Tactile Sensing System Based on Arrays of Graphene Woven

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A Tactile Sensing System Based on Arrays of Graphene Woven MicroFabrics: Electromechanical Behavior and Electronic Skin Application Tingting Yang, Wen Wang, Hongze Zhang, Xinming Li, Jidong Shi, Yijia He, Quan-Shui Zheng, Zhihong Li, and Hongwei Zhu ACS Nano, Just Accepted Manuscript • DOI: 10.1021/acsnano.5b03851 • Publication Date (Web): 15 Oct 2015 Downloaded from http://pubs.acs.org on October 16, 2015

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A Tactile Sensing System Based on Arrays of Graphene Woven Micro-Fabrics: Electromechanical Behavior and Electronic Skin Application Tingting Yang1,2, Wen Wang2,3, Hongze Zhang4, Xinming Li5, Jidong Shi5, Yijia He1,2, Quan-shui Zheng2,3, Zhihong Li2,4*, Hongwei Zhu1,2* 1

School of Materials Science and Engineering, State Key Laboratory of New Ceramics and

Fine Processing, Tsinghua University, Beijing 100084, China 2

Center for Nano and Micro Mechanics, Tsinghua University, Beijing 100084, China

3

Department of Engineering Mechanics, Tsinghua University, Beijing 100084, China

4

National Key Laboratory of Science and Technology on Micro/Nano Fabrication, Institute of

Microelectronics, Peking University, Beijing 100871, China 5

National Center for Nanoscience and Technology, Zhongguancun, Beijing 100190, China

*Address correspondence to [email protected], [email protected].

Abstract Nanomaterials serve as promising candidates for strain sensing due to unique electromechanical properties by appropriately assembling and tailoring their configurations. Through the crisscross interlacing of graphene micro-ribbons in an over-and-under fashion, the obtained graphene woven fabric (GWF) indicates a good trade-off between the sensitivity and stretchability compared with those in previous studies. In this work, the function of woven fabrics for highly sensitive strain sensing is investigated although network configuration is always a strategy to retain resistance stability. The experimental and simulation results indicate that the ultrahigh mechano-sensitivity with gauge factors of 500 1 ACS Paragon Plus Environment

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under 2% strain is attributed to the macro woven-fabric geometrical conformation of graphene which induces a large interfacial resistance between the interlaced ribbons and the formation of microscale controllable, locally oriented zigzag cracks near the crossover location, both of which have synergistic effect on improving sensitivity. Meanwhile, the stretchability of GWF could be tailored to as high as over 40% strain by adjusting graphene growth parameters and adopting oblique angle direction stretching simultaneously. We also demonstrate that sensors based on GWFs are applicable to human motion detection, sound signal acquisition and spatially resolved monitoring of external stress distribution. Keywords: graphene, strain sensor, e-skin, interface, crack, woven fabrics

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Recently, progress has been achieved in implementing flexible mechanosensors to mimic tensile, bent and tactile sensing capabilities of human skin.1-8 Important considerations for the development of the flexible mechanosensors are the choice of sensing materials and device structures to accomplish the requirements of ultrahigh sensitivity, flexibility, durability, fast response, stability, linearity, etc. Among those criterions, gauge factor which refers to the resistance change under strain, and flexibility which refers to the reversible movement range without damage, are mostly discussed and primarily focused. However, there exists a trade-off between the gauge factor and flexibility, i.e., a reasonable design strategy for highly sensitive mechanosensors always restrains the sensor stretchability, and vice versa.7, 9-16 For example, a previous work11 reported a mechanical crack-based sensor inspired by the spider sensory system attaining ultrahigh sensitivity with a gauge factor of 2000 in the 0~2 % strain range, which is the highest value so far to our knowledge. Another work17 introduced a film composed of nanographene flakes to detect small strains with a gauge factor of over 500 below 2 % due to the tunneling effect. However, the pure crack or tunneling effect dominant mechanism tends to make an over-abrupt response, then results in a limited work range which inhibits them from detecting large deformation induced by movements such as walking, running, and grasping, etc. On the contrary, stretchable mechanosensors can be fabricated by developing materials with intrinsic stretchability or adopting appropriate geometrical arrangement of sensing materials, such as buckling, patterning and meshing.18-24 For example, a previous work25 demonstrated an EGaIn-based strain sensor to function well over 100% strain due to the intrinsic stretchability of liquid metal. Another work26 showed aligned single-walled carbon 3 ACS Paragon Plus Environment

