., 2012, 24(1): 34.
[23]

Castro Neto A H, Guinea F, Peres N M R, Novoselov K S, Geim A K. Rev. Mod. Phys., 2009, 81(1): 109.
[24]

He Q Y, Sudibya H G, Yin Z Y, Wu S X, Li H, Boey F, Huang W, Chen P, Zhang H. ACS Nano, 2010, 4(6): 3201.
[25]

Yu C M. Doctoral Dissertation of Shaanxi Normal University, 2015.
[26]

(鱼春萌. 陕西师范大学博士论文, 2015.).
[27]

Zheng Q B, Li Z G, Yang J H, Kim J K. Prog. Mater. Sci., 2014, 64: 200.
[28]

Zhao G K, Li X M, Huang M R, Zhen Z, Zhong Y J, Chen Q, Zhao X L, He Y J, Hu R R, Yang T T, Zhang R J, Li C L, Kong J, Xu J B, Ruoff R S, Zhu H W. Chem. Soc. Rev., 2017, 46(15): 4417.
[29]

Zheng Y Q, Wang H, Hou S F, Xia D Y. Adv. Mater. Technol., 2017, 2(5): 1600237.
[30]

Park S, Ruoff R S. Nat. Nanotechnol., 2009, 4(4): 217.
[31]

Schniepp H C, Li J L, McAllister M J, Sai H, Herrera-Alonso M, Adamson D H, Prud’Homme R K, Car R, Saville D A, Aksay I A. J. Phys. Chem. B, 2006, 110(17): 8535.
[32]

Tour J M. Chem. Mater., 2014, 26(1): 163.
[33]

Bai H, Li C, Shi G Q. Adv. Mater., 2011, 23(9): 1089.
[34]

Jiang H J, Mao B X. Chin. J. Inorg. Chem., 2013, 29(11): 2305.
[35]

(姜鸿基, 毛炳雪. 无机化学学报, 2013, 29(11): 2305.)
[36]

Stankovich S, Dikin D A, Piner R D, Kohlhaas K A, Kleinhammes A, Jia Y Y, Wu Y, Nguyen S T, Ruoff R S. Carbon, 2007, 45(7): 1558.
[37]

Bai H, Li C, Shi G Q. Adv. Mater., 2011, 23(9): 1089.
[38]

Singh E, Meyyappan M, Nalwa H S. ACS Appl. Mater. Interfaces, 2017, 9(40): 34544.
[39]

Fu W Y, Jiang L, van Geest E P, Lima L M C, Schneider G F. Adv. Mater., 2017, 29(6): 1603610.
[40]

Suvarnaphaet P, Pechprasarn S. Sensors, 2017, 17(10): 2161.
[41]

Tan R K L, Reeves S P, Hashemi N, Thomas D G, Kavak E, Montazami R, Hashemi N N. J. Mater. Chem. A, 2017, 5(34): 17777.
[42]

Yang H G, Xue T Y, Li F Y, Liu W T, Song Y L. Adv. Mater. Technol., 2018: 1800574.
[43]

Chen K, Gao W, Emaminejad S, Kiriya D, Ota H, Nyein H Y Y, Takei K, Javey A. Adv. Mater., 2016, 28(22): 4397.
[44]

Torrisi F, Carey T. Nano Today, 2018, 23: 73.
[45]

Yao B, Zhang J, Kou T Y, Song Y, Liu T, Li Y. Adv. Sci., 2017, 4(7): 1700107.
[46]

Lv L, Zhang P P, Xu T, Qu L T. ACS Appl. Mater. Interfaces, 2017, 9(27): 22885.
[47]

Wang Y, Wang L, Yang T T, Li X, Zang X B, Zhu M, Wang K L, Wu D H, Zhu H W. Adv. Funct. Mater., 2014, 24(29): 4666.
[48]

Yang T T, Jiang X, Zhong Y J, Zhao X L, Lin S Y, Li J, Li X M, Xu J L, Li Z H, Zhu H W. ACS Sens., 2017, 2(7): 967.
[49]

Yang J, Wei D P, Tang L L, Song X F, Luo W, Chu J, Gao T P, Shi H F, Du C L. RSC Adv., 2015, 5(32): 25609.
[50]

Hong S Y, Lee Y H, Park H, Jin S W, Jeong Y R, Yun J, You I, Zi G, Ha J S. Adv. Mater., 2016, 28(5): 930.
[51]

