Pressure Insensitive Strain Sensor with Facile Solution-Based Process

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Pressure Insensitive Strain Sensor with Facile SolutionBased Process for Tactile Sensing Applications Jinwon Oh, Jun Chang Yang, Jin-Oh Kim, Hyunkyu Park, Se Young Kwon, Serin Lee, Joo Yong Sim, Hyun Woo Oh, Jung Kim, and Steve Park ACS Nano, Just Accepted Manuscript • DOI: 10.1021/acsnano.8b03488 • Publication Date (Web): 11 Jul 2018 Downloaded from http://pubs.acs.org on July 13, 2018

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Pressure Insensitive Strain Sensor with Facile Solution-Based Process for Tactile Sensing Applications Jinwon Oh,†, # Jun Chang Yang, †, # Jin-Oh Kim, † Hyunkyu Park, ‡ Se Young Kwon, † Serin Lee, † Joo Yong Sim, § Hyun Woo Oh,∥ Jung Kim, ‡ and Steve Park*, †

†

Department of Materials Science and Engineering, ‡Department of Mechanical Engineering,

Korea Advanced Institute of Science and Technology (KAIST), 34141, Republic of Korea

§

Bio-Medical IT Convergence Research Department, ∥Hyper-connected Basic Technology

Research Division, Electronics and Telecommunications Research Institute (ETRI), 34129, Republic of Korea [#] Equal contribution [*] Corresponding Author E-mail: [email protected]

KEYWORDS: strain sensor, tactile sensor, pressure insensitive, solution process, electrical impedance tomography

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ABSTRACT

Tactile sensors that can mechanically decouple, and therefore differentiate, various tactile inputs are highly important to properly mimic the sensing capabilities of human skin. Herein, we present an all-solution processable pressure insensitive strain sensor that utilizes the difference in structural change upon the application of pressure and tensile strain. Under the application of strain, microcracks occur within the multi-walled carbon nanotube (MWCNT) network, inducing a large change in resistance with gauge factor of ~56 at 70 % strain. On the other hand, under the application of pressure to as high as 140 kPa, negligible change in resistance is observed, which can be attributed to the pressure working primarily to close the pores, and hence minimally changing the MWCNT network conformation. Our sensor can easily be coated onto irregularly shaped 3-dimensional objects (e.g. robotic hand) via spray coating, or be attached to human joints, to detect bending motion. Furthermore, our sensor can differentiate between shear stress and normal pressure, and the local strain can be spatially mapped without the use of patterned electrode array using electrical impedance tomography. These demonstrations make our sensor highly useful and important for the future development of high performance tactile sensors.


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There is currently considerable interest and active on-going research in tactile sensors due to their wide-variety of exciting applications such as interactive touch screens, 1-4 robotics with human-like functionalities (humanoids), 5-9 and wearable healthcare devices. 10-18 The two most common tactile inputs measured with tactile sensors are normal pressure and lateral strain; therefore, many devices have been fabricated to measure pressure and strain simultaneously.

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However, many devices yield similar electrical output under both

pressure and strain, making differentiation of these mechanical inputs highly challenging. Differentiation of tactile inputs is often a critical feature in many applications. For instance, for wearable health monitoring applications, differentiating between pressure and strain is necessary to precisely monitor human motion and vital signs. 1, 23-24 A straightforward and facile way to distinguish between pressure and strain is to fabricate a sensor that is sensitive to only one of the two inputs (i.e. mechanically decoupled sensor). Recently, Ro et al. have reported strain insensitive stretchable pressure sensor, which shows a low signal change under lateral strain by using micro-pattern to control local strain.25 On the other hand, strain sensors that specifically demonstrate insensitivity to pressure have rarely been reported. Some previously reported strain sensors could have been insensitive to pressure given their demonstration of application.26 Pressure insensitive strain sensors, if developed, will be important as it can be used with strain insensitive pressure sensors to properly distinguish between pressure and strain. Herein, we demonstrate the design and performance of stretchable pressure insensitive strain (SPIS) sensor based on porous multi-walled carbon nanotube (MWCNT)– polydimethylsiloxane (PDMS) composite, made by all solution-based process. Our SPIS sensor shows nearly no response to pressure (gauge factor = 0.1, at 70 % compressive strain), but high sensitivity to tensile strain (gauge factor = 55.8, at 70 % tensile strain). We attribute such a difference in sensitivity between pressure and strain to the difference in structural 3 ACS Paragon Plus Environment

