Perovskite-Enhanced Silicon-Nanocrystal Optoelectronic Synaptic Devices for the Simulation of Biased and Correlated Random-Walk Learning  

作　　者：Yiyue Zhu Wen Huang Yifei He Lei Yin Yiqiang Zhang Deren Yang Xiaodong Pi 

机构地区：[1]State Key Laboratory of Silicon Materials and School of Materials Science and Engineering,Zhejiang University,Hangzhou,Zhejiang 310027,China [2]School of Materials Science and Engineering,Henan Institute of Advanced Technology,Zhengzhou University,Zhengzhou,Henan 450001,China [3]Institute of Advanced Semiconductors,Hangzhou Innovation Center,Zhejiang University,Hangzhou,Zhejiang 311215,China

出　　处：《Research》2020年第1期1321-1329,共9页研究（英文）

基　　金：This work is mainly supported by the National Key Research and Development Program of China(Grant Nos.2017YFA0205704 and 2018YFB2200101);Natural Science Foundation of China(Grant Nos.91964107 and 61774133);Fundamental Research Funds for the Central Universities(Grant No.2018XZZX003-02);Partial support from the Natural Science Foundation of China for Innovative Research Groups(Grant No.61721005);Zhejiang University Education Foundation Global Partnership Fund is also acknowledged.

摘　　要：Silicon-(Si-)based optoelectronic synaptic devices mimicking biological synaptic functionalities may be critical to the development of large-scale integrated optoelectronic artificial neural networks.As a type of important Si materials,Si nanocrystals(NCs)have been successfully employed to fabricate optoelectronic synaptic devices.In this work,organometal halide perovskite with excellent optical asborption is employed to improve the performance of optically stimulated Si-NC-based optoelectronic synaptic devices.The improvement is evidenced by the increased optical sensitivity and decreased electrical energy consumption of the devices.It is found that the current simulation of biological synaptic plasticity is essentially enabled by photogating,which is based on the heterojuction between Si NCs and organometal halide perovskite.By using the synaptic plasticity,we have simulated the well-known biased and correlated random-walk(BCRW)learning.

关 键 词：PEROVSKITE PLASTICITY SILICON 

分 类 号：TB383[一般工业技术—材料科学与工程]