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nanotubes of a string cheese structure that could measure and withstand strain up to 280%. However, these flexible mechanosensors suffer a low gauge factor of below 10 which lacks the sensitivity to make a prompt and accurate detection of weak human motions including phonation, expression change and pulse, etc. In all, the development of a multifunctional mechanosensor satisfying the requirements of ultrahigh sensitivity and good flexibility simultaneously remains a challenge. Consequently, certain structural engineering is urgently required to provide solutions. In this work, we demonstrated a highly strain sensitive graphene based electromechanical sensor with a gauge factor of 500 below 2 % and 104 over 8% through tailoring the graphene integral network configuration, crack formation and propagation mode. Furthermore, the working range can be improved to more than 40% by adjusting the growth parameters and adopting oblique direction stretching with a certain lower gauge factor. The experimental and simulation results show that the macro woven-fabric geometrical conformation of graphene induces a large interfacial resistance between the interlaced ribbons and formation of micro-scale controllable, locally oriented zigzag crack near the crossover location, both of which have synergistic effect on improving the sensitivity. The analysis and discussion will provide a meaningful reference for geometrical design of strain sensing materials to become highly sensitive and stretchable. Moreover, we also illustrate the use of such stretchable and sensitive graphene based mechanical sensor for human motion detection, sound signal acquisition and spatially resolved monitoring of external stress distribution, suggesting a promising route toward displays, robotics, fatigue detection, body monitoring, and so forth. Based on the above discussion, the electromechanical behavior and 4 ACS Paragon Plus Environment

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e-skin application are illustrated in Fig. 1a. Results and Discussion Structural characteristics of GWF. Fig. 1b provides the schematic illustration of graphene woven fabrics (GWF) based strain sensor. The details of fabrication and operation of GWF-based strain sensor have been reported previously.27, 28 In general, the crisscross copper mesh was used as the template for atmospheric pressure chemical vapor deposition (APCVD) graphene growth. Similar to the graphene growth on the copper foil substrate, the obtained GWF covered the surface of copper mesh and kept the complete crisscross geometry as copper mesh. After copper was etched, the GWF was transferred to polydimethylsiloxane (PDMS) substrate pretreated by oxygen plasma and connected to silver wires with silver paste on both ends. Raman spectra in Fig. S1 clearly reveal the evidences of few-layer graphene on PDMS, which are confirmed by the 2D, G peaks. The weak peak of D-band in the spectra indicates the presence of imperfections (e.g., surface defects, wrinkles, edges, grain boundaries) in the GWF.


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Figure 1. (a) Illustration of the electromechanical behavior and e-skin application of GWF-on-polymer sensors. (b) Schematic of a GWF-based strain sensor. (c) Top-view optical image of GWF on Si/SiO2 substrate, and an enlarged view of the crisscross point (inset), scale bar: 100 µm. (d) Lateral view photograph of a GWF-based strain sensor. (e) Relative resistances and gauge factors under different strains.

As obviously shown in Fig. 1c, three key structural characteristics are included in the GWF: i) Rectangular holes of uniform arrangement, of which the size and density can be adjusted through changing the geometry of copper mesh; ii) Graphene micro ribbons (GMR) are crisscross assembled and interlaced with each other in an over-and-under fashion instead of welding, riveting or else integral connecting; iii) Some kind of flaws, accurately located at the lower ribbon and close proximity to the interlacing point, are formed in a controlled manner in terms of crack density and direction. Electromechanical test. Fig. 1d supplies the photograph of a GWF based strain sensor, and 6 ACS Paragon Plus Environment

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graphene adheres well to the PDMS substrate and follow the exact deformation of the substrate upon stretching. Fig. 1e characterizes the typical resistive response behavior of the strain sensor to the external loading, displaying the resistance monotonously increases with the applied strain, approximately exponential fashions. According to the response curve, the woven mesh structure of GWF is highly sensitive to deformation with ∆R/R0 values of 1~2 at 1%, 5~10 at 2% and 103~104 at 8%. The corresponding gauge factors (∆R/(R0×ε)) are dependent on the strain range and are calculated to be almost 500 below 2 % and 104 over 8%. Compared with other works,10, 11, 17, 29 the woven structure of GWF achieves high gauge factor under small strains with balanced stretchability and stability. The relative resistance change of the strain sensor during 1000 cycles from 0% to 2% strain is recorded (Fig. S2). The valley value of resistance keeps almost the same while the peak value attenuates slightly during the cycling test. At the 1000th cycle, the relative resistance at 2% strain shows a 24% drop which is comparable with the nanoparticle based strain sensor.11 The stability is expected to be further improved by suppressing the creep deformation of PDMS and enhancing interfacial interaction between GWFs and PDMS. Electromechanical behavior analysis. It is supposed the woven mesh structure endows the GWF with enhanced stretchability because the adjacent woven graphene ribbons are just partially bonded at the cross point thus the cross-yarns should slide and regulate rectangular GWF to parallelogram structure21 under stretching. To understand the underlying mechanism of GWF’s high sensitivity and explain the correlation between internal structure and electromechanical property, each of above-mentioned three key structural characteristics of 7 ACS Paragon Plus Environment

