Effect of Plasma Treatment on the Long-term Plasticity of Synaptic Transistor

doi:10.15541/jim20220675

Abstract

Abstract:

As the basic and essential unit of neuromorphic computing system, artificial synaptic devices exhibit great potential in accelerating the high-performance parallel computation, artificial intelligence, and adaptive learning. Among them, electrolyte-gated synaptic transistors (EGSTs) have received increasing attention as the next generation neuromorphic devices owing to its controllable channel conductance. The devices exhibit the abilities of simulating the short-term plasticity (STP) and long-term plasticity (LTP) of the neural synapses. However, most of EGSTs exhibit short persistence for LTP and their channel conductance is difficult to be adjusted due to the rapid self-discharge of the electric double layer. In this work, the EGSTs based on water-induced In₂O₃ as the channel and chitosan as gate electrolyte were constructed and the O₂plasma treatments were performed. The formation of traps on the channel surface is caused by the O₂plasma treatments, which leads to capturing hydrogen ions at interface of the electrolyte/channel layer, and the device performance exhibits an enlarged hysteresis window, so as to regulate LTP of EGSTs. Biological synaptic functions, including excitatory postsynaptic current (EPSC), paired-pulse facilitation (PPF), STP, and LTP, were mimicked by electrochemical doping and electrostatic coupling effects. Meanwhile, based on the experimentally verified potentiation/depression characteristics of the EGSTs, a three-layer artificial neural network is applied for handwritten digit recognition, and simulation tests can obtain high recognition accuracy of 94.7%. These results reveal that surface plasma treatment is one of the key technologies to affect the device performance, which has great potential in regulating synaptic function of EGSTs.

Key words: electrolyte-gated synaptic transistor, synaptic plasticity, plasma treatment, pattern recognition

CLC Number:

TQ174

QIU Haiyang, MIAO Guangtan, LI Hui, LUAN Qi, LIU Guoxia, SHAN Fukai. Effect of Plasma Treatment on the Long-term Plasticity of Synaptic Transistor[J]. Journal of Inorganic Materials, 2023, 38(4): 406-412.

Figures/Tables 5

Fig. 1 AFM images of (a) untreated and (b) plasma-treated In2O3 films

Fig. 2 Schematic illustration and properties of synaptic transistor (a) Schematic illustration of a synapse; (b) Device structure; (c) Frequency-dependent characteristics of chitosan electrolyte with inset showing device configuration for C-F measurement; (d) Transfer curves of untreated and O2 plasma-treated (W/O2 plasma) device; (e) Output curves of untreated device; (f) Output curves of O2 plasma treated device

Fig. 3 STP (a) and LTP (b) characteristics of untreated and O2 plasma-treated (W/O2 plasma) device, (c) paired-pulse facilitation curves for device with and without O2 plasma treatment and (d) PPF index as a function of pulse interval Colorful figures are available on website

Fig. 4 Potentiation/depression characteristics of untreated (a) and O2 plasma-treated (c) devices, repeatability, and stability of P-D curves after 50 cycles of untreated (b) and O2 plasma-treated (d) devices

Fig. 5 Artificial neural network, synaptic weight cross array of hardware and supervised learning outcome tests (a) Diagram of the ANN for pattern recognition; (b) Schematic diagram showing a hardware implemented synaptic weight cross-bar array with EGSTs with evolution classification accuracy as a function of training epochs for small digits (c), large digits (d), and file types datasets (e), respectively Colorful figures are available on website

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