Research Article  Open Access
Asar Ali, Adam Khan, Kh. S. Karimov, Amjad Ali, Adnan Daud Khan, "Pressure Sensitive Sensors Based on Carbon Nanotubes, Graphene, and Its Composites", Journal of Nanomaterials, vol. 2018, Article ID 9592610, 12 pages, 2018. https://doi.org/10.1155/2018/9592610
Pressure Sensitive Sensors Based on Carbon Nanotubes, Graphene, and Its Composites
Abstract
Carbon nanotubes (CNTs) and graphene have attracted a great deal of interest due to their outstanding mechanical, optical, electrical, and structural properties. Most of the scientists and researchers have investigated the optical and electrical properties of these materials. However, due to unique electromechanical properties of these materials, it is required to explore the piezoresistive properties of bulk nanostructured CNTs, graphene, and CNTgraphene composites. We investigated and compared the sensitivities and piezoresistive properties of sandwichtype pure CNT, pure graphene, and CNTgraphene composite pressure sensors. For all the samples, increase in pressure from 0 to 0.183 kNm^{−2} results in a decrease in the impedance and direct current (DC) resistance. Sensitivity and percentage decrease in resistance and impedance of CNTgraphene composite were lower than pure CNT while being higher than pure graphene based sample. Moreover, under the same external applied pressure, the sensitivity and percentage decrease in impedance for pure CNT, pure graphene, and CNTgraphene composite were smaller than the corresponding sensitivity and percentage decrease in resistance. The achieved experimental results of the composite sample were compared with simulated results which exhibit reasonable agreement with each other. The deviations of simulated resistancepressure and impedancepressure curves from experimental graphs were 0.029% and 0.105%, respectively.
1. Introduction
The concept of nanomaterials was presented by Herbert Gleiter for the first time over 20 years back. Since then, research interest in the field of nanostructured materials has grown rapidly. The unusual properties, potential applications, and scientific and technological importance of these materials lead them to the current advancement in the sensing technology [1, 2]. Carbon nanotubes (CNTs) and graphene are the two most important representatives of the nanostructural materials [3]. Its density is six times lower than steel. The tensile strength and elasticity of carbon nanotubes (CNTs) are hundred and five times higher than steel, respectively [4]. On the other hand, graphene can withstand with a strain up to 20% and its Young’s modulus is almost six hundred and thousand times higher than semiconductors and metals, respectively [5, 6].
These unique electromechanical properties have made CNTs and graphene the most suitable materials for pressure sensing technology. Therefore, CNTs and graphene have been employed in various electronic devices such as pressure sensors, gas sensor, displacement sensors, strain sensors, temperature sensors, humidity sensors, solar cells, and chemical sensors [7–9]. Pressure sensor is one of the promising sensing elements in the sensing technology. Pressure sensing elements can be used in touch screen devices, automotive industry, aviation, biomedical measurements, and so forth. [10]. Most of the pressure sensors are fabricated on the base of inductive, capacitive, and piezoresistive phenomena that can be employed to control and monitor the pressure in various practical applications [11]. Capacitive pressure sensors show somewhat nonlinear behavior to the input stimuli. Inductive pressure sensors are required complex fabrication techniques because it is difficult to bring the materials into coil shape. Also, leakage of the induced e.m.f. and magnetic flux in the inductive pressure sensors can affect the neighborhood circuitry. Hence, it is difficult to get an accurate response of the inductive pressure sensors. Piezoresistive pressure sensors exhibit outstanding promise for real time applications because of its easy fabrication process, easy signal collection, low cost, and simple device structure [12]. Therefore, a large number of CNTs, graphene, and its compositebased piezoresistive sensing elements have been investigated. Li et al. [13] enhanced the mechanical and piezoresistive properties of graphene by preparing graphene/CNTs hybrid foam (GCFs) by facile selfassembly process. Sahatiya and Badhulika [14] patterned MWCNTs on pencil eraser to develop skin like strain and pressure sensor. The sensitivity and gauge factor of the sensor were 0.135 Mpa^{−1} and 2.4, respectively. Yao et al. demonstrated a high sensitive flexible piezoresistive pressure sensor based on micropatterned films with the layer of carbon nanotubes. The fabricated sensor was applied to measure the pressure of fluid in a curved shaped microtube [15]. Flexible resistive tensile MWCNTs/rubber load sensors were fabricated and investigated by Karimov et al. As the force was increased up to 0.045 N, a 1.37time average increase in the resistance of the sensors was observed [16]. Khan et al. [17] fabricated and characterized a CNTVO_{2} (3fl) composite piezoresistive pressure sensor. A decrease in the sensor resistance with increase in external uniaxial pressure up to 50 kNm^{−2} was observed. Karimov et al. [10] reported CNTCu_{2}O compositebased piezoresistive pressure sensor, and a 3.3fold decrement in DC resistance of the sensor was noted as the pressure increased up to 37 kNm^{−2}. Xue and Cui [18] fabricated SWNT thinfilm transistors on plastic substrates and reported that, with increase in bending of the elastic substrate, the decrement in the resistance of the SWNT thin film was 10 times greater than silicon. Grow et al. [19] investigated piezoresistance of CNTs on deformable thinfilm silicon nitride membranes. The maximum gauge factor () in silicon was 200, while for SGS and semiconducting tubes it was 850 and 400, respectively. Similarly, a large number of graphenebased pressure sensors have been fabricated and investigated [12, 20–30].
