Chitosan-Based Polysaccharide-Gated Flexible Indium Tin Oxide Synaptic Transistor with Learning Abilities.

Recently, environment-friendly electronic devices are attracting increasing interest. "Green" artificial synapses with learning abilities are also interesting for neuromorphic platforms. Here, solution-processed chitosan-based polysaccharide electrolyte-gated indium tin oxide (ITO) synaptic transistors are fabricated on polyethylene terephthalate substrate. Good transistor performances against mechanical stress are observed. Short-term synaptic plasticities are mimicked on the proposed ITO synaptic transistor. When applying presynaptic and postsynaptic spikes on gate electrode and drain electrode respectively, spike-timing-dependent plasticity function is mimicked on the synaptic transistor. Transitions from sensory memory to short-term memory (STM) and from STM to long-term memory are also mimicked, demonstrating a "multistore model" brain memory. Furthermore, the flexible ITO synaptic transistor can be dissolved in deionized water easily, indicating potential green neuromorphic platform applications.

[1]  Daniel Moses,et al.  Electrochemical doping in electrolyte-gated polymer transistors. , 2007, Journal of the American Chemical Society.

[2]  W. Regehr,et al.  Short-term synaptic plasticity. , 2002, Annual review of physiology.

[3]  Bernabé Linares-Barranco,et al.  On Spike-Timing-Dependent-Plasticity, Memristive Devices, and Building a Self-Learning Visual Cortex , 2011, Front. Neurosci..

[4]  Nektarios Tavernarakis,et al.  The role of synaptic ion channels in synaptic plasticity , 2006, EMBO reports.

[5]  Young Sun,et al.  A Synaptic Transistor based on Quasi‐2D Molybdenum Oxide , 2017, Advanced materials.

[6]  Jianting Ye,et al.  Strong dopant dependence of electric transport in ion-gated MoS2 , 2017, 1704.07618.

[7]  Weipeng Xuan,et al.  Transient Resistive Switching Devices Made from Egg Albumen Dielectrics and Dissolvable Electrodes. , 2016, ACS applied materials & interfaces.

[8]  Feng Shao,et al.  Starch as ion-based gate dielectric for oxide thin film transistors , 2017 .

[9]  Li Qiang Zhu,et al.  Multi-gate synergic modulation in laterally coupled synaptic transistors , 2015 .

[10]  Kee Woei Ng,et al.  Human Hair Keratin for Biocompatible Flexible and Transient Electronic Devices. , 2017, ACS applied materials & interfaces.

[11]  Nicolas Locatelli,et al.  Learning through ferroelectric domain dynamics in solid-state synapses , 2017, Nature Communications.

[12]  David Nilsson,et al.  Bi-stable and dynamic current modulation in electrochemical organic transistors , 2002 .

[13]  G. Tröster,et al.  Ferroelectric‐Like Charge Trapping Thin‐Film Transistors and Their Evaluation as Memories and Synaptic Devices , 2017 .

[14]  George G. Malliaras,et al.  Neuromorphic device architectures with global connectivity through electrolyte gating , 2017, Nature Communications.

[15]  R. Sun,et al.  Recent Advancements in Flexible and Stretchable Electrodes for Electromechanical Sensors: Strategies, Materials, and Features. , 2017, ACS applied materials & interfaces.

[16]  Wei D. Lu,et al.  Sparse coding with memristor networks. , 2017, Nature nanotechnology.

[17]  Richard C. Atkinson,et al.  Human Memory: A Proposed System and its Control Processes , 1968, Psychology of Learning and Motivation.

[18]  Tingrui Pan,et al.  Flexible Transparent Iontronic Film for Interfacial Capacitive Pressure Sensing , 2015, Advanced materials.

[19]  B. Pakkenberg,et al.  Aging and the human neocortex , 2003, Experimental Gerontology.

[20]  Manuel Le Gallo,et al.  Stochastic phase-change neurons. , 2016, Nature nanotechnology.

[21]  Takao Someya,et al.  Inflammation-free, gas-permeable, lightweight, stretchable on-skin electronics with nanomeshes. , 2017, Nature nanotechnology.

[22]  Qinghua Zhang,et al.  Electric-field control of tri-state phase transformation with a selective dual-ion switch , 2017, Nature.

