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A skin-like sensor for intelligent Braille recognition
Journal Pre-proof A Skin-Like Sensor for Intelligent Braille Recognition Xue-Feng Zhao, Cheng-Zhou Hang, Hong-Liang Lu, Ke Xu, Hao Zhang, Fan Yang, Ru-Guang Ma, Jia-Cheng Wang, David Wei Zhang PII:
S2211-2855(19)31053-5
DOI:
https://doi.org/10.1016/j.nanoen.2019.104346
Reference:
NANOEN 104346
To appear in:
Nano Energy
Received Date: 28 August 2019 Revised Date:
1 November 2019
Accepted Date: 29 November 2019
Please cite this article as: X.-F. Zhao, C.-Z. Hang, H.-L. Lu, K. Xu, H. Zhang, F. Yang, R.-G. Ma, J.C. Wang, D.W. Zhang, A Skin-Like Sensor for Intelligent Braille Recognition, Nano Energy, https:// doi.org/10.1016/j.nanoen.2019.104346. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Elsevier Ltd. All rights reserved.
A Skin-Like Sensor for Intelligent Braille Recognition
Xue-Feng Zhaoa, b,⊥, Cheng-Zhou Hanga,⊥, Hong-Liang Lua*, Ke Xuc, Hao Zhangc, Fan Yanga, Ru-Guang Mab, Jia-Cheng Wangb, *, David Wei Zhanga,* a
State Key Laboratory of ASIC and System, Shanghai Institute of Intelligent
Electronics & Systems, School of Microelectronics, Fudan University, Shanghai 200433, China. b
State Key Laboratory of High Performance Ceramics and Superfine Microstructure,
Shanghai Institute of Ceramics, Chinese Academy of Sciences, 1295 Dingxi Road, Shanghai 200050, China. c
Key Laboratory of Micro and Nano Photonic Structures (MOE), Department of
Optical Science and Engineering, Fudan University, Shanghai 200433, China
*
Email: [email protected]; [email protected]; [email protected]
⊥
These authors contribute the work equally.
Abstract A flexible skin-like tactile sensor as one of the key components in the next generation for robots should have the ability to perform real-time feedback, continuous measurement, and quantization of weak target signals in the real applications (e.g. intelligent Braille recognition). Herein, inspired by human skin, a novel flexible piezoresistive tactile sensor with high sensitivity and linearity is designed and fabricated. It is composed of three main parts including the random Gaussian distribution (RGD) spinosum on polydimethylsiloxane as the top substrate, the multilayer Ti2C-MXene film as the intermediate conductive filler, and the commercial polyimide-based interdigital electrodes as the bottom substrate. The working mechanism of RGD spinosum and Ti2C-MXene films in the flexible tactile sensor are clarified by COMSOL Multiphysics simulations and density functional theory calculations, respectively. The assembled sensor demonstrates ultrahigh sensitivity, large linearity, excellent cycling stability, and fast response speed in the milliseconds. Moreover, the development of advanced neural network technology makes it possible to realize intelligent skin-like sensor. In this study, it is the first time to realize real-time Braille effective intelligent recognition by such a flexible skin-like tactile sensor with the random decision forests algorithm. This study is of great significance to solve the social and public issues of information exchange for the vision-impaired or even the blind that has been highly concerned in recent years. Keywords: Flexible tactile sensor, Random Gaussian distribution, Ti2C-MXene, Random decision forest algorithm, Braille recognition
1.
Introductions Information exchange for the vision-impaired or even the blind is a public and
social concern nowadays [1]. According to data released by the World Health Organization, the total number of blind people in the world is about 40 million, of which China is the country with the largest proportion. Braille is one important communication tools for the vision-impaired and the blind, which helps them to write and read [2]. For the existing Braille recognition methods, the extraction of Braille feature points is usually done manually, which is time-consuming, laborious, and unable to guarantee the validity of the extracted features [3, 4]. In addition, because the classification and recognition of the Braille characters by feature point comparison method is limited to the artificially defined feature points, the recognition accuracy is usually very low and the anti-interference capability is poor. Therefore, it is of great importance to develop a high-accurate and practical Braille recognition device for the management of ancient Braille books, the mental health, and the teaching of the blind. With the rapid development of flexible electronic technology [5] and artificial intelligence [6], the flexible pressure sensors [7] are expected to be a new way to realize effective and real-time Braille recognition due to their unique advantages such as easy to fit the tested object, test-accuracy, and strong anti-interference ability. Although many simple display-related applications have been reported recently [8-10], the flexible pressure sensors have not play an important role in our everyday life. One of the main reasons is the trade-off between sensitivity and stability of the pressure sensors has not been well balanced. As a result, the measured objects cannot be
measured and distinguished in real time and long-term stability. In recent years, two effective methods have been proven to solve the above problems. The first method is to introduce the nanoscale materials with excellent electrical and mechanical properties as the conductive fillers in flexible pressure sensors or the sensing elements such as silver nanowire [11], copper nanowire [12], graphene [13, 14], biomass-derived carbon[15] and so on[16]. Another method is to construct different surface microstructures or geometries (nanowires [17], pyramids [18], hemispheres [19], and prisms [20]) to gain high sensitivity and low detectable limitation. However, the technical bottlenecks still exist regarding how to fabricate a flexible pressure sensor with low cost, high sensitivity, large linearity, fast response speed, and high accuracy of recognition results. Thus, developing a flexible, skin-like, and effective pressure sensor is not only a huge challenge but also a significant research topic. 2.
Results and discussion Herein, we propose a skin-like sensor, based on piezoresistive sensing and its
capability of intelligent Braille recognition in real time. It is composed of three main parts, which corresponding to the three parts (epidermis, dermis and subcutaneous tissue) of human skin. The top substrate is the force perception layer with random Gaussian distribution (RGD) spinosum from lotus leaf, which is similar with the structural morphology of epidermis. This microstructure is essential for enhancing sensitivity and measuring and discriminating weak force. The intermediate conductive filler is the force treatment layer, which is formed by the multilayer Ti2C-MXene film
and can be compressed and released with external forces loading and unloading. The bottom substrate is the force signal-receiving layer, which is capable of converting the force signal into an electrical signal. By using the flexible skin-like tactile sensor, it is the first time to realize real-time Braille effective recognition with the random decision forests algorithm (RDFA). Wherein, the RDFA has great advantages over other algorithms in many data sets, such as fast training speed, strong anti-interference ability, simple implementation, parallel processing, etc., which are widely used in the fields of medicine, economics, management and remote sensing. 2.1 Skin-Like Sensor design concept and synthesis process Nature often provides the inspiration for the engineering development, particularly artificial electronic devices with various bionic structures. As a tissue covering the surface of human body, skin is the most critical tactile sensing tissue in the human body (Fig. 1a). On the one hand, there is spinosum layer under the epidermis. A particular interesting feature of the spinosum is RGD microstructure [14], which playing a key role to ensure an extremely sensitive response under low-intensity external stimuli. On the other hand, the dermis has excellent elasticity because it contains a large number of fibers such as collagen fibers, elastic fibers and reticular fibers [21]. Bioinspired by the tissue structure and the force perception process of human skin, a skin-like flexible tactile sensor (Fig. 1b) is designed. In this sensor, polydimethylsiloxane (PDMS) with lotus leaf surface microstructures is selected as the top substrate. Moreover, the overwhelming elasticity, biocompatibility and optical
properties of PDMS have been proven the most effective route to fabricate flexible electronic skin [22, 23]. Ti2C-MXene is selected as the intermediate conductive filler. MXene [24], as a new type of two-dimensional (2D) transition metal carbides and nitrides, are of interest in some important applications due to the excellent characteristics such as favorable strength, outstanding metallic electrical conductivity and large specific surface [25, 26]. Moreover, it has been reported that the pressure sensor based on Ti3C2-MXene accordion-like multilayer structure has high sensitivity [27]. In particular, compared to the most extensively researched Ti3C2-MXene, Ti2C-MXene has the thinner single layer thickness and larger specific surface area because Ti2C consists of two Ti layers and one C layer, while Ti3C2 consists of three Ti layers and two C layers [28]. The above superiorities of Ti2C make the conductivity change broader than Ti3C2 under the equal pressure loading, which will greatly improve the sensitivity of the sensor. The bottom substrate is a polyimide (PI)-based commercial interdigital electrode, which has excellent mechanical properties in terms of stretch ability and durability. Fig. 1c shows that the fabrication process of the random-distribution spinosum and Ti2C-based flexible pressure sensor. Wherein, the replication process of the micro-pattern on the top PDMS substrate was based on dual molding of the lotus leaves, which is a type of soft-lithography [29]. To improve the quality of replication, hard PDMS in the first molding and standard PDMS in the second molding was utilized. The multilayer Ti2C-MXene film was produced by immersing Ti2AlC powders in the mixture solution to remove off the Al layer, followed by suction
filtering to form multilayer film. After the spinosum of the lotus leaf surface was replicated on the PDMS, the Ti2C-MXene multilayer film was coated on the PDMS substrate with RGD spinosum. Finally, the bottom interdigital electrode was laminated onto the Ti2C-MXene film, completing a sandwich structure. To investigate the piezoresistive effect of the sensor, the electrical response of the device at different pressure levels was examined by an electrical signal testing system (see in the experimental section).