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GWF is discussed as follows in sequence. Planar network structure versus woven fabric. We first infer woven fabric structure is much more sensitive than planar network structure of patterned graphene and exclude the possibility that network configuration contributes to the high sensitivity. To clearly compare the sensing performance of these two structures, we fabricated a planar network structure of graphene based strain sensor with the same size and density of holes and growth condition as GWF. The detail of synthesize process is illustrated in Fig. 2a and Materials and Methods section. Fig. 2b displays the optical image of a representative region of the graphene planar grid (GPG). Fig. 2c indicates the measured gauge factor under 1% strain for GPG is 1-2 orders lower than that of GWF, manifesting the effect of network configuration itself is negligible for high sensitivity, i.e. the woven fabric structure with interlaced crisscross and regulated flaw pattern is the contributing factor.

Figure 2. (a) Preparation schematic of GPG using copper mesh as the shadow mask. (b) Top-view optical image of GPG on Si/SiO2 substrate, and an enlarged view of the crisscross point (inset), scale bar: 100 µm. (c) Relative resistances for GPG and GWF under 1% strain. 8 ACS Paragon Plus Environment

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To help understand the effect of the interlaced interface between the upper and lower ribbons, we first measured the resistance of the ribbon segment across and non-across a crisscrossing interface, respectively, illustrated as Fig. S3. The measured across resistance is from 104 to 105 Ω while the non-across one is around 103. Hence the interfacial resistance between the adjacent ribbons is evaluated from 103 to 105 Ω which should be considerable. Voronoi diagram. Then we used the Voronoi diagram to model the electrical resistance change of GWF taking interlaced interfacial resistance into consideration.23 Fig. 3a shows the two-dimensional (2D) Voronoi diagram with the length L = 50 µm and width W = 50 µm and the inset demonstrates overlapping area between graphene grains. On the premise that the graphene inter-grain resistance is much larger than the graphene grain resistance, so by replacing the overlapping area with resistances characterized by the overlapping width, the equivalent resistance network is shown in Fig. 3b.


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Figure 3. (a) 2D Voronoi diagram with a fixed edge-overlapping width (w = 200 nm, an enlarged view of overlapped neighboring grains (inset). (b) Equivalent resistance network by replacing two neighboring graphene flakes with a resistance characterized by the overlapping width. (c) Comparison of theoretical and experimental results. (d) Current pathways in the cases of small (top) and large (bottom) interfacial resistance.

Since the GWF has a complicated structure, we therefore first analyzed the response of resistance of graphene strips between two crossing nodes. Then we established a number of strip models (typically 10 models parallel and perpendicular to the tensile direction respectively in the calculation), and each model consists of randomly seeded graphene sheets. We calculated the resistance change of these strip models. After finishing that, we randomly assigned these models to the GWF. After adding the interfacial resistance to the calculation model, the resistance changes of GWF with different interfacial resistance are presented in Fig. 3c. Our calculated results are consistent with the observed behavior, informing the interfacial resistances play an important role in amplifying resistance change of individual graphene strips because the interlaced interfaces are barriers for current conduction resulting in fast decreased efficient current pathway under stretching, as shown in Fig. 3d. Thus the strain sensitivity could be enhanced through increasing the interfacial resistance. Cracking formation. Furthermore, to capture the main deformation characteristic of GWF, a group of SEM images presenting the formation of crack and their evolution in GWF under different strain are shown in Fig. 4. The main feature of interest for tensile tests is to define the effect of the structural flaws in close proximity to the interlacing point. The origin of the 10 ACS Paragon Plus Environment

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flaws is the shear effect between the over-and-under graphene ribbons produced by the surface tension of water during the etching and transfer process. At a structural weak point, high-density cracks predominantly perpendicular to the ribbon direction are formed under no strain while no clear cracks are seen away from the flaw region in the SEM images (Fig. 4a). At large strains of 8%, the cracks continue to propagate leading to almost cut through of the GMR near the crossing point nevertheless no clear cracks are initiated in the far distance yet (Fig. 4b). According to observation, the cracks are centralized around the crossing point of interlaced adjacent graphene ribbons instead of uniform distributed in the stretched GWF within the working range. In short, the macro woven-fabric geometrical conformation of graphene induces the formation and propagation of micro controllable local oriented zigzag cracks near the crossover location, which is inferred as a vital factor in determining the sensitivity.