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change each type of mechanical input induces. We observed that the application of pressure (i.e. compressive strain) simply closes the pores, which does not significantly alter the percolation network of MWCNTs. Therefore, the change in the resistance of the sensor is negligible. On the other hand, under the application of tensile strain, we have observed microcracks forming on the wall of the pores, which induces large change in the MWCNT percolation paths. Hence, a relatively large change in the resistance is observed. Furthermore, due to the porous structure, SPIS sensor shows high stretchability (up to 120 %).14 Our solution-based process is easily scalable to large areas and can be coated as a thin-film on 3dimensional irregularly shaped objects via spray coating. Furthermore, we demonstrate the use of electrical impedance tomography (EIT) to spatially map the local strain without the use of patterned electrode array, greatly simplifying the spatially sensitive sensor fabrication process. These demonstrations make our material and processing technique highly suitable for robotic electronic skin or wearable electronic applications.


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RESULTS AND DISCUSSION

Figure 1. Overview of the stretchable pressure insensitive strain (SPIS) sensor. a) Schematic depiction of the SPIS sensor fabrication process and functionality. b,c) SEM images of the SPIS sensor showing porous structure. d,e) Optical photograph of the SPIS sensor showing stretchability (d) and large area scalability (e). The logo is used with permission from KAIST and Steve Park Research Group. Fabrication of Stretchable Pressure Insensitive Strain sensor. Figure 1a is a schematic depiction of the SPIS sensor fabrication process. Briefly stated, water-in-oil emulsion was made by mixing MWCNT solution (MWCNT and surfactant in DI water: aqueous phase) and PDMS solution (PDMS in hexane: oil phase) under ultrasonication for 30 minutes. The surfactant helps disperse MWCNT in water and stabilizes the small aqueous phase droplets inside the oil phase (see Figure S1a in the Supporting Information). After the ultrasonication process, MWCNT/PDMS mixture was poured into a mold, followed by two sequential heat treatments. Firstly, the mixture was heated at 70 °C for 4 hours to cure the PDMS and 5 ACS Paragon Plus Environment

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evaporate away the PDMS solvent. Secondly, the mixture was heated at 120 °C for 2 hours to evaporate away the DI water to finally form the porous structure. Upon inspection with SEM, the MWCNTs were embedded within the walls of the pores (Figure S1b and S2 in the Supporting Information). Figure 1b and 1c are SEM images showing the porous structure; the pores had mean diameter and standard deviation of 23 µm and 5.28 µm, respectively. (Figure S3 in the Supporting Information). As depicted on the right-hand side of Figure 1a, our sensor is designed to be sensitive to tensile strain (i.e. laterally being stretched), but nonresponsive to compressive strain (i.e. pressure being applied in the vertical direction). Figure 1d shows our SPIS sensor being laterally stretched. Figure 1e shows large area SPIS sensor (11 cm by 9 cm), which can easily be made by scaling up our process to accommodate larger quantities of solution. Since our technique can form porous structure without a template directly from a solution phase, we can use solution-based techniques such as spray coating to generate a film on 3-dimensional irregularly shaped objects (e.g. robotic hand). This is in contrast to many template-based porous structure fabrication techniques using sugar particle,27 polystyrene (PS) beads,28 polyurethane (PU) sponge,29 and Ni foam,3, 16 where fabrication onto 3-dimensional irregularly shaped surfaces is challenging.


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Figure 2. Decoupling the response from tensile and compressive strain. a) Curve of relative change in resistance versus compressive or tensile strain. The inset is a zoom-in of the curve at 0 to 5 % strain. b) Relative change in resistance versus tensile strain curve, with different pressure levels applied at each strain. c,d) SEM images of the SPIS sensor being laterally stretched up to 70 % strain and released back to the original state (c) and being pressed down to 80 % strain and released back to the original state (d). All images were taken at different positions within the sample. Working Principle of SPIS Sensor. Figure 2a depicts a typical response of our sensor due to compressive and tensile strain. The relative change in resistance (∆R/Ro) (where Ro is the initial resistance before deformation and ∆R is the change in resistance induced by deformation) under tensile strain increases to 6.89 at 50 % strain; whereas, ∆R/Ro under 50 % compressive strain increases only slightly to 0.01. Figure 2b and Table S1 in the 7 ACS Paragon Plus Environment

