Epidermis Microstructure Inspired Graphene Pressure Sensor with

Subscriber access provided by Thompson Rivers University | Library

Article

Epidermis Microstructure Inspired Graphene Pressure Sensor with Random Distributed Spinosum for High Sensitivity and Large Linearity Yu Pang, Kunning Zhang, Zhen Yang, Song Jiang, Zhen-Yi Ju, Yuxing Li, Xuefeng Wang, DanYang Wang, Muqiang Jian, Yingying Zhang, Renrong Liang, He Tian, Yi Yang, and Tian-Ling Ren ACS Nano, Just Accepted Manuscript • DOI: 10.1021/acsnano.7b07613 • Publication Date (Web): 29 Jan 2018 Downloaded from http://pubs.acs.org on January 30, 2018

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a free service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are accessible to all readers and citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

ACS Nano is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 32 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Nano

Epidermis Microstructure Inspired Graphene Pressure Sensor with Random Distributed Spinosum for High Sensitivity and Large Linearity Yu Pang†,#, Kunning Zhang†,#, Zhen Yang†, Song Jiang†, Zhenyi Ju†, Yuxing Li†, Xuefeng Wang,† Danyang Wang†, Muqiang Jian‡, Yingying Zhang‡, Renrong Liang, †* He Tian†*, Yi Yang†*, TianLing Ren†* †

Institute of Microelectronics, Tsinghua University, Beijing, 100084, China

‡

Department of Chemistry and Center for Nano and Micro Mechanics (CNMM), Tsinghua

University, Beijing 100084, China

ABSTRACT: Recently, wearable pressure sensors have attracted tremendous attentions because of their potential applications in monitoring physiological signals for human healthcare. The sensitivity and linearity are the two most essential parameters to pressure sensors. Although various designed micro/nano-structure morphologies introduced, the trade-off between sensitivity and linearity can not be well balanced. The human skin that contains force receptors in reticular layer owns high sensitivity even for large external stimulus. Herein, inspired by the skin epidermis with high-performance force sensing we have proposed a special surface

ACS Paragon Plus Environment

1

ACS Nano 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 2 of 32

morphology with spinosum microstructure of random distribution via the combination of abrasive paper template and reduced graphene oxide (rGO). The sensitivity of graphene pressure sensor with random distribution spinosum (RDS) microstructure is as high as 25.1 kPa-1 in a wide linearity range of 0-2.6 kPa. Our pressure sensor exhibits the superior comprehensive properties compared with previous surface modified pressure sensors. According to simulation and mechanism analysis, the spinosum microstructure and random distribution contribute to the high sensitivity and large linearity range respectively. In addition, the pressure sensor shows promising potential in detecting human physiological signals, such as heart beat, respiration, phonation, human motions of pushup, arm bending, and walking. The wearable pressure sensor array was further used to detect gait states of supination, neutral and pronation. The RDS microstructure provides alternative strategy to improve performance of pressure sensors and extend its potential applications in monitoring human activities.

KEYWORDS: pressure sensor, graphene, flexible device, spinosum microstructure, random distribution People have witnessed the considerable development of wearable, flexible and stretchable electronic devices for monitoring physiological signals and motion activities in the past decade. This area exhibits a growth of the fitness market to $5 billion in 2015.1,2 Continuous measuring and quantifying vital physical signals including body temperature, blood pressure, pulse and limb movement provide plenty of valuable information for disease diagnoses, therapy, and rehabilitation. The pressure sensor, as an important transducer among mechanical sensors, is a great interest as revealed by the increasing researches.3-10 Although significant advancement has been achieved to fabricate pressure sensors with high performance, comfortable attachment and


2

Page 3 of 32 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Nano

technological compatibility, the trade-off between sensitivity and linear range remains a huge challenge.11-15 With the development of material science, advanced materials with different morphologies or microstructures have been widely utilized to fabricate temperature sensor, gas sensor, strain sensor and pressure sensor.16-23 Particularly, carbon-based materials in the morphology of carbon black,24 carbon tubes25,26 and graphene27-33 have been used as the sensing elements or conductive fillers in pressure sensors due to their outstanding electrical and mechanical properties. Moreover, different microstructure or nanostructure geometries (pyramid,34-39 nanowires,40-43 hemisphere44-46 and prism47) have been introduced to improve the sensitivity and detectable limitation of planar structured pressure sensors. For example, Lin and co-workers have reported a self-powered pressure sensor based on polydimethylsiloxane (PDMS) pyramid microstructure, which exhibits a large linearity range of 0-2.6 kPa but low sensitivity of 0.31 kPa-1.35 Thus, its application in detecting subtle pressure is limited. Whereas, another work44 reported a piezoresistive pressure sensor with high sensitivity of 15.1 kPa-1 using the interlocked hemisphere structure. However, the linear measuring range is only 0-0.5 kPa, which shows sharply performance degradation for large pressure. Therefore, a pressure sensor with high sensitivity as well as large linearity is beneficial to expand its potential applications. The epidermis that serves as the most important pressure perception tissue in human skin offers inspired strategy for a bionic structure. The reticular layer of the dermis with spinosum surface consists of two types of touch/pressure receptors48 which are extremely sensitive to low-intensity external stimulus. To the best of our knowledge, the spinosum microstructure used in sensor fabrication has not been explored.


3

ACS Nano 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 4 of 32

Bio-inspired by the epidermis tissue structure in human skin, we have prepared the pressure sensors with bionic spinosum microstructure. Based on the employment of abrasive paper as template and graphene as sensing material, the pressure sensor with high sensitivity and large linearly range can be achieved. The experimental and theoretical simulation results of RDS graphene pressure sensor have been established to explore its working mechanism and high performance. Due to the effective interlocking of RDS layers with uniform graphene coating, the pressure sensor shows great potential in detecting human physiological signals, voice and motion activities. It is worth to note that the RDS presents an alternative strategy to

improve other

sensor properties, allowing haptic sensing wearable electronics for healthcare and activity monitoring.