Fig. 1. Skin-Like Sensor design concept and synthesis process. (a) Schematic diagram of human skin, which is mainly composed of three parts: epidermis, dermis and subcutaneous tissue. The RGD spinosum of the outer epidermis is one of the most the crucial factors for obtaining high sensitivity. (b) Schematic diagram of the skin-like tactile sensor, consisting of the top PDMS surface layer with RGD spinosums, the
intermediate Ti2C-MXene assembly films as flexible conductive sensing layer, and the bottom PI-based interdigital electrode. (c) Fabrication process of the skin-like tactile sensor. 2.2 Force perception layer characterization and sensing mechanism. The photo image of a fresh lotus leaf is shown in Fig.2a. It can be clearly seen from the SEM images (Fig. 2b) that the surface of lotus leaf has the RGD spinosum. The average distance between the RGD spinosum is about 7 µm. The replication result after the second molding is obtained by the SEM (Fig. 2c) and the Confocal Laser Scanning Microscope (CLSM) image (Fig. 2d). By comparing the statistics of the spinosum on the lotus leaf and PDMS in the direction of height, it can be found that PDMS is intact to replicate the surface morphology of the lotus leaf, and the resultant spinosum have the characteristics of RGD in height as well as those on the lotus leaf (Fig. 2e). In general, the sharp microstructures are helpful to improve the sensitivity, because the contact area is dramatically increased under a small external pressure. However, when further deformation occurs, the sensitivity of this sensor decreases sharply, resulting in nonlinearity and rapid saturation. In view of the comprehensive performance and practical application of the pressure sensor, a high sensitivity and a large linearity range are desired for coexistence. In order to study the influence of different geometric shapes on the pressure distribution of the pressure sensor, the displacement distributions of nanowire (Fig. 2f), pyramid (Fig. 2g) and RGD spinosum (Fig. 2h) under 10 kPa loading are simulated by COMSOL Multiphysics.
The simulation results illustrated that the nanowire structures presents a uniform pressure distribution along the altitude direction (Fig. 2f), and the sharp pyramid structures have the force concentration at the top cusp region (Fig. 2g). Interestingly, the force of the RGD spinosum is concentrated on the initial contact peak and transferred to the adjacent peaks (Fig. 2h), which indicates that the pressure distribution of the RGD spinosum is more homogeneous than the pressure distribution of the other two regular morphologies. Therefore, under less pressure, the RGD spinosum is more likely to reach saturation than other structures, which provides favorable conditions for the device to achieve high sensitivity. At the same time, with the increase of pressure, the deformation of the contact point of the RGD spinosum transfers to the periphery, which makes the resistance change of the device continue to show a linear relationship, and effectively improves the range of pressure measurement of the device.
Fig. 2. Micropattern morphology and force perception mechanism of RGD spinosum PDMS. (a) The photo image of a lotus leaf. (b) SEM picture of the spinosum set on the lotus leaf. (c) SEM image and, (d) CLSM image of the RGD spinosum PDMS. (e) Comparison of the microstructural height distribution between the lotus leaf and RGD spinosum PDMS. (f), (g), (h) COMSOL Multiphysics simulation results of the displacement distribution of different geometries: nanowire, pyramid and RGD spinosum under the external loading pressure of 10 kPa. 2.3 Force treatment layer characterization and sensing mechanism. The schematic diagram for the synthesis process of multilayer Ti2C-MXene film is illustrated in Fig. S1, and the photograph of the Ti2C-MXene film is shown in Fig.
S2. The X-ray diffraction (XRD) patterns (Fig. S3) indicate that the Ti2AlC was successfully converted into Ti2C-MXene. As observed in the SEM images (Fig. S4a-c) and the transmission electron microscopy (TEM) image (Fig. 3a), Ti2AlC has changed into a loosely stacked structure after solution etching. The elemental mapping in Fig. S4d shows that all elements distribute homogeneously. The corresponding diffraction pattern in the inset of Fig. 3a and the high-resolution TEM images (HRTEM) image (Fig. 3b-d) clearly illustrates the crystalline lattice of multilayer Ti2C nanosheets with hexagonal structure, which indicates the good crystallization characteristics of the as-synthesized Ti2C nanosheets. Fig. 3b1, b2 show the distinct lamellar structure with an average interlayer distance of 1.10 nm, and the hexagonal characteristics can be recognized well in Fig. 3d1, d2 with the (100) plane distance of 0.25 nm. In particular, the first-principles calculations is carried out using density function theory (DFT) [30] to directly illustrate the working mechanism of Ti2C in the tactile sensor. As shown in Fig. 3e, the monolayer Ti2C, consisting of a planar C sublayer sandwiched by two Ti sublayers, possesses a low symmetry of C3v point group, with the symmetry operations of C3 and vertical mirror reflection σv [31]. The C-C, Ti-C and Ti-C are covalently bonded to each other according to the charge density distribution of a five-layer Ti2C from side view, as shown in Fig. 3f. The ab-initio calculations of the band structure and the orbital projection of monolayer Ti2C are shown in Fig. 3g. Monolayer Ti2C is gapless and the valence and conduction bands around Fermi level are dominantly composed by Ti-d orbitals. For more details, dxz+dyz+dz2 orbitals contribute more to valence and conduction bands of monolayer
Ti2C than dxy+dx2-y2 orbitals. We also calculated the band structure and orbital projection for five-layer Ti2C, which can be regarded as bulk phase indeed, as shown in Fig. 3h. Similar orbital contributions can be found. To compare experiments and investigate the piezoresistive effect of monolayer and multilayer Ti2C, we calculated the electron conductivity relaxation time
in the unit of
for different strains, which was performed based on the rigid-band
approximation using Boltztrap [32]. The resistance ρ can be calculated by the inverse of electron conductivity , and the relaxation time
can be treated as that of
free electron life time ~10-14s (100 ps). To clarify the influence from dimension, we studied the electronic transport at room temperature of monolayer and five-layer Ti2C respectively, as shown in Fig. 3i-k. Generally, when applying compressive strains, the interlayer distance becomes smaller, leading to a higher overlap integral V between layers due to
∝ 1/
[33]. According to the molecular orbital theory, the
bandwidth W is roughly determined by the overlap integral by
∝ , and when
compressive strains apply, the overlap integral increases, which will enlarge the bandwidth W and result in a narrow parabola near VBM or CBM, finally leading to a decreasing effective mass m* [34]. The decreasing effective mass increase the value of carrier mobility according to
=
∗
. Subsequently, the electron conductivity
increase due to σ=neµ, where n represents the electron concentration, e is the electronic charge. Therefore, applying the compressive strains will lower the resistance ρ, which is valid for both bulk and monolayer Ti2C as shown in Fig. 3i-k. Moreover, the resistance along z direction is larger than that along x/y direction.
When applying the compressive strain along both z and x/y directions, the resistance decreases with the increasing strain due to a larger overlap integral
∝ 1/
, since
the bond length decreases. We supposed that since dxz+dyz+dz2 orbitals contribute more to the valence and conduction bands of monolayer Ti2C than dxy+dx2-y2 orbitals , the resistance of z direction will be more susceptible to the strain than that of x/y direction, leading to a bigger decrease along z direction with increasing strains. We can also find the resistance of five-layer Ti2C (shown in Fig. 3k is much smaller than that of monolayer Ti2C because of the existence of the overlap integral between layers in multilayer structures. Therefore, the change of the overlap integral between layers due to strains will play a significant role on the piezoresistive effect of monolayer and multilayer Ti2C.
Fig. 3. Ti2C-MXene characterization and working mechanism. (a) Ti2C-MXene’s TEM image and its corresponding diffraction pattern in the inset, showing accordion-like fluffy features and well the hexagonal characteristics. (b) HRTEM images of Ti2C-MXene displaying the lamellar structure. (c), (d) The plan view
HRTEM images shows the well-crystallized feature of the Ti2C-MXene nanosheets. (e) Atomic structure of the single layer of Ti2C-MXene from top view and side view. (f) Atomic structure and charge density of a five-layer Ti2C-MXene from side view. (g), (h) The band structure and orbital projection of monolayer and multilayer Ti2C-MXene respectively. (i), (j) The evolution of the resistance of monolayer Ti2C-MXene as a function of chemical potential at 300K under the compressive strain along x and z direction respectively. (k) The evolution of the resistance of multilayer Ti2C-MXene as a function of chemical potential at 300K under the compressive strain along z direction. 2.4 The properties of the skin-like sensor. To investigate the piezoresistive effect of the sensor, the rectangular commercial interdigital electrodes are used to receive the varying electrical signals (Fig. S5a, b), and the electrical response of the device at different pressure levels is examined by an electrical signal testing system (see in the materials and methods sections). The I–T curves with the pressure less than 40 kPa shows a monotonic increase in current with higher pressure (Fig. 4a). This suggested shows that our pressure sensor can clearly distinguish between different levels of the external force. The linear relationship of the I–V curves (Fig. 4b) for the voltage from −0.1 to 0.1 V indicates that an Ohmic contact is formed between the multilayer Ti2C-MXene film and interdigital electrode. As the applied load increases, the slope of the I-V curve increases correspondingly, indicating that the resistance of the multilayer Ti2C-MXene film of this sensor is reduced accordingly. Furthermore, the forward and backward sweeping I-V curves of
the fabricated sensor are measured in a voltage range from -0.1 to 0.1 V at an external pressure (Fig. S6). It can be observed clearly that the forward and backward sweeping I-V curves are completely coincident, suggesting that the Ti2C-MXene film have an excellent Ohmic contact with the interdigital electrodes. The sensitivity of a piezoresistive device is a significant parameter for evaluating device performance, which is generally defined as S = (∆I /I0 )/∆P, where ΔI denotes the current change before and after applying pressure, I0 represents the initial current without pressure, and ∆P is the amount of pressure change from I0 to I. We measured the ∆I /I0 relative to the pressure value, as shown in Fig. 4c. The result indicates that the current curve varies linearly in three regions with the change of pressure. In the low pressure region (0-5.75 kPa), the sensitivity of the device is as high as 507 kPa−1, while in the high pressure region (12-40 kPa) and the transitional pressure region (5.75-12 kPa), the sensitivity of device is 25 kPa−1 and 224 kPa−1, respectively. As far as we know, the sensitivity and linearity of the present pressure sensor are much higher than other sensors (Fig. 4e). The reasons may be as follows (Fig. 4i). In the low pressure region, the pressure on the contact point of the RGD spinosum on the PDMS is concentrated, which results in the interlayer distance of multilayer Ti2C-MXene rapidly gradually reduced while the atomic distance of monolayer Ti2C-MXene also gradually reduced, thus reducing the total resistance of Ti2C-MXene film and increasing the output current. It is worth noting that the atomic distance is much smaller than the interlayer distance, so the rate of the interlayer distance dominant. In the transitional pressure region, the interlayer distance and the atomic distance is further reduced
simultaneously while the contact point of the RGD structure transfers to the periphery, which leads to the increase of the contact area between MXene-RGD spinosum and interdigital electrode, and then slowly reduces the total resistance of Ti2C-MXene film. In the high-pressure region, the descent rate of the interlayer distance and the atomic distance is very small, but the contact area between MXene-RGD structure and interdigital electrode is greatly increased, so that the total resistance of Ti2C-MXene film is basically unchanged. Meanwhile, both the output current and external pressure were in good synchronization with the loading and unloading, as shown in Fig. 4d. As presented in Fig. 4f, our sensor can clearly detect a very small pressure of 8 Pa. In addition, we measured the response and recovery time of the device under pressure with specific results of 60 ms and 40 ms, which makes it possible to implement real-time testing (Fig. 4g). In order to further evaluate the mechanical stability and operational life of the sensor, the 5,000 cycles of loading and unloading pressures were tested, as shown in Fig. 4h. After cyclic testing, the current signal shows a little attenuation,
and
keeps
almost
the
same
current
variation
after
each
compression-release cycle, which proves that the device has high stability and long durability.