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Supporting Information show negligible change in ∆R/Ro under various pressure levels (up to 140 kPa) at various tensile strains. These demonstrations confirm that our SPIS sensor can accurately detect strain without being interfered by the presence of pressure. We also conducted bending test (Figure S4 in the Supporting Information), which further confirmed that the sensor is highly responsive to tensile bending compared to compressive bending. Figure 2c and 2d are SEM images of the SPIS sensor under different levels of tensile and compressive strain, respectively. All images were taken at different positions within the sample. The leftmost side images of Figure 2c and 2d are images before the application of strains (i.e. initial state); whereas, the rightmost side images are images after the release of strains, back to the initial state. As seen in Figure 2c, the application of tensile strain causes microcracks to occur within the MWCNT network. Interestingly, the microcracks were primarily observed within the surface of the pores and less so in the regions between the pores. We can also observe that the pores are elongated along the direction of strain. We can therefore deduce that tension primarily deforms the pores, thereby creating local high strains in the MWCNT network near the surface of the pores. With increasing strain (from 30 % to 70 % strain), the number of microcracks increases, which results in the reduction of MWCNT network percolation paths, and consequently, an increase in the resistance of the SPIS sensor.30-31 Interestingly, after the release of strain, the microcracks are closed once again, reverting the resistance back to its original value. The situation is vastly different under the application of compressive strain (i.e. pressure). As seen in Figure 2d, rather than forming microcracks, the pores begin to collapse, eventually being closed at 80 % compressive strain. As mentioned above, the resistance of our SPIS sensor undergoes negligible change under compressive strain. On the contrary, previously reported work on piezoresistive porous sensors exhibited rather large change in the resistance with the application of pressure,22, 32-34 where we can presume similar structural 8 ACS Paragon Plus Environment

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change under the application of pressure (i.e. collapsing of pores). These sensors generally had large amounts of conductive material on the surface of the pores; hence, the closing of pores generated extra conductive paths, through which change in resistance is induced. On the other hand, our SPIS sensors only had a small portion of MWCNT protruding out of the surface of the pore walls (i.e. most of the MWCNTs are embedded within the PDMS) (Figure S2 in the Supporting information). Hence, closing of pores only negligibly increases the MWCNT-MWCNT connections. Furthermore, we hypothesize that since pressure dominantly works to close the pores, the MWCNT network within the PDMS undergoes minimal conformational change. Both of the above effects are likely to contribute to the insensitivity of our SPIS sensor to pressure.

Figure 3. The sensing performance of SPIS sensor. a) Relative change in resistance as a function of pressure for samples with different volume percentages of MWCNT solution to 9 ACS Paragon Plus Environment

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PDMS solution. b,c) SEM images of the SPIS sensor at 36 vol% (b) and 57 vol% (c). d) Relative change in resistance versus pressure for samples with different MWCNT weight percentages. Weight percentage is defined as the weight of MWCNT divided by the weight of PDMS x 100 %. e,f) The relative change in resistance (e) and the gauge factor (f) versus tensile strain for samples with different MWCNT weight percentages. g,h) relative change in resistance under repeated application and release of 30 % and 50 % strain under 5 cycles (g) and under 10,000 cycles at 30 % strain (h). i) The response time of resistance change due to the application of small tensile strain. Optimization and Performance of SPIS sensor. We have varied the proportion of each component in our sensor to see its effects on the overall property of the sensor. Figure 3a is a plot of ∆R/Ro versus pressure for sensors made with various volume percentages (vol%) of the MWCNT solution with respect to the PDMS solution. Evidently, lower the volume percentage of MWCNT solution, the higher was the sensor’s response to pressure. As can be seen from the SEM images in Figure 3b and 3c and from micro-CT images from Figure S5 in the Supporting Information, the sample made with 36 vol% MWCNT solution had lower porosity than that of the sample with 57 vol% MWCNT solution. This trend corresponds well to our previously stated hypothesis, in that the higher porosity causes less change in the conformation of the MWCNT network, resulting in lower change in resistance. Figure S6 in the Supporting Information shows that the lateral strain sensitivity increases for samples with lower porosities. We can again attribute this to the porosity causing less conformational change in the MWCNT network, and that the change in resistance due to this effect is higher than the change in resistance due to the crack formation in the MWCNT network along the periphery of the pores. Figure S7 in the Supporting Information shows ∆R/Ro as a function of pressure and strain for sensors of varying thickness from 0.8 mm to 1.4 mm. The samples 10 ACS Paragon Plus Environment