To the best of our knowledge, no sandwichtype piezoresistive pressure sensor based on bulk nanostructured CNT, graphene, and CNTgraphene composite is reported to date. CNTgraphene composites may take the benefits of outstanding features of both the CNTs and graphene, such as low weight, high strength, large flexibility, high fracture toughness, and especially high gauge factor that may have a good impact in the field of pressure sensing technology. From practical point of view, it will be useful to investigate the resistancepressure relationships to deepen the knowledge about the physical, electrical, and electromechanical properties of the CNTs, graphene, and its composites.
In this work, instead of focusing on the internal complex structures of CNT and graphene, we explored a novel approach to fabricate sandwichtype pure CNT, pure graphene, and CNTsgraphene compositebased piezoresistive pressure sensors. The term “sandwichtype” is used in the sense that both sides of samples were painted with silver paste (Ag/CNT/Ag, Ag/graphene/Ag, Ag/CNTgraphene/Ag) to provide low resistance electrical contacts. The sensitivities and piezoresistive properties of these sensors were investigated and compared. We believe that this approach will further enhance the practical applications of CNTs, graphene, and its composites in the field of nanomaterial based pressure sensors and other electronic devices.
2. Materials and Experimental Details
2.1. Materials
Graphene and multiwalled carbon nanotubes (MWCNTs) powders were commercially purchased from Sun nanotech Co, Ltd. China. According to the supplier, thickness range and area size of the graphene are 5–20 nm and 10 × 10 μm, respectively. The length and diameter range of multiwalled carbon nanotubes (MWCNTs) are 1–10 μm and 10–35 nm, respectively. The purity of MWCNTs is higher than 90%. No further purification was done in the materials. These materials were used for the sample’s fabrication as received.
2.2. Sample Preparation
Electronic analytical balance (model: ALS , weighing range (max): 220 g, readability (d): 0.1 mg, reproducibility: 0.2 mg, linearity: ±0.2 mg) was used to measure the material amount. Initially, the balance was set to zero by pressing the TARE key and then the materials were weighed accurately. CNT (50 wt.%) and graphene (50 wt.%) powder were blended very carefully by utilizing mortar and pestle to make the composite.
A thick walled stainless steel cylinder, stainless steel movable piston, and well fitted stainless steel plunger were utilized to make the samples. The inner diameter of the cylinder was 15 mm, while the outer diameter of each of the movable piston and plunger was 14.9 mm as shown in Figure 1. The bottom of the cylinder was closed by stainless steel movable piston. The blend of the materials was poured into the cylinder from the top. The top of the thick walled stainless steel cylinder was closed by a plunger that was allowed to move down in the cylinder.
To make a durable sample, the material composite within the cylinder was pressed at a pressure of 353 MPa by using hydraulic press. The pellet with diameter of 15 mm and thickness of 1.5 mm was then ejected from the cylinder as shown in Figure 2.
2.3. Measurements and Setup
To provide low resistance electric contacts, both sides of the pressed tablets were covered by silver paste as shown in Figure 3.
Schematic diagram of Ag/sample/Ag, placed on aluminum support with external uniaxial applied pressure is shown in Figure 4. Silver paste (Ag) is assumed as a part of the pellet and has not been shown in the Figure 4. The aluminum foils are used to act as leads and to avoid scratches on the sample as well.
Figure 5 shows the installment of the sample in experimental setup to investigate its piezoresistive properties. The experimental setup contained the metallic support (a), aluminum support (b), pressure sensitive sensor (pure CNT, pure graphene, and CNTgraphene composite (c)), terminals (d), weight holder (e), and weight (f).
The corresponding conceptual schematic of experimental setup (Figure 5) is depicted in Figure 6. It can be seen from Figure 6 that the piezoresistive pressure element has been placed on aluminum support. The terminals (Al foils) of the sample were connected with the test clips of the MT 4090 LCR Meter. The change in DC resistance of the sensor was noted from the display readings of the MT 4090 LCR Meter. The basic accuracy, ultimate resolution, and measurement range of MT 4090 LCR Meter were 0.2%, 0.001 Ω, and 0.0 Ω to 500 MΩ, respectively.
The pressure value was changed by variation in the weights holding by the weight holder. Weight and weight holder are the major elements of the experimental setup utilized from the typical Cantilever Flexure Frame (Flexor) laboratory setup.
