600 K temperature robustness and ten resistance levels memristor based on aluminum nitride films

作者：Peng Zhu, Chenjia Xu, Ying Yang, Jin Cai, Lili Ma, Ping Zhu, Xiaoqin Yang, Zengli Huang, Hong Gu · 发表于：Chip · 年份：2025 · DOI：10.1016/j.chip.2025.100173 · 被引用次数：1 · 研究领域：Advanced Memory and Neural Computing、GaN-based semiconductor devices and materials、Ferroelectric and Negative Capacitance Devices

The deployment of artificial intelligence hardware in extreme environments presents substantial technological challenges, particularly regarding multi-level data storage and operational stability. This work focuses on highly crystalline aluminum nitride (AlN) as memristive material with a large bandgap that is reported to exhibit outstanding thermal stability. Utilizing plasma-enhanced atomic layer deposition (PEALD), we have produced AlN films with low impurity concentrations through controlled plasma exposure duration, which permits the fabrication on Al/AlN/W memristor devices. The resulting memristor devices exhibit a pronounced dependence of electrical characteristics on film quality, demonstrating remarkable performance metrics including: (1) an on/off ratio surpassing 10 7 , (2) programmable 10-level resistance modulation, and (3) robust switching stability across an extensive temperature spectrum (@298-600 K) and retention time of >10 3 s (@600K). These advancements establish a viable framework for engineering high-performance, thermally robust memristors while contributing critical technical foundations for AI implementation under harsh operational conditions.