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with higher thickness exhibited higher pressure sensitivity but lower strain sensitivity. When the sensor’s thickness became too thin, the baseline resistance became too large (in the MΩ range) to detect resistance. Hence, considering these factors, 0.7-0.8 mm was deemed the ideal thickness. Figure 3d is a plot of ∆R/Ro as a function of pressure for samples made with different weight percentages (wt%) of MWCNTs in the SPIS sensor (MWCNT:PDMS). The sensors’ response to pressure were all similarly low and did not depend on the weight percentages of the MWCNTs. On the other hand, under tension, the sensor responded differently for samples made with different MWCNT weight percentages (Figure 3e). Such a contrast in response to pressure and strain can again be attributed to the fact that under pressure, the MWCNT network conformation undergoes negligible change; hence, the change in the percolation density of the MWCNT network (due to the change in weight percentage of MWCNT) does not affect the sensitivity of the sensor. On the contrary, the change in the MWCNT network percolation density affects the change in resistance of the sensor under strain, as it affects the relative degree of percolation breakage under microcrack formation. The weight percentage of 0.7 wt% yielded the highest sensitivity, likely because MWCNT network was near the percolation threshold35; higher weight percentages of 0.8 and 1.0 wt% likely oversaturate the MWCNTs in the network. This is supported in Figure S8 in the Supporting Information, as beyond 0.7 wt%, the resistance begins to saturate. The gauge factor versus strain plot (Figure 3f) shows that the sample with 0.7 wt% of MWCNTs reaches gauge factor of ~56 at 70 % strain. Figure S9 in the Supporting Information shows the current level of the sensor under strain from 0 % to 70 %. The gauge factor is relatively high compared to other previously reported strain sensors which used CNT/graphene (gauge factor 2~ 20.5),3 Carbon Nanofiber (gauge factor 1.0 ~6.5),27 and AgNWs/PEDOT:PSS (gauge factor 1.07 ~ 12.4).36


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Figure 3g is ∆R/Ro versus time plot for our SPIS sensor under repeated application and release of strain at 30 % and 50 %. Figure S10 in the Supporting Information is the same plot, when the sensor is stretched under repeated static strain for 3 seconds. Under static strain, we have observed overshooting of resistance initially, and gradual decline of resistance with time. This is due to the viscoelastic nature of PDMS that causes creep behavior, which has been reported previously by Wu et al.27 Figure 3h is the ∆R/Ro versus time plot when the sensor is under 10,000 cycles of strain at 30 %, and Figure S11 in the Supporting Information is the ∆R/Ro versus time plot when the sensor is under cyclic pressure of 80 kPa. Figure 3i shows the response time of 90 ms under the application of strain. These results together confirm reasonable repeatability, durability and temporal response of our SPIS sensor.


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Figure 4. Detecting shear stress and electrical impedance tomography-based SPIS sensor. a,b) Sensor response due to shear stress (a) and pressure (b). c) Photograph of the SPIS sensor with 24 electrodes connect at the periphery of the sensor for electrical impedance tomography analysis. d) Photograph of the SPIS sensor with pressure being applied using a finger. e) Photograph of the SPIS sensor being locally strained using two fingers. f-h) Electrical impedance tomography map corresponding to no pressure or strain applied (f), pressure applied using finger (g), and local strain being applied using two finger (h). The conductivity does not change under pressure; whereas, conductivity locally decreases under strain, 13 ACS Paragon Plus Environment

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resulting in blue coloring of the corresponding region. The area of the SPIS sensor was 11 by 11 cm2. Differentiation of Shear Stress and Local Strain. Figure 4a and 4b are images of our SPIS sensor under manually applied shear stress and normal pressure, respectively. Figure S12 in the Supporting Information shows sensor’s response to shear stress under constant lateral strain.

Since the application of shear stress causes local strain, the sensor responds

with corresponding signal change. Conversely, when normal pressure is applied, negligible response is observed. This can be useful for future robotic applications, as the detection of shear without the interference from normal pressure can enable robots to manipulate delicate objects with precise grasp control.23 Another important aspect to tactile devices is spatial sensitivity. Herein, we demonstrate that the location of local strain can be detected using electrical impedance tomography or EIT.37 EIT is an imaging method that measures the conductivity distribution within a conductive material only using electrodes at the periphery of the material. Using EIT to detect local strain has a few key advantages over that of using patterned electrode array throughout the sensor. Firstly, since no patterning of electrodes is required, EIT-based sensors have a relatively facile processability, especially on 3dimensional surfaces. Secondly, EIT would in principle have superior durability as the electrodes are not directly being mechanically deformed. Figure 4c is an optical image of our SPIS sensor (area: 11 by 11 cm2) with 24 electrodes connected at the periphery. Figure 4d and 4e are images of our sensor under pressure and under strain, respectively. As seen in the conductivity maps in Figure 4f, 4g, and 4h, under pressure, no change in conductivity is detected. However, under strain, conductivity map locally turns blue, indicating that the conductivity decreased in that region. The data acquisition, processing, and image generation was conducted at a frequency of 30 Hz (i.e. time delay of 33 ms). 14 ACS Paragon Plus Environment