RESULTS AND DISCUSSION Nature often offers the inspiration for the advancement of engineering, especially all sorts of bionic structures for artificial electronic devices. Actually, as a tissue overlapped all over the human body surface, skin is a critical element to sense the surrounding environment variation, such as temperature, humidity and force. For instance, the beneath spinosum surface of dermis that consists of Merkel disk for pressure receptor has highly sensitive response to the impact of object attachment, as shown in Figure 1A. Due to the fact that spinosum microstructure can produce a high and local stress concentration at ridge tips near receptors,49 it plays a major role to afferent stimulus for improved pressure perception. As we can see from Figure 1B-C, the microscopic structure of human epidermis owns similar topography with that of abrasive paper. Bio-inspired by this structure, we used the abrasive paper as template to prepare the spinosum surface with random height distribution. Figure 1D shows the fabrication process of RDS


4

Page 5 of 32 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Nano

pressure sensor. The PDMS was coated on the abrasive paper to get micro-patterned flexible substrate. After dip-coating the graphene oxide (GO), the high temperature was followed to make GO reduced. Finally, a face-to-face package was used to prepare pressure sensors with different roughness surface. The optical images of micro-patterned PDMS substrate using No. 150 abrasive paper is shown in Figure 1E. The morphology of patterned spinosum PDMS shows smoothly interconnected ridges and dispersive holes, and the small roughness abrasive papers No. 280, 400 and 600 displays high density of spinosum surface (Figure S1). In order to obtain uniform GO film with large area, the surface treatment was performed by oxygen plasma to decrease the contact angle (Figure S2). Figure 1F shows a claybank color photograph for the GO/PDMS while a brownish color under the microscope, which is also found in small roughness samples (Figure S3). Noted that some deep brownish color area is appeared, indicating thick GO layer located at the bottom surface of concave. After high temperature reduction, Figure 1G shows that the color of rGO becomes dark while modena under the microscope. The photos of other three rGO/PDMS samples (Figure S4) with small roughness clearly shows that uniform graphene has covered on the PDMS surface. Figure 2A shows a typical three dimensional (3D) image of a micro-patterned PDMS using abrasive No. 600, indicating non-uniform height distribution within the range of 0-30 µm for the spinosum PDMS (Figure 2B). In addition, the height probability distribution in Figure 2C exhibits a random distribution that is colse to normal distribution with center height around 14 µm. The 3D images for the patterned PDMS using abrasive No. 150, 280, and 400 (Figure S5) shows the maximum heights of 120, 60, and 40 µm, respectively. Due to the fixed focus of microscope, the statistical results of probability distribution in those samples displays some degree of distortion for the large roughness samples. The Raman spectrum of the micro-patterned


5

ACS Nano 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 6 of 32

PDMS (Figure 2D) shows that the substrate owns three characteristic peaks around 860, 1260, and 1410 cm-1, corresponding to the symmetric rocking, symmetric bend, and asymmetric bend of CH3, respectively.50 After the GO coating, it shows an obvious peak around 1593 cm-1 which belongs to G-band of graphene. The peak shows a slight red shift to 1600 cm-1 when the GO reduced at high temperature, which also observed in previous work.51 Moreover, a subtle peak of graphene D-band around 1350 cm-1 can be identified because of overlap of characteristic peaks between PDMS and graphene, revealing little defects or heteroatom doping in graphene layer. Figure 2E shows the scanning electron microscopy (SEM) of the rGO/PDMS structure using abrasive paper No. 600. The holes with tens of microns distribute all over the surface, which becomes larger in large rough rGO/PDMS samples (Figure S6). The magnified SEM images in Figure 2F shows that crumpled graphene layer with some cracks evenly covers on the spinosum PDMS surface, which may contribute to the resistance variation. The rGO thickness is about 500 nm as shonwn in magnified SEM image (Figure 2G). The pressure sensor made from rGO coated spinosum surface exhibits high sensitivity and large linearity. Figure 3A shows the relative resistance variation versus pressure of RDS graphene pressure sensor. As we can see that the RDS pressure sensors clearly exhibit two linear resistance segments, a sharp decrease in low pressure range and a gradually decrease in high pressure range. The sensitivity which expresses as (R0-R)/(R0·P) is usually used to evaluate the performance of pressure sensor, where R and R0 are initial resistance and resistance under applied pressure, respectively. For the RDS pressure sensor prepared using abrasive paper No. 150-400, the calculated sensitivity is 25.1 kPa-1 in the range of 0-2.6 kPa, while a value of 0.45 kPa-1 in the high pressure range. Noted that the RDS pressure sensors prepared using abrasive paper No. 150-280 and No. 150-600 have higher sensitivity but narrow linearity range than that


6

Page 7 of 32 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Nano

of pressure sensor using No.150-400. And the calculated sensitivities are 30.3 kPa-1 and 27.5 kPa-1 in pressure range of 0-1.1 and 0-2.1 kPa, respectively. For the high pressure range, the calculated sensitivity of RDS pressure sensors prepared using abrasive paper No. 150-280 and No. 150-600 are 0.18 and 0.68 kPa-1, respectively. Generally, the tradeoff between sensitivity and linearity is necessarily considered for each special application. Namely, the high sensitivity means low measuring linear range or vice versa. Therefore, the relationship of sensitivity and linearity usually distributes in a shape of “L” area, as shown in Figure 3B. It can be clearly seen that compared with other patterned surface pressure sensors the RDS graphene pressure sensor displays the excellent performance with both high sensitivity and large linear range (Table S1). The working mechanism and simulation in detail will be discussed to explain the superior properties later. We suppose that the high sensitivity in large linear range is crucial for their extensive applications to detect subtle and medium pressure. To investigate the detection limit of pressure sensor, Figure 3C shows that the pressure sensor can detect the subtle pressure of 16 Pa and 35 Pa for rice and drawing pin, respectively. Moreover, the response time of RDS pressure sensor is shown in Figure 3D. It can be seen that the rise time and drop time are 120 ms and 80 ms, respectively, indicating a faster resistance signal variation for force unloading than force loading process. The hysteresis of response time mainly attributes to elastic recovery of PDMS substrate. Besides, the relative resistance variation of RDS pressure sensor exhibits high stability and durability under both small (Figure 3E) and large pressure loading (Figure S7). The magnified insets clearly show that there is no obvious degeneration during the whole cyclic process, which is great important for long-period usage. To understand the working mechanism of RDS graphene pressure sensor, we observed the gap variation between the two layers during loading process. As shown in Figure 4A, the initial