3. Results and Discussion
3.1. Scanning Electron Microscopy
The surface morphology of pure CNT, pure graphene, and CNTgraphene compositebased pellets was examined by scanning electron microscope (SEM, model: JSM 5910, energy: 30 kV, magnification (max): 300,000x, resolution power (max): 2.3 nm, manufacturer: JEOL, Japan). The SEM images of pure CNT, pure graphene, and CNTgraphene compositebased pellets are shown in Figure 7. The scale bar is 5 μm in all images (Figures 7(a)–7(c)). As seen in Figure 7(a), the surface morphology of pure CNTbased sample is not uniform. The CNTs are randomly aligned on the surface of the sample. Some of the CNTs seem to be straight (red arrow) and curved in shape (white arrow), but most of them are even circular in shape (blue arrow), which shows that the carbon nanotubes are flexible in nature. The flexibility of CNTs makes them suitable materials for sensing technology. Figure 7(b) reveals that the rough surface of pure graphenebased sample contains higher porosity and dislocations (green arrows) as compared to the pure CNTbased sample (Figure 7(a)). The higher porosity and dislocations in graphenebased sample cause a higher resistance and hence smaller conductivity than pure CNTbased sample (see Section 3.2). Furthermore, graphene nanosheets seem to be densified under the external applied pressure. It can be seen from Figure 7(b) that most of the graphene nanosheets are aligned parallel to each other, which increases the capacitive effect in the sample. The higher capacitance effect leads to smaller impedance () of the graphene sample. Therefore, the impedance () of graphenebased sample is lower than the other two samples (see Sections 3.3 and 3.4).
(a)
(b)
(c)
It can be observed from Figure 7(c) that CNTs and graphene are not uniformly distributed throughout the composite. Multiple contacts between CNTs and graphene particles can be seen in Figure 7(c). The dimensions of graphene nanoparticles seem to be larger than the dimensions of CNTs nanoparticles. The smaller particle size of CNTs reduces the amount of porosity and dislocations which make the CNTgraphene composite sample more uniform as compared to the pure graphenebased sensor (see Section 3.2).
3.2. ResistancePressure Relationships
The resistancepressure relationships for pure CNT and pure graphenebased pressure sensors are shown in Figure 8. It can be seen from Figure 8 that as the external uniaxial pressure increases from 0 kNm^{−2} to 0.183 kNm^{−2}, the DC resistances of the pure CNT (Figure 8(a)) and pure graphene (Figure 8(b)) pressure sensors decrease from 1.5 kΩ to 0.3 kΩ and from 65 kΩ to 24 kΩ, respectively. This shows 80% and 63.24% decrease in DC resistance for CNT and graphenebased samples, respectively. Thickness of the fabricated sample is a significant factor which affects the overall performance of the sample and has an impact on the resistivity and conductivity of the composite materials [31]. Therefore, it is very important to point out the sample thickness dependence on the external applied pressure. Smaller pressure required to compress and deform the thinner sample and vice versa [32]. Even under a smaller external applied pressure, large increase in charge carrier’s concentration may completely fill the localized energy states present between the HOMOLUMO levels which may lead to larger electrical conductivity and hence smaller resistance of the samples [33]. Furthermore, the external uniaxial applied pressure can be equally transferred to every place throughout the thinner samples. Therefore, under the same external applied pressure, this effect increases the mean coordination number, which leads to a more decrease in the resistance of the thinner sample than the thicker one [34].
(a)
(b)
Resistancepressure relationship for the CNTgraphene compositebased pressure sensor is shown in Figure 9. It can be observed from Figure 9 that the DC resistance of the CNTgraphene compositebased pressure sensor decreases by 70.32% as the pressure increases from 0 to 0.183 kNm^{−2}. The decrease in resistivity and hence increase in conductivity in the observed resistancepressure relationship are most probably due to squeezing and densification of CNTs and graphene nanopowder particles under the pressure effect [10]. The decrease percentage in resistance can be computed by the following equation [35]:where is the initial resistance at 0 kNm^{−2} and is the resistance of the sample at maximum pressure (0.183 kNm^{−2}).
The sensor’s resistance () can be calculated as [10]where is the interelectrode distance or thickness of the pressed pellet, is the crosssectional of pellet, and ρ is the resistivity ( = 1/, is the conductivity) of the pellet. The total changes in the resistivity of the material due to both the fractional change in resistivity () and geometric effects (1 + ) can be expressed as [36]In nanomaterials, the change in resistivity is large enough as compared to the geometrical parameters; hence the geometrical factor is often negligible and the change in the resistivity is dominated in this case [7].
The conductivity mechanism in pure CNT, pure graphene, and CNTgraphene compositebased pressure sensors (2) can be assumed as hopping charge transport between specially separated sites in which charges hop out from one localized state to another to contribute to conductivity [10, 17]. The charge transport mechanism in this random geometry can be described by percolation theory. Percolation theory is widely used in bulk heterojunction systems, conductive polymers, and the composites of nanomaterials because the charge transport mechanism in these materials is based on hopping phenomena [37].