Fig. 4. The properties of the skin-like sensor. (a) The I–T curves with the pressure less than 40 kPa. (b) The linear relationship of the I–V curves for the voltage from −0.1 to 0.1 V. (c) The sensitivity of the sensor, exhibiting a high sensitivity of 507 kPa−1 below 5.75 kPa, 224 kPa−1 in the transitional pressure region (5.75-12 kPa) and 25 kPa−1 in the high pressure region (12-40 kPa). (d) The synchronization relation between I-T and P-T curves. (e) Comparison between our pressure sensor and previous reported pressure sensors in terms of the sensitivities within a linear pressure
range and the linearity. (f) The detection limit of the sensor. (g) The response time with loading and unloading pressure of the sensor. (h) Stability of this sensor with press-release 5,000 cycles. (i) Schematic diagram of sensing principle in different pressure stages of RGD spinosum surface. 2.5 The topographical map scanner by the skin-like sensor. A randomly-distribution spinous, MXene-based flexible skin-like tactile sensor exhibits ultrahigh sensitivity, large linearity, fast response speed and high stability. It has great potential application value in the field of Internet of Things and artificial intelligence. We attached it directly on the joint or muscle, and then fixed it with the transparent tape to monitor human physiological activities, e.g. throat swallowing (insets in Fig. S7a), eye blinking (insets in Fig. S7b), cheek bulging (insets in Fig. S7c), finger touching (insets in Fig. S7d) and finger bending (insets in Fig. S7e). The results show that the relative I-T curves of different physiological activities are different and easy to distinguish by comparing the intensity change and shape of these diagrams. Moreover, the current value remained nearly unchanged under the same motion when the physiological activity switched rapidly. To get closer to a more practical application, a 16-pixel pressure sensor array (4 × 4 elements) is fabricated to detect pressure distribution (Fig. 5a, b), and the simple electrical signal monitoring system is designed as shown as Fig. S8. When no pressure on the sensor array, the column colors in the upper computer are all blue (representing zero pressure). When the position on the sensor array is pressed, the column colors changed due to the different force of each individual sensor (Fig. 5c).
Then we pressed the other different positions of the sensor array (Fig. S9 and Movie S1) and the results show that the sensor array is very sensitive for external force loading and unloading, which make it possible to achieve the force direction detecting and topographical maps scanning. We use small Aluminum cubes (5 mm×5 mm ×5 mm) to shape the letters, such as F, U, D, A and N (Fig. 5d). The normalized grayscales display the sensor array is able to clearly identifying the complex shapes. This phenomenon further demonstrates that the piezoresistive sensors have excellent resistance change performance.
Fig. 5. The applications of the skin-like sensor for the topographical map scanner. (a) The structural diagram of the 4 × 4 elements array interdigital electrode parameters. (b) The physical picture of the 16-pixel pressure sensor array. (c) The response of the upper computer when press a position on the sensor array. (d) F, U, D, A and N
patterns using cubes and topographical maps of normalized grayscales variations for the F, U, D, A and N patterns. 2.6 The sensor for intelligent Braille recognition in real-time. To further extend the application of this device, the tactile sensor combined with the RDFA is used to realize the real-time Braille effective recognition (Fig. 6a). RDFA is a comprehensive learning method for tasks such as classification and regression. And it operates by building multiple decision trees during training time and outputting a single tree's class (classification) or mean prediction (regression) [35]. We used our sensor array to test the Braille bumps of 26 English letters and common punctuation marks five times, respectively. Then all data were input to the RDFA. After the training, we tested the Braille of single letters (Fig. 6b), words (Fig. 6c) and sentences (Fig. 6d) respectively. The accuracy of the real-time Braille recognition is more than 99% and the results illustrate that the high sensitivity of the flexible tactile sensing system which opens up a new field for wearable devices and electronic skin (Movie S2)
Fig. 6. Recognition Braille in real-time by the sensor array based on the RDFA. (a) Schematic diagram of Braille recognition process. (b) Recognition results of single Braille letters, such as ‘A’, ‘B’ and ‘C’. (c) Recognition results of Braille words, such as ‘we’, and ‘ok’. (d) Recognition results of Braille sentences, such as ‘Hello world!’. 3.
Conclusions A biomimetic flexible skin-like tactile sensor with RGD spinosum as the
substrate and Ti2C-MXene film as the conductive filler was fabricated. COMSOL Multiphysics study and DFT study directly illustrated the working mechanism of RGD spinosum and materials in the skin-like sensor, respectively. The spinosum microstructure and RGD contribute to the ultra-high sensitivity and large linearity
range, respectively. The huge change of the interlayer distances in the Ti 2C-MXene film under pressure is the herent working mechanism for the piezoresistive sensor. The value of sensitivity reached to 507 kPa-1, which is obviously higher than other pressure/tactile sensors reported. Based on the excellent performance of the device, we applied the sensor in human activities monitor and topographical map scanner. In addition, the sensor array combined with the RDFA is used to realize real-time Braille effective recognition. For the first time, we demonstrated a new type of the flexible pressure sensor to serve this purpose. Our solution offers low cost while maintaining high sensitivity, large linearity, fast response speed, and high accuracy. Therefore, it is of great potential for practical adoption in the near future. 4.
Materials and methods
4.1 Materials Polydimethylsiloxane (PDMS) elastomer (Sylgard 184) was purchased from Dow Corning Co., Ltd. The MAX- Ti2AlC (400 mesh) was purchased from 11 Technology Co., Ltd. Lithium fluoride (LiF, 98.5 % purity), concentrated hydrochloric acid (HCl, 37.2% purity) were purchased from Aladdin Inc. (China). The interdigital electrode (5 mm×5 mm, line width 100 µm, line space 100 µm ) was purchased from Shangyou Electronic Technology Co., Ltd. (China). 4.2 Device fabrication 4.2.1
Fabrication of PDMS substrates with lotus leaf surface micropattern The fabrication process diagram is shown in Fig. 1c. Fresh lotus leaves were cut
into rectangles (5 mm× 5 mm) and washed three times with deionized water. After
being dried by nitrogen, fasten the lotus leaf to the 4-inch silica wafer substrate with double-sided tapes. For better replication quality, PDMS prepolymer was prepared with a base to curing agent ratio of 5:1 and degassed in a vacuum desiccator for 20 minutes to remove air bubbles at room temperature. A quantity of PDMS mixture was spin coated (at 400 rpm) onto the leaves. Then, after curing at 70 °C for 1 h, the PDMS film with opposite structures of lotus leaf was peeled off and used as a second molding template. In order to reduce the adhesion during the second molding process, the surface of the molding template was fluorinated. Particularly, the two molding processes were similar, the only difference was that the second molding process utilized the standard PDMS (the weight ratio of base to cross linker was 10:1). Finally, the PDMS film with delicate spinous pattern from lotus leaf was fabricated by the hard and standard PDMS double-layer molding process. 4.2.2
Synthesis of multilayer Ti2C-MXene film
The multilayer Ti2C-MXene was produced by immersing Ti2AlC powders in the mixture solution to remove the Al layer. Etching solution was made by adding two grams of LiF into 40 ml HCl (6 M, 36–38 wt.%) solution. The solution was mixed by sonication for 15 min to dissolve all LiF. Thereafter, 2 g of Ti2AlC powders were immersed in the above solution, stirred for 1 min, and then the mixture was held at 40 ℃ for 48 h with magnetic stirring. Thereafter the mixture was separated by centrifugation, washed with deionized water and ethanol several times, until the supernatant reached a pH value of ~6. Obtained Ti2C powders were dried in vacuum at 80 ℃ for 12 h. In order to facilitate the operation, the powder was prepared into
membrane by the suction filter process. 4.3 DFT calculation method All the first principle calculations are performed using the Vienna ab-initio simulation package (VASP) based on density functional theory (DFT) [36]. The exchange-correlation energy is described by the generalized gradient approximation (GGA) in the Perdew-Burke-Ernzerhof (PBE) parametrization. The DFT-D3 approach is chosen to involve the long-distance van der Waals (vdW) interactions [37]. The calculation is carried out by using the projector-augmented-wave (PAW) pseudopotential method with a plane-wave basis set with a kinetic energy cutoff of 600 eV. A 15×15×1 Γ-centered k-mesh was used during structural relaxation for the unit cell until the energy differences are converged within 10−6eV, with a Hellman-Feynman force convergence thresh-old of 10−4eV/Å. The vacuum size is about 16 Å between two adjacent atomic layers to eliminate artificial interactions between them. The electrical transport properties, such as electronic conductivity, were computed by solving the semiclassical Boltzmann transport equation, which is implemented in Boltztrap code [38]. Through Fourier expansion, the code fits an analytical function to the ab initio electronic band structure [39]. The transport coefficient is calculated from the analytical expression of the conductivity tensor ( ), as σ
( , )= !
