Optoelectronic Perovskite Synapses for Neuromorphic Computing

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 t...

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Veröffentlicht in:Advanced functional materials 2020-03, Vol.30 (11), p.n/a
Hauptverfasser: Ma, Fumin, Zhu, Yangbin, Xu, Zhongwei, Liu, Yang, Zheng, Xiaojing, Ju, Songman, Li, Qianqian, Ni, Ziquan, Hu, Hailong, Chai, Yang, Wu, Chaoxing, Kim, Tae Whan, Li, Fushan
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Sprache:eng
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Zusammenfassung: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. Artificial optoelectronic synapses are considered to be essential cornerstones of visual‐related artificial intelligence. A two‐terminal optoelectronic synapse employing CsPbBr3 perovskite nanoplates, which implement electronic synaptic plasticity and photonic synaptic plasticity simultaneously, is fabricated. In‐depth research shows that these devices have a unique memory backtracking function that can extract historical optoelectronic information to emulate the biological synapse.
ISSN:1616-301X
1616-3028
DOI:10.1002/adfm.201908901