Smith A D, Elgammal K, Niklaus F, Delin A N, Fischer A C, Vaziri S, Forsberg F, Råsander M, Hugosson H, Bergqvist L, Schröder S, Kataria S, Östling M, Lemme M C. Nanoscale, 2015, 7(45): 19099.
[52]

Popov V I, Nikolaev D V, Timofeev V B, Smagulova S A, Antonova I V. Nanotechnology, 2017, 28(35): 355501.
[53]

Yavari F, Koratkar N. J. Phys. Chem. Lett., 2012, 3(13): 1746.
[54]

Tao L Q, Zhang K N, Tian H, Liu Y, Wang D Y, Chen Y Q, Yang Y, Ren T L. ACS Nano, 2017, 11(9): 8790.
[55]

Samad Y A, Li Y Q, Schiffer A, Alhassan S M, Liao K. Small, 2015, 11(20): 2380.
[56]

Yao H B, Ge J, Wang C F, Wang X, Hu W, Zheng Z J, Ni Y, Yu S H. Adv. Mater., 2013, 25(46): 6692.
[57]

Huang J K, Zeng J B, Liang B Q, Wu J W, Li T G, Li Q, Feng F, Feng Q W, Rood M J, Yan Z F. ACS Appl. Mater. Interfaces, 2020, 12(14): 16822.
[58]

Ge G, Cai Y C, Dong Q C, Zhang Y Z, Shao J J, Huang W, Dong X C. Nanoscale, 2018, 10(21): 10033.
[59]

Zhang X C, Scarpa F, McHale R, Limmack A P, Peng H X. RSC Adv., 2016, 6(83): 80334.
[60]

Chen Z F, Wang Z, Li X M, Lin Y X, Luo N Q, Long M Z, Zhao N, Xu J B. ACS Nano, 2017, 11(5): 4507.
[61]

Pyo S, Choi J, Kim J. Adv. Electron. Mater., 2018, 4(1): 1700427.
[62]

Kang M, Kim J, Jang B, Chae Y, Kim J H, Ahn J H. ACS Nano, 2017, 11(8): 7950.
[63]

Yang J, Luo S, Zhou X, Li J L, Fu J T, Yang W D, Wei D P. ACS Appl. Mater. Interfaces, 2019, 11(16): 14997.
[64]

Shi G, Zhao Z H, Pai J H, Lee I, Zhang L Q, Stevenson C, Ishara K, Zhang R J, Zhu H W, Ma J. Adv. Funct. Mater., 2016, 26(42): 7614.
[65]

Wang X N, Qiu Y F, Cao W W, Hu P G. Chem. Mater., 2015, 27(20): 6969.
[66]

Li X T, Hua T, Xu B G. Carbon, 2017, 118: 686.
[67]

Zhao J, Zhang G Y, Shi D X. Chin. Phys. B, 2013, 22(5): 057701.
[68]

Kim Y J, Cha J Y, Ham H, Huh H, So D S, Kang I. Curr. Appl. Phys., 2011, 11(1): S350.
[69]

Liang K, Spiesz E M, Schmieden D T, Xu A W, Meyer A S, Aubin-Tam M E. ACS Nano, 2020, 14(11): 14731.
[70]

Qin Y Y, Peng Q Y, Ding Y J, Lin Z S, Wang C H, Li Y, Xu F, Li J J, Yuan Y, He X D, Li Y B. ACS Nano, 2015, 9(9): 8933.
[71]

Kim S J, Mondal S, Min B K, Choi C G. ACS Appl. Mater. Interfaces, 2018, 10(42): 36377.
[72]

Jing X, Mi H Y, Peng X F, Turng L S. Carbon, 2018, 136: 63.
[73]

Tang Y C, Zhao Z B, Hu H, Liu Y, Wang X Z, Zhou S K, Qiu J S. ACS Appl. Mater. Interfaces, 2015, 7(49): 27432.
[74]

Pang K, Song X, Xu Z, Liu X T, Liu Y J, Zhong L, Peng Y X, Wang J X, Zhou J Z, Meng F X, Wang J, Gao C. Sci. Adv., 2020, 6(46): eabd4045.
[75]

Sun S B, Liu Y Q, Chang X T, Jiang Y C, Wang D S, Tang C J, He S Y, Wang M W, Guo L, Gao Y. J. Mater. Chem. C, 2020, 8(6): 2074.
[76]

Chen Z P, Ren W C, Gao L B, Liu B L, Pei S F, Cheng H M. Nat. Mater., 2011, 10(6): 424.
[77]

