Bioinspired Tribotronic Resistive Switching Memory for Self-Powered

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Bioinspired Tribotronic Resistive Switching Memory for Self-Powered Memorizing Mechanical Stimuli Yihui Sun, Xin Zheng, Xiaoqin Yan, Qingliang Liao, Shuo Liu, Guangjie Zhang, Yong Li, and Yue Zhang ACS Appl. Mater. Interfaces, Just Accepted Manuscript • DOI: 10.1021/acsami.7b15269 • Publication Date (Web): 21 Nov 2017 Downloaded from http://pubs.acs.org on November 22, 2017

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ACS Applied Materials & Interfaces

Bioinspired Tribotronic Resistive Switching Memory for Self-Powered Memorizing Mechanical Stimuli

Yihui Sun1,†, Xin Zheng1,3,†, Xiaoqin Yan*,1, Qingliang Liao1, Shuo Liu1, Guangjie Zhang1, Yong Li1, Yue Zhang*,1,2

1

State Key Laboratory for Advanced Metals and Materials, School of Materials Science and

Engineering, University of Science and Technology Beijing, Beijing 100083, China E-mail: [email protected]; [email protected]. Tel: +86 10 62334725; fax: +86 10 62332011. 2

Beijing Municipal Key Laboratory of New Energy Materials and Technologies, University of

Science and Technology Beijing, Beijing, 100083, China 3

College of Materials & Environmental Engineering, Hangzhou Dianzi University, Hangzhou,

China †

These authors contributed equally to this work.

Keywords: haptic memory, electronic skin, resistive random access memory, triboelectric nanogenerator, bioinspired Abstract Haptic memory, from the interaction of skin and brain, can not only perceive external stimuli but also memorize it after removing the external stimuli. For the mimicry of human sensory memory, a self-powered artificial tactile memorizing system were developed by coupling bionic electronic skin and nonvolatile resistive random access

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memory (RRAM). The tribotronic nanogenerator is utilized as electronic skin to transform the touching signal into electric pulse, which will be programmed into the artificial brain: RRAM. Owing to the advanced structural designs and accurately parameter matching, including the output voltages and the resistances in different resistive states, the artificial brain can be operated at self-powered mode to memorize the touch stimuli with the responsivity up to 20 times. For demonstrating the application potential of this system, it was fabricated as an independently addressed matrix to realize the memorizing of motion trace in two-dimensional space. The newly designed self-powered nonvolatile system has broad applications in next-generation high performed sensors, artificial intelligence and bionics. Introduction With the springing up of flexible electronic device, all kinds of sensors become research hotspots, such as electronic skin, which promises to be an excellent substitutes of natural skin to perceive extremal stimuli.1-3 Considerable researches focused on the sensing performance of electronic skin to achieve high sensitivities, fast response, low energy consumption (even self-power) and assembling.4 For example, the introduction of single electrode-triboelectric nanogenerator (TENG) provides an exciting strategy to achieve high response and self-powered touch sensor, and multi-cells can be assembled to detect the movement path, kinematic velocity and accelerated speed.5-10 However, for a complete sensing system, there are two sections which contains of signal detecting unit and signal storage unit. Just like human touching behavior, the skin sends the signal to brain after it suffers from the external


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stimuli and the brain is responsible to memory the significant sensation information such as force, pain, shape, and texture.11 So, the volatile characteristic of electronic skin limited its applications towards emulating the exquisite tactile sensation of natural skin, and a suitable signal storage unit is desired. Traditional flash memory,12 phase change material (PCM)13 and other memory solutions14 are attempted to be brought in electronic skin to carry out the goal of sensing-memorizing-integrating. Compared with other memory devices, resistive random access memory (RRAM) device is more promising as an excellent candidate for its superior memory performance: high scalability, low operating energy, great endurance, long retention time and simple device structure.