( ) "−
$%& ( ,',() $'
)
(1)
where Ω and f0 were the volume of unit cell and Fermi-Dirac distribution respectively.
Also, the relaxation time approximation was used to treated the relaxation time as both energy and direction independent constant [40]. 4.4 Device characterization 4.4.1
Force response measurement setup
The measurement setup consisted of a computer servo control vertical pressure testing machine (HD-B609B-S) to carry out uniaxial compression and release, and the current of each sensor under the different pressure was measured by a SourceMeter (Keithley 2450). The input voltage was set as 0.1 V during the tests. 4.4.2
Real-time Braille recognition system setup
In order to demonstrate the Braille recognition process, the Braille used in this study was customized, and the diameter of each Braille bumps was 5 mm. Random forests consisted of decision trees, each of which was not related. Through bootstrap sampling of training sets, training subsets were generated, and then decision trees were generated to form random forests. The training set was sampled by bootstrap sampling method to generate a training subset, which was a decision tree. In this study, we trained 100 decision trees to form a random forest.
ACKNOWLEDGMENTS We acknowledge the great help from Prof. Z.G.Ji at Liverpool John Moores University. This work is supported by the National Key R&D Program of China (No.2016YFE0110700), National Natural Science Foundation of China (No. 11804055, 51861135105 and 61874034), and Natural Science Foundation of
Shanghai (No. 18ZR1405000). Prof. J.C.Wang acknowledges support by Equipment Research Program (6140721050215) and State Key Laboratory of High Performance Ceramics and Superfine Microstructure.
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Biography for Nano Energy Xue-Feng Zhao is a Ph.D. candidate in the Laboratory of Nanosensor, School of Microelectronics, Fudan University, Shanghai, China. He obtained his M.S. degree from North University of China, Taiyuan, China. His current research interests include preparation and integration of flexible wearable devices, fabrication and functionalization of novel and advanced nanomaterials.
Cheng-Zhou Hang is a master's student from the School of Microelectronics at Fudan University in Shanghai, China. He received his bachelor's degree from Dalian University of Technology, Dalian, China. His research interests focus on the flexible sensors and wearable devices.
Prof. Hong-Liang Lu received the Ph.D. degree in microelectronics from Fudan University, Shanghai, China. He was a JSPS Research Fellow with the Department of Electrical Engineering and Information Systems, The University of Tokyo, Tokyo, Japan. He is currently a Professor with the School of Microelectronics, Fudan University. His current research interests include atomic layer deposition of thin films, high mobility semiconductor devices, advanced micro-nano sensors, and so on
Ke Xu is a master student in the Department of Optical Science and Engineering, Fudan University, Shanghai, China. His current research interests focus on topological materials, non-Hermitian
topological
phases,
thermoelectrics,
density-functional theory and many-body perturbation theory.
Hao Zhang received the Ph.D. degree in optics from Fudan University, Shanghai, China. He is currently an Associate Professor with the Department of Optical Science and Engineering, Fudan University. His research interests include density-functional
theory,
thermoelectrics,
exciton,
two-dimensional materials and topological materials.
Prof. Fan Yang received the B.E. degree from Xi’an Jiaotong University in 2003 and his Ph.D. degree from Fudan University in 2008. He is currently a Professor with the School of Microelectronics, Fudan University. His current research interests include circuit simulation, yield analysis and design for manufacturability. Ru-Guang Ma received his Ph.D. in materials science from City University of Hong Kong in 2013. Then he worked at Nanyang Technological University as a post-doctoral
researcher. In July 2014, he joined Shanghai Institute of Ceramics, Chinese Academy of Sciences (SICCAS). He is currently an associate professor in the State Key Lab of High Performance Ceramics and Superfine Microstructure, SICCAS. His research interests include design and synthesis of new nanostructured electrode materials for Li ion batteries, supercapacitors, metal–oxygen batteries and non-precious metal catalysts.
Prof. Jia-Cheng Wang received the Ph.D. in 2007 from Shanghai Institute of Ceramics, Chinese Academy of Sciences (CAS). He previously held several fellowships and awards including JSPS (Japan Society for the Promotion of Science) postdoctoral fellowship (2010, the University of Tokyo), Alexander von Humboldt Fellowship (2011, Dresden University of Technology), Marie-Curie Intra-European Fellowship (2012, Cardiff University) and “One Hundred Talent Plan” of CAS (2014). He is currently co-Editor-in-Chief of Nano Advances (ISSN 2415-1386) and editorial member of Scientific Reports. He has strong backgrounds in high-throughput screening of energy conversion and storage materials, electrochemical energy devices, and their scale-up and commercialization. Prof. David Wei Zhang received the Ph.D. degree from Xi'an Jiaotong University, Shaanxi, China. He was a Humboldt Research Fellow with the TU-Chemnitz, Germany. He is currently a full Professor and Deputy Dean with the School of
Microelectronics, Fudan University. He was also named as the Yangtze River Scholars Distinguished Professor, China. His current research interests include advanced IC materials and processes, high-speed and low-power semiconductor devices, and so on.
Supplementary Materials for A Skin-Like Sensor for Intelligent Braille Recognition Xue-Feng Zhaoa, b,⊥, Cheng-Zhou Hanga,⊥, Hong-Liang Lua*, Ke Xuc, Hao Zhangc, Fan Yanga, Ru-Guang Mab, Jia-Cheng Wangb, *, David Wei Zhanga,* a
State Key Laboratory of ASIC and System, Shanghai Institute of Intelligent
Electronics & Systems, School of Microelectronics, Fudan University, Shanghai 200433, China. b
State Key Laboratory of High Performance Ceramics and Superfine Microstructure,
Shanghai Institute of Ceramics, Chinese Academy of Sciences, 1295 Dingxi Road, Shanghai 200050, China. c
Key Laboratory of Micro and Nano Photonic Structures (MOE), Department of
Optical Science and Engineering, Fudan University, Shanghai 200433, China
The file includes: Fig. S1. Scheme of Ti2C-MXene nanosheets preparation process. Fig. S2. Photograph of Ti2C-MXene membrane. Fig. S3. XRD patterns of MAX (Ti2AlC) and MXene (Ti2C) Fig. S4. Representative SEM images of Ti2C-MXene and EDS mapping images of Ti2CTx. Fig. S5. Commercial single interdigital electrode parameters and physical map. Fig. S6. I-V measurements for forward and backward sweepings of voltages from -0.1 to 0.1 V at an external pressure of 5.75 kPa. Fig. S7. The sensor was used to monitor human physiological activities. Fig. S8. Physical picture of the simple electrical signal monitoring system. Fig. S9. Response results of the upper computer when pressed the different positions on the sensor array.
Other Supplementary Material for this manuscript includes the following: Movie S1. (.mp4 format). When the position on the sensor array is pressed, the column colors is changed. Movie S2. (.mp4 format). The real-time Braille recognition process of the sentence ‘Hello word!’.
Fig. S1. Scheme of Ti2C-MXene nanosheets preparation process.
Fig. S2. Photograph of Ti2C-MXene membrane.
Fig. S3. XRD patterns of MAX (Ti2AlC) and MXene (Ti2C).
Fig. S4. (a), (b), (c) Representative SEM images of Ti2C-MXene after HCl and LiF etching. (d) EDS mapping images of Ti2CTx.
Fig. S5. (a), (b) Commercial single interdigital electrode parameters and physical map.
Fig. S6. The I-V curves of the sample under forward and backward sweepings in a voltage range from -0.1 to 0.1 V at an external pressure of 5.75 kPa.
Fig. S7. The sensor was used to monitor human physiological activities. The current of the sensor changes in real time, corresponding to throat swallowing (a), eye blinking (b), cheek bulging (c), finger touching (d) and finger bending (e) were also recorded.
Fig. S8. Physical picture of the simple electrical signal monitoring system.
Fig. S9. Response results of the upper computer when pressed the different positions on the sensor array.
Highlights A skin-like tactile sensor based on multilayer Ti2C-MXene film was designed and fabricated. The skin-like sensor displayed an ultrahigh sensitivity of 507 kPa-1, which is obviously higher than other pressure/tactile sensors reported. Intelligent Braille recognition by such a flexible skin-like tactile sensor with the random decision forests algorithm was realized.