Figure 4. SEM images of stretched GWFs, (a) 0% strain, (b) 8%strain, indicating the cracks emerge and propagate predominantly near the crisscross points, scale bars: 50, 20, 5, 5 µm respectively. 11 ACS Paragon Plus Environment

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Interestingly, if more carbon source is introduced in the growth process, the as-obtained GWF becomes thicker and keeps visually intact interlaced crisscross after transferred onto Si/SiO2 substrate, as shown in Fig. S4a. Fig. S4b illustrates the corresponding resistance behavior during stretching and indicates the measured gauge factor is reduced in exchange for a larger strain range as high as more than 20% which is supposed to be further enhanced by stretching in oblique angle direction. The thicker graphene fabrics is more stretchable than thinner ones as it leads to stronger interlaced interface between the upper and lower ribbons, which is confirmed by the decreased interfacial resistance. The measured interfacial resistance promptly decreases with increased thickness and finally turns close to zero over a critical thickness. Meanwhile the locally oriented zigzag crack near the crossover location is almost missing, as shown in Fig. S4a. The thickness influence can be an effective experimental support to the previous electromechanical behavior analysis further providing a tuning of both sensitivity and stretchability of graphene strain sensing devices. The large working range makes the material promising candidate in detecting large deformation induced by movements such as walking, running, and grasping, etc. E-skin application. Furthermore, the GWF provides a feasible solution for artificial skins once we transfer the GWF films onto a thin soft polymer substrate (e.g., PDMS). As Fig. 5a illustrates, the GWF based strain sensor was attached conformably to highly deformed skin surface with plainly visible crease below. The PDMS substrate film should be made as thin as possible to help avoid the partial slip or delamination of sensor from the skin due to sheer force during test. 12 ACS Paragon Plus Environment

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Fig. 5b displays the possibility of using GWF as a pulse detector by arranging the sensor around the wrist of one of the authors. The electrical signal is stable and important peaks of the human pulse waveform, namely, the percussion, tidal and diastolic peaks are distinguishable. Jugular venous pressure (JVP) is another significant signal for exigent heart diseases clinically. The measurement of JVP signal in real-time was performed by placing the GWF based sensor directly on the targets’ jugular vein. As Fig. 5c demonstrates, a typical biphasic waveform of JVP is observed with reproductive waveform shape which carries valuable information about the human physical condition.30 For example, “A” is correlated to atrial contraction, “C” represents ventricular contraction and “V” is related to atrial venous filling. Except from weak motion signal, such strain sensor can be easily attached to the body arthrosis surface to monitor large movement, as they are highly elastic and stretchable. Fig. 5d demonstrates the resistance change of GWF adhered to the finger joint during the movement of making a fist.

Figure 5. (a) Conformal adhesion of GWF based strain sensor on the human skin. (b) 13 ACS Paragon Plus Environment

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Measured relative resistances of pulse (insets: photograph, typical pulse waveform, measured profile) and (c) Jugular venous pressure measured in real time (insets: photograph, a typical Juqular venous pulse, measured profile). (d) Resistance response at the successive stage of making a fist. (e) Recognition of sound signal using GWF strain sensor, the insets show the sensor on an earphone and the sound wave profile.

Sound vibration represents another typical mechanical wave of pressure, of which the perception and processing is an integral part of human intelligence. The inset of Fig. 5e shows the audio testing procedure with music played by a loudspeaker and the GWF-based strain sensor attached on the surface of the loudspeaker vibrating membrane. Due to the low sampling frequency limit (100 Hz) of the signal processing system, some acoustic information gets lost. However, the collected signal (Fig. 5e) displays an almost synchronous response to audio frequency and retains most characteristic peak quite well. This GWF based strain sensor provides an interesting proof of concept to recognize vibration signal, e.g., acoustic vibration. Besides, we fabricated a proof-of-concept flexible GWF based tactile sensor array to resolve the spatial distribution of applied external stimuli such as touch. The schematic model and photograph of the sensor arrays with 8×8 pixels for electronic skin are provided in Figs. 6a,b, respectively. Pressing stimulus was applied by an indenter to introduce a local strain of GWF of which the deformation extent is determined by the applied force, geometrical size of the PDMS substrate and the device holding manner.