7

ACS Nano 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 8 of 32

interface of pressure sensor shows few contact under the unloading state. Thus, a high initial resistance is obtained for its starting state. We have investigated the interfacial contact status under light and heavy loading. It can be seen from Figure 4B that the gap between the top and bottom rGO/PDMS layers exhibits sharp decrease for light loading. The contact area would exhibit dramatic enhancement due to the effective interlocking between the small and large roughness surface. Therefore, a sharp resistance decrease and a high sensitivity can be obtained, which agrees well with the experimental results within low pressure range. Under heavy loading (Figure 4C), the subtle peaks of RDS contribute to the further decrease of contact resistance but a slow increase of contact interface and a low sensitivity at high pressure range. To understand the resistance variation during loading process, a circuit model has been supposed to describe the resistance contribution. The total resistance can be calculated as following equation: ୖ ୖ

R = ܴ௛ + ୖ ౙభାୖౙమ ౙభ

(1)

ౙమ

where Rh, Rc1, Rc2 are the resistance in the hole, resistance of contact interfaces, and cracks in the rGO, respectively. The Rh can not contact with another surface during the whole loading process, and shows a constant value. Under the light loading within tens of microns, the Rc1 mainly contributes to the total resistance as result of sharp increase of contact interface while the Rc2 is neglected. Thus, the equation in the low pressure range can be simplified as following: R=Rh+Rc1

(2)

Under the heavy loading, the Rc1 has no dramatic increase due to the high Poisson ratio of 0.5 for the PDMS substrate.52 The rGO cracks covered on micro-patterned PDMS surface would has more effective interconnection during the heavy compress, which becomes the main contribution to the further decrease of resistance.


8

Page 9 of 32 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Nano

Generally, the sharp structures are beneficial to enhancement of sensitivity due to the dramatically increased contact area under small applied force. However, the sensitivity of pressure sensor displays sharp decrease when the further deformation takes place, leading to nonlinearity and fast saturation. Considering the comprehensive performance to sensor applications, the high sensitivity within large linearity range is most desirable. To investigate the pressure distribution for pressure sensors with different surface geometries, we have simulated the pressure distribution under light and heavy applied force. Figure 4D-G shows the pressure distribution after loading of 5 kPa for pyramid, hemi-sphere, nanowire and RDS structures, respectively. As we can see that the pyramid and hemi-sphere structures owns the stress concentration on their top cusp area, while the nanowire displays homogeneous pressure distribution along the altitude direction. Interestingly, the stress of RDS structure concentrates on the initial contact peak and can transmit to root segment of adjacent peaks, indicating a small deformation under low pressure range. The simulated results for the four structures under high pressure (Figure S8) shows that the RDS exhibits more homogeneous pressure distribution than those of other three regular morphologies. In order to get a quantified results of sensing performance for different surface shapes, the Matlab model of the resistance variation under pressure loading was established. Based on the discussion above, the enhanced contact area brings more conductive paths for the current with the applied pressure increasing. Also, the contact area changes with the structure compressing caused by the pressure. Firstly, the structure model of pyramid, hemi-sphere, nanowire and RDS structures is established, by defining a height distribution matrix for each structure. Secondly, the element of the contact area is selected under different compressing degree. Each element can be considered as a small resistance and the total resistance can be considered as these resistances


9

ACS Nano 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 10 of 32

with parallel connection. Then we can get the relation of resistance and structure compressing degree for pyramid, hemi-sphere, nanowire and RDS structures. By inputting the relation of compressing degree and pressure got from the experiment, the relation of resistance and pressure of the four structure is shown in Figure 4H. The RDS pressure sensor exhibits the highest sensitivity and the broadest linearity range than other surface microstructures, which is coincident with the experimental results. On one hand, the pressure sensors with sharp microstructures display much higher sensitivity compared with that of flat microstructure or unstructured sensors due to the rapidly enhancement of contact area in the low pressure range.36,40 Thus the spinosum microstructure is beneficial to the high sensitivity of graphene pressure sensor. On another hand, the surface treated microstructure usually can induce large yield strength and get wide linear range between strain and stress.53 Thus, large deformation and increased pressure range can be obtained in RDS microstructure. During the pressure increasing, the resistance variation of uniform distribution with constant contact points mainly attributes to enhancement of contact area, which can easily achieve saturation in small deformation and loading force. Although the initial contact points of random distribution structure firstly show saturation under certain pressure, the new contact points induced sharp increased contact area can compensate to the whole resistance variation. Therefore, the relative resistance variation still exhibits a linearity within the large pressure range. It can be concluded that the spinosum microstructure with sharp morphology mainly contributes to the high sensitivity, while the random distribution mainly contributes to the large linear range due to its gradual decreasing distribution of spinosum height for the force loading. Owing to the excellent high sensitivity, the RDS pressure sensor exhibits tremendous utility for the detection of human physiological signals, voice and motion activities. Before the


10

Page 11 of 32 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Nano

physiological signals detection, we have evaluated the breathability and durability of graphene pressure sensor. After the pressure sensor was attached on the volunteer’s arm skin for two days, the volunteer felt no obvious uncomfortable and allergic contact but light stamp below the area of pressure sensor (Figure S9). Moreover, the durability of RDS graphene pressure sensor has been tested using steel rod under a pressure of about 200 kPa. After the pressure sensor was impacted for 50 times, the reduced graphene layers show no desquamation and damage (Figure S10). The heart rate is the frequency of cardiac cycles induced by the heart muscle contracts and pumps blood from the chambers into the arteries, which is one of the important vital sign and capable of evaluating the physical and mental state of a person. Figure 5A shows a graphene pressure sensor attached on the wrist by a medical tape to detect the wrist pulse. It can be seen that the heart rate is clearly measured by the RDS pressure sensor from the radial artery of wrist (Figure 5B). The pulse can be calculated by the interval between two systolic peaks, showing an interval of 0.85 s and beats per minute of ~70. Moreover, due to the high sensitivity of RDS pressure sensor it exhibits the ability to detect the weak pulse on the finger tips (Figure S11). The magnification of a single peak clearly exhibits the details of finger pulse condition, where are the percussion wave (P-wave) and diastolic wave (D-wave), indicating potential applications in vital signal monitoring. Moreover, the RDS graphene pressure sensor exhibits the ability to monitor respiration states. In the inset of Figure 5C shows a pressure sensor attached to the human chest area. It can be seen that the person has a normal respiratory rate of 18 per minute and a clear smooth peak for every time breathing, whereas the intensity displays an enhancement and the signal shape shows a square-like wave for the deep breathing. Interestingly, the flat waveband indicates the maintain time after deep breathing, which is different from other reports with sharp


