Harnessing conversion bridge strategy by organic semiconductor in polymer matrix memristors for high‐performance multi‐modal neuromorphic signal processing

Harnessing conversion bridge strategy by organic semiconductor in polymer matrix memristors for high‐performance multi‐modal neuromorphic signal processing

Abstract Organic memristors, integrating chemically designed resistive switching and mechanical flexibility, present promising hardware opportunities for neuromorphic computing, particularly in the development of next‐generation wearable artificial intelligence devices. However, challenges persist i...

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Bibliographic Details
Main Authors: Weijia Dong, Xuan Ji, Chuanbin An, Chenhui Xu, Xuwen Zhang, Bin Zhao, Yuqian Liu, Shiyu Wang, Xi Yu, Xinjun Liu, Yang Han, Yanhou Geng
Format: Article
Language:English
Published: Wiley 2025-05-01
Series:InfoMat
Subjects:
convolutional neural network
neuromorphic computing
organic memristors
reservoir computing
stretchable electronics
Online Access:https://doi.org/10.1002/inf2.12659
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https://doi.org/10.1002/inf2.12659

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