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Figure 6. (a) Schematic diagrams and (b) photograph of the strain sensor array for e-skin. (c) Electrical response when “point” pressure is applied at the position of R4-C4. (d) Electrical response when uniform normal stress of rhombic shape is applied.

The detailed fabrication is supplied in the Materials and Methods section and each sensing unit can be addressed individually with proper testing scheme, as shown in Fig. S5. The real-time resistance variation of a single pixel is monitored during applying continuously increased pressure (Fig. S6), with gauge factors of 0.02~1.1 kPa-1, working range of 0~100 kPa and response time of 10~30 ms. Figs. 6c,d demonstrate the electromechanical response of an 8×8 device array when “point” and “specific pattern” forces are afforded, respectively. When we touched the individual pixel on R4-C4 position with normal stress of 60 kPa, resistance of that pixel changes obviously meanwhile the resistances of other pixels are tested without apparent variation, which suggests that the influence of pressure is confined within the local area. 15 ACS Paragon Plus Environment

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When “rhombic pattern” forces of uniform normal stress of 30 kPa are applied, the profile of applied stress can be spatially imaged through collecting the output resistance change. The resistance change of the eight pixels varies from 0.9 to 1.0 on “rhombic pattern” position, revealing good uniformity in electrical characteristics. The uniformity in the resistance distribution of GWF can be further improved by optimizing the fabrication process. The GWF based tactile sensor array represents a facile, reliable candidate for artificial e-skin because it could provide a spatially resolved mapping of the touch positions and pressure. Summary and Conclusion In this study, we systematically investigated the mechanism of the ultrahigh mechano-sensitivity of GWF. We found that the configuration of woven fabric has three unique structural characteristics, including network geometry, crisscross interlaced ribbons and expected local flaws. Firstly, we conclude the network geometry itself could not endow the graphene with high sensitivity by performing a control test using GPG. The gauge factor of GPG is 1~2 orders lower than GWF. Secondly, we discovered that the interfacial resistance between the adjacent upper and lower graphene ribbons is much larger than the pristine graphene resistance. A simulation was provided to explore the effect and the conclusion is drawn that the interfacial resistance plays a significant role in enhancing the sensitivity. Thirdly, we observed that local oriented cracks emerge, propagate and finally cut through predominantly in close proximity to the interlacing point at the location of original flaws during stretching. The non-uniform cracking phenomenon is supposed to be the vital factor in determining the sensitivity. 16 ACS Paragon Plus Environment

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The large interfacial resistance between adjacent ribbons and controlled selective cracking property provide a way to obtain a highly sensitive graphene-based strain sensor. Furthermore, the GWF is able to endure large stretch of more than 20% strain by introducing more carbon source during growth and even larger deformation of more than 40% by oblique angle direction stretch at the expense of reduced sensitivity to a certain degree. We also demonstrate the use of such GWF based strain sensors with high sensitivity and comparatively good flexibility for e-skin applications such as human motion detection, acoustic signal acquisition and spatially resolved monitoring of external stress distribution. In future, precise engineering of controlled crack formation of GWF may render a better and more stable performance of our ultrasensitive mechanosensors, for the water surface tension induced cracking is random and out of control. In addition, the size effect should be taken into consideration especially when the mesh number is small. In such a case, the current cracking behavior of GWF fails to conform to statistical results. So far, we have focused on GWF, but other conductive material combinations might open the way for the integration of woven fabrics in highly sensitive strain sensor with better stretchability. Materials and Methods Preparation of GWF based strain sensors. Copper meshes (100 mesh, wire diameter of 60

µm) were used as the template substrate for APCVD graphene growth. After cleaning and drying, the meshes were placed in the center of a CVD tube furnace and GWF were synthesized at 1000 °C under a flow of Ar/H2/CH4 (200/2/30 mL min−1). Similar to graphene films grown on copper foil, GWF grown on copper meshes at such parameters were polycrystalline and had few layers (2~8 layers). The concentration of CH4 could be further 17 ACS Paragon Plus Environment