15-18

The two-terminal

geometry of RRAM with a metal-insulator-metal (MIM) architecture makes it very convenient to couple with other devices. 19,20 More inspiringly, the resistive switching memory, or sometime termed memristor, can be used in neuron computing to simulate synaptic plasticity.

21-24

So RRAM has a broader application in cooperating with

electronic skin to imitate the interaction of human skin and human brain. The resistive switching memory, as the signal storage unit, is also chosen to integrate with resistive pressure sensors to achieve touching memory. 25 But the complex writing and reading operations with pressure partly cripple its superiority, and the continuously energy supply is another problem. Herein, the resistive random access memory (Au/Ta2O5/AZO) and single electrode triboelectric nanogenerator (PTFE/Al) are integrated to develop a self-powered sensing-memorizing-integrated system to simulate the cooperation of human skin and



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human brain. The TENG is used as signal detector (like human skin) and power source, while the RRAM is used as recorder (like human brain). After modulating the performance of each cell, the integrated system successfully achieves the touch sensing and memorizing. 5 * 5 matrix of the device array is designed to detect the motion trajectory, and the signal can be saved even ending the touching. The fabricated system may propel the research in electronic skin and artificial intelligence. Results and Discussion Like

brain

in

haptic

memory,

the

RRAM

is

the

key

in

the

sensing-memorizing-integrated system, which is different from traditional sensors. So, Ta2O5 is selected to sandwiched between Au squared top electrode and AZO bottom electrode to develop a RRAM device (Figure 1a), while reliable switching up to a trillion cycles has been demonstrated in TaOx based devices. 26, 27 The memory device exhibits a typical hysteresis loop in the current-voltage (I-V) curve at positive and negative voltages (Figure 1b). An increasing negative bias is applied on top electrode and abruptly raising of current is occurred at -0.75 V. The sharp change of I-V curve in resistive switching behavior owes to the formation of conducting filaments in the Ta2O5-x film, differing from the homogeneous resistive switching. The device switches its resistance from high resistive state (HRS) to low resistive state (LRS), which is called “programming process”, and the threshold point of voltage is defined as Vset. It keeps in LRS even though the bias is moved, which shows nonvolatile feature. By that, after the device was switched on or off, the written data can be memorized, and no electrical power is needed to maintain the resistance at the given state. 28 The resistive


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state cannot change back to HRS until the applied voltage is over 0.75V, which is “erasing process”. Identically, it can also retain its resistive state under the threshold voltage or without electrical power. Quantized conductance, where the conductance is in units of the quantum of conductance G0=2e2/h, has been found in filamentary resistive switching.29 The I-V curves in reset process are chosen to compare with the G0 boundary (Figure S3). The current jumps (at ~0.75 V) crossing the G0 boundary represents the breaking of CF, which also confirms the filamentary resistive switching. 30

Meanwhile, the device demonstrates reliable endurance of over 80 cycles as shown in

Figure 1b. The endurance measurements that ensured the switching between on and off states were highly controllable, reversible, and reproducible.

31, 32

The resistances in

LRS and HRS are particularly important for the output voltage of TENG. The different resistances will result in the different output voltages of TENG. So, the resistances in LRS and HRS are measured at 0.1 V read voltage as presented in Figure 1c. The resistances almost keep about 105 Ω in HRS and 104 Ω in LRS. What`s more, the output voltages must higher than the SET voltage to drive the device switching from HRS to LRS. Cumulative distribution of the SET and RESET voltages illustrates that the SET voltage is ranging from -0.61 V to -0.92 V while the RESET voltage is ranging from 0.365 V to 0.875 V (Figure 1d). In general, there is compliance current (CC) to confine the growth of conductive filament in RS process, which is a big limit for its practical application.

33

The compliance current is set by external device, which makes the

system more complex and non-self-powered. In our work, the device can operate reliably without compliance current, which is necessary for our fully self-powered



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integrated system.

Figure 1. The performance of Au/Ta2O5/AZO device. (a) Schematic illustration of the Au/Ta2O5/AZO junction structure. (b) Endurance of I-V curve with 80 cycles. (c)The endurance of resistances in HRS and LRS under 0.1 V read voltage with 80 cycles. (d) Cumulative distribution of the SET/RESET voltages.

