Neural Functions Enabled by a Polarity-Switchable Nanofluidic Memristor
Reproducing neural functions with artificial nanofluidic systems has long been an aspirational goal for neuromorphic computing. In this study, neural functions, such as neural activation and synaptic plasticity, are successfully accomplished with a polarity-switchable nanofluidic memristor (PSNM), which is based on the anodized aluminum oxide (AAO) nanochannel array. The PSNM has unipolar memristive behavior at high electrolyte concentrations and bipolar memristive behavior at low electrolyte concentrations, which can emulate neural activation and synaptic plasticity, respectively. The mechanisms for the unipolar and bipolar memristive behaviors are related to the polyelectrolytic Wien (PEW) effect and ion accumulation/depletion effect, respectively. These findings are beneficial to the advancement of neuromorphic computing on nanofluidic platforms.
Authors
- Weiling Sun (ORCID: https://orcid.org/0000-0002-5064-0351)
- Chuanxiang Sheng (ORCID: https://orcid.org/0000-0001-7821-0014)
- Yefeng Yu (ORCID: https://orcid.org/0000-0002-4624-310X)
- Muhammad Siraj (ORCID: https://orcid.org/0000-0002-3151-5977)
- Cheng Gao (ORCID: https://orcid.org/0009-0005-5659-1676)
- Pingyuan Yan (ORCID: https://orcid.org/0000-0003-0704-1692)
- Jun‐Cheng Jin (ORCID: https://orcid.org/0000-0002-3021-1023)
- Xuan Zhang (ORCID: https://orcid.org/0000-0001-8149-4580)
- Wei Huang (ORCID: https://orcid.org/0000-0001-7004-6408)
- Yike Xiao
- Fei Sun (ORCID: https://orcid.org/0000-0002-4595-5420)
- Qi Wang (ORCID: https://orcid.org/0009-0004-6707-6613)
Institutions
- Chinese Academy of Sciences (CN)
- Fudan University (CN)
- Nanjing University of Science and Technology (CN)
- Suzhou Institute of Nano-tech and Nano-bionics (CN)
- Nanjing University of Industry Technology (CN)
- Ministry of Industry and Information Technology (CN)
Publication Details
- Journal
- Nano Letters
- Published
- 2024-09-30
- DOI
- https://doi.org/10.1021/acs.nanolett.4c03449
- Citations
- 16
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 3.34
Funders
- National Natural Science Foundation of China
- Fundamental Research Funds for the Central Universities