Declaration of interests ☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. ☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:
Xue-Feng Zhao [email protected] Cheng-Zhou Hang [email protected] Hong-Liang Lu [email protected] Ke Xu [email protected] Hao Zhang [email protected] Fan Yang [email protected] Ru-Guang Ma [email protected] Jia-Cheng Wang [email protected] David Wei Zhang [email protected]
S2211-2855(19)31053-5
DOI:
https://doi.org/10.1016/j.nanoen.2019.104346
Reference:
NANOEN 104346
To appear in:
Nano Energy
Received Date: 28 August 2019 Revised Date:
1 November 2019
Accepted Date: 29 November 2019
Please cite this article as: X.-F. Zhao, C.-Z. Hang, H.-L. Lu, K. Xu, H. Zhang, F. Yang, R.-G. Ma, J.C. Wang, D.W. Zhang, A Skin-Like Sensor for Intelligent Braille Recognition, Nano Energy, https:// doi.org/10.1016/j.nanoen.2019.104346. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Elsevier Ltd. All rights reserved.
A Skin-Like Sensor for Intelligent Braille Recognition
Xue-Feng Zhaoa, b,⊥, Cheng-Zhou Hanga,⊥, Hong-Liang Lua*, Ke Xuc, Hao Zhangc, Fan Yanga, Ru-Guang Mab, Jia-Cheng Wangb, *, David Wei Zhanga,* a
State Key Laboratory of ASIC and System, Shanghai Institute of Intelligent
Electronics & Systems, School of Microelectronics, Fudan University, Shanghai 200433, China. b
State Key Laboratory of High Performance Ceramics and Superfine Microstructure,
Shanghai Institute of Ceramics, Chinese Academy of Sciences, 1295 Dingxi Road, Shanghai 200050, China. c
Key Laboratory of Micro and Nano Photonic Structures (MOE), Department of
Optical Science and Engineering, Fudan University, Shanghai 200433, China
*
Email: [email protected]; [email protected]; [email protected]
⊥
These authors contribute the work equally.
Abstract A flexible skin-like tactile sensor as one of the key components in the next generation for robots should have the ability to perform real-time feedback, continuous measurement, and quantization of weak target signals in the real applications (e.g. intelligent Braille recognition). Herein, inspired by human skin, a novel flexible piezoresistive tactile sensor with high sensitivity and linearity is designed and fabricated. It is composed of three main parts including the random Gaussian distribution (RGD) spinosum on polydimethylsiloxane as the top substrate, the multilayer Ti2C-MXene film as the intermediate conductive filler, and the commercial polyimide-based interdigital electrodes as the bottom substrate. The working mechanism of RGD spinosum and Ti2C-MXene films in the flexible tactile sensor are clarified by COMSOL Multiphysics simulations and density functional theory calculations, respectively. The assembled sensor demonstrates ultrahigh sensitivity, large linearity, excellent cycling stability, and fast response speed in the milliseconds. Moreover, the development of advanced neural network technology makes it possible to realize intelligent skin-like sensor. In this study, it is the first time to realize real-time Braille effective intelligent recognition by such a flexible skin-like tactile sensor with the random decision forests algorithm. This study is of great significance to solve the social and public issues of information exchange for the vision-impaired or even the blind that has been highly concerned in recent years. Keywords: Flexible tactile sensor, Random Gaussian distribution, Ti2C-MXene, Random decision forest algorithm, Braille recognition
1.
Introductions Information exchange for the vision-impaired or even the blind is a public and
social concern nowadays [1]. According to data released by the World Health Organization, the total number of blind people in the world is about 40 million, of which China is the country with the largest proportion. Braille is one important communication tools for the vision-impaired and the blind, which helps them to write and read [2]. For the existing Braille recognition methods, the extraction of Braille feature points is usually done manually, which is time-consuming, laborious, and unable to guarantee the validity of the extracted features [3, 4]. In addition, because the classification and recognition of the Braille characters by feature point comparison method is limited to the artificially defined feature points, the recognition accuracy is usually very low and the anti-interference capability is poor. Therefore, it is of great importance to develop a high-accurate and practical Braille recognition device for the management of ancient Braille books, the mental health, and the teaching of the blind. With the rapid development of flexible electronic technology [5] and artificial intelligence [6], the flexible pressure sensors [7] are expected to be a new way to realize effective and real-time Braille recognition due to their unique advantages such as easy to fit the tested object, test-accuracy, and strong anti-interference ability. Although many simple display-related applications have been reported recently [8-10], the flexible pressure sensors have not play an important role in our everyday life. One of the main reasons is the trade-off between sensitivity and stability of the pressure sensors has not been well balanced. As a result, the measured objects cannot be
measured and distinguished in real time and long-term stability. In recent years, two effective methods have been proven to solve the above problems. The first method is to introduce the nanoscale materials with excellent electrical and mechanical properties as the conductive fillers in flexible pressure sensors or the sensing elements such as silver nanowire [11], copper nanowire [12], graphene [13, 14], biomass-derived carbon[15] and so on[16]. Another method is to construct different surface microstructures or geometries (nanowires [17], pyramids [18], hemispheres [19], and prisms [20]) to gain high sensitivity and low detectable limitation. However, the technical bottlenecks still exist regarding how to fabricate a flexible pressure sensor with low cost, high sensitivity, large linearity, fast response speed, and high accuracy of recognition results. Thus, developing a flexible, skin-like, and effective pressure sensor is not only a huge challenge but also a significant research topic. 2.
Results and discussion Herein, we propose a skin-like sensor, based on piezoresistive sensing and its
capability of intelligent Braille recognition in real time. It is composed of three main parts, which corresponding to the three parts (epidermis, dermis and subcutaneous tissue) of human skin. The top substrate is the force perception layer with random Gaussian distribution (RGD) spinosum from lotus leaf, which is similar with the structural morphology of epidermis. This microstructure is essential for enhancing sensitivity and measuring and discriminating weak force. The intermediate conductive filler is the force treatment layer, which is formed by the multilayer Ti2C-MXene film
and can be compressed and released with external forces loading and unloading. The bottom substrate is the force signal-receiving layer, which is capable of converting the force signal into an electrical signal. By using the flexible skin-like tactile sensor, it is the first time to realize real-time Braille effective recognition with the random decision forests algorithm (RDFA). Wherein, the RDFA has great advantages over other algorithms in many data sets, such as fast training speed, strong anti-interference ability, simple implementation, parallel processing, etc., which are widely used in the fields of medicine, economics, management and remote sensing. 2.1 Skin-Like Sensor design concept and synthesis process Nature often provides the inspiration for the engineering development, particularly artificial electronic devices with various bionic structures. As a tissue covering the surface of human body, skin is the most critical tactile sensing tissue in the human body (Fig. 1a). On the one hand, there is spinosum layer under the epidermis. A particular interesting feature of the spinosum is RGD microstructure [14], which playing a key role to ensure an extremely sensitive response under low-intensity external stimuli. On the other hand, the dermis has excellent elasticity because it contains a large number of fibers such as collagen fibers, elastic fibers and reticular fibers [21]. Bioinspired by the tissue structure and the force perception process of human skin, a skin-like flexible tactile sensor (Fig. 1b) is designed. In this sensor, polydimethylsiloxane (PDMS) with lotus leaf surface microstructures is selected as the top substrate. Moreover, the overwhelming elasticity, biocompatibility and optical
properties of PDMS have been proven the most effective route to fabricate flexible electronic skin [22, 23]. Ti2C-MXene is selected as the intermediate conductive filler. MXene [24], as a new type of two-dimensional (2D) transition metal carbides and nitrides, are of interest in some important applications due to the excellent characteristics such as favorable strength, outstanding metallic electrical conductivity and large specific surface [25, 26]. Moreover, it has been reported that the pressure sensor based on Ti3C2-MXene accordion-like multilayer structure has high sensitivity [27]. In particular, compared to the most extensively researched Ti3C2-MXene, Ti2C-MXene has the thinner single layer thickness and larger specific surface area because Ti2C consists of two Ti layers and one C layer, while Ti3C2 consists of three Ti layers and two C layers [28]. The above superiorities of Ti2C make the conductivity change broader than Ti3C2 under the equal pressure loading, which will greatly improve the sensitivity of the sensor. The bottom substrate is a polyimide (PI)-based commercial interdigital electrode, which has excellent mechanical properties in terms of stretch ability and durability. Fig. 1c shows that the fabrication process of the random-distribution spinosum and Ti2C-based flexible pressure sensor. Wherein, the replication process of the micro-pattern on the top PDMS substrate was based on dual molding of the lotus leaves, which is a type of soft-lithography [29]. To improve the quality of replication, hard PDMS in the first molding and standard PDMS in the second molding was utilized. The multilayer Ti2C-MXene film was produced by immersing Ti2AlC powders in the mixture solution to remove off the Al layer, followed by suction
filtering to form multilayer film. After the spinosum of the lotus leaf surface was replicated on the PDMS, the Ti2C-MXene multilayer film was coated on the PDMS substrate with RGD spinosum. Finally, the bottom interdigital electrode was laminated onto the Ti2C-MXene film, completing a sandwich structure. To investigate the piezoresistive effect of the sensor, the electrical response of the device at different pressure levels was examined by an electrical signal testing system (see in the experimental section).