An intelligent detector and power strategy can extremely simplify the integrated system. The high performed, self-powered TENG (PTFE/Al) has been successfully fabricated with Al electrodes array (1.0 cm * 1.0 cm for each cell) as described in Figure 2a. The charges, generated by the frication of human skin and PTFE, result in the output voltage/current for the electrostatic induction to achieve the touching sensor.

34

This

self-powered touching sensing can reliability service hundreds times with 6 Hz touching as shown in Figure S4b. The cell size has a strong influence on the output of TENG, and the open-circuit voltage (Voc) with different electrode sizes is recorded in Figure S4c. The open-circuit voltage increases from 80 V, 175 V to 250 V, while the electrode size increases from 0.25 cm2, 0.5 cm2 to 1.0 cm2. Regulating cell size can be


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utilized to modulate the performance of TENG, especially the output voltage. The large output voltage not only lead large driving force for the resistive switching of RRAM, but also has the potential of breaking RRAM and small space resolution. Here, a suitable electrode size of 1.0 cm * 1.0 cm is accepted to explore the matching with RRAM. Besides, the effective output power of the TENG also depends on the loading resistance.

35

Figure 2b shows the resistance dependence of output voltage with the

resistance increasing from 1 KΩ to 1 GΩ. The output voltage of the device rises up with increasing loading resistance. The output voltage is the key factor of matching TENG with RRAM. The RRAM integrates with TENG as an external load, and the output voltage of TENG with the loading resistance of HRS must be large enough to drive RRAM switching its resistance from HRS to LRS. The output voltage is 1.2 V with the loading resistance of 100 KΩ which could meet the requirement of integration. Owning to the coupling between contact electrification and electrostatic induction, the inducted charge of TENG is decisive for its output. In the short-circuit (SC) condition, the inducted charge density is a function of short-circuit current density and time, which is given by the following: t

∆σ = ∫ J SC dt t0

Where JSC is the short-circuit current density, t and t0 are the time with and without contact, respectively, and ∆σ is the accumulated charge density. With a 0.5 Hz cyclic pressing on the TENG, it produces a short-circuit current density of ~200 µA/m2 and accumulated charge density of ~-30 µC/m2 as shown in Figure 2c and Figure S4d. The inducted charge will generate to a potential gradient in the load and drive it work.



Figure 2. The performance of PTFE/Al devices. (a)The schematic diagram of single-electrode TENG. (b)The output voltage with different loading resistances. (c)The measured short-circuit current density with the size of 1.0 cm * 1.0 cm. (d) Finite element simulation of the potential distribution in the TENG for the different separation distances between the skin and PTFE film.

To obtain a more quantitative understanding of the working principle, finite element simulations was employed to calculate the electric potential distribution in the TENG and the charge transfer between the AZO electrode and ground by COMSOL Multiphysics. The model constructed here has the same structure and dimensions (1.0 cm * 1.0 cm for TENG and 1.0 mm * 1.0 mm for RRAM). According to the measurement as displayed in Figure S4d, the triboelectric charge densities on the skin and PTFE film were assumed to be +30 and -30 µC/m2, respectively, while the AZO film is grounded. The electric potential distributions between skin and PTFE (in the top panels), and between Au electrode and AZO (in the bottom panels) are calculated under different separation distances of 0.1 mm, 1.0 mm, 2.0 mm, and 3.0 mm, respectively, as


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described in Figure 2d. When the skin and PTFE fully contact with each other, the electric potentials on both of panels approach zero. The electric potential difference was found to increase dramatically with increasing the separation distance. When they are separated by 3.0 mm, the electric potential on the skin surface can reach 1500 V. For the single-electrode-TENG, the electric potential difference between Au and AZO is more important, which is the actual output of TENG. Meanwhile, the electric potential gradient in Ta2O5 film is the most important driving force to drive the active ion in Ta2O5 migrating to achieve the switching from HRS to LRS. When the skin and PTFE are separated by 3.0 mm, the electric potential difference between AZO and Au can reach ~-180 V. For that the conductivity of Ta2O5 in AC/DC module is zero, the calculated potential difference is close to open-circuit voltage, which is matching with the experiment data.

