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 (>10 5 ) and long‐term retention (>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.
Authors
- Y Anita Li (ORCID: https://orcid.org/0009-0003-7540-6603)
- Xi Zhang (ORCID: https://orcid.org/0000-0002-4638-3997)
- Qiong Lu
- Yuanzhang Zhao (ORCID: https://orcid.org/0009-0004-4419-7308)
- Jianbiao Chen
- Xiaofei Dong
- Hao Sun (ORCID: https://orcid.org/0009-0006-5438-8962)
- Jiangtao Chen (ORCID: https://orcid.org/0000-0001-7853-7914)
- Fengxia Yang
Institutions
- Northwest Normal University (CN)
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
Funders
- National Natural Science Foundation of China