Fig. 1. Skin-Like Sensor design concept and synthesis process. (a) Schematic diagram of human skin, which is mainly composed of three parts: epidermis, dermis and subcutaneous tissue. The RGD spinosum of the outer epidermis is one of the most the crucial factors for obtaining high sensitivity. (b) Schematic diagram of the skin-like tactile sensor, consisting of the top PDMS surface layer with RGD spinosums, the
intermediate Ti2C-MXene assembly films as flexible conductive sensing layer, and the bottom PI-based interdigital electrode. (c) Fabrication process of the skin-like tactile sensor. 2.2 Force perception layer characterization and sensing mechanism. The photo image of a fresh lotus leaf is shown in Fig.2a. It can be clearly seen from the SEM images (Fig. 2b) that the surface of lotus leaf has the RGD spinosum. The average distance between the RGD spinosum is about 7 µm. The replication result after the second molding is obtained by the SEM (Fig. 2c) and the Confocal Laser Scanning Microscope (CLSM) image (Fig. 2d). By comparing the statistics of the spinosum on the lotus leaf and PDMS in the direction of height, it can be found that PDMS is intact to replicate the surface morphology of the lotus leaf, and the resultant spinosum have the characteristics of RGD in height as well as those on the lotus leaf (Fig. 2e). In general, the sharp microstructures are helpful to improve the sensitivity, because the contact area is dramatically increased under a small external pressure. However, when further deformation occurs, the sensitivity of this sensor decreases sharply, resulting in nonlinearity and rapid saturation. In view of the comprehensive performance and practical application of the pressure sensor, a high sensitivity and a large linearity range are desired for coexistence. In order to study the influence of different geometric shapes on the pressure distribution of the pressure sensor, the displacement distributions of nanowire (Fig. 2f), pyramid (Fig. 2g) and RGD spinosum (Fig. 2h) under 10 kPa loading are simulated by COMSOL Multiphysics.
The simulation results illustrated that the nanowire structures presents a uniform pressure distribution along the altitude direction (Fig. 2f), and the sharp pyramid structures have the force concentration at the top cusp region (Fig. 2g). Interestingly, the force of the RGD spinosum is concentrated on the initial contact peak and transferred to the adjacent peaks (Fig. 2h), which indicates that the pressure distribution of the RGD spinosum is more homogeneous than the pressure distribution of the other two regular morphologies. Therefore, under less pressure, the RGD spinosum is more likely to reach saturation than other structures, which provides favorable conditions for the device to achieve high sensitivity. At the same time, with the increase of pressure, the deformation of the contact point of the RGD spinosum transfers to the periphery, which makes the resistance change of the device continue to show a linear relationship, and effectively improves the range of pressure measurement of the device.
Fig. 2. Micropattern morphology and force perception mechanism of RGD spinosum PDMS. (a) The photo image of a lotus leaf. (b) SEM picture of the spinosum set on the lotus leaf. (c) SEM image and, (d) CLSM image of the RGD spinosum PDMS. (e) Comparison of the microstructural height distribution between the lotus leaf and RGD spinosum PDMS. (f), (g), (h) COMSOL Multiphysics simulation results of the displacement distribution of different geometries: nanowire, pyramid and RGD spinosum under the external loading pressure of 10 kPa. 2.3 Force treatment layer characterization and sensing mechanism. The schematic diagram for the synthesis process of multilayer Ti2C-MXene film is illustrated in Fig. S1, and the photograph of the Ti2C-MXene film is shown in Fig.
S2. The X-ray diffraction (XRD) patterns (Fig. S3) indicate that the Ti2AlC was successfully converted into Ti2C-MXene. As observed in the SEM images (Fig. S4a-c) and the transmission electron microscopy (TEM) image (Fig. 3a), Ti2AlC has changed into a loosely stacked structure after solution etching. The elemental mapping in Fig. S4d shows that all elements distribute homogeneously. The corresponding diffraction pattern in the inset of Fig. 3a and the high-resolution TEM images (HRTEM) image (Fig. 3b-d) clearly illustrates the crystalline lattice of multilayer Ti2C nanosheets with hexagonal structure, which indicates the good crystallization characteristics of the as-synthesized Ti2C nanosheets. Fig. 3b1, b2 show the distinct lamellar structure with an average interlayer distance of 1.10 nm, and the hexagonal characteristics can be recognized well in Fig. 3d1, d2 with the (100) plane distance of 0.25 nm. In particular, the first-principles calculations is carried out using density function theory (DFT) [30] to directly illustrate the working mechanism of Ti2C in the tactile sensor. As shown in Fig. 3e, the monolayer Ti2C, consisting of a planar C sublayer sandwiched by two Ti sublayers, possesses a low symmetry of C3v point group, with the symmetry operations of C3 and vertical mirror reflection σv [31]. The C-C, Ti-C and Ti-C are covalently bonded to each other according to the charge density distribution of a five-layer Ti2C from side view, as shown in Fig. 3f. The ab-initio calculations of the band structure and the orbital projection of monolayer Ti2C are shown in Fig. 3g. Monolayer Ti2C is gapless and the valence and conduction bands around Fermi level are dominantly composed by Ti-d orbitals. For more details, dxz+dyz+dz2 orbitals contribute more to valence and conduction bands of monolayer
Ti2C than dxy+dx2-y2 orbitals. We also calculated the band structure and orbital projection for five-layer Ti2C, which can be regarded as bulk phase indeed, as shown in Fig. 3h. Similar orbital contributions can be found. To compare experiments and investigate the piezoresistive effect of monolayer and multilayer Ti2C, we calculated the electron conductivity relaxation time
in the unit of
for different strains, which was performed based on the rigid-band
approximation using Boltztrap [32]. The resistance ρ can be calculated by the inverse of electron conductivity , and the relaxation time
can be treated as that of
free electron life time ~10-14s (100 ps). To clarify the influence from dimension, we studied the electronic transport at room temperature of monolayer and five-layer Ti2C respectively, as shown in Fig. 3i-k. Generally, when applying compressive strains, the interlayer distance becomes smaller, leading to a higher overlap integral V between layers due to
∝ 1/
[33]. According to the molecular orbital theory, the
bandwidth W is roughly determined by the overlap integral by
∝ , and when
compressive strains apply, the overlap integral increases, which will enlarge the bandwidth W and result in a narrow parabola near VBM or CBM, finally leading to a decreasing effective mass m* [34]. The decreasing effective mass increase the value of carrier mobility according to
=
∗
. Subsequently, the electron conductivity
increase due to σ=neµ, where n represents the electron concentration, e is the electronic charge. Therefore, applying the compressive strains will lower the resistance ρ, which is valid for both bulk and monolayer Ti2C as shown in Fig. 3i-k. Moreover, the resistance along z direction is larger than that along x/y direction.
When applying the compressive strain along both z and x/y directions, the resistance decreases with the increasing strain due to a larger overlap integral
∝ 1/
, since
the bond length decreases. We supposed that since dxz+dyz+dz2 orbitals contribute more to the valence and conduction bands of monolayer Ti2C than dxy+dx2-y2 orbitals , the resistance of z direction will be more susceptible to the strain than that of x/y direction, leading to a bigger decrease along z direction with increasing strains. We can also find the resistance of five-layer Ti2C (shown in Fig. 3k is much smaller than that of monolayer Ti2C because of the existence of the overlap integral between layers in multilayer structures. Therefore, the change of the overlap integral between layers due to strains will play a significant role on the piezoresistive effect of monolayer and multilayer Ti2C.
Fig. 3. Ti2C-MXene characterization and working mechanism. (a) Ti2C-MXene’s TEM image and its corresponding diffraction pattern in the inset, showing accordion-like fluffy features and well the hexagonal characteristics. (b) HRTEM images of Ti2C-MXene displaying the lamellar structure. (c), (d) The plan view
HRTEM images shows the well-crystallized feature of the Ti2C-MXene nanosheets. (e) Atomic structure of the single layer of Ti2C-MXene from top view and side view. (f) Atomic structure and charge density of a five-layer Ti2C-MXene from side view. (g), (h) The band structure and orbital projection of monolayer and multilayer Ti2C-MXene respectively. (i), (j) The evolution of the resistance of monolayer Ti2C-MXene as a function of chemical potential at 300K under the compressive strain along x and z direction respectively. (k) The evolution of the resistance of multilayer Ti2C-MXene as a function of chemical potential at 300K under the compressive strain along z direction. 2.4 The properties of the skin-like sensor. To investigate the piezoresistive effect of the sensor, the rectangular commercial interdigital electrodes are used to receive the varying electrical signals (Fig. S5a, b), and the electrical response of the device at different pressure levels is examined by an electrical signal testing system (see in the materials and methods sections). The I–T curves with the pressure less than 40 kPa shows a monotonic increase in current with higher pressure (Fig. 4a). This suggested shows that our pressure sensor can clearly distinguish between different levels of the external force. The linear relationship of the I–V curves (Fig. 4b) for the voltage from −0.1 to 0.1 V indicates that an Ohmic contact is formed between the multilayer Ti2C-MXene film and interdigital electrode. As the applied load increases, the slope of the I-V curve increases correspondingly, indicating that the resistance of the multilayer Ti2C-MXene film of this sensor is reduced accordingly. Furthermore, the forward and backward sweeping I-V curves of
the fabricated sensor are measured in a voltage range from -0.1 to 0.1 V at an external pressure (Fig. S6). It can be observed clearly that the forward and backward sweeping I-V curves are completely coincident, suggesting that the Ti2C-MXene film have an excellent Ohmic contact with the interdigital electrodes. The sensitivity of a piezoresistive device is a significant parameter for evaluating device performance, which is generally defined as S = (∆I /I0 )/∆P, where ΔI denotes the current change before and after applying pressure, I0 represents the initial current without pressure, and ∆P is the amount of pressure change from I0 to I. We measured the ∆I /I0 relative to the pressure value, as shown in Fig. 4c. The result indicates that the current curve varies linearly in three regions with the change of pressure. In the low pressure region (0-5.75 kPa), the sensitivity of the device is as high as 507 kPa−1, while in the high pressure region (12-40 kPa) and the transitional pressure region (5.75-12 kPa), the sensitivity of device is 25 kPa−1 and 224 kPa−1, respectively. As far as we know, the sensitivity and linearity of the present pressure sensor are much higher than other sensors (Fig. 4e). The reasons may be as follows (Fig. 4i). In the low pressure region, the pressure on the contact point of the RGD spinosum on the PDMS is concentrated, which results in the interlayer distance of multilayer Ti2C-MXene rapidly gradually reduced while the atomic distance of monolayer Ti2C-MXene also gradually reduced, thus reducing the total resistance of Ti2C-MXene film and increasing the output current. It is worth noting that the atomic distance is much smaller than the interlayer distance, so the rate of the interlayer distance dominant. In the transitional pressure region, the interlayer distance and the atomic distance is further reduced
simultaneously while the contact point of the RGD structure transfers to the periphery, which leads to the increase of the contact area between MXene-RGD spinosum and interdigital electrode, and then slowly reduces the total resistance of Ti2C-MXene film. In the high-pressure region, the descent rate of the interlayer distance and the atomic distance is very small, but the contact area between MXene-RGD structure and interdigital electrode is greatly increased, so that the total resistance of Ti2C-MXene film is basically unchanged. Meanwhile, both the output current and external pressure were in good synchronization with the loading and unloading, as shown in Fig. 4d. As presented in Fig. 4f, our sensor can clearly detect a very small pressure of 8 Pa. In addition, we measured the response and recovery time of the device under pressure with specific results of 60 ms and 40 ms, which makes it possible to implement real-time testing (Fig. 4g). In order to further evaluate the mechanical stability and operational life of the sensor, the 5,000 cycles of loading and unloading pressures were tested, as shown in Fig. 4h. After cyclic testing, the current signal shows a little attenuation,
and
keeps
almost
the
same
current
variation
after
each
compression-release cycle, which proves that the device has high stability and long durability.
