journal article·2025-01Open access

MoxRe(1−x)S2‐Based Optoelectronic Synapse for Artificial Neural Visual System Application

Xiaona Sun, Zhengjie Wang, Chen Si, Chengbao Jiang, Shengxue Yang

Advanced Functional Materials· Volume 35· Issue 1

Abstract

Abstract Optoelectronic synapses, constructed from 2D transition metal dichalcogenides (TMDs) with atomic‐scale thickness, offer substantial benefits for the development of high‐density integrated artificial neural visual systems (ANVSs). Effective charge capture and retention are essential for realizing synaptic memory function. Although charge trapping is realized by gate‐voltage‐regulated three‐terminal devices or interface‐modulated heterostructures, they involve high energy consumption and complex device structures. Another approach is to introduce material defects by post‐processing methods to trap carriers, but this method inevitably damages the pristine materials and requires intricate fabrication processes. In this study, the chemical vapor deposition (CVD) method is employed to directly introduce Re atoms as point defects into MoS2, which act as trap centers for capturing carriers, eliminating the need for complex device structures or post‐processing procedures. The resultant MoxRe(1−x)S2 nanofilms and nanoribbons exhibit excellent optoelectronic synaptic properties and broadband photoresponse characteristics respectively, due to varying doping concentrations. The optoelectronic synapses based on MoxRe(1−x)S2 nanofilms can simulate human color recognition, attributed to their differential response to varying light wavelengths, and possess image preprocessing capabilities for noise reduction and contrast enhancement. The study provides a simple approach for fabricating optoelectronic synapses, thereby facilitating the integration of 2D TMDs into ANVSs.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Neural Networks and Reservoir Computing · Advanced Memory and Neural Computing · Photonic and Optical Devices

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

School of Materials Science and Engineering Beihang University Beijing 100191 P. R. China

Funding

National Natural Science Foundation of China

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