11

ACS Nano 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 12 of 32

peaks.54,55 It can be concluded that the RDS graphene pressure sensor shows excellent ability for healthcare monitoring of vital signals. Besides, the voice and phonation signals could also be recognized by the RDS pressure sensor. Figure 5D shows a pressure sensor fixed on the Ecoflex surface and put it above the loudspeaker. As shown in Figure 5E, we observed that the pressure sensor can exhibit signal distinction for the American pronunciation and British pronunciation of word “graphene”, as well as the word “sensor” (Figure S12). The magnified image in the inset clear shows that both pronunciations have two characteristic subtle peaks, indicating not only the capability to identify different accents but also the stress of syllable. In addition, the pressure sensor can also be attached on the throat to monitor the muscle movement caused by the phonation (Figure S13). The output signals of pressure sensor exhibit repeatable characteristic peaks for the pronunciation of “graphene” and “sensor”. Both characteristic peaks show subtle peaks for each pronunciations, indicating high sensitivity to accent identification. The RDS graphene pressure sensor also shows the ability to recording the sentence signals (Figure S14), indicating good stability and signal feature for different words. In addition, the pressure sensor can also response to the other natural sounds, such as the bird chirp, deer bleat, temple bell and ceramic peening (Figure S15). Therefore, the RDS graphene pressure sensor owns superior ability of sound and word identification, which shows potential capability in the man-machine interaction. Furthermore, the RDS graphene pressure sensor exhibits excellent ability to detect the huge deformation of person motions. Figure 5F shows a pressure sensor attached on the heel by the medical tape to detect the walking states. As shown in Figure 5G, the pressure sensor displays different signal shapes and intensities for walking, running and jumping. The normal walking state has square wave signal response, about one second for each time of foot lifting and foot


12

Page 13 of 32 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Nano

landing, and walking stride frequency of 60 per minute. Whereas, for running state the stride frequency increases up to 120 per minute, and sharp peaks of enhanced signal intensity can be observed. Moreover, the pressure sensor displays a distinguishable response signal for jumping state. Apart from the impulse peaks for foot landing, the hanging time of about 0.4s can be clearly observed, indicating superior capability to investigate detail information of walking state recognition. Usually, the human foot gait refers to locomotion achieved through the movement of human walking, which can be caused by the neurologic diseases, arthritis and acquired foot deformities.56 The three typical types of foot gait are shown in Figure 5H, including supination, neutral and pronation. Because of the stress concentration located on the calcaneus, first metatarsal and fifth metatarsal, three pressure sensors were fixed on those corresponding sites of insole for gait detection (Figure 5I). The system design of gait detection is shown in Figure 5J, which mainly consists of sensor array, microprocessor and computer for data recording. As we can see from Figure 5K-M, the resistance variations show different signal shapes and intensities for three gait states. For the neutral gait, the sensor 1 exhibits the largest resistance change due to human weight mainly acts on the heel, while a decreased intensity and smooth peaks from supination to pronation. However, the intensity of sensor 2 shows a gradual enhancement from neutral to supination and to pronation, indicating a clear transfer of human barycenter. Although the intensities of sensor 3 have no obvious variation for different gaits, they show entirely different shapes for neutral, supination and pronation. When comprehensive considering detected signals of both intensity and shape variation, we suppose that the three types of gait states can be distinguished. Moreover, the RDS pressure sensor attached on the palm and brachioradialis shows signal variation for the human push-up and arm bending (Figure S16), which exhibits great performance to detect the various grass motion movements.


13

ACS Nano 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 14 of 32

CONCLUSIONS Inspired by the human skin for high-performance haptic sensing, we have fabricated wearable graphene pressure sensors with combination of spinosum surface microstructure and random height distribution based on the abrasive paper template. These structural designs, material and method allow the following advantages: (1) the low cost, simple-steps and soft/wearable graphene pressure sensors with spinosum structure can be obtained, and shows random height distribution compared with previous surface structures; (2) both high sensitivity and large linearity can be achieved simultaneously due to the contribution of spinosum microstructure and random distribution, respectively; (3) The RDS graphene pressure sensors are promising wearable electronics to detect subtle and large motions for human healthcare monitoring. In summary, we have demonstrated a highly sensitive and large linear range pressure sensor inspired by the skin epidermis. By using the abrasive paper as template and thermal reduction method, a simple and low-cost fabrication process was presented to prepare RDS graphene pressure sensor. The height probability distribution of pressure sensor exhibits a random distribution. The sensitivity of pressure sensor is as high as 25.1 kPa-1 with a linearity range up to 2.6 kPa. Due to the effective interlocking of RDS structure between large and small roughness as proved by both experimental and simulation results, the pressure sensor shows an excellent comprehensive performance than other patterned surface pressure sensors. The pressure sensor exhibits promising potential in detection of physiological activities, such as human healthcare monitoring, voice, phonation identification, and motion movement. The RDS can be applied in fabrication of capacitive and piezoelectric pressure sensors, which may contribute to their superior sensing properties. MATERIALS AND METHODS