Fig. 4. The properties of the skin-like sensor. (a) The I–T curves with the pressure less than 40 kPa. (b) The linear relationship of the I–V curves for the voltage from −0.1 to 0.1 V. (c) The sensitivity of the sensor, exhibiting a high sensitivity of 507 kPa−1 below 5.75 kPa, 224 kPa−1 in the transitional pressure region (5.75-12 kPa) and 25 kPa−1 in the high pressure region (12-40 kPa). (d) The synchronization relation between I-T and P-T curves. (e) Comparison between our pressure sensor and previous reported pressure sensors in terms of the sensitivities within a linear pressure
range and the linearity. (f) The detection limit of the sensor. (g) The response time with loading and unloading pressure of the sensor. (h) Stability of this sensor with press-release 5,000 cycles. (i) Schematic diagram of sensing principle in different pressure stages of RGD spinosum surface. 2.5 The topographical map scanner by the skin-like sensor. A randomly-distribution spinous, MXene-based flexible skin-like tactile sensor exhibits ultrahigh sensitivity, large linearity, fast response speed and high stability. It has great potential application value in the field of Internet of Things and artificial intelligence. We attached it directly on the joint or muscle, and then fixed it with the transparent tape to monitor human physiological activities, e.g. throat swallowing (insets in Fig. S7a), eye blinking (insets in Fig. S7b), cheek bulging (insets in Fig. S7c), finger touching (insets in Fig. S7d) and finger bending (insets in Fig. S7e). The results show that the relative I-T curves of different physiological activities are different and easy to distinguish by comparing the intensity change and shape of these diagrams. Moreover, the current value remained nearly unchanged under the same motion when the physiological activity switched rapidly. To get closer to a more practical application, a 16-pixel pressure sensor array (4 × 4 elements) is fabricated to detect pressure distribution (Fig. 5a, b), and the simple electrical signal monitoring system is designed as shown as Fig. S8. When no pressure on the sensor array, the column colors in the upper computer are all blue (representing zero pressure). When the position on the sensor array is pressed, the column colors changed due to the different force of each individual sensor (Fig. 5c).
Then we pressed the other different positions of the sensor array (Fig. S9 and Movie S1) and the results show that the sensor array is very sensitive for external force loading and unloading, which make it possible to achieve the force direction detecting and topographical maps scanning. We use small Aluminum cubes (5 mm×5 mm ×5 mm) to shape the letters, such as F, U, D, A and N (Fig. 5d). The normalized grayscales display the sensor array is able to clearly identifying the complex shapes. This phenomenon further demonstrates that the piezoresistive sensors have excellent resistance change performance.
Fig. 5. The applications of the skin-like sensor for the topographical map scanner. (a) The structural diagram of the 4 × 4 elements array interdigital electrode parameters. (b) The physical picture of the 16-pixel pressure sensor array. (c) The response of the upper computer when press a position on the sensor array. (d) F, U, D, A and N
patterns using cubes and topographical maps of normalized grayscales variations for the F, U, D, A and N patterns. 2.6 The sensor for intelligent Braille recognition in real-time. To further extend the application of this device, the tactile sensor combined with the RDFA is used to realize the real-time Braille effective recognition (Fig. 6a). RDFA is a comprehensive learning method for tasks such as classification and regression. And it operates by building multiple decision trees during training time and outputting a single tree's class (classification) or mean prediction (regression) [35]. We used our sensor array to test the Braille bumps of 26 English letters and common punctuation marks five times, respectively. Then all data were input to the RDFA. After the training, we tested the Braille of single letters (Fig. 6b), words (Fig. 6c) and sentences (Fig. 6d) respectively. The accuracy of the real-time Braille recognition is more than 99% and the results illustrate that the high sensitivity of the flexible tactile sensing system which opens up a new field for wearable devices and electronic skin (Movie S2)
Fig. 6. Recognition Braille in real-time by the sensor array based on the RDFA. (a) Schematic diagram of Braille recognition process. (b) Recognition results of single Braille letters, such as ‘A’, ‘B’ and ‘C’. (c) Recognition results of Braille words, such as ‘we’, and ‘ok’. (d) Recognition results of Braille sentences, such as ‘Hello world!’. 3.
Conclusions A biomimetic flexible skin-like tactile sensor with RGD spinosum as the
substrate and Ti2C-MXene film as the conductive filler was fabricated. COMSOL Multiphysics study and DFT study directly illustrated the working mechanism of RGD spinosum and materials in the skin-like sensor, respectively. The spinosum microstructure and RGD contribute to the ultra-high sensitivity and large linearity
range, respectively. The huge change of the interlayer distances in the Ti 2C-MXene film under pressure is the herent working mechanism for the piezoresistive sensor. The value of sensitivity reached to 507 kPa-1, which is obviously higher than other pressure/tactile sensors reported. Based on the excellent performance of the device, we applied the sensor in human activities monitor and topographical map scanner. In addition, the sensor array combined with the RDFA is used to realize real-time Braille effective recognition. For the first time, we demonstrated a new type of the flexible pressure sensor to serve this purpose. Our solution offers low cost while maintaining high sensitivity, large linearity, fast response speed, and high accuracy. Therefore, it is of great potential for practical adoption in the near future. 4.
Materials and methods
4.1 Materials Polydimethylsiloxane (PDMS) elastomer (Sylgard 184) was purchased from Dow Corning Co., Ltd. The MAX- Ti2AlC (400 mesh) was purchased from 11 Technology Co., Ltd. Lithium fluoride (LiF, 98.5 % purity), concentrated hydrochloric acid (HCl, 37.2% purity) were purchased from Aladdin Inc. (China). The interdigital electrode (5 mm×5 mm, line width 100 µm, line space 100 µm ) was purchased from Shangyou Electronic Technology Co., Ltd. (China). 4.2 Device fabrication 4.2.1
Fabrication of PDMS substrates with lotus leaf surface micropattern The fabrication process diagram is shown in Fig. 1c. Fresh lotus leaves were cut
into rectangles (5 mm× 5 mm) and washed three times with deionized water. After
being dried by nitrogen, fasten the lotus leaf to the 4-inch silica wafer substrate with double-sided tapes. For better replication quality, PDMS prepolymer was prepared with a base to curing agent ratio of 5:1 and degassed in a vacuum desiccator for 20 minutes to remove air bubbles at room temperature. A quantity of PDMS mixture was spin coated (at 400 rpm) onto the leaves. Then, after curing at 70 °C for 1 h, the PDMS film with opposite structures of lotus leaf was peeled off and used as a second molding template. In order to reduce the adhesion during the second molding process, the surface of the molding template was fluorinated. Particularly, the two molding processes were similar, the only difference was that the second molding process utilized the standard PDMS (the weight ratio of base to cross linker was 10:1). Finally, the PDMS film with delicate spinous pattern from lotus leaf was fabricated by the hard and standard PDMS double-layer molding process. 4.2.2
Synthesis of multilayer Ti2C-MXene film
The multilayer Ti2C-MXene was produced by immersing Ti2AlC powders in the mixture solution to remove the Al layer. Etching solution was made by adding two grams of LiF into 40 ml HCl (6 M, 36–38 wt.%) solution. The solution was mixed by sonication for 15 min to dissolve all LiF. Thereafter, 2 g of Ti2AlC powders were immersed in the above solution, stirred for 1 min, and then the mixture was held at 40 ℃ for 48 h with magnetic stirring. Thereafter the mixture was separated by centrifugation, washed with deionized water and ethanol several times, until the supernatant reached a pH value of ~6. Obtained Ti2C powders were dried in vacuum at 80 ℃ for 12 h. In order to facilitate the operation, the powder was prepared into
membrane by the suction filter process. 4.3 DFT calculation method All the first principle calculations are performed using the Vienna ab-initio simulation package (VASP) based on density functional theory (DFT) [36]. The exchange-correlation energy is described by the generalized gradient approximation (GGA) in the Perdew-Burke-Ernzerhof (PBE) parametrization. The DFT-D3 approach is chosen to involve the long-distance van der Waals (vdW) interactions [37]. The calculation is carried out by using the projector-augmented-wave (PAW) pseudopotential method with a plane-wave basis set with a kinetic energy cutoff of 600 eV. A 15×15×1 Γ-centered k-mesh was used during structural relaxation for the unit cell until the energy differences are converged within 10−6eV, with a Hellman-Feynman force convergence thresh-old of 10−4eV/Å. The vacuum size is about 16 Å between two adjacent atomic layers to eliminate artificial interactions between them. The electrical transport properties, such as electronic conductivity, were computed by solving the semiclassical Boltzmann transport equation, which is implemented in Boltztrap code [38]. Through Fourier expansion, the code fits an analytical function to the ab initio electronic band structure [39]. The transport coefficient is calculated from the analytical expression of the conductivity tensor ( ), as σ
( , )= !