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Figure 5. Detecting strain for wearable and robotic applications. a,b) Detection of bending motion of finger (a) and knee (b). c-e) Nozzle printed SPIS sensor on a cotton bandage connected serially to a 9V battery and a LED. d,e) SPIS sensor with a 0.6 kg weight placed on top (d), and under lateral strain (e). f) Before (left) and after (right) spray coating our SPIS sensor solution onto a hand figurine. g) Signal change exhibited when the index finger is repeatedly bent. The logo is used with permission from KAIST and Steve Park Research Group.


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Detection of Strain for Wearable and Robotic Applications. Figure 5a and 5b are images of SPIS sensor films attached on human finger and knee, respectively. Upon repeated bending of finger and knee, corresponding repeated change in signal is observed. Figure 5c is an image of our SPIS sensor printed on a stretchable cotton bandage by nozzle printing; the SPIS sensor was then connected serially to a battery (9V) and a LED diode. The LED that is normally on remains on even when a 0.6 kg weight is placed on top of the SPIS sensor (Figure 5d). On the other hand, when the sensor is laterally stretched (Figure 5e), the LED turns off due to the increase in resistance of the SPIS sensor. The LED reverts back on when strain is relieved. One advantage of our SPIS sensor is that it can easily be coated as a film on 3-dimensional irregularly shaped objects using solution-based process such as spray coating. Such a facile processability has significant implications for future robotics and wearable electronics. As a demonstration, we have spray coated our solution onto a wooden hand model, and subsequently used sequential heat treatments as described above (Figure 5f). We made electrical contacts at the tip and base of the index finger and repeatedly bent the finger, as seen in Figure 5g; evidently, the signal changes with each bending cycle. These demonstrations together verify that our SPIS sensor can potentially be used in wearable devices or as robotic electronic skin to detect motion.

CONCLUSIONS In summary, we report a stretchable pressure insensitive strain (SPIS) sensor by using all solution-based process. Due to the different structural changes induced by compressive and tensile strain, the SPIS sensor shows high sensitivity to strain and negligible response to pressure. The SEM images confirmed that under tensile strain, microcracks form within the MWCNT network; whereas, under compressive strain, pores are being collapsed, resulting in 16 ACS Paragon Plus Environment

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negligible change in the MWCNT network. Our sensors exhibited relatively high gauge factor and repeatability. As a practical demonstration, we have formed a film of our SPIS sensor on a hand figurine, a stretchable cotton bandage, and on human joints to detect bending and strain. We also showed that our device can be used to distinguish between shear stress and normal pressure. In addition, we demonstrate the use of electrical impedance tomography to spatially map the local strain without the use of patterned electrode arrays. We project that the features of our sensor, and the facile and scalable manner in which it can be fabricated, will be highly useful for a wide variety of tactile sensing applications in the near future.

MATERIALS AND METHODS Preparation of PDMS solution. PDMS (sylgard 184, Dow corning, USA) prepolymer solution was prepared by mechanically mixing the base and curing agent in a weight ratio of 10: 1. Next, degassing was performed using a vacuum pump and a desiccator. The PDMS prepolymer solution was mechanically mixed with hexane (Sigma-Aldrich) in a weight ratio of 1: 2 to lower the viscosity. Preparation of MWCNT solution. MWCNT solution was prepared by adding 30 mg of Multi-walled carbon nanotube (Applied Carbon Nano Technology Co., Ltd.), 10 mg of Sodium dodecylbenzenesulfonate (SDBS) (Sigma-Aldrich) surfactant and 10 ml of deionized (DI) water, followed by ultrasonication for 20 min at 30 % amplitude. Unless stated otherwise, MWCNT weight percentage (MWCNT: PDMS) was 0.7 wt%. Formation of mixture. MWCNT solution was poured into the PDMS solution at various volume percentages (MWCNT solution/PDMS solution x 100 %) using micropipette. The 17 ACS Paragon Plus Environment