14

Page 15 of 32 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Nano

Fabrication of RDS graphene pressure sensors. Commercial abrasive papers with four roughness No. 150, 280, 400 and 600 were utilized as templates. The polydimethylsiloxane (PDMS, Sylgard 184, Dow Corning) prepolymer was prepared by mixing base silicone gel well with a curing agent in a weight ratio of 10:1. After vacuumized the mixture for 30 min in chamber, the mixture was toppled on the abrasive paper surface to naturally form a thin film. Then, they cured on the hotplate at temperature of 100 ºC for 1h. To enhance the dispersion of GO (XFNANO, Materials Tech CO. Ltd) the tetrahydrofuran (A.R., Peking Reagent) was added into GO solution with a volume ratio of 1:5. Before the dip coating GO layer on the PDMS surface, the oxygen plasma was carried out to decrease the contact angle. The peeled and cut PDMS was dipped and dried at 60 ºC, and repeat this procedure for three times to get uniform GO layer. Finally, all samples were put in the heating chamber at 200 ºC for 2 h to reduce the GO. The obtained samples ware cut into rectangular shape and connected to copper wire at one end of the pieces with silver paste. The pressure sensor can be fabricated by face-to-face package of different roughness rGO/PDMS samples. Characterization of morphology and performance for RDS graphene pressure sensors. The morphology and structure of fabricated sensors were characterized by the optical microscope (Olympus MX61), 3D imaging system (SENSOFAR AVIT5), and field emission SEM (Quanta 450 FEG, FEI Inc.). Raman spectra was carried out using the wavelength of 514.5 nm laser (Lab Ram Infinity Raman). The contact angle was performed with the contact angle analyzer (OCA15Pro, Dataphysics). The loading of applied force was carried out with a testing machine (SHIMADZU AGS-X), while the electrical signals of the pressure sensors were recorded at the same time by a digital electrometer (RIGOL DM 3068). ASSOCIATED CONTENT


15

ACS Nano 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 16 of 32

Supporting Information. The following files are available free of charge on the ACS Publications Website. Additional information and figures (PDF) AUTHOR INFORMATION Corresponding Authors *

E-mail: [email protected]

*


*


*


Author Contributions #

Y. Pang and K. Zhang contributed equally to this work.

Notes The authors declare no competing financial interest. ACKNOWLEDGMENT This work was supported by National Key R&D Program (2016YFA0200400), National Natural Science Foundation (61574083, 61434001), National Basic Research Program (2015CB352101), Special Fund for Agroscientific Research in the Public Interest of China (201303107), and Rese arch Fund from Beijing Innovation Center for Future Chip. The author also thankful for the support of the Independent Research Program of Tsinghua University (2014Z01006), and


16

Page 17 of 32 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Nano

Shenzhen Science and Technology Program (JCYJ20150831192224146). We thank Dr. Yi Zhao at Beijing Tsinghua Changgeng Hospital for his help to observe the microscopy of human skin. REFERENCES (1) Khan, Y.; Ostfeld, A. E.; Lochner, C. M.; Pierre, A.; Airas, A. C. Monitoring of Vital Signs with Flexible and Wearable Medical Devices. Adv. Mater. 2016, 28, 4373-4395. (2) Trung, T. Q.; Lee, N. E. Flexible and Stretchable Physical Sensor Integrated Platforms for Wearable Human-Activity Monitoring and Personal Healthcare. Adv. Mater. 2016, 28, 43384372. (3) Dagdeviren, C.; Su, Y.; Joe, P.; Yona, R.; Liu, Y.; Kim, Y.-S.; Huang, Y.; Damadoran, A. R.; Xia, J.; Martin, L. W.; Huang, Y.; Rogers, J. A. Conformable Amplified Lead Zirconate Titanate Sensors with Enhanced Piezoelectric Response for Cutaneous Pressure Monitoring. Nat. Commun. 2014, 5, 4496. (4) Wu, W.; Wen, X.; Wang, Z. L. Taxel-Addressable Matrix of Vertical-Nanowire Piezotronic Transistors for Active and Adaptive Tactile Imaging. Science 2013, 340, 952-957. (5) Yao, H. B.; Ge, J.; Wang, C. F.; Wang, X.; Hu, W.; Zheng, Z. J.; Ni, Y.; Yu, S. H. A Flexible and Highly Pressure-Sensitive Graphene–Polyurethane Sponge Based on Fractured Microstructure Design. Adv. Mater. 2013, 25, 6692-6698. (6) Pan, L.; Chortos, A.; Yu, G.; Wang, Y.; Isaacson, S.; Allen, R.; Shi, Y.; Dauskardt, R.; Bao, Z. An Ultra-Sensitive Resistive Pressure Sensor Based on Hollow-Sphere Microstructure Induced Elasticity in Conducting Polymer Film. Nat. Commun. 2014, 5, 3002.


17

ACS Nano 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 18 of 32

(7) Kim, J.; Kim, M.; Lee, M.; Kim, K.; Ji, S.; Kim, Y.; Park, J.; Na, K.; Bae, K.; Kim, H. K.; Bien, F.; Lee, C.; Park, J. Wearable Smart Sensor Systems Integrated on Soft Contact Lenses for Wireless Ocular Diagnostics. Nat. Commun. 2017, 8, 14997. (8) Yeom, C.; Chen, K.; Kiriya, D.; Yu, Z.; Cho, G.; Javey, A. Large-Area Compliant Tactile Sensors using Printed Carbon Nanotube Active-Matrix Backplanes. Adv. Mater. 2015, 27, 1561-1566. (9) Zang, Y.; Zhang, F.; Huang, D.; Gao, X.; Di, C. A.; Zhu, D. Flexible Suspended Gate Organic Thin-Film Transistors for Ultra-Sensitive Pressure Detection. Nat. Commun. 2015, 6, 6269. (10) Wang, X.; Que, M.; Chen, M.; Han, X.; Li, X.; Pan, C.; Wang, Z. L. Full Dynamic-Range Pressure Sensor Matrix Based on Optical and Electrical Dual-Mode Sensing. Adv. Mater. 2017, 29, 1605817. (11) Wang, C.; Li, X.; Gao, E.; Jian, M.; Xia, K.; Wang, Q.; Xu, Z.; Ren, T.; Zhang, Y. Carbonized Silk Fabric for Ultrastretchable, Highly Sensitive, and Wearable Strain Sensors. Adv. Mater. 2016, 28, 6640-6648. (12) Ryu, S.; Lee, P.; Chou, J. B.; Xu, R.; Zhao, R.; Hart, A. J.; Kim, S. G. Extremely Elastic Wearable Carbon Nanotube Fiber Strain Sensor for Monitoring of Human Motion. ACS Nano 2015, 9, 5929-5936. (13) Cheng, Y.; Wang, R.; Sun, J.; Gao, L. A Stretchable and Highly Sensitive Graphene-Based Fiber for Sensing Tensile Strain, Bending, and Torsion. Adv. Mater. 2015, 27, 7365-7371.


