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Updated: Dec 3, 2025

A Standard and Reliable Method to Fabricate Two-Dimensional Nanoelectronics
Published on: August 28, 2018
Hardware implementation of photoelectrically modulated dendritic arithmetic and spike-timing-dependent plasticity
Yongchao Cheng1, Kexiang Shan, Yan Xu
1Hunan Key Laboratory of Super Microstructure and Ultrafast Process, School of Physics and Electronics, Central South University, Changsha 410083, China. jiangjie@csu.edu.cn junhe@csu.edu.cn.
Abstract:
Brain-inspired nanodevices have been demonstrated to possess outstanding characteristics for implementing neuromorphic computing. Among these devices, photoelectrically modulated neuromorphic transistors are regarded as the basic building blocks for applications in emerging brain-like devices. However, to date, efficient optoelectronic-hybrid neuromorphic devices are still lacking. Because conventional transistors based on mono-semiconductor materials cannot absorb adequate light to ensure efficient light-matter interactions, they pose significant challenges to the synchronous processing of photoelectric information. Here, a novel photoelectrically modulated neuromorphic device based on an ion-coupling gate-tunable vertical 0D-CsPbBr3-quantum-dots/2D-MoS2 hybrid-dimensional van der Waals heterojunction is demonstrated by using a polymer ion gel electrolyte as the gate dielectric. A super-efficient heterojunction interface for photo-carrier transport is developed by integrating CsPbBr3 quantum dots with 2D-layered MoS2 semiconductors. We experimentally demonstrate that the drain-source current can be modulated by applying spikes to the drain and gate terminals, and the conductance can also be tuned by external light stimulus. Most importantly, photoelectrically modulated spiking Boolean logics, dendritic integrations in both temporal and spatial modes, and Hebbian learning rules can be successfully mimicked in our proposed hybrid-dimensional device using this intriguing optical and electrical synergy approach. These results suggest that the proposed device has great potential in intelligent cognitive systems and neuromorphic computing applications.
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