Tribo‐ferro‐optoelectronic neuromorphic transistor of α‐In2Se3
Zhenyu Feng,
Jinran Yu,
Yichen Wei,
Yifei Wang,
Bobo Tian,
Yonghai Li,
Liuqi Cheng,
Zhong Lin Wang,
Qijun Sun
Affiliations
Zhenyu Feng
Center on Nanoenergy Research School of Physical Science and Technology Guangxi University Nanning Guangxi China
Jinran Yu
Beijing Institute of Nanoenergy and Nanosystems Chinese Academy of Sciences Beijing China
Yichen Wei
Center on Nanoenergy Research School of Physical Science and Technology Guangxi University Nanning Guangxi China
Yifei Wang
Beijing Institute of Nanoenergy and Nanosystems Chinese Academy of Sciences Beijing China
Bobo Tian
Key Laboratory of Polar Materials and Devices (MOE) Department of Electronics Ministry of Education Shanghai Center of Brain‐inspired Intelligent Materials and Devices East China Normal University Shanghai China
Yonghai Li
Center on Nanoenergy Research School of Physical Science and Technology Guangxi University Nanning Guangxi China
Liuqi Cheng
Center on Nanoenergy Research School of Physical Science and Technology Guangxi University Nanning Guangxi China
Zhong Lin Wang
Center on Nanoenergy Research School of Physical Science and Technology Guangxi University Nanning Guangxi China
Qijun Sun
Center on Nanoenergy Research School of Physical Science and Technology Guangxi University Nanning Guangxi China
Abstract Inspired by biological neural networks, the fabrication of artificial neuromorphic systems with multimodal perception capacity shows promises in overcoming the “von Neumann bottleneck” and takes advantage of the efficient perception and computation of diverse types of signals. Here, we combine a triboelectric nanogenerator with an α‐phase indium selenide (α‐In2Se3) optoelectronic synaptic transistor to construct a tribo‐ferro‐optoelectronic artificial neuromorphic device with multimodal plasticity. Based on the excellent ferroelectric and optoelectronic characteristics of the α‐In2Se3 channel, typical synaptic behaviors (e.g., pair‐pulse facilitation and short‐term/long‐term plasticity) are successfully simulated in response to the synergistic effect of mechanical and optical stimuli. The interaction of mechanical displacement and light illumination enables heterosynaptic plasticity and spatiotemporal dynamic logic. Furthermore, multiple Boolean logical functions and associative learning behaviors are successfully implemented using the paired stimuli of displacement pulses and light pulses. The proposed tribo‐ferro‐optoelectronic artificial neuromorphic devices have great potential for application in interactive neural networks and next‐generation artificial intelligence.