18

Page 19 of 32 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Nano

(14) Choong, C.-L.; Shim, M.-B.; Lee, B.-S.; Jeon, S.; Ko, D.-S.; Kang, T.-H.; Bae, J.; Lee S. H.; Byun, K.-E.; Im, J.; Jeong, Y. J.; Park, C. E.; Park, J.-J.; Chung, U. I. Highly Stretchable Resistive Pressure Sensors using a Conductive Elastomeric Composite on a Micropyramid Array. Adv. Mater. 2014, 26, 3451-3458. (15) Zhao, J.; Wang, G.; Yang, R.; Lu, X.; Cheng, M.; He, C.; Xie, G.; Meng, J.; Shi, D.; Zhang, G. Tunable Piezoresistivity of Nanographene Films for Strain Sensing. ACS Nano 2015, 9, 1622-1629. (16) Webb, R. C.; Bonifas, A. P.; Behnaz, A.; Zhang, Y.; Yu, K. J.; Cheng, H.; Shi, M.; Bian, Z.; Liu, Z.; Kim, Y.-S.; Yeo, W.-H.; Park, J. S.; Song, J.; Li, Y.; Huang, Y.; Gorbach, A. M.; Rogers, J. A. Ultrathin Conformal Devices for Precise and Continuous Thermal Characterization of Human Skin. Nat. Mater. 2013, 12, 938. (17) Yun, J.; Lim, Y.; Jang, G. N.; Kim, D.; Lee, S. J.; Park, H.; Hong, S. Y.; Lee, G.; Zi, G.; Ha, J. S. Stretchable Patterned Graphene Gas Sensor Driven by Integrated Micro-Supercapacitor Array. Nano Energy 2016, 19, 401-414. (18) Chen, S.; Lou, Z.; Chen, D.; Jiang, K.; Shen, G. Polymer-Enhanced Highly Stretchable Conductive Fiber Strain Sensor Used for Electronic Data Gloves. Adv. Mater. Tech. 2016, 1, 1600136. (19) Lee, S.; Reuveny, A.; Reeder, J.; Lee, S.; Jin, H.; Liu, Q.; Yokota, T.; Sekitani, T.; Isoyama, T.; Abe, Y.; Suo, Z.; Someya T. A Transparent Bending-Insensitive Pressure Sensor. Nat. Nanotech. 2016, 11, 472-478.


19

ACS Nano 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 20 of 32

(20) Kim, G.; Cho, S.; Chang, K.; Kim, W. S.; Kang, H.; Ryu, S. P.; Myoung, J.; Park, J.; Park, C.; Shim, W. Spatially Pressure-Mapped Thermochromic Interactive Sensor. Adv. Mater. 2017, 29, 1606120. (21) Pang, C.; Lee, G. Y.; Kim, T.; Kim, S. M.; Kim, H. N.; Ahn, S. H.; Suh, K. Y. A Flexible and Highly Sensitive Strain-Gauge Sensor using Reversible Interlocking of Nanofibres. Nat. Mater. 2012, 11, 795-801. (22) Park, H.; Jeong, Y. R.; Yun, J.; Hong, S. Y.; Jin, S.; Lee, S. J.; Zi, G.; Ha, J. S. Stretchable Array of Highly Sensitive Pressure Sensors Consisting of Polyaniline Nanofibers and AuCoated Polydimethylsiloxane Micropillars. ACS Nano. 2015, 9, 9974-9985. (23) Shao, Q.; Niu, Z.; Hirtz, M.; Jiang, L.; Liu, Y.; Wang, Z.; Chen, X. High-Performance and Tailorable Pressure Sensor Based on Ultrathin Conductive Polymer Film. Small. 2014, 10, 1466-1472. (24) Lu, N.; Lu, C.; Yang, S.; Rogers, J. Highly Sensitive Skin-Mountable Strain Gauges Based Entirely on Elastomers. Adv. Funct. Mater. 2012, 22, 4044-4050. (25) Chen, H.; Su, Z.; Song, Y.; Cheng, X.; Chen, X.; Meng, B.; Song, Z.; Chen, D.; Zhang, H. Omnidirectional Bending and Pressure Sensor Based on Stretchable CNT-PU Sponge. Adv. Funct. Mater. 2017, 27, 1604434. (26) Habibi, M.; Darbari, S.; Rajabali, S.; Ahmadi, V. Fabrication of a Graphene-Based Pressure Sensor by Utilising Field Emission Behavior of Carbon Nanotubes. Carbon 2016, 96, 259267.


20

Page 21 of 32 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Nano

(27) Song, X.; Sun, T.; Yang, J.; Yu, L.; Wei, D.; Fang, L.; Lu, B.; Du, C.; Wei, D. Direct Growth of Graphene Films on 3D Grating Structural Quartz Substrates for High-Performance Pressure-Sensitive Sensors. ACS Appl. Mater. Inter. 2016, 8,16869-16875. (28) Pang, Y.; Tian, H.; Tao, L.; Li, Y.; Wang, X.; Deng, N.; Yang, Y.; Ren, T. Flexible, Highly Sensitive, and Wearable Pressure and Strain Sensors with Graphene Porous Network Structure. ACS Appl. Mater. Inter. 2016, 8, 26458-26462. (29) Smith, A. D.; Niklaus, F.; Paussa, A.; Schröder, S.; Fischer, A. C.; Sterner, M.; Wagner, S.; Vaziri, S.; Forsberg, F.; Esseni, D.; Östling, M.; Lemme, M. C. Piezoresistive Properties of Suspended

Graphene

Membranes

Under

Uniaxial

and

Biaxial

Strain

in

Nanoelectromechanical Pressure Sensors. ACS Nano 2016, 10, 9879-9886. (30) Chen, Z.; Ming, T.; Goulamaly, M. M.; Yao, H.; Nezich, D.; Hempel, M.; Hofmann, M.; Kong, J.

