AgBiS <sub>2</sub> Memristor‐Enabled Dual‐Functional of Unclonable Hardware Authorized Encryption and Dynamic Intelligent Perception for Neuromorphic Systems

ABSTRACT Integrating the intrinsic in‐memory computing and temporal dynamic response characteristics of memristors directly into the design of time‐varying information processing and hardware security is pivotal for boosting the efficiency, security, and dynamic adaptability of big data‐driven artificial intelligence. Herein, we report an Ag/AgBiS 2 /Mo synaptic memristor featuring a high switching ratio (&gt;10 5 ) and long‐term retention (&gt;10 4 s), which exhibits electrically and optically modulated diverse synaptic plasticity behaviors, including excitatory postsynaptic current (EPSC), paired‐pulse facilitation/depression (PPF/D), long‐term potentiation/depression (LTP/D), short/long‐term memory (S/LTM) spike‐timing/rate/duration/voltage‐dependent plasticity (STDP, SRDP, SDDP, SVDP). Notably, this AgBiS 2 ‐based memristor enables co‐integrated two core functionalities: 1) Model‐level encryption and authorized inference. Device‐based physically unclonable constraints yield an inference accuracy of 88.5% under a valid authorization key, whereas the accuracy plummets to 18.9% with an invalid key. 2) Time‐fading trajectory (TF‐Traj) modeling and dynamic perception. A trajectory classification accuracy of 95.2% is achieved on the constructed 2D TF‐Traj with significantly enhanced accuracy and stability of single‐step trajectory prediction. The results directly bridge the device physics, dynamic intelligent perception, and information security, highlighting the promise of memristor's intrinsic dynamics for advancing trustworthy, multi‐scenario neuromorphic computing and high‐confidence intelligent systems.

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Publication Details

Journal
Advanced Functional Materials
Published
2026-05-11
DOI
https://doi.org/10.1002/adfm.75808
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.00

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article

AgBiS 2 Memristor‐Enabled Dual‐Functional of Unclonable Hardware Authorized Encryption and Dynamic Intelligent Perception for Neuromorphic Systems

Y Anita Li, Xi Zhang, Qiong Lu, Yuanzhang Zhao et al.
Advanced Functional Materials
Advanced Memory and Neural Computing
article

AgBiS 2 Memristor‐Enabled Dual‐Functional of Unclonable Hardware Authorized Encryption and Dynamic Intelligent Perception for Neuromorphic Systems

Y Anita Li, Xi Zhang, Qiong Lu, Yuanzhang Zhao, Jianbiao Chen, Xiaofei Dong, Hao Sun, Jiangtao Chen, Fengxia Yang
article en

Abstract

ABSTRACT Integrating the intrinsic in‐memory computing and temporal dynamic response characteristics of memristors directly into the design of time‐varying information processing and hardware security is pivotal for boosting the efficiency, security, and dynamic adaptability of big data‐driven artificial intelligence. Herein, we report an Ag/AgBiS 2 /Mo synaptic memristor featuring a high switching ratio (&gt;10 5 ) and long‐term retention (&gt;10 4 s), which exhibits electrically and optically modulated diverse synaptic plasticity behaviors, including excitatory postsynaptic current (EPSC), paired‐pulse facilitation/depression (PPF/D), long‐term potentiation/depression (LTP/D), short/long‐term memory (S/LTM) spike‐timing/rate/duration/voltage‐dependent plasticity (STDP, SRDP, SDDP, SVDP). Notably, this AgBiS 2 ‐based memristor enables co‐integrated two core functionalities: 1) Model‐level encryption and authorized inference. Device‐based physically unclonable constraints yield an inference accuracy of 88.5% under a valid authorization key, whereas the accuracy plummets to 18.9% with an invalid key. 2) Time‐fading trajectory (TF‐Traj) modeling and dynamic perception. A trajectory classification accuracy of 95.2% is achieved on the constructed 2D TF‐Traj with significantly enhanced accuracy and stability of single‐step trajectory prediction. The results directly bridge the device physics, dynamic intelligent perception, and information security, highlighting the promise of memristor's intrinsic dynamics for advancing trustworthy, multi‐scenario neuromorphic computing and high‐confidence intelligent systems.

Advanced Functional Materials
Northwest Normal University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 9%
Advanced Memory and Neural Computing
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