Li J H, Zhao S F, Zeng X L, Huang W P, Gong Z Y, Zhang G P, Sun R, Wong C P. ACS Appl. Mater. Interfaces, 2016, 8(29): 18954.
[78]

Sarker F, Karim N, Afroj S, Koncherry V, Novoselov K S, Potluri P. ACS Appl. Mater. Interfaces, 2018, 10(40): 34502.
[79]

Li W G, Guo J H, Fan D L. Adv. Mater. Technol., 2017, 2(6): 1700070.
[80]

Zhou R, Li P C, Fan Z, Du D H, Ouyang J Y. J. Mater. Chem. C, 2017, 5(6): 1544.
[81]

Kim K S, Zhao Y, Jang H, Lee S Y, Kim J M, Kim K S, Ahn J H, Kim P, Choi J Y, Hong B H. Nature, 2009, 457(7230): 706.
[82]

Yan C Y, Wang J X, Kang W B, Cui M Q, Wang X, Foo C Y, Chee K J, Lee P S. Adv. Mater., 2014, 26(13): 2022.
[83]

Cai Y C, Shen J, Dai Z Y, Zang X X, Dong Q C, Guan G F, Li L J, Huang W, Dong X C. Adv. Mater., 2017, 29(31): 1606411.
[84]

Wang S, Fang Y L, He H, Zhang L, Li C A, Ouyang J Y. Adv. Funct. Mater., 2021, 31(5): 2007495.
[85]

Lv C, Hu C, Luo J H, Liu S, Qiao Y, Zhang Z, Song J F, Shi Y, Cai J G, Watanabe A. Nanomaterials, 2019, 9(3): 422.
[86]

Yavari F, Kritzinger C, Gaire C, Song L, Gulapalli H, Borca-Tasciuc T, Ajayan P M, Koratkar N. Small, 2010, 6(22): 2535.
[87]

Li X Y, Chen X D, Yao Y, Li N, Chen X P, Bi X. IEEE Sens. J., 2013, 13(12): 4749.
[88]

Sun J W, Xie X, Bi H C, Jia H Y, Zhu C Y, Wan N, Huang J Q, Nie M, Li D, Sun L T. Nanotechnology, 2017, 28(13): 134004.
[89]

Bi H C, Yin K B, Xie X, Ji J, Wan S, Sun L T, Terrones M, Dresselhaus M S. Sci. Rep., 2013, 3(1): 1.
[90]

Shojaee M, Nasresfahani S, Dordane M K, Sheikhi M H. Sens. Actuat. A: Phys., 2018, 279: 448.
[91]

Trung T Q, Ramasundaram S, Hwang B U, Lee N E. Adv. Mater., 2016, 28(3): 394.
[92]

Choi S J, Yu H, Jang J S, Kim M H, Kim S J, Jeong H S, Kim I D. Small, 2018, 14(13): 1703934.
[93]

Ding X, Chen X D, Chen X P, Zhao X, Li N. Sens. Actuat. B: Chem., 2018, 266: 534.
[94]

Yao Y, Xue Y J. Sens. Actuat. B: Chem., 2015, 211: 52.
[95]

Tai H L, Zhen Y, Liu C H, Ye Z B, Xie G Z, Du X S, Jiang Y D. Sens. Actuat. B: Chem., 2016, 230: 501.
[96]

Yuan Z, Tai H L, Ye Z B, Liu C H, Xie G Z, Du X S, Jiang Y D. Sens. Actuat. B: Chem., 2016, 234: 145.
[97]

Wang S, Xie G Z, Su Y J, Su L, Zhang Q P, Du H F, Tai H L, Jiang Y D. Sens. Actuat. B: Chem., 2018, 255: 2203.
[98]

Zhang D Z, Wang D Y, Li P, Zhou X Y, Zong X Q, Dong G K. Sens. Actuat. B: Chem., 2018, 255: 1869.
[99]

Zhang D Z, Wang D Y, Zong X Q, Dong G K, Zhang Y. Sens. Actuat. B: Chem., 2018, 262: 531.
[100]

Yuan Z, Tai H L, Bao X H, Liu C H, Ye Z B, Jiang Y D. Mater. Lett., 2016, 174: 28.
[101]

Trung T Q, Ramasundaram S, Hong S W, Lee N E. Adv. Funct. Mater., 2014, 24(22): 3438.
[102]

Jiang H J. Small, 2011, 7(17): 2413.
[103]

Wu S X, He Q Y, Tan C L, Wang Y D, Zhang H. Small, 2013, 9(8): 1160.
[104]

