Metaplasticity‐Enabled Graphene Quantum Dot Devices for Mitigating Catastrophic Forgetting in Artificial Neural Networks (Adv. Mater. 6/2025)
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.
Authors
- Xiaolei Zhu (ORCID: https://orcid.org/0000-0003-2331-2739)
- Anzhe Chen (ORCID: https://orcid.org/0009-0005-5921-3160)
- Zongwen Li (ORCID: https://orcid.org/0000-0002-8700-5685)
- Zijian Wang (ORCID: https://orcid.org/0009-0002-0566-2970)
- Pengtao Li (ORCID: https://orcid.org/0009-0000-9108-1640)
- Bin Yu (ORCID: https://orcid.org/0000-0003-0237-6311)
- Zhihao Gong (ORCID: https://orcid.org/0000-0002-0362-5482)
- Yishu Zhang (ORCID: https://orcid.org/0000-0001-8774-7374)
- Xuemeng Fan (ORCID: https://orcid.org/0009-0000-0184-3382)
- Yang Xu (ORCID: https://orcid.org/0000-0003-3148-7678)
- Changhong Wang (ORCID: https://orcid.org/0000-0002-4201-0130)
- Rong Zhao (ORCID: https://orcid.org/0000-0002-2320-0326)
- Guobin Zhang (ORCID: https://orcid.org/0000-0003-3938-5879)
- Hua Wang (ORCID: https://orcid.org/0000-0002-7319-6249)
Institutions
- Zhejiang University of Science and Technology (CN)
- Zhejiang University (CN)
- Tsinghua University (CN)
Publication Details
- Journal
- Advanced Materials
- Published
- 2025-02-01
- DOI
- https://doi.org/10.1002/adma.202570051
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00