JOURNAL ARTICLE

Photoelectronic synaptic transistor with tunable plasticity for neuromorphic computing system

Abstract

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.

Keywords:
Neuromorphic engineering Excitatory postsynaptic potential Long-term potentiation Synaptic plasticity Inhibitory postsynaptic potential Computer science Neuroscience Materials science Metaplasticity Optoelectronics Artificial neural network Chemistry Artificial intelligence Psychology

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Topics

Advanced Memory and Neural Computing
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Photoreceptor and optogenetics research
Life Sciences →  Neuroscience →  Cellular and Molecular Neuroscience
Neural Networks and Reservoir Computing
Physical Sciences →  Computer Science →  Artificial Intelligence
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