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.

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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
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article

Molecular-Layer-Deposited Amino Acid Hybrid Memristor: Bilayer Design Enabling Robust Synaptic Plasticity and Image Recognition

Chuyi Zhang, Di Wu, Aidong Li, Song Sun et al.
The Journal of Physical Chemistry Letters
Advanced Memory and Neural Computing
article

Molecular-Layer-Deposited Amino Acid Hybrid Memristor: Bilayer Design Enabling Robust Synaptic Plasticity and Image Recognition

Chuyi Zhang, Di Wu, Aidong Li, Song Sun, Yanqiang Cao, Lin Zhu, Weimin Li, Li-Ling Fu
article en

Abstract

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.

The Journal of Physical Chemistry LettersVol. 16(49)
WuXi AppTec (China) (CN), Nanjing University of Science and Technology (CN), Vimicro (China) (CN), Collaborative Innovation Center of Advanced Microstructures (CN), Nanjing University (CN)
Openalex Percentile: Top 62%
Advanced Memory and Neural Computing
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Molecular-Layer-Deposited Amino Acid Hybrid Memristor: Bilayer Design Enabling Robust Synaptic Plasticity and Image Recognition — Chuyi Zhang, Di Wu, et al. · The Journal of Physical Chemistry Letters (2025) | TGRS Research Map | TGRS