Figure 3. (a)Schematic diagram of the integrated system. (b)The current response with touching,



releasing and another touching operation at the reading voltage of 0.1 V, and the performance after electrically erasing. (c) The response time at touching operation.

On the basis, the Au/Ta2O5/AZO RRAM device and PTFE/Al TENG device are combined as touching sensing-memorizing integrated system, and the structure diagram is illustrated in Figure 3a. The TENG is used as the smart signal sensor and power source, while the RRAM is the nonvolatile artificial brain. The bias of 0.1 V, which cannot switch the resistance of RRAM, is applied for real time observing the touch-response, as shown in Figure 3b. At first, the current keeps at 5*10-7 A. While the finger touches on the surface of PTFE, the current is suddenly elevated to 1*10-5 A, which exhibits excellent touching response and the responsivity reaches 20 times (the current ratio after and before touching). After releasing the pressure, the current still maintains unchanged, which shows the nonvolatile characteristic. The nonvolatile property is necessary for haptic memory to record the touching signal. Identically, another touching was added to show the outstanding ability of anti-interference. After electrically erasing, the memory device was reset into HRS, and the current at 0.1 V bias went back to 5*10-7 A. The ability of reverting to HRS reveals the potential application in reusable integrated system. The detailed response process is magnified in Figure 3c. The response time is about 1.46 s, which contains three processes: the transform process from pressure signal to electrical signal, the electrical program process and reading process.


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Figure 4. A series of measurements, containing of responsive test, nonvolatile test, anti-interference

test and recoverable test. In step 1, 3, 5 and 7, 0.1 V bias was applied to read the resistive state and cannot change the resistive state. In step 2 & 4, mechanical stimuli was programmed by touching without any bias. In step 6, a reset voltage was applied to erase the touching signal.

Meanwhile, a series of measurements without external bias, containing of responsive test, nonvolatile test, anti-interference test and recoverable test, are carried out as presented in Figure 4: (1) a read voltage of 0.1 V is applied on the RRAM device to confirm the HRS of RRAM; (2) a finger-contact operation is made on the top surface of PTFE to write the touching signal into RRAM without any external energy; (3) a read voltage of 0.1 V is applied and RRAM is found to have been switched from HRS to LRS, which verified the successfully touch-programming; (4) and (5) are “touch programming” and “reading” again after first recording to test its anti-interference performance. The anti-interference performance indicates that only the first touching



can be memorized and the subsequent touching is useless which can effectively prevent the missing of recorded data, just like the fingerprint identification; (6) an electrically erasing is applied in RRAM to switch the memory back to HRS, which is detailed showed in Figure 4 and certified in (7). The touching sensing-memorizing integrated system successfully achieve touching-programing and electrically-erasing, which illustrates the function of haptic memory and reusability. The nonvolatile characteristic, after repealing touching or applying another touching, makes sense for its applications. There are two key issues in this integrated system: One is how to make sure that the output voltage of TENG could drive the memory device switching from HRS to LRS. For the self-powered characteristic of our system without compliance current, excessive output voltage of TENG would lead to permanent breakdown and result in RRAM failure. So, the resistance of RRAM in HRS is controlled to maintain at ~105 Ω. Meanwhile, different cell sizes of TENG are adopted to modulate its output to meet the threshold voltage of RRAM as presented in Figure S4c. The output voltage with the cell size of 1 cm2 can reach ~1.2 V at a loading resistance of 105 Ω, which is larger than the set voltage of RRAM and won`t give rise to the failure of RRAM. The other concern is how to prevent the opposite output voltage switching the memory back to HRS. In TENG, the positive electric potential and negative electric potential appear alternately, which is detrimental for recording. For instance, a positive electric potential can be used to program the data into memory, but the subsequent negative electric potential may erase it, and as a result, the data still won`t been record. Rectifier


