A Multifunctional Volatile Memristor Based on Organic–Inorganic Hybrid Ultrathin Films for Artificial Nociceptor and Edge/Reservoir Computing
It is a challenge to endow intelligent robots with damage perception and forecast temporal data using nonvolatile memristor devices; however, volatile memristors can circumvent this issue owing to their unique ability of efficient encoding information and oblivion feature. At present, the emerging study mainly concentrates on inorganic volatile memristive materials. Herein, a multifunctional volatile memristor based on organic-inorganic hybrid ultrathin thin films has been developed for artificial nociceptor and edge/reservoir computing, which consists of a functional layer of 6 nm thick titanium-based maleic acid (Ti-MA) and 4 nm thick Al<sub>2</sub>O<sub>3</sub> prepared by molecular/atomic layer deposition (MLD/ALD). The ultrathin bilayer memristor of TiN/Ti-MA/Al<sub>2</sub>O<sub>3</sub>/Pt (TTAP) contributes to the precise tuning of the gradient distribution of oxygen vacancies, ensuring excellent reproducibility, endurance, and consistency of the memristor with a lower set/reset energy consumption. The volatility nature of the TTAP device originates from the natural diffusion of oxygen vacancies in the absence of external voltage. A series of important biosynaptic functions have been emulated in a single TTAP device. The multifunctional applications, including biological nociceptor, edge computing and reservoir computing, Pavlovian conditioning, and pattern recognition, are demonstrated in volatile organic-inorganic hybrid devices, showcasing exceptional capacity to process data. This work opens an avenue for MLD/ALD organic-inorganic hybrid volatile memristor applications in brain-inspired neuromorphic computing and artificial intelligence based on the versatility and multifunctionality of the TTAP memristor.
Authors
- Di Wu (ORCID: https://orcid.org/0000-0003-3619-1411)
- Jingjing Wei (ORCID: https://orcid.org/0000-0002-2197-8062)
- Aidong Li (ORCID: https://orcid.org/0000-0003-3628-0393)
- Song Sun (ORCID: https://orcid.org/0000-0001-9944-7192)
- Yingjie Ma (ORCID: https://orcid.org/0000-0002-3911-5134)
- Lin Zhu (ORCID: https://orcid.org/0000-0001-6687-2707)
- Fu‐Rui Teng
- Chang Liu (ORCID: https://orcid.org/0000-0002-4708-4470)
- Xinxin Wang (ORCID: https://orcid.org/0000-0002-0286-3681)
- Liling Fu (ORCID: https://orcid.org/0000-0001-6114-1788)
Institutions
- Division of Materials Science and Engineering (AU)
- Collaborative Innovation Center of Advanced Microstructures (CN)
- Nanjing University (CN)
Publication Details
- Journal
- ACS Applied Materials & Interfaces
- Published
- 2025-09-25
- DOI
- https://doi.org/10.1021/acsami.5c15142
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00