Enhancing the Sensitivity of Percolative Graphene Films for Flexible and

Transparent Pressure Sensor Arrays. Adv. Funct. Mater. 2016, 26, 5061-5067. (31) Shin, S. H.; Ji, S.; Choi, S.; Pyo, K. H.; An, B. W.; Park, J.; Kim, J.; Kim, J.; Lee, K.; Kwon, S.; Heo, J.; Park, B.; Park, J. Integrated Arrays of Air-Dielectric Graphene Transistors as Transparent Active-Matrix Pressure Sensors for Wide Pressure Ranges. Nat. Commun. 2017, 8, 14950. (32) Qiu, L.; Coskun, M. B.; Tang, Y.; Liu, J. Z.; Alan, T.; Ding, J.; Truong, V.; Li, D. Ultrafast Dynamic Piezoresistive Response of Graphene-Based Cellular Elastomers. Adv. Mater. 2016, 28, 194-200.


21

ACS Nano 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 22 of 32

(33) Bae, G. Y.; Pak, S. W.; Kim, D.; Lee, G.; Kim, D. H.; Chung, Y.; Cho, K. Linearly and Highly Pressure-Sensitive Electronic Skin Based on a Bioinspired Hierarchical Structural Array. Adv. Mater. 2016, 28, 5300-5306. (34) Boutry, C. M.; Nguyen, A.; Lawal, Q. O.; Chortos, A.; Rondeau-Gagné, S.; Bao, Z. A Sensitive and Biodegradable Pressure Sensor Array for Cardiovascular Monitoring. Adv. Mater. 2015, 27, 6954-6961. (35) Lin, L.; Xie, Y.; Wang, S.; Wu, W.; Niu, S.; Wen, X.; Wang, Z. L. Triboelectric Active Sensor Array for Self-Powered Static and Dynamic Pressure Detection and Tactile Imaging. ACS Nano 2013, 7, 8266-8274. (36) Mannsfeld, S. C. B.; Tee, B. C. K.; Stoltenberg, R. M.; Chen, C. V. H-H.; Barman, S.; Muir, B. V. O.; Sokolov, A. N.; Reese, C.; Bao, Z. Highly Sensitive Flexible Pressure Sensors with Microstructured Rubber Dielectric Layers. Nat. Mater. 2010, 9, 859-864. (37) Pang, C.; Koo, J. H.; Nguyen, A.; Caves, J. M.; Kim, M.; Chortos, A.; Kim, K.; Wang, P. J.; Tok, J. B.; Bao, Z. Highly Skin-Conformal Microhairy Sensor for Pulse Signal Amplification. Adv. Mater. 2015, 27, 634-640. (38) Tee, B. C. K.; Chortos, A.; Dunn, R. R.; Schwartz, G.; Eason, E.; Bao, Z. Tunable Flexible Pressure Sensors using Microstructured Elastomer Geometries for Intuitive Electronics. Adv. Funct. Mater. 2014, 24, 5427-5434. (39) Zhu, B.; Niu, Z.; Wang, H.; Leow, W. R.; Wang, H.; Li, Y.; Zheng, L.; Wei, J.; Huo, F.; Chen, X. Microstructured Graphene Arrays for Highly Sensitive Flexible Tactile Sensors. Small 2014, 10, 3625-3631.


22

Page 23 of 32 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Nano

(40) Ha, M.; Lim, S.; Park, J.; Um, D.; Lee, Y.; Ko, H. Bioinspired Interlocked and Hierarchical Design of ZnO Nanowire Arrays for Static and Dynamic Pressure-Sensitive Electronic Skins. Adv. Funct. Mater. 2015, 25, 2841-2849. (41) He, W.; Li, G.; Zhang, S.; Wei, Y.; Wang, J.; Li, Q.; Zhang, X. Polypyrrole/Silver Coaxial Nanowire Aero-Sponges for Temperature-Independent Stress Sensing and Stress-Triggered Joule Heating. ACS Nano 2015, 9, 4244-4251. (42) Joo, Y.; Byun, J.; Seong, N.; Ha, J.; Kim, H.; Kim, S.; Kim, T.; Im, H.; Kim, D.; Hong, Y. Silver Nanowire-Embedded PDMS with a Multiscale Structure for a Highly Sensitive and Robust Flexible Pressure Sensor. Nanoscale. 2015, 7, 6208-6215. (43) Wang, J.; Jiu, J.; Nogi, M.; Sugahara, T.; Nagao, S.; Koga, H.; He, P.; Suganuma, K. A Highly Sensitive and Flexible Pressure Sensor with Electrodes and Elastomeric Interlayer Containing Silver Nanowires. Nanoscale 2015, 7, 2926-2932. (44) Park, J.; Lee, Y.; Hong, J.; Ha, M.; Jung, Y.; Lim, H.; Kim, S. Y.; Ko, H. Giant Tunneling Piezoresistance of Composite Elastomers with Interlocked Microdome Arrays for Ultrasensitive and Multimodal Electronic skins. ACS Nano 2014, 8, 4689-4697. (45) Park, J.; Kim, M.; Lee, Y.; Ko, H. Fingertip Skin–Inspired Microstructured Ferroelectric Skins Discriminate Static/Dynamic Pressure and Temperature Stimuli. Sci. Adv. 2015, 1, e1500661. (46) Lee, K. Y.; Yoon, H. J.; Jiang, T.; Wen, X.; Seung, W.; Kim, S. W.; Wang, Z. L. Fully Packaged Self-Powered Triboelectric Pressure Sensor using Hemispheres-Array. Adv. Energy Mater. 2016, 6, 1502566.


