Multifunctional Memory-Synaptic Hybrid Optoelectronic Transistors for Neuromorphic Computing
Gengxu Chen, Gang Peng, Xipeng Yu, Weijie Yu, Yanxue Hao, Yan Dai, Huipeng Chen, Tailiang Guo
Abstract
Multifunctional neuromorphic devices, integrating the acquisition, computation, and processing of information, have exceptional advantages to simulate biological behaviors and become one of the foundations of future neuromorphic computing. However, the realization of sensor-memory-calculation in a single device remains a great challenge. Herein, memory-synaptic hybrid optoelectronic transistors were developed with hydrolyzed silica-coated lead-free double perovskite Cs <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> AgBiBr <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">6</sub> and organic semiconductors, which exhibited sensor-memory-calculation behavior. This work offers a novel strategy for constructing multifunctional neuromorphic devices, which will further inspire the development of floating-gate device in future neuromorphic computing.