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and other solutions can be used to avoid this phenomenon, but it will also make the sensor system more complex, and bring in other problems. The RRAM can perfectly overcome the shortcoming for the different resistances in HRS and LRS. As measured in Figure 2b, the output voltage of TENG will increase with the load resistance, and the RRAM can be regarded as an external load of TENG in RRAM -TENG integrated system. So, the TENG can obtain a high output voltage when the RRAM is in HRS, and achieve a low output voltage when the RRAM is in LRS. The high output voltage is used as programing voltage to record the touching signal, while the low output voltage doesn`t work. By that, the shortcoming of the bipolar output of TENG can be effectively overcome. In experiment, the fabricated system successfully realized touch programming and haptic memory as described in Figure 4. The opposite output voltage and another touch, have no effect on the recorded data. For the further confirmation and interpretation by calculating simulation, COMSOL Multiphysics with the same parameters as above is used to analyze the electric potential distribution in Ta2O5 film with ruptured and connected conductive filament. Figure 5 describes the totally running process. Skin is positively charged and the PTFE is negatively charged, after they rub against each other. The negative charge in PTFE surface repels the electrons from Al in TENG device into Au in RRAM device, when skin and PTFE are separated, as analyzed in Figure 4. The repelled electrons in Au electrode results in the potential difference between Au electrode and AZO electrode. When the conductive filament is ruptured and the RRAM device is in HRS, the potential difference between Au and AZO can reach ~-5 V (the



separated distance between skin and PTFE is 3 mm). The potential difference is high enough to drive the conductive filament connecting and RRAM device switching from HRS to LRS. As skin is drawn closer to PTFE, the electrons are attracted from Au electrode to Al electrode. The potential difference resulted from the equal electrons can only achieve 4*10-4 V, as simulated in Figure 5f. The small potential difference is useless for resistive switching of RRAM. So, the skin touching can only switch the memory device once: from HRS to LRS, which can effectively avoid the disadvantage of bipolar output voltage of TENG. The simplified mechanism can be found in Figure 5g. Meanwhile, the constructed system can also be reused after external electrically erasing. In our system, RRAM and TENG devices are integrated to utilize respective characteristics and to overcome respective shortages to realize the functions of completely self-powered, nonvolatile sensing and memorizing.

Figure 5. Mechanism diagram of integrated system in a fully cycle: (a)Fully contact between

human skin and the PTFE film; (b)The two surfaces are separated; (c)The two surfaces are separated by a large distance; (d)The two surfaces contact again. (e) and (f) are the simulated potential


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distribution with the cracked conductive filament (HRS) and formed conductive filament (LRS). (g)The simplified mechanism diagram.

Figure 6. (a) Photograph of cell matrix with 3 * 3 pixels and relevant current mapping before, in and

after press. The bottom panels of (b), (c), (d) and (e) correspond to the illustration of the finger moving along the paths of letters “U”, “S”, “T” and “B”. The top panels are the calculated current peak areas for each PTFE/Al-Au/Ta2O5/AZO sample in response to the motion trajectory of letters “U”, “S”, “T” and “B”.

The cell (integrating RRAM and TENG) matrix with 3 * 3 pixels in size of 1 cm * 1 cm is constructed as can be seen in Figure 6(a). Before press, the current read from RRAM device is only ~10-6 A, which demonstrates the HRS in RRAM. When touch operation is applied on the middle cell of the matrix, its read current becomes ~10-5 A, while others remain unchanged. More uplifting is that, this change in resistance can be maintained, even though the finger is taken away, or touch again. To get it vivid, the