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solution was then ultrasonicated for 30 minutes at 30 % amplitude to form water-in-oil emulsion. Unless stated otherwise, the MWCNT solution volume percentage was 57 vol%. Fabrication of SPIS sensor. We poured the prepared mixture into a mold and placed conductive mesh that will eventually serve as electrodes into the mixture at various locations. The mixture was heated at 70℃ for 4 hours followed by heating at 120℃ for 2 hours. The strain limit of our sensor was 120 %, and our sensor reliably and repeatedly measured strain up to 70%. The conductive meshes (Shieldex, USA) had average sheet resistance < 1.0 Ohms/□. The conductive mesh is composed of nylon coated with silver. Figure S13 in the Supporting Information shows that the resistance of the conductive mesh changes negligibly under repeated application and release of 70% strain and 100 kPa of pressure. Characterization of SPIS sensor morphology. Images were obtained using scanning electron microscopy (SEM, Hitachi S-4800, Japan). To image the cross-sections of the SPIS sensors, samples were first immersed into liquid nitrogen for a few seconds and cut by razor blade (Doruko). SEM mounts capable of applying compressive and tensile strain were used. Characterization of electrical performance of SPIS sensor. The samples were cut to a width and length of 2 cm and 5 cm, respectively. The samples had thickness of 0.7-0.8 mm. Force gauge (maximum force is 50 N, Mark-10) and stand with motor (strain speed : 0.4 ~ 50 mm/min, Mark -10) was used to apply strain and pressure. Resistance was measured (LCR meter, 4284A, HP) at 1 kHz frequency, 1V voltage and 14 data points per second. Prior to being used as strain sensors, our sensors were pre-strained to 70 %. Characterization of electrical impedance tomography (EIT) based SPIS sensor. A total of 24 electrodes are arranged regularly at the periphery of an 11 cm by 11 cm square-shaped SPIS sensor. Strips of conductive mesh are embedded at the boundary of the SPIS sensor prior to curing. Standard metal-based contacts are clipped to the conductive mesh strips. The 18 ACS Paragon Plus Environment

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conductive mesh enables low-contact resistance between the metal contacts and the SPIS sensor, and minimizes parasitic signal due to the change in contact resistance. EIT hardware system is developed based on FPGA-based embedded controller (NI cRio-9035, National Instruments™, USA), and related programming tool (LabVIEW, National Instruments™, USA). An algorithm is constructed using MATLAB™ EIDORS toolbox (Electrical Impedance and Diffused Optical Reconstruction Software). The conductivity difference distribution was reconstructed without any spatial filter. Due to nonlinear piezoresistive property of SPIS sensor, the estimated conductivity difference was calibrated. Simple linear calibration by multiplying constant was used to match the estimated conductivity difference with the actual conductivity difference based on measured piezoresistive property of the SPIS sensor.

ASSOCIATED CONTENT Supporting Information. Table S1: Numerical analysis on the SPIS sensor performance. (PDF) Figures S1-S13: Schematic diagram of the formation of porous structure; cross-sectional SEM images of SPIS sensor; pore size distribution; relative change in resistance under repeated bending to bending radius of 1.65 mm; µ-CT image of SPIS sensor; gauge factor of the SPIS sensor at different volume percentages of MWCNT solution with respect to PDMS solution.; relative change in resistance of samples with different thickness under pressure and under strain; resistance and performance of the SPIS sensor at different MWCNT weight percentages; current level versus strain of a sample with 0.7 wt.% of MWCNT.; relative change in resistance under repeated static strain of 30 % and 50 %; relative change in resistance under repeated pressure of 80 kPa; the sensor response to shear stress under constant lateral strain.; The resistance of conductive meshes under repeated strain of 70 % and repeated pressure of 100 kPa. (PDF) 19 ACS Paragon Plus Environment

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These materials are available free of charge via the Internet at “http://pubs.acs.org.”

AUTHOR INFORMATION Corresponding Author *E-mail: [email protected] Author Contributions #

Jinwon Oh and #Jun Chang Yang contributed equally to this work

ACKNOWLEDGMENT This work was supported by Institute for Information & Communications Technology Promotion (IITP) grant funded by the Korea government (MSIT) (No.2017-0-00052, Omnisensory smart physical sensor original technology for human body sensing and diagnosis/Hybrid composite load cell soft-sensor original technology) and National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No.2016RlC1B1009949).


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Pressure Insensitive Strain Sensor with Facile Solution-Based Process

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