Optoelectronic Perovskite Synapses for Neuromorphic Computing
Fumin Ma, Yangbin Zhu, Zhongwei Xu, Yang Liu, Xiaojing Zheng, Songman Ju, Qianqian Li, Ziquan Ni, Hailong Hu, Yang Chai, Chaoxing Wu, Tae Whan Kim, Fushan Li
Abstract
Abstract Simulating the human brain for neuromorphic computing has attractive prospects in the field of artificial intelligence. Optoelectronic synapses have been considered to be important cornerstones of neuromorphic computing due to their ability to process optoelectronic input signals intelligently. In this work, optoelectronic synapses based on all‐inorganic perovskite nanoplates are fabricated, and the electronic and photonic synaptic plasticity is investigated. Versatile synaptic functions of the nervous system, including paired‐pulse facilitation, short‐term plasticity, long‐term plasticity, transition from short‐ to long‐term memory, and learning‐experience behavior, are successfully emulated. Furthermore, the synapses exhibit a unique memory backtracking function that can extract historical optoelectronic information. This work could be conducive to the development of artificial intelligence and inspire more research on optoelectronic synapses.