Molecular-Layer-Deposited Amino Acid Hybrid Memristor: Bilayer Design Enabling Robust Synaptic Plasticity and Image Recognition
Ultrathin bilayer biomolecular memristors based on molecular layer deposition (MLD) are fabricated to achieve high-performance neuromorphic computing. The device with a TiN/Ti-cysteine/Al-cysteine/Pt structure exhibits reproducible nonvolatile bipolar resistive switching with an on/off ratio (>10<sup>2</sup>), excellent retention (>10<sup>5</sup> s), and low operating voltages (-1.28 V/+2.10 V). Improved uniformity and multistate controllability stem from a charge trapping/detrapping-assisted conductive filament mechanism, while the Al-Cys layer enhances resistive switching and retention characteristics, the Ti-Cys layer stabilizes and regulates conductive filament formation. Critically, the memristor emulates key synaptic functionalities, including long-term potentiation/depression (LTP/LTD), paired-pulse facilitation/depression (PPF/PPD), and spike-rate-dependent plasticity (SRDP). When deployed in a neural network for MNIST handwritten digit recognition, it achieves 93.7% accuracy. This work resolves limitations of single-layer biomemristors by synergistic bilayer design, advancing biohybrid electronics for energy-efficient neuromorphic hardware.
Authors
- Chuyi Zhang (ORCID: https://orcid.org/0000-0003-3369-1883)
- Di Wu (ORCID: https://orcid.org/0000-0003-3619-1411)
- Aidong Li (ORCID: https://orcid.org/0000-0003-3628-0393)
- Song Sun (ORCID: https://orcid.org/0000-0001-9944-7192)
- Yanqiang Cao (ORCID: https://orcid.org/0000-0002-4198-7652)
- Lin Zhu (ORCID: https://orcid.org/0000-0001-6687-2707)
- Weimin Li (ORCID: https://orcid.org/0000-0001-8134-2157)
- Li-Ling Fu
Institutions
- WuXi AppTec (China) (CN)
- Nanjing University of Science and Technology (CN)
- Vimicro (China) (CN)
- Collaborative Innovation Center of Advanced Microstructures (CN)
- Nanjing University (CN)
Publication Details
- Journal
- The Journal of Physical Chemistry Letters
- Published
- 2025-12-03
- DOI
- https://doi.org/10.1021/acs.jpclett.5c02883
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00