According to the percolation theory, the average conductivity () of pure CNT, pure graphene, and CNTgraphene composite can be calculated using the following expression [7, 38]:where is the characteristic length and depends on the concentration of the localized states and is path resistance between sites with the lower average resistance. When external uniaxial pressure increases, the pellets are squeezed between the Al foils (Figures 4–6). This causes a decrease in and , which, in turn, increases the conductivity and hence decreases the resistance of the sensors. This can also be explained as the conduction in disordered nanomaterials limited by the trap states of high potential barrier which exists below the localized states. The trap effect is minimized by filling the trap regions due to increase in the charge carrier’s concentration under the squeezing effect that causes an increase in the conductivity and hence decrease in the resistance of the sample [17].
Change in resistance of the sample affects the sensitivity of the sample as well. Large percentage change in resistance increases the sensitivity of the sample.
The sensitivity () of all the samples can be calculated as [39]where shows the change in the external uniaxial pressure, denotes the initial resistance at pressure 0 kNm^{−2}, and is the variation in the DC resistance. The sensitivities of pure CNT (Figure 8(a)), pure graphene (Figure 8(b)), and CNTgraphene composite (Figure 9) samples were 4.37, 3.44, and 3.82 m^{2}/kN, respectively.
Sensitivity and decrease percentage in the DC resistance for pure CNT, pure graphene, and CNTgraphene compositebased pressure sensors are reported in Table 1. It can be seen from Table 1 that under the same external applied pressure, the decrease percentage in resistance () and sensitivity () for the pure graphenebased pressure sensor is lower than the other two samples. This can be attributed to two factors: higher structural strength and large particle size. The structural strength of graphene is higher than carbon nanotubes [40].

Under the same external applied pressure, higher structural strength causes smaller deformation in pure graphene sample than the other two samples. This smaller deformation in pure graphene sample leads to a smaller effect on the HOMOLUMO bandgap of the material, which, in turn, leads to a smaller decrease in the resistance of the sample. Large particle size causes a lower surface areatovolume ratio, which, in turn, decreases the reactivity of a material to external stimuli [2]. Moreover, large particles sizes of material decrease uniformity and increase dislocations, porosity, and other defects in the material [1]. Most of the carbon nanotubes currently available in the open literature have smaller surface area (100–850 m^{2}g^{−1}) than graphene surface area (up to 2675 m^{2}g^{−1}) [41, 42]. The large size of graphene nanosheets results in a greater amount of dislocations, porosity, and other defects as compared to carbon nanotubes [1]. Most of the external applied pressure can be absorbed by the dislocations, porosity, and other defects in graphene nanopowder. Therefore, the sensitivity and decrease percentage in resistance of pure graphenebased pressure sensor are lower than the pure CNTbased sample (Table 1). In case of CNTgraphene composite pressure sensor, it can be assumed that CNTs make the composite more responsive to the external stimuli (pressure in our case) by increasing the uniformity. Therefore, sensitivity and decrease percentage in resistance of the CNTgraphene composite sample are higher than pure graphene but smaller than pure CNTbased sample. The incorporation of CNTs into graphene increases the uniformity and decreases dislocations, porosity, and other defects in graphene nanopowder, which, in turn, decreases the resistance and hence increases the conductivity of the material. Therefore, CNTs can be considered as an excellent filler to reduce the resistivity and enhance the conductivity of graphene nanopowder.
3.2.1. Relative ResistancePressure Relationship
The relative resistancepressure relationships for pure CNT, pure graphene, and CNTgraphene composite are shown in Figure 10.
The characteristic curves of pure CNT, pure graphene, and their composite (Figure 10) significantly differ from each other due to their very different aspect ratio. The sensors show a significant decrease in DC resistance as the pressure increases from 0 to 0.183 kNm^{−2}; however, the effect is more pronounced in pure CNTbased sensor than the other two. It can be observed from Figure 10 that the pure CNTbased pressure sensor has aggressive slope when the pressure increases from 0 to 0.069 kNm^{−2}. At a pressure level of 0.069 kNm^{−2}, CNTbased pressure sensor reaches its operating limit (saturation) and is almost no longer responsive even when the input stimulus (pressure) is increased beyond this level. Resistancepressure relationship curve (Figure 10) for pure graphenebased pressure sensor is more uniform than pure CNTbased sensor. Surprisingly, CNTgraphene compositebased pressure sensor shows less aggressive slope to the external uniaxial applied pressure than the other two sensors. The compositebased pressure sensor relative resistancepressure characteristic exhibits quasilinear behavior (Figure 10) that can be linearized by using nonlinear operationalamplifiers for practical applications of the sensors [43].
