Two-Dimensional Electrically Conductive Metal–Organic Framework Boosts Synaptic Plasticity for Dynamic Image Refresh, Classification, and Efferent Neuromuscular Systems
We present a two-dimensional (2D) electrically conductive metal-organic framework (EC-MOF)-based artificial synapse. The intrinsic electronic conductivity and subnanometer channels of the EC-MOF facilitate efficient ion diffusion, enable a high density of active redox centers, and significantly enhance capacitance within the artificial synapse. As a result, the synapse operates at an ultralow voltage of 10 mV and exhibits a remarkably low power consumption of approximately 1 fW, along with the longest retention time recorded for two-terminal electrolyte-type artificial synapses to date. The alignment of the quantum size of the subnanometer pores in the EC-MOF with various cations allows for versatile synaptic plasticity. This capability is applied to image refresh, classification, and efferent signal transmission for controlling artificial muscles, thereby offering a methodology for achieving tunable neuromorphic properties. These findings suggest the potential application of metal-organic frameworks in artificial nervous systems for future brain-inspired computation, peripheral interfaces, and neurorobotics.
Authors
- Xuanxin Hu (ORCID: https://orcid.org/0000-0003-0074-2496)
- Dawei Feng (ORCID: https://orcid.org/0000-0002-6285-850X)
- Yang Lu (ORCID: https://orcid.org/0000-0002-0946-7155)
- Wentao Xu (ORCID: https://orcid.org/0000-0002-1054-6037)
- Yao Ni (ORCID: https://orcid.org/0000-0002-6370-4799)
- Xiu‐Liang Lv (ORCID: https://orcid.org/0000-0002-7533-2718)
- Chengpeng Jiang (ORCID: https://orcid.org/0000-0003-4052-0804)
- Huanhuan Wei (ORCID: https://orcid.org/0000-0002-1306-5941)
- Zhipeng Xu (ORCID: https://orcid.org/0000-0002-2048-3789)
- Gang He (ORCID: https://orcid.org/0000-0003-4711-0568)
- Jiaqi Liu (ORCID: https://orcid.org/0000-0002-2481-6827)
- Jiangdong Gong (ORCID: https://orcid.org/0009-0001-8055-6580)
Institutions
- University of Wisconsin–Madison (US)
- Anhui University (CN)
- Nankai University (CN)
Publication Details
- Journal
- Nano Letters
- Published
- 2024-11-21
- DOI
- https://doi.org/10.1021/acs.nanolett.4c04650
- Citations
- 6
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 1.25
Funders
- National Natural Science Foundation of China
- China Postdoctoral Science Foundation
- Natural Science Foundation of Tianjin City
- Anhui Postdoctoral Science Foundation
- Natural Science Foundation of Anhui Province
- Jiangsu Planned Projects for Postdoctoral Research Funds
- National Key Research and Development Program of China
- National Science Fund for Distinguished Young Scholars
- Basic and Applied Basic Research Foundation of Guangdong Province
- Division of Materials Research