Shang N G, Papakonstantinou P, McMullan M, Chu M, Stamboulis A, Potenza A, Dhesi S S, Marchetto H. Adv. Funct. Mater., 2008, 18(21): 3506.
[105]

Li J, Guo S J, Zhai Y M, Wang E K. Anal. Chimica Acta, 2009, 649(2): 196.
[106]

Li J, Guo S, Zhai Y M, Wang E K. Electrochem. Commun., 2009, 11(5): 1085.
[107]

Shan C S, Yang H F, Han D X, Zhang Q X, Ivaska A, Niu L. Biosens. Bioelectron., 2010, 25(6): 1504.
[108]

Dong X C, Ma Y W, Zhu G Y, Huang Y X, Wang J, Chan-Park M B, Wang L H, Huang W, Chen P. J. Mater. Chem., 2012, 22(33): 17044.
[109]

Xu H F, Dai H, Chen G N. Talanta, 2010, 81(1/2): 334.
[110]

Zhan B B, Liu C B, Shi H X, Li C, Wang L H, Huang W, Dong X C. Appl. Phys. Lett., 2014, 104(24): 243704.
[111]

de Ohno Y, Maehashi K, Matsumoto K. Biosens. Bioelectron., 2010, 26(4): 1727.
[112]

Wang X N, Sun X L, Hu P G, Zhang J, Wang L F, Feng W, Lei S B, Yang B, Cao W W. Adv. Funct. Mater., 2013, 23(48): 6044.
[113]

Zou J F, Liu Z G, Guo Y J, Dong C. Anal. Methods, 2017, 9(1): 134.
[114]

Ohno Y, Maehashi K, Matsumoto K. J. Am. Chem. Soc., 2010, 132(51): 18012.
[115]

Song Y, Luo Y N, Zhu C Z, Li H, Du D, Lin Y H. Biosens. Bioelectron., 2016, 76: 195.
[116]

Shao Y Y, Wang J, Wu H, Liu J, Aksay I, Lin Y H. Electroanalysis, 2010, 22(10): 1027.
[117]

Jang H D, Kim S K, Chang H, Roh K M, Choi J W, Huang J X. Biosens. Bioelectron., 2012, 38(1): 184.
[118]

Zhan B B, Liu C B, Chen H P, Shi H X, Wang L H, Chen P, Huang W, Dong X C. Nanoscale, 2014, 6(13): 7424.
[119]

Fu C L, Yang W S, Chen X, Evans D G. Electrochem. Commun., 2009, 11(5): 997.
[120]

Ambrosi A, Pumera M. Phys. Chem. Chem. Phys., 2010, 12(31): 8943.
[121]

Wang Z R, Hao Z, Wang X J, Huang C, Lin Q, Zhao X Z, Pan Y L. Adv. Funct. Mater., 2021, 31(4): 2170026.
[122]

Dong X C, Shi Y M, Huang W, Chen P, Li L J. Adv. Mater., 2010, 22(14): 1649.
[123]

Schedin F, Geim A K, Morozov S V, Hill E W, Blake P, Katsnelson M I, Novoselov K S. Nat. Mater., 2007, 6(9): 652.
[124]

Yuan W J, Shi G Q. J. Mater. Chem. A, 2013, 1(35): 10078.
[125]

Singh V, Joung D, Zhai L, Das S, Khondaker S I, Seal S. Prog. Mater. Sci., 2011, 56(8): 1178.
[126]

Huang D, Yang Z, Li X L, Zhang L L, Hu J, Su Y J, Hu N T, Yin G L, He D N, Zhang Y F. Nanoscale, 2017, 9(1): 109.
[127]

Huang B, Li Z Y, Liu Z R, Zhou G, Hao S G, Wu J, Gu B L, Duan W H. J. Phys. Chem. C, 2008, 112(35): 13442.
[128]

Leenaerts O, Partoens B, Peeters F M. Phys. Rev. B, 2008, 77(12): 125416.
[129]

Robinson J T, Perkins F K, Snow E S, Wei Z Q, Sheehan P E. Nano Lett., 2008, 8(10): 3137.
[130]

Fowler J D, Allen M J, Tung V C, Yang Y, Kaner R B, Weiller B H. ACS Nano, 2009, 3(2): 301.
[131]

Yuan W J, Liu A R, Huang L, Li C, Shi G Q. Adv. Mater., 2013, 25(5): 766.
[132]

Huang L, Wang Z P, Zhang J K, Pu J L, Lin Y J, Xu S H, Shen L, Chen Q, Shi W Z. ACS Appl. Mater. Interfaces, 2014, 6(10): 7426.
[133]