3.2.2. Experimental versus Simulation
A mathematical formula, which forms a basis for operation of the sensor, can be used to compute the transfer function of the sensor. However, if a solvable formula for the transfer function of a complex sensor does not exist, then one can apply a number of approximations for the transfer function of the sensor. The purpose of the approximation is to fit the observed experimental data with the calculated values of the approximation function. The most important approximations used for the transfer function of the sensors are linear, exponential, and polynomial regression approximation [44]. If none of the linear and exponential approximations are fitting the experimental data well. Then the suitable approximation is polynomial regression model. Unfortunately, this model does not provide enough information about the internal structure and properties of the materials. However, it provides a best fit to the experimental data (Figure 9). If higher accuracy is required, then higher order polynomials can be considered [44]. However, in our case, 3rd order polynomial regression model (6) gives acceptable range of accuracy and a best fit to the experimental data (Figure 9) as shown in Figure 11. The selected approximation function (6) is then transferred to the relative values (7). The fitting parameters , , and (pressure factors) are used to calculate the resistance at various pressure levels. The mathematical model used in the simulation is a polynomial regression model that can be expressed as follows [44]:In our case, (6) can be written in the following form:where is the pressure, , , and are the fitting parameters or pressure factors, is the intercept, and and are the resistances of the pellets at initial state and under pressure. The values of , , , and calculated at pressure level of 0.183 kNm^{−2} are 15.90686, 5.93051, −922.99399, and 3052.92373 kN^{−2}m^{2}, respectively.
Experimental data (Figure 9) and simulated results (7) have excellent agreement with each other as shown in Figure 11. The simulated resistancepressure curve deviates by only 0.029% from the experimental resistancepressure graph. The deviation of experimental data from simulation can be calculated as [45]
3.3. ImpedancePressure Relationships
Impedancepressure relationships for pure CNT and pure graphenebased pressure sensors at 1 kHz are shown in Figure 12.
(a)
(b)
It can be observed from Figure 12 that as the pressure increases from 0 to 0.183 kNm^{−2}, the impedance of pure CNT (Figure 12(a)) and that of pure graphene (Figure 12(b)) pressure sensors decrease by 72.85% and 48.33%, respectively. The impedance of the sample is assumed as parallel connected resistor and capacitor. The equivalent circuit diagram shown in Figure 13 seems to be valid for the sample.
The charge carrier transport occurs through the nanoparticles (resistors) and micropores (capacitors). The impedance () of the equivalent RC circuit of the sample can be calculated using the following equation [46, 47]:where is the frequency, is the admittance, and and represents the resistance and capacitance of the sample, respectively. The capacitancepressure relationship [11] shows increase in capacitance with increase in pressure. However, in our case, it can be seen that both the resistance and impedance decrease with increase in pressure. The variation in impedance occurs in the same fashion as the variation in the resistance of the sensor. Therefore, it can be concluded that the impedance is more dominated by the resistance effect than the corresponding capacitance effect.
The impedancepressure relationship for CNTgraphene compositebased pressure sensor at 1 kHz is shown in Figure 14.
The impedance of the composite sample decreases by 64.23% with increase in external uniaxial pressure from 0 to 0.183 kNm^{−2}.
For sensitivity computation, the term in (5) was replaced with [39]:The sensitivities of the pure CNT, pure graphene, and CNTgraphene composite samples were 3.98, 2.64, and 3.53 m^{2}/kN, respectively. For the same pressure range, decrease percentage in the impedance and corresponding sensitivities for pure CNT, pure graphene, and CNTgraphene compositebased pressure sensors are reported in Table 2. It can be seen from Table 2 that the sensitivity and decrease percentage in impedance of the samples is greater in the following order: pure CNT > CNTgraphene composite > pure graphene.

3.3.1. Relative ImpedancePressure Relationship
The relative impedancepressure relationships for the three pellets are shown in Figure 15, where the values are measured at a frequency of 1 kHz at room temperature.
The behavior of relative impedancepressure characteristics shown in Figure 15 is similar to that of relative resistancepressure characteristics (Figure 10). Therefore, it can be concluded that impedance is more dominated by the resistance effect than the corresponding capacitance effect.
3.3.2. Experimental versus Simulation
The variation in impedance (Figure 14) occurs in the same fashion as the variation in resistance (Figure 9) of the sensor. Therefore, for the CNTgraphene composite, in (7) can be replaced by [44]:The values of , , , and calculated at pressure level of 0.183 kNm^{−2} are 14.87078, 29.0523, −1097.2955, and 3564.15746 kN^{−2}m^{2}, respectively.
Experimental data (Figure 14) and simulated results (11) have excellent agreement with each other as shown in Figure 16.
The maximum deviation of simulated impedancepressure graph from experimental curve is 0.105% only.