finger is reddened, and incarnadine the surface of PTFE. Meanwhile, the stamp of finger will stay in the surface, even though the finger is taken away, which is just like the cooperation of human skin and brain. When touching something, we can not only feel the shape of it, but also remember it. Our integrated system can also realize this function, which may be applied in electric skin and artificial intelligence (AI) device. To illustrate the broaden applications of the integrated system, 5 * 5 matrix of the device array is fabricated. Human finger or hand is slid across the top surface of PTFE matrix, and the outputs are generated to drive the RRAM memorizing the output signals. As exhibited in Figure 6b-e, when the finger moves on the PTFE matrix along the path of letter “U”: electrode 51 (E51) → electrode 41 (E41) → electrode 31 (E31) → electrode 21 (E21) → electrode 11 (E11) → electrode 12 (E12) → electrode 13 (E13)

→ electrode 14 (E14) → electrode 15 (E15) → electrode 25 (E25) → electrode 35 (E35) → electrode 45 (E45) → electrode 55 (E55), the generated triboelectric signal can be recorded by each RRAM cell. All the processes are self-powered. Then, a voltage of 0.1 V is applied in RRAM to read the recorded signal in each cell. The read currents are collected and arranged according to the position of each cell as summarized in the bottom panel of Figure 6b. The cells related to the motion trajectory clearly possessed higher current and the letter “U” can be observed, which proved the possibility of trace memorization. Then, other moving trajectories of letter “S”, “T” and “B” was also performed on the surface of the TENG matrix, as shown in Figure 6c-e. Accordingly, the measured currents from each RRAM cell were summarized and the results were in good agreements with the motion trajectory.


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Conclusion In summary, a fully self-powered smart skin integrating with RRAM and TENG has been developed to successfully memorize the mechanical stimuli. The mechanical touching signal was transformed into electrical signal by TENG, and was subsequently written into RRAM. The resistances of the CC-free RRAM in HRS and LRS were maintained at 105 Ω and 104 Ω, respectively. At the loading resistance of 105 Ω, the output voltage of TENG is just a little larger than the SET voltage of RRAM to make sure the resistive switching of RRAM without permanent breakdown. Meanwhile, at the loading resistance of 104 Ω, the output voltage of TENG makes no sense for the RRAM, which could automatically exclude the concomitant reverse stimuli from TENG or another triboelectric signal. By that, the integrated system could be programmed by finger touch to come true the function of haptic memory and ideal anti-interference ability, exhibiting the coupling of sensing and recording to simulate the interaction of skin and brain. The responsivity and response time reached about 20 times and 1.46 s, respectively. Moreover, the achieved integrated system array demonstrated the capability of memorizing the finger motion trajectory in two-dimensional

space.

The

rise

of

completely

self-powered,

sensing-memorizing-integrated system may open new avenues for the next generation high-performance smart systems for applications in smart sensors, electronic skins and artificial intelligence. Experimental Section

Fabrication of RRAM-TENG-integrated system. The RRAM devices used in this work



with a size of 1 mm * 1 mm were fabricated on AZO (1 µm)/glass substrates with electrodes patterned using traditional photolithography. First, a 300 nm Ta2O5 layer was deposited by RF sputtering (100 W) using a Ta2O5 ceramic target in an Ar/O2 gas mixture at room temperature. The argon partial pressure and oxygen partial pressure are 32 sccm and 8 sccm, respectively. Then, a 100 nm top Au electrode was then deposited by photolithography, thermal evaporation, and lift-off processes. For the TENG, the Al foils with different sizes (1.0 cm * 1.0 cm, 0.5 cm * 1.0 cm, and 0.5 cm * 0.5 cm) were adhered on the PTFE surface. The Au electrode of RRAM and Al electrode of TENG are simply connected by copper wire.

