📄 Title: Selector-Free 16 × 16 CrOx/TiO2-Based Memristor Array for Synaptic Dynamics and LTP/LTD Emulation: Experimental–Computational Correlation
🔗 DOI: https://doi.org/10.1002/adfm.202516695🌐 Full Access: Link
This publication reports a selector-free 16 × 16 (8-bit) memristor crossbar array based on the CrOx/TiO2 system, tailored for neuromorphic computing applications. By combining experimental fabrication & characterization with first-principles simulations (DFT), the study demonstrates a pathway toward energy-efficient and scalable neuromorphic hardware.
The work highlights a close collaboration between VNU-HCM and VNU-Hanoi, while also establishing new international ties with EPFL (Switzerland) through a summer internship of MSc. Pham Phu Quan, and receiving valuable theoretical support from Tohoku University (Japan).
On this occasion, the authors gratefully dedicate this achievement to People’s Teacher, Prof. Dr. Le Khac Binh, on his 85th birthday, honoring his pioneering role in founding the Faculty of Materials Science and guiding Assoc. Prof. Dr. Pham Kim Ngoc from the very beginning of her scientific journey.
🌟 Key Highlights
- Chip Fabrication: Room-temperature DC sputtering + stencil lithography, fully CMOS-compatible, fabricated at the Faculty of Materials Science.
- Memristor–Diode–Capacitor Coupling: Capacitor-coupled memristive dynamics with built-in diode rectification.
- Uniformity & Scalability: 16 × 16 crossbar demonstrates stable and uniform switching, with sneak currents suppressed down to the nanoampere level.
- Computational Insights: DFT reveals electronic structures, band alignments, and oxygen vacancy migration consistent with experiments.
- Synaptic Emulation: Devices reproduce key synaptic functions (LTP/LTD, reversible conductance tuning, accumulative plasticity), supporting neuromorphic network applications.
👉 This milestone demonstrates the strength of cross-institutional and international collaboration, contributing to Vietnam’s long-term vision in AI hardware and semiconductor technologies.
Funding
This study was supported by Vingroup Innovative Fund, grant number VinIF 2023.DA130.
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