Metaplasticity-Enabled Graphene Quantum Dot Devices for Mitigating Catastrophic Forgetting in Artificial Neural Networks (Adv. Mater. 6/2025)

IF 27.4 1区 材料科学 Q1 CHEMISTRY, MULTIDISCIPLINARY
Xuemeng Fan, Anzhe Chen, Zongwen Li, Zhihao Gong, Zijian Wang, Guobin Zhang, Pengtao Li, Yang Xu, Hua Wang, Changhong Wang, Xiaolei Zhu, Rong Zhao, Bin Yu, Yishu Zhang
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Abstract

Metaplastic Synaptic Devices for Continual Learning

In article number 2411237, Yishu Zhang, Changhong Wang, Xiaolei Zhu, and co-workers demonstrat an innovative metaplastic artificial synaptic device, enabling artificial neural networks with multitask continual learning capabilities. The introduction of graphene quantum dots mediates electron motion to balance weight stability and plasticity, successfully mimicking the advanced learning characteristics of biological brains and addressing the issue of catastrophic forgetting in artificial neural networks.

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来源期刊
Advanced Materials
Advanced Materials 工程技术-材料科学:综合
CiteScore
43.00
自引率
4.10%
发文量
2182
审稿时长
2 months
期刊介绍: Advanced Materials, one of the world's most prestigious journals and the foundation of the Advanced portfolio, is the home of choice for best-in-class materials science for more than 30 years. Following this fast-growing and interdisciplinary field, we are considering and publishing the most important discoveries on any and all materials from materials scientists, chemists, physicists, engineers as well as health and life scientists and bringing you the latest results and trends in modern materials-related research every week.
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