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increased (50-200 mL min-1) to obtain thicker GWF of more than 10 layers. Then, a small amount of PDMS (the weight ratio of base to cross linker was 10:1) was degassed under vacuum for 20 min and finally solidified at 80°C for 3h. Solidified PDMS film was used to collect the GWF. The GWF/PDMS film was cut into strips (1×1 cm2) and silver adhesive was coated on the two ends to make electrical connection. Preparation of graphene planar grid. Firstly, copper foil (99.8% purity) was used as the template substrate for APCVD graphene. The growing parameter was the same as that of GWF. The as-obtained graphene thin film was collected by solidified PDMS film. Then a copper mesh (100 mesh) was put on the graphene film to act as a shadow mask for protecting the underneath graphene from O2 plasma etching. After O2 plasma process, the graphene film turned into a planar network graphene with the same net pattern as copper meshes. Flexible force distribution sensing matrix fabrication and measurement circuit. This fabrication process included the following steps: (i) fabrication of the patterned GWF film on a PDMS substrate by physical erasure. The pattern size of individual pixel of GWFs is 3×3 mm2, and the gap of each square is around 1.5 mm; (ii) the bottom electrode array was fabricated by evaporation of 10-nm Ti and 50-nm Au through a shadow mask; (iii) the PDMS was coated onto each cross position of the top and bottom electrodes to form insulating layer with the thickness of 100 µm; (iv) the top electrode array was fabricated by the same method as the bottom electrode array. Each of the 8×8 pixels formed the individual electromechanical sensor. The schematic of the measurement circuit for individual pixel addressing is shown in Supporting Information Fig. S5. Voronoi micromechanics model and finite element analysis. We employed a modified 18 ACS Paragon Plus Environment

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Voronoi polycrystalline micromechanics model and studied the main mechanism of resistance change of individual graphene strips and GWFs.23 Voronoi diagram is a widely used tool to model the grain structure of two- or three-dimensional polycrystalline solids. Here, to make Voronoi diagram, we modeled the graphene strips of W=50µm and L=50µm between two crossing nodes first, then integrated the results of graphene strips into the network of a GWFs by adding interfacial resistance between two strips. (i) Each Voronoi cell was produced as a single graphene grain by increasing or decreasing the number of the random points. Here, we adjusted the number of random points to match the experimental observed mean graphene grain size l=5µm. (ii) Afterwards each Voronoi cell was extended for a width w/2 (w=200nm), resulting in the same overlapped width w between any two neighboring graphene grain. (iii) Based on the fact that the graphene interlayer resistance is always much larger than intralayer resistance thus we only considered the contributions of interlayer resistance in simulation. Assuming the interlayer resistance obey the Ohm’s law thus Rinter=ρct/(lw), where ρc represents the graphene interlayer resistivity 20Ωm and t=0.34nm is the graphene interlayer distance, the equivalent resistance network of single graphene strip was then established by replacing two neighboring graphene flakes with a resistance characterized by the overlapping width. (iv) Then we established a number of strip models (typically 10 models parallel and perpendicular to the tensile direction respectively in the calculation), and each model consists of randomly seeded graphene sheets. (v) Finally, we randomly assigned these models to the GWF. After adding the interfacial resistance to the calculation model, the resistance changes of GWF with different interfacial resistance are presented in Fig. 3c. We made finite element simulation of the tensile strain contours εxx for surface of PDMS film (6×6×0.5 mm3) under 19 ACS Paragon Plus Environment

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pressure. The young’s modulus of PDMS is set to be 500 kPa and the bottom surface is constrained. An uniform pressure of 0.8×0.8mm2 is applied on the top surface. Characterization and measurement. The electrical response of the strain sensor was recorded in real time by a digital meter Keithley 4200-SCS with a test step of 10ms. The morphology of the GWF was characterized by an optical microscope (Axio Scope A1) and scanning electron microscopy (LEO 1530). Audio tests were performed with a computer controlled loudspeaker.

Conflict of Interest: The authors declare no competing financial interest. Acknowledgements This work was supported by Beijing Science and Technology Program (D141100000514001), National Science Foundation of China (51372133, 91323304), and National Program on Key Basic Research Project (2013CB934201, 2011CB013000). Supporting Information Available: Supplementary data including Raman spectra, stability test, photographs and sensing behaviors of the sensors. This material is available free of charge via the Internet at http://pubs.acs.org. References and Notes 1.

Choong, C. L.; Shim, M. B.; Lee, B. S.; Jeon, S.; Ko, D. S.; Kang, T. H.; Bae, J.; Lee, S.

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Tactile Sensing System Based on Arrays of Graphene Woven

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