3.4. Resistance versus Impedance
The decrease percentage values in impedance (Table 2) for pure CNT, pure graphene, and CNTgraphene composite are smaller than the corresponding values of decrease percentage in resistance (Table 1). This is due to the additional resistance offered by the reactance in the denominator of (9). Under the same external applied pressure, the decrease percentages in (Table 2) for pure CNT, pure graphene, and CNTgraphene composite are, respectively, 8.9%, 24.57%, and 8.66% smaller than the corresponding decrease percentages in resistances (Table 1). For graphene sample, the higher reduction in (24.57%) is due to the fact that the impedance of the sample is inversely proportional to the capacitance of the sample (9); that is, the value of decreases with the increase in . Also, large plate area causes more charge collection that results in greater capacitance of the capacitor. The surface area of graphene nanosheets (2675 m^{2}g^{−1}) is larger than the surface area of carbon nanotubes (100–850 m^{2}g^{−1}) [37, 38]. Therefore, the overall capacitance performance of graphene nanopowder is better than the carbon nanotubes (CNTs). In other words, the capacitance of graphenebased pressure sensor is greater than the capacitance of pure CNT and CNTcompositebased pressure sensors. Therefore, for graphene sample, higher capacitance causes a smaller value of impedance ().
4. Conclusion
Pure CNT, pure graphene, and CNTgraphene composite sandwichtype pressure sensors (Ag/CNT/Ag, Ag/graphene/Ag, Ag/CNTgraphene/Ag) were fabricated in the form of pellets. The sensitivities and piezoresistive properties of the samples were investigated and compared. Decrease in impedance and DC resistance with the increase in pressure was observed for all the samples. As the pressure was increased from 0 to 0.183 kNm^{−2}, the decrease percentages in DC resistance of the pure CNT, pure graphene, and CNTgraphene composite pressure sensors were 80%, 63.24%, and 70.32%, respectively. The sensitivities based on the resistance change for pure CNT, pure graphene, and CNTgraphene composite samples were 4.37, 3.44, and 3.82 m^{2}/kN, respectively. For the same pressure range, the decrease percentages in impedance for pure CNT, pure graphene, and CNTgraphene compositebased sample were 72.85%, 48.33%, and 64.23%, respectively. The sensitivities based on impedance decrease for pure CNT, pure graphene, and CNTgraphene composite samples were 3.98, 2.64, and 3.53 m^{2}/kN, respectively. The reasons for the decrease in resistance and impedance of each sample were explored. The simulated resistancepressure and impedancepressure relationships for the composite pressure sensor were compared with the experimental data, which exhibit an excellent agreement with each other. For all the samples, it was realized that the behavior of impedance is more dominated by the resistance effect of the pressure sensor than the corresponding capacitance effect. Moreover, the percolation theory was used to explain the conduction mechanism of the sensors. The mechanism of conductivity and the change in resistance of the sensor under the effect of pressure were also discussed.
Conflicts of Interest
The authors declare that they have no conflicts of interest.
References
 J. Li, Mechanical Properties of Nanocrystalline Materials, Pan Stanford Publishing, 2011. View at: Publisher Site
 H.J. Fecht, K. Brühne, and P. Gluche, CarbonBased Nanomaterials and Hybrids: Synthesis, Properties and Commercial Applications, CRC Press, Boca Raton, Fla, USA, 2014. View at: Publisher Site
 B. Marinho, M. Ghislandi, E. Tkalya, C. E. Koning, and G. De With, “Electrical conductivity of compacts of graphene, multiwall carbon nanotubes, carbon black, and graphite powder,” Powder Technology, vol. 221, pp. 351–358, 2012. View at: Publisher Site  Google Scholar
 H. Hofmann, ““Advanced nanomaterials,” Powder Technology, Laboratory, 2009”. View at: Google Scholar
 J. H. Warner, F. Schaffel, M. Rummeli, and A. Bachmatiuk, Graphene: Fundamentals and Emergent Applications, Newnes, Australia, 2012.
 A. M. Hurst, S. R. Lee, N. Petrone et al., “A transconductive graphene pressure sensor,” in Proceedings of the In Sensors, Actuators and Microsystems, Transducers Eurosensors XXVII: 17th International Conference, pp. 586–589, 2013. View at: Google Scholar
 A. Khan, Characterization of Organic Materials for Electromechanical Sensors, Ghulam Ishaq Khan Institute of Engineering Sciences & Technology, Swabi, 2013.