Characterization and Electrical measurements: Field emission scanning electron microscopy (FESEM) (Quanta 3D FEG) with a 20 kV operating voltage was utilized to study the morphologies of the samples. The electrical properties of the device were performed by Keithley 4200 testing system with a limited compliance current of 100 mA to avoid permanent damaging. The valence states of Ta and O elements were analyzed by X-ray photoelectron spectroscopy (XPS, ESCALAB 250 Xi). The numerical simulation of the potential distribution in PTFE and Ta2O5 was completely done using COMSOL. Supporting Information

Supporting Information Available: The characterization of RRAM device, the analysis of quantized conductance and the performance of TENG are included. Acknowledgements This work was supported by National Natural Science Foundation of China (No.


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51372023, 51772024, 51702014), the National Key Research and Development Program of China (No. 2016YFA0202702), the National Major Research Program of China (No. 2013CB932601), the Program of Introducing Talents of Discipline to Universities (B14003), Beijing Municipal Science & Technology Commission, and the Fundamental Research Funds for Central Universities. Author Contributions List Yihui Sun is responsible for the proposing of the idea and completing the whole experiment. Xin Zheng is responsible for the theory analysis and the application of haptic memory system. Xiaoqin Yan is help for the improvement of original idea and the theory analysis. Qingliang Liao is help for the design of whole experiment. Shuo Liu is help for the fabrication of micro/ nano structures in RRAM units. Guangjie Zhang is help for the test of TENG units. Yong Li is help for the growth of Ta2O5 in RRAM. Yue Zhang is help for the writing of manuscript and the further applications of this haptic memory system.

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TOC

A self-powered artificial tactile memorizing system were developed by coupling the tribotronic nanogenerator (TENG) and nonvolatile resistive random access memory (RRAM) for the mimicry of human sensory memory. TheTENG is utilized as electronic skin to transform the touching signal into electric pulse, which will be programmed into the RRAM.



Figure 1. The performance of Au/Ta2O5/AZO device. (a) Schematic illustration of the Au/Ta2O5/AZO junction structure. (b) Endurance of I-V curve with 80 cycles. (c)The endurance of resistances in HRS and LRS under 0.1 V read voltage with 80 cycles. (d) Cumulative distribution of the SET/RESET voltages. 159x121mm (300 x 300 DPI)


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Figure 2. The performance of PTFE/Al devices. (a)The schematic diagram of single-electrode TENG. (b)The output voltage with different loading resistances. (c)The measured short-circuit current density with the size of 1.0 cm * 1.0 cm. (d) Finite element simulation of the potential distribution in the TENG for the different separation distances between the skin and PTFE film. 118x67mm (300 x 300 DPI)



Figure 3. (a)Schematic diagram of the integrated system. (b)The current response with touching, releasing and another touching operation at the reading voltage of 0.1 V, and the performance after electrically erasing. (c) The response time at touching operation. 162x140mm (300 x 300 DPI)


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Figure 4. A series of measurements, containing of responsive test, nonvolatile test, anti-interference test and recoverable test. In step 1, 3, 5 and 7, 0.1 V bias was applied to read the resistive state and cannot change the resistive state. In step 2 & 4, mechanical stimuli was programmed by touching without any bias. In step 6, a reset voltage was applied to erase the touching signal. 170x124mm (300 x 300 DPI)



Figure 5. Mechanism diagram of integrated system in a fully cycle: (a)Fully contact between human skin and the PTFE film; (b)The two surfaces are separated; (c)The two surfaces are separated by a large distance; (d)The two surfaces contact again. (e) and (f) are the simulated potential distribution with the cracked conductive filament (HRS) and formed conductive filament (LRS). (g)The simplified mechanism diagram. 111x72mm (300 x 300 DPI)


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Figure 6. (a) Photograph of cell matrix with 3 * 3 pixels and relevant current mapping before, in and after press. The bottom panels of (b), (c), (d) and (e) correspond to the illustration of the finger moving along the paths of letters “U”, “S”, “T” and “B”. The top panels are the calculated current peak areas for each PTFE/AlAu/Ta2O5/AZO sample in response to the motion trajectory of letters “U”, “S”, “T” and “B”. 184x163mm (300 x 300 DPI)


Bioinspired Tribotronic Resistive Switching Memory for Self-Powered

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