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Jianyu Li

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Proceedings Article | 24 November 2023 Paper

Photoelectronic synaptic transistor with tunable plasticity for neuromorphic computing system

Qing-an Ding, Chaoran Gu, Jianyu Li, Youli Yao, Xiaoyuan Li, Binghui Hou, Kexin Yu, Xiaoling Zuo

Proceedings Volume 12935, 1293511 (2023) https://doi.org/10.1117/12.3005283

KEYWORDS: Transistors, Synaptic plasticity, Silicon, Computing systems, Brain, Modulation, Design and modelling, Pulse signals

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Neuromorphic computing system inspired by the human brain has the capability of breaking through the von Neumann bottleneck, which can improve the efficiency of data processing. To deploy efficient neuromorphic systems, the development of synaptic devices is imperative. However, achieving tunable synaptic behaviors in a single transistor remains challenging. In this work, a silicon nanowire-based photoelectronic synaptic transistor is developed to achieve tunable synaptic behaviors. Using the floating-body effect and a cylindrical surrounding double-gate (CSDG) structure, we simulated excitatory and inhibitory synaptic plasticity in a single device. Additionally, our device also simulated various synaptic characteristics by modulating the bias voltages and light pulses, such as excitatory and inhibitory postsynaptic current (PSC), short-term potentiation (STP), short-term depression (STD), long-term potentiation (LTP), and forgetting behavior. This study provides an effective strategy for developing tunable photoelectronic synapses. Furthermore, Si processing compatibility also makes the synaptic device a promising contender for the implementation of neuromorphic computing.

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