 K. S. Karimov, K. Sulaiman, Z. Ahmad, K. M. Akhmedov, and A. Mateen, “Novel pressure and displacement sensors based on carbon nanotubes,” Chinese Physics B, vol. 24, no. 1, Article ID 018801, 2015. View at: Publisher Site  Google Scholar
 C. M. Jureschi, J. Linares, A. Rotaru et al., “Pressure sensor via optical detection based on a 1D spin transition coordination polymer,” Sensors, vol. 15, no. 2, pp. 2388–2398, 2015. View at: Publisher Site  Google Scholar
 K. S. Karimov, M. T. S. Chani, F. A. Khalid, A. Khan, and R. Khan, “Carbon nanotube  Cuprous oxide composite based pressure sensors,” Chinese Physics B, vol. 21, no. 1, Article ID 016102, 2012. View at: Publisher Site  Google Scholar
 K. S. Karimov, M. Abid, M. MahroofTahir et al., “V_{2}O_{4}PEPC composite based pressure sensor,” Microelectronic Engineering, vol. 88, no. 6, pp. 1037–1041, 2011. View at: Publisher Site  Google Scholar
 H. Tian, Y. Shu, X. Wang et al., “A graphenebased resistive pressure sensor with recordhigh sensitivity in a wide pressure range,” Scientific Reports, vol. 5, article 8603, pp. 1–6, 2015. View at: Publisher Site  Google Scholar
 J. Li, W. Li, W. Huang, G. Zhang, R. Sun, and C.P. Wong, “Fabrication of highly reinforced and compressible graphene/carbon nanotube hybrid foams via a facile selfassembly process for application as strain sensors and beyond,” Journal of Materials Chemistry C, vol. 5, no. 10, pp. 2723–2730, 2017. View at: Publisher Site  Google Scholar
 P. Sahatiya and S. Badhulika, “Eraserbased ecofriendly fabrication of a skinlike largearea matrix of flexible carbon nanotube strain and pressure sensors,” Nanotechnology, vol. 28, no. 9, Article ID 095501, 2017. View at: Publisher Site  Google Scholar
 J.L. Yao, X. Yang, N. Shao, H. Luo, T. Zhang, and W.G. Jiang, “A flexible and highly sensitive piezoresistive pressure sensor based on micropatterned films coated with carbon nanotubes,” Journal of Nanomaterials, vol. 2016, Article ID 3024815, 5 pages, 2016. View at: Publisher Site  Google Scholar
 K. S. Karimov, N. Ahmed, M. M. Bashir et al., “Flexible resistive tensile load cells based on MWCNT/rubber composites,” Pigment & Resin Technology, vol. 44, no. 3, pp. 187–191, 2015. View at: Publisher Site  Google Scholar
 A. Khan, K. S. Karimov, Z. Ahmad, K. Sulaiman, M. Shah, and S. A. Moiz, “Pressure sensitive organic sensor based on CNTVO2 (3fl) Composite,” Sains Malaysiana, vol. 43, no. 6, pp. 903–908, 2014. View at: Google Scholar
 W. Xue and T. Cui, “Electrical and electromechanical characteristics of nanoassembled carbon nanotube thin film resistors on flexible substrates,” in Proceedings of the 4th International Conference on SolidState Sensors, Actuators and Microsystems, (TRANSDUCERS and EUROSENSORS '07), pp. 1047–1050, Lyon, France, June 2007. View at: Publisher Site  Google Scholar
 R. J. Grow, Q. Wang, J. Cao, D. Wang, and H. Dai, “Piezoresistance of carbon nanotubes on deformable thinfilm membranes,” Applied Physics Letters, vol. 86, no. 9, Article ID 093104, pp. 93104–93107, 2005. View at: Publisher Site  Google Scholar
 H. Tian, Y. Yang, D. Xie et al., “Waferscale integration of graphenebased electronic, optoelectronic and electroacoustic devices,” Scientific Reports, vol. 4, Article ID 03598, 9 pages, 2014. View at: Publisher Site  Google Scholar
 A. Lipatov, A. Varezhnikov, M. Augustin et al., “Intrinsic devicetodevice variation in graphene fieldeffect transistors on a Si/SiO_{2} substrate as a platform for discriminative gas sensing,” Applied Physics Letters, vol. 104, no. 1, Article ID 013114, p. 13114, 2014. View at: Publisher Site  Google Scholar
 H.B. Yao, J. Ge, C.F. Wang et al., “A flexible and highly pressuresensitive graphenepolyurethane sponge based on fractured microstructure design,” Advanced Materials, vol. 25, no. 46, pp. 6692–6698, 2013. View at: Publisher Site  Google Scholar
 A. D. Smith, S. Vaziri, F. Niklaus et al., “Pressure sensors based on suspended graphene membranes,” SolidState Electronics, vol. 88, pp. 89–94, 2013. View at: Publisher Site  Google Scholar
 A. D. Smith, F. Niklaus, A. Paussa et al., “Electromechanical piezoresistive sensing in suspended graphene membranes,” Nano Letters, vol. 13, no. 7, pp. 3237–3242, 2013. View at: Publisher Site  Google Scholar
 H. C. P. Movva, M. E. Ramón, C. M. Corbet et al., “Graphene fieldeffect transistors with selfaligned spinondoping of source/drain access regions,” in Proceedings of the 70th Device Research Conference, (DRC '12), pp. 175176, University Park, TX, USA, June 2012. View at: Publisher Site  Google Scholar
