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

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 was developed by coupling bionic electronic skin and nonvolatile resistive random access 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. Because of the advanced structural designs and accurate parameter matching, including the output voltages and the resistances in different resistive states, the artificial brain can be operated in 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-performance sensors, artificial intelligence, and bionics.

[1]  Benjamin C. K. Tee,et al.  Highly sensitive flexible pressure sensors with microstructured rubber dielectric layers. , 2010, Nature materials.

[2]  Rainer Waser,et al.  Complementary resistive switches for passive nanocrossbar memories. , 2010, Nature materials.

[3]  R. Waser,et al.  Nanoionics-based resistive switching memories. , 2007, Nature materials.

[4]  Mitsumasa Iwamoto,et al.  Self‐Powered Trace Memorization by Conjunction of Contact‐Electrification and Ferroelectricity , 2015 .

[5]  Yue Zhang,et al.  Effect of carrier screening on ZnO-based resistive switching memory devices , 2016, Nano Research.

[6]  J. Tour,et al.  Highly transparent nonvolatile resistive memory devices from silicon oxide and graphene , 2012, Nature Communications.

[7]  Kinam Kim,et al.  A fast, high-endurance and scalable non-volatile memory device made from asymmetric Ta2O(5-x)/TaO(2-x) bilayer structures. , 2011, Nature materials.

[8]  Y. Liu,et al.  Synaptic Learning and Memory Functions Achieved Using Oxygen Ion Migration/Diffusion in an Amorphous InGaZnO Memristor , 2012 .

[9]  T. Hasegawa,et al.  Short-term plasticity and long-term potentiation mimicked in single inorganic synapses. , 2011, Nature materials.

[10]  Qingliang Liao,et al.  High on-off ratio improvement of ZnO-based forming-free memristor by surface hydrogen annealing. , 2015, ACS Applied Materials and Interfaces.

[11]  Yu-Lun Chueh,et al.  ZnO1-x nanorod arrays/ZnO thin film bilayer structure: from homojunction diode and high-performance memristor to complementary 1D1R application. , 2012, ACS nano.

[12]  G. Zhu,et al.  A Shape‐Adaptive Thin‐Film‐Based Approach for 50% High‐Efficiency Energy Generation Through Micro‐Grating Sliding Electrification , 2014, Advanced materials.

[13]  Y. Chueh,et al.  Manipulated transformation of filamentary and homogeneous resistive switching on ZnO thin film memristor with controllable multistate. , 2013, ACS applied materials & interfaces.

[14]  Xiaodong Chen,et al.  Skin‐Inspired Haptic Memory Arrays with an Electrically Reconfigurable Architecture , 2016, Advanced materials.

[15]  龙世兵 Quantum-size effects in hafnium-oxide resistive switching , 2013 .

[16]  Wei Yang Lu,et al.  Nanoscale memristor device as synapse in neuromorphic systems. , 2010, Nano letters.

[17]  Benjamin C. K. Tee,et al.  Skin-like pressure and strain sensors based on transparent elastic films of carbon nanotubes. , 2011, Nature nanotechnology.

[18]  Sang Hoon Lee,et al.  Resistive Switching Memory Integrated with Nanogenerator for Self‐Powered Bioimplantable Devices , 2016 .

[19]  S. Yao,et al.  Nanomaterial‐Enabled Stretchable Conductors: Strategies, Materials and Devices , 2015, Advanced materials.

[20]  Wei Tang,et al.  Investigation of power generation based on stacked triboelectric nanogenerator , 2013 .

[21]  J. Randall Flanagan,et al.  Coding and use of tactile signals from the fingertips in object manipulation tasks , 2009, Nature Reviews Neuroscience.

[22]  Zhong Lin Wang,et al.  Human skin based triboelectric nanogenerators for harvesting biomechanical energy and as self-powered active tactile sensor system. , 2013, ACS nano.

[23]  Benjamin C. K. Tee,et al.  Flexible polymer transistors with high pressure sensitivity for application in electronic skin and health monitoring , 2013, Nature Communications.

[24]  Zhong Lin Wang,et al.  Tribotronics—A new field by coupling triboelectricity and semiconductor , 2016 .

[25]  W. Lu,et al.  High-density Crossbar Arrays Based on a Si Memristive System , 2008 .

[26]  Wen Liu,et al.  A transparent single-friction-surface triboelectric generator and self-powered touch sensor , 2013 .

[27]  Jing Li,et al.  Flexible Organic Tribotronic Transistor Memory for a Visible and Wearable Touch Monitoring System , 2016, Advanced materials.

[28]  Yiwei Liu,et al.  Observation of Conductance Quantization in Oxide‐Based Resistive Switching Memory , 2012, Advanced materials.

[29]  Li Min Zhang,et al.  Tribotronic Logic Circuits and Basic Operations , 2015, Advanced materials.

[30]  J Joshua Yang,et al.  Memristive devices for computing. , 2013, Nature nanotechnology.

[31]  Wei Tang,et al.  Contact electrification field-effect transistor. , 2014, ACS nano.

[32]  Jianjun Luo,et al.  Flexible transparent tribotronic transistor for active modulation of conventional electronics , 2017 .

[33]  Yanwei Shen,et al.  Influence of carrier concentration on the resistive switching characteristics of a ZnO-based memristor , 2016, Nano Research.

[34]  F. Zeng,et al.  Fully room-temperature-fabricated nonvolatile resistive memory for ultrafast and high-density memory application. , 2009, Nano letters.