( ) "−
$%& ( ,',() $'
)
(1)
where Ω and f0 were the volume of unit cell and Fermi-Dirac distribution respectively.
Also, the relaxation time approximation was used to treated the relaxation time as both energy and direction independent constant [40]. 4.4 Device characterization 4.4.1
Force response measurement setup
The measurement setup consisted of a computer servo control vertical pressure testing machine (HD-B609B-S) to carry out uniaxial compression and release, and the current of each sensor under the different pressure was measured by a SourceMeter (Keithley 2450). The input voltage was set as 0.1 V during the tests. 4.4.2
Real-time Braille recognition system setup
In order to demonstrate the Braille recognition process, the Braille used in this study was customized, and the diameter of each Braille bumps was 5 mm. Random forests consisted of decision trees, each of which was not related. Through bootstrap sampling of training sets, training subsets were generated, and then decision trees were generated to form random forests. The training set was sampled by bootstrap sampling method to generate a training subset, which was a decision tree. In this study, we trained 100 decision trees to form a random forest.
ACKNOWLEDGMENTS We acknowledge the great help from Prof. Z.G.Ji at Liverpool John Moores University. This work is supported by the National Key R&D Program of China (No.2016YFE0110700), National Natural Science Foundation of China (No. 11804055, 51861135105 and 61874034), and Natural Science Foundation of
Shanghai (No. 18ZR1405000). Prof. J.C.Wang acknowledges support by Equipment Research Program (6140721050215) and State Key Laboratory of High Performance Ceramics and Superfine Microstructure.
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Biography for Nano Energy Xue-Feng Zhao is a Ph.D. candidate in the Laboratory of Nanosensor, School of Microelectronics, Fudan University, Shanghai, China. He obtained his M.S. degree from North University of China, Taiyuan, China. His current research interests include preparation and integration of flexible wearable devices, fabrication and functionalization of novel and advanced nanomaterials.
Cheng-Zhou Hang is a master's student from the School of Microelectronics at Fudan University in Shanghai, China. He received his bachelor's degree from Dalian University of Technology, Dalian, China. His research interests focus on the flexible sensors and wearable devices.
Prof. Hong-Liang Lu received the Ph.D. degree in microelectronics from Fudan University, Shanghai, China. He was a JSPS Research Fellow with the Department of Electrical Engineering and Information Systems, The University of Tokyo, Tokyo, Japan. He is currently a Professor with the School of Microelectronics, Fudan University. His current research interests include atomic layer deposition of thin films, high mobility semiconductor devices, advanced micro-nano sensors, and so on
Ke Xu is a master student in the Department of Optical Science and Engineering, Fudan University, Shanghai, China. His current research interests focus on topological materials, non-Hermitian
topological
phases,
thermoelectrics,
density-functional theory and many-body perturbation theory.
Hao Zhang received the Ph.D. degree in optics from Fudan University, Shanghai, China. He is currently an Associate Professor with the Department of Optical Science and Engineering, Fudan University. His research interests include density-functional
theory,
thermoelectrics,
exciton,
two-dimensional materials and topological materials.
Prof. Fan Yang received the B.E. degree from Xi’an Jiaotong University in 2003 and his Ph.D. degree from Fudan University in 2008. He is currently a Professor with the School of Microelectronics, Fudan University. His current research interests include circuit simulation, yield analysis and design for manufacturability. Ru-Guang Ma received his Ph.D. in materials science from City University of Hong Kong in 2013. Then he worked at Nanyang Technological University as a post-doctoral
researcher. In July 2014, he joined Shanghai Institute of Ceramics, Chinese Academy of Sciences (SICCAS). He is currently an associate professor in the State Key Lab of High Performance Ceramics and Superfine Microstructure, SICCAS. His research interests include design and synthesis of new nanostructured electrode materials for Li ion batteries, supercapacitors, metal–oxygen batteries and non-precious metal catalysts.
Prof. Jia-Cheng Wang received the Ph.D. in 2007 from Shanghai Institute of Ceramics, Chinese Academy of Sciences (CAS). He previously held several fellowships and awards including JSPS (Japan Society for the Promotion of Science) postdoctoral fellowship (2010, the University of Tokyo), Alexander von Humboldt Fellowship (2011, Dresden University of Technology), Marie-Curie Intra-European Fellowship (2012, Cardiff University) and “One Hundred Talent Plan” of CAS (2014). He is currently co-Editor-in-Chief of Nano Advances (ISSN 2415-1386) and editorial member of Scientific Reports. He has strong backgrounds in high-throughput screening of energy conversion and storage materials, electrochemical energy devices, and their scale-up and commercialization. Prof. David Wei Zhang received the Ph.D. degree from Xi'an Jiaotong University, Shaanxi, China. He was a Humboldt Research Fellow with the TU-Chemnitz, Germany. He is currently a full Professor and Deputy Dean with the School of
Microelectronics, Fudan University. He was also named as the Yangtze River Scholars Distinguished Professor, China. His current research interests include advanced IC materials and processes, high-speed and low-power semiconductor devices, and so on.
Supplementary Materials for A Skin-Like Sensor for Intelligent Braille Recognition Xue-Feng Zhaoa, b,⊥, Cheng-Zhou Hanga,⊥, Hong-Liang Lua*, Ke Xuc, Hao Zhangc, Fan Yanga, Ru-Guang Mab, Jia-Cheng Wangb, *, David Wei Zhanga,* a
State Key Laboratory of ASIC and System, Shanghai Institute of Intelligent
Electronics & Systems, School of Microelectronics, Fudan University, Shanghai 200433, China. b
State Key Laboratory of High Performance Ceramics and Superfine Microstructure,
Shanghai Institute of Ceramics, Chinese Academy of Sciences, 1295 Dingxi Road, Shanghai 200050, China. c
Key Laboratory of Micro and Nano Photonic Structures (MOE), Department of
Optical Science and Engineering, Fudan University, Shanghai 200433, China
The file includes: Fig. S1. Scheme of Ti2C-MXene nanosheets preparation process. Fig. S2. Photograph of Ti2C-MXene membrane. Fig. S3. XRD patterns of MAX (Ti2AlC) and MXene (Ti2C) Fig. S4. Representative SEM images of Ti2C-MXene and EDS mapping images of Ti2CTx. Fig. S5. Commercial single interdigital electrode parameters and physical map. Fig. S6. I-V measurements for forward and backward sweepings of voltages from -0.1 to 0.1 V at an external pressure of 5.75 kPa. Fig. S7. The sensor was used to monitor human physiological activities. Fig. S8. Physical picture of the simple electrical signal monitoring system. Fig. S9. Response results of the upper computer when pressed the different positions on the sensor array.
Other Supplementary Material for this manuscript includes the following: Movie S1. (.mp4 format). When the position on the sensor array is pressed, the column colors is changed. Movie S2. (.mp4 format). The real-time Braille recognition process of the sentence ‘Hello word!’.
Fig. S1. Scheme of Ti2C-MXene nanosheets preparation process.
Fig. S2. Photograph of Ti2C-MXene membrane.
Fig. S3. XRD patterns of MAX (Ti2AlC) and MXene (Ti2C).
Fig. S4. (a), (b), (c) Representative SEM images of Ti2C-MXene after HCl and LiF etching. (d) EDS mapping images of Ti2CTx.
Fig. S5. (a), (b) Commercial single interdigital electrode parameters and physical map.
Fig. S6. The I-V curves of the sample under forward and backward sweepings in a voltage range from -0.1 to 0.1 V at an external pressure of 5.75 kPa.
Fig. S7. The sensor was used to monitor human physiological activities. The current of the sensor changes in real time, corresponding to throat swallowing (a), eye blinking (b), cheek bulging (c), finger touching (d) and finger bending (e) were also recorded.
Fig. S8. Physical picture of the simple electrical signal monitoring system.
Fig. S9. Response results of the upper computer when pressed the different positions on the sensor array.
Highlights A skin-like tactile sensor based on multilayer Ti2C-MXene film was designed and fabricated. The skin-like sensor displayed an ultrahigh sensitivity of 507 kPa-1, which is obviously higher than other pressure/tactile sensors reported. Intelligent Braille recognition by such a flexible skin-like tactile sensor with the random decision forests algorithm was realized.
Declaration of interests ☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. ☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:
Xue-Feng Zhao [email protected] Cheng-Zhou Hang [email protected] Hong-Liang Lu [email protected] Ke Xu [email protected] Hao Zhang [email protected] Fan Yang [email protected] Ru-Guang Ma [email protected] Jia-Cheng Wang [email protected] David Wei Zhang [email protected]