23

ACS Nano 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 24 of 32

(47) Wang, X.; Gu, Y.; Xiong, Z.; Cui, Z.; Zhang, T. Silk-Molded Flexible, Ultrasensitive, and Highly Stable Electronic Skin for Monitoring Human Physiological Signals. Adv. Mater. 2014, 26, 1336-1342. (48) Gauglitz, G. G.; Schauber, J. Skin: Architecture and Function in Dermal Replacements in General, Burn, and Plastic Surgery. Springer, Vienna, 2013; pp 1-11. (49) Gerling, G. J.; Thomas, G. W. The Effect of Fingertip Microstructures on Tactile Edge Perception. in Proceeding of the First Joint Eurohaptics Conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems. Pisa, Italy, 18-20 March 2005, 63-72. (50) Cai, D.; Neyer, A.; Kuckuk, R.; Heise, H. M. Raman, Mid-Infrared, Near-Infrared and Ultraviolet-Visible Spectroscopy of PDMS Silicone Rubber for Characterization of Polymer Optical Waveguide Materials. J. Mol. Struct. 2010, 976, 274-281. (51) Chen, W.; Yan, L. Preparation of Graphene by a Low-Temperature Thermal Reduction at Atmosphere Pressure. Nanoscale 2010, 2, 559-563. (52) Pritchard, R. H.; Lava, P.; Debruyne, D.; Terentjev, E. M. Precise Determination of the Poisson Ratio in Soft Materials with 2D Digital Image Correlation. Soft Matter 2013, 9, 60376045. (53) Lu, K.; Lu, J. Nanostructured Surface Layer on Metallic Materials Induced by Surface Mechanical Attrition Treatment. Mater. Sci. Eng. A 2004, 375, 38-45.


24

Page 25 of 32 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Nano

(54) Drotlef, D. M.; Amjadi, M.; Yunusa, M.; Sitti, M. Bioinspired Composite Microfibers for Skin Adhesion and Signal Amplification of Wearable Sensors. Adv. Mater. 2017, 29, 1701353. (55) Bai, P.; Zhu, G.; Jing, Q.; Yang, J.; Chen, J.; Su, Y.; Ma, J.; Zhang, G.; Wang, Z. L. Membrane-Based Self-Powered Triboelectric Sensors for Pressure Change Detection and its Uses in Security Surveillance and Healthcare Monitoring. Adv. Funct. Mater. 2014, 24, 58075813. (56) Verghese, J.; Liption, R. B.; Hall, C. B.; Kuslansky, G.; Katz, M. J.; Buschke, H. Abnormality of Gait as a Predictor of Non-Alzheimer's Dementia. N. Engl. J. Med. 2002, 347, 1761-1768.


25

ACS Nano 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 26 of 32

Figure 1. Bio-inspired graphene pressure sensor with RDS microstructure. (A) Illustration showing the biological microstructure of human epidermis, and the beneath spinosum of epidermis layer is a crucial element for high sensitivity. (B) The microscopy of epidermis showing a spinosum surface, and (C) 3D morphology of turnover abrasive paper shows similar topography. (D) The fabrication process of graphene pressure sensor. The photographs (insets) and optical micrographs of the patterned PDMS (E), GO coating on PDMS (F) and after high temperature reduction (G) using abrasive paper No. 150.


26

Page 27 of 32 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Nano

Figure 2. Characterization of the prepared RDS samples. (A) The 3D morphology of graphene pressure sensor using abrasive paper No. 600 in the area of 1×1 mm2, (B) height profile corresponding to the marked cross profile on the diagonal, (C) probability distribution and cumulative distribution of the height for the SM structure. (D) The Raman spectra of the PDMS, GO/PDMS and rGO/PDMS. (E) The SEM image, (F) high magnification SEM image and (G) corresponding magnified SEM image of the rGO/PDMS structure using abrasive paper No. 600.


27

ACS Nano 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 28 of 32

Figure 3. Electromechanical properties of the RDS graphene pressure sensors. (A) The relative resistance variation versus the pressure for the pressure sensors using different roughness of No. 150-280, 150-400, and 150-600 PDMS substrates. (B) Comparison of the sensitivities within linearity pressure range between RDS graphene pressure sensor and previous reported surface patterned microstructures. (C) The relative resistance variation of the pressure sensor under the subtle pressure of rice and pushpin loading and unloading. (D) The rise and drop time of RDS pressure sensor. (E) The relative change in resistance under repeated loading and


28

Page 29 of 32 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Nano

unloading pressure of 1.5 kPa for 3000 cycles, indicating stability and durability of the pressure sensor.

Figure 4. The working mechanism of RDS graphene pressure sensor. Photographs and schematic illustrations of circuit models corresponding to (A) initial state of unloading, (B) light loading, and (C) heavy loading. The pressure distribution of simulation result for different geometries of (D) pyramid, (E) hemisphere, (F) nanowire, and (G) RDS microstructure at an external loading pressure of 5 kPa. (H) The simulation results of resistance variation versus applied pressure for different surface microstructures.


29

ACS Nano 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 30 of 32

Figure 5. Applications of the RDS graphene pressure sensor for various physiological signals detection. The photograph of pressure sensor assembled on (A) wrist and corresponding signals of the (B) wrist pulse. (C) Photograph of a pressure sensor attached on the human chest area, indicating different signal variations for normal and deep respiration. Photograph of pressure sensor attached on a (D) loudspeaker and corresponding signals (E) when it phonated the word “graphene”, showing the ability to distinguish U.S. and U. K. pronunciation. (F) The photograph of sensor put on the foot heel and (G) its detected signal for walking, running, and jumping. (H) The illustration of foot states for supination, neutral, and pronation, and (I) the photograph of pressure sensors fixed on the insole. (J) The schematic diagram of system design


30

Page 31 of 32 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Nano

for the gait detection. The signals of pressure array to detect gait states of (K) neutral, (L) supination, and (M) pronation, respectively.


31

ACS Nano 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 32 of 32

Graphical Table of Contents


32

Epidermis Microstructure Inspired Graphene Pressure Sensor with

Recommend Documents