 X. Chen, X. Zheng, J. K. Kim, X. Li, and D. W. Lee, “Investigation of graphene piezoresistors for use as strain gauge sensors,” Journal of Vacuum Science & Technology B, vol. 29, no. 6, Article ID 06FE01, 2011. View at: Google Scholar
 V. Sorkin and Y. W. Zhang, “Graphenebased pressure nanosensors,” Journal of Molecular Modeling, vol. 17, no. 11, pp. 2825–2830, 2011. View at: Publisher Site  Google Scholar
 Q. Sun, D. H. Kim, S. S. Park et al., “Transparent, lowpower pressure sensor matrix based on coplanargate graphene transistors,” Advanced Materials, vol. 26, no. 27, pp. 4735–4740, 2014. View at: Publisher Site  Google Scholar
 S.E. Zhu, M. Krishna Ghatkesar, C. Zhang, and G. C. A. M. Janssen, “Graphene based piezoresistive pressure sensor,” Applied Physics Letters, vol. 102, no. 16, Article ID 161904, 2013. View at: Publisher Site  Google Scholar
 S.H. Shin, S. Ji, S. Choi et al., “Integrated arrays of airdielectric graphene transistors as transparent activematrix pressure sensors for wide pressure ranges,” Nature Communications, vol. 8, Article ID 14950, 2017. View at: Publisher Site  Google Scholar
 E. Mansfield, A. Feldman, A. N. Chiaramonti, J. Lehman, and A. E. Curtin, “Morphological and electrical characterization of MWCNT papers and pellets,” Journal of research of the National Institute of Standards and Technology, vol. 120, pp. 304–315, 2015. View at: Publisher Site  Google Scholar
 Y. Huang, W. Wang, Z. Sun, Y. Wang, P. Liu, and C. Liu, “A multilayered flexible piezoresistive sensor for wideranged pressure measurement based on CNTs/CB/SR composite,” Journal of Materials Research, vol. 30, no. 12, pp. 1869–1875, 2015. View at: Publisher Site  Google Scholar
 A. Ali, A. Khan, A. Ali, and M. Ahmad, “Pressuresensitive properties of carbon nanotubes/bismuth sulfide composite materials,” Nanomaterials and Nanotechnology, vol. 7, pp. 1–9, 2017. View at: Publisher Site  Google Scholar
 A. Celzard, J. F. Marêché, F. Payot, and G. Furdin, “Electrical conductivity of carbonaceous powders,” Carbon, vol. 40, no. 15, pp. 2801–2815, 2002. View at: Publisher Site  Google Scholar
 A. Rani, S. Nam, K. Oh, and M. Park, “Electrical conductivity of chemically reduced graphene powders under compression,” Carbon Letters, vol. 11, no. 2, pp. 90–95, 2010. View at: Publisher Site  Google Scholar
 N. Angelidis, C. Y. Wei, and P. E. Irving, “The electrical resistance response of continuous carbon fibre composite laminates to mechanical strain,” Composites Part A: Applied Science and Manufacturing, vol. 35, no. 10, pp. 1135–1147, 2004. View at: Publisher Site  Google Scholar
 S. T. Saeed, Fabrication and investigation of organic and nanomaterials based sensors [Doctoral, thesis], Ghulam Ishaq Khan Institute of Engineering Sciences & Technology, Swabi, 2012.
 W. Bauhofer and J. Z. Kovacs, “A review and analysis of electrical percolation in carbon nanotube polymer composites,” Composites Science and Technology, vol. 69, no. 10, pp. 1486–1498, 2009. View at: Publisher Site  Google Scholar
 S. A. Hasan, Y. Jung, S. Kim et al., “A sensitivity enhanced MWCNT/PDMS tactile sensor using micropillars and low energy Ar+ ion beam treatment,” Sensors, vol. 16, no. 1, p. 93, 2016. View at: Google Scholar
 J. Shi, X. Li, H. Cheng et al., “Graphene reinforced carbon nanotube networks for wearable strain sensors,” Advanced Functional Materials, vol. 26, no. 13, pp. 2078–2084, 2016. View at: Publisher Site  Google Scholar
 J. J. Niu, J. N. Wang, Y. Jiang, L. F. Su, and J. Ma, “An approach to carbon nanotubes with high surface area and large pore volume,” Microporous and Mesoporous Materials, vol. 100, no. 13, pp. 1–5, 2007. View at: Publisher Site  Google Scholar
 Q. Ke and J. Wang, “Graphenebased materials for supercapacitor electrodes – A review,” Journal of Materiomics, vol. 2, no. 1, pp. 37–54, 2016. View at: Publisher Site  Google Scholar
 R. G. Irvine, Operational Amplifier Characteristics and Applications, PrenticeHall, 2ND edition, 1994.
 J. Fraden, Handbook of modern sensors: physics, designs, and applications, Springer Science & Business Media, NY, USA, 4th edition, 2010.
 N. Kumar, Comprehensive Physics, Department of Physics. S.D. G. College, Ludhian, India, 2005.
 M. T. S. Chani, K. S. Karimov, F. A. Khalid, and S. A. Moiz, “Polyaniline based impedance humidity sensors,” Solid State Sciences, vol. 18, pp. 78–82, 2013. View at: Publisher Site  Google Scholar
 J. D. Irwin, Basic Engineering Circuits Analysis, John Wiley & Sons, NY, USA, 1999.
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