神经形态工程学
记忆电阻器
材料科学
双模
计算
对偶(语法数字)
纳米技术
模式(计算机接口)
光电子学
电子工程
人工神经网络
计算机科学
人工智能
物理
量子力学
文学类
工程类
艺术
操作系统
算法
作者
Yuanhui Yang,Yuanjie Yang,Shifu Xiong,Yuchan Wang,Kai Hu,Fang Wang,Xiaolei Li,Lin Feng,Hongling Guo,Lei Zheng,Kailiang Zhang
标识
DOI:10.1002/adfm.202510212
摘要
Abstract The brain‐inspired dual‐mode memristor integrates analog conductance modulation and digital threshold switching, enabling dynamic adaptability and real‐time responses in a single‐device architecture for further all‐in‐one neuromorphic computing. Antimony sulfide (Sb 2 S 3 ) exhibits unique electronic and optical properties, making it ideal for above smart memory systems. However, current studies achieve only single synaptic functionality with monotonous conductive mechanisms and lack dual‐mode collaborative regulation strategies for complex sensing‐computing integration. Herein, a polymethyl methacrylate (PMMA)‐engineered Ag/Sb 2 S 3 /FTO memristor (APSF) is developed, which enables voltage‐gated analog‐to‐digital hybrid switching to bridge this gap. The introduced PMMA layer acts as an interface barrier for Ag⁺ migration and a mediator for sulfur vacancy (V S ) pathways, enabling dual conduction via Ag filaments and V S pathways. The voltage‐regulated digital‐to‐analog mode transition in APSF devices originates from bias‐coordinated charge trapping/release by the polar functional groups and interchain voids of PMMA, allowing single‐device integration of artificial synaptic and nociceptive functions. Moreover, the memristor array achieves 93.09% recognition accuracy and enables real‐time edge detection and motion tracking through in‐memory computing for convolutional processing. The results introduce an innovative paradigm for exploring multi‐functional memristor materials and devices.
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