Al Mashat L, Shin K, Kalantar zadeh K, Plessis J D, Han S H, Kojima R W. J. Phys. Chem. C, 2010, 114(39): 16168.
[134]

Bai H, Sheng K X, Zhang P F, Li C, Shi G Q. J. Mater. Chem., 2011, 21(46): 18653.
[135]

Bai S L, Guo J, Sun J H, Tang P G, Chen A F, Luo R X, Li D Q. Ind. Eng. Chem. Res., 2016, 55(19): 5788.
[136]

Sundaram R S, GÓmez-Navarro C, Balasubramanian K, Burghard M, Kern K. Adv. Mater., 2008, 20(16): 3050.
[137]

Chu B H, Lo C F, Nicolosi J, Chang C Y, Chen V, Strupinski W, Pearton S J, Ren F. Sens. Actuat. B: Chem., 2011, 157(2): 500.
[138]

Yi J, Lee J M, Park W I. Sens. Actuat. B: Chem., 2011, 155(1): 264.
[139]

Song Z L, Wei Z R, Wang B C, Luo Z, Xu S M, Zhang W K, Yu H X, Li M, Huang Z, Zang J F, Yi F, Liu H. Chem. Mater., 2016, 28(4): 1205.
[140]

Choi S J, Choi C, Kim S J, Cho H J, Hakim M, Jeon S, Kim I D. Sci. Rep., 2015, 5(1): 1.
[141]

Pang Y, Yang Z, Han X L, Jian J M, Li Y X, Wang X F, Qiao Y C, Yang Y, Ren T L. ACS Appl. Mater. Interfaces, 2018, 10(50): 44173.
[142]

Wang Z F, Huang Y, Sun J F, Huang Y, Hu H, Jiang R J, Gai W M, Li G M, Zhi C Y. ACS Appl. Mater. Interfaces, 2016, 8(37): 24837.
[143]

Robert C, Feller J F, Castro M. ACS Appl. Mater. Interfaces, 2012, 4(7): 3508.
[144]

Pang Y, Tian H, Tao L Q, Li Y X, Wang X F, Deng N Q, Yang Y, Ren T L. ACS Appl. Mater. Interfaces, 2016, 8(40): 26458.
[145]

Wang Y, Wu H T, Xu L, Zhang H N, Yang Y, Wang Z L. Sci. Adv., 2020, 6(34): abb9083.
[146]

Ho D H, Sun Q J, Kim S Y, Han J T, Kim D H, Cho J H. Adv. Mater., 2016, 28(13): 2601.
[147]

Zhao X L, Long Y, Yang T T, Li J, Zhu H W. ACS Appl. Mater. Interfaces, 2017, 9(35): 30171.
[148]

Wang Q, Ling S J, Liang X P, Wang H M, Lu H J, Zhang Y Y. Adv. Funct. Mater., 2019, 29(16): 1808695.
[149]

Chen Y A, Pötschke P, Pionteck J, Voit B, Qi H S. J. Mater. Chem. A, 2018, 6(17): 7777.
[150]

Liu H B, Xiang H C, Wang Y, Li Z J, Qian L W, Li P, Ma Y C, Zhou H W, Huang W. ACS Appl. Mater. Interfaces, 2019, 11(43): 40613.
[151]

Zhao F, Zhao Y, Cheng H H, Qu L T. Angew. Chem. Int. Ed., 2015, 54(49): 14951.
[152]

Huang X, Yin Z Y, Wu S X, Qi X Y, He Q Y, Zhang Q C, Yan Q Y, Boey F, Zhang H. Small, 2011, 7(14): 1876.
[153]

Zhu W J, Tai G A, Wang X F, Gu Q L, Wu Z X, Zhu K J. Prog. Chem., 2017, 29(11): 1285.
[154]

(朱文杰, 台国安, 王旭峰, 古其林, 伍增辉, 朱孔军. 化学进展, 2017, 29(11): 1285.)
[155]

Wu N, Cheng X F, Zhong Q Z, Zhong J W, Li W B, Wang B, Hu B, Zhou J. Adv. Funct. Mater., 2015, 25(30): 4788.
[156]

Khalifa M, Wuzella G, Lammer H, Mahendran A R. Synth. Met., 2020, 266: 116420.

Funding

Major Basic Research Project of the Ministry of Science and Technology(2012CB933301)

General Program of the National Natural Science Foundation of China(21574068)

Construction Project of Superior Disciplines in Jiangsu Universities(YX03001)

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