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

[24]  Qing Wan,et al.  Artificial synapse network on inorganic proton conductor for neuromorphic systems. , 2014, Nature communications.

[25]  Yi Shi,et al.  Proton Conducting Graphene Oxide/Chitosan Composite Electrolytes as Gate Dielectrics for New-Concept Devices , 2016, Scientific Reports.

[26]  D. Feldman.  The Spike-Timing Dependence of Plasticity , 2012, Neuron.

[27]  E. J. Kim,et al.  Investigation of the ferroelectric switching behavior of P(VDF-TrFE)-PMMA blended films for synaptic device applications , 2016 .

[28]  C. Gamrat,et al.  An Organic Nanoparticle Transistor Behaving as a Biological Spiking Synapse , 2009, 0907.2540.

[29]  Se Hyun Kim,et al.  Electrolyte‐Gated Transistors for Organic and Printed Electronics , 2013, Advanced materials.

[30]  Rohit Abraham John,et al.  Flexible Ionic-Electronic Hybrid Oxide Synaptic TFTs with Programmable Dynamic Plasticity for Brain-Inspired Neuromorphic Computing. , 2017, Small.

[31]  Li Qiang Zhu,et al.  Activity Dependent Synaptic Plasticity Mimicked on Indium-Tin-Oxide Electric-Double-Layer Transistor. , 2017, ACS applied materials & interfaces.

[32]  Xue-Bing Yin,et al.  Synaptic Metaplasticity Realized in Oxide Memristive Devices , 2016, Advanced materials.

[33]  John W. Backus,et al.  Can programming be liberated from the von Neumann style?: a functional style and its algebra of programs , 1978, CACM.

[34]  Hyunsang Hwang,et al.  Organic core-sheath nanowire artificial synapses with femtojoule energy consumption , 2016, Science Advances.

[35]  Youngjune Park,et al.  Artificial Synapses with Short- and Long-Term Memory for Spiking Neural Networks Based on Renewable Materials. , 2017, ACS nano.

[36]  Yan Wang,et al.  Biological Spiking Synapse Constructed from Solution Processed Bimetal Core-Shell Nanoparticle Based Composites. , 2018, Small.

[37]  Li Qiang Zhu,et al.  Laser directly written junctionless in-plane-gate neuron thin film transistors with AND logic function , 2012 .

[38]  Y. Dan,et al.  Spike timing-dependent plasticity: a Hebbian learning rule. , 2008, Annual review of neuroscience.

[39]  Jang-Sik Lee,et al.  Biocompatible and Flexible Chitosan‐Based Resistive Switching Memory with Magnesium Electrodes , 2015 .

[40]  G. Bi,et al.  Synaptic Modifications in Cultured Hippocampal Neurons: Dependence on Spike Timing, Synaptic Strength, and Postsynaptic Cell Type , 1998, The Journal of Neuroscience.

[41]  Shimeng Yu,et al.  Ultra-low-energy three-dimensional oxide-based electronic synapses for implementation of robust high-accuracy neuromorphic computation systems. , 2014, ACS nano.

[42]  L. Abbott,et al.  Cortical Development and Remapping through Spike Timing-Dependent Plasticity , 2001, Neuron.

[43]  M. Marinella,et al.  A non-volatile organic electrochemical device as a low-voltage artificial synapse for neuromorphic computing. , 2017, Nature materials.

[44]  Zhenyu Zhou,et al.  Memristors: Memristor with Ag‐Cluster‐Doped TiO2 Films as Artificial Synapse for Neuroinspired Computing (Adv. Funct. Mater. 1/2018) , 2018 .

[45]  Zhengguo Xiao,et al.  Energy‐Efficient Hybrid Perovskite Memristors and Synaptic Devices , 2016 .

[46]  Yang Hui Liu,et al.  Freestanding Artificial Synapses Based on Laterally Proton‐Coupled Transistors on Chitosan Membranes , 2015, Advanced materials.

[47]  Sam Emaminejad,et al.  Fully integrated wearable sensor arrays for multiplexed in situ perspiration analysis , 2016, Nature.

[48]  Dominique Vuillaume,et al.  Filamentary switching: synaptic plasticity through device volatility. , 2015, ACS nano.

[49]  Daoben Zhu,et al.  A Dual‐Organic‐Transistor‐Based Tactile‐Perception System with Signal‐Processing Functionality , 2017, Advanced materials.