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高度可复制和CMOS兼容的基于VO2的振荡器用于大脑启发的计算
Olivier Maher1,2, Roy Bernini3, Nele Harnack3
1IBM Research Europe - Zurich, Säumerstrasse 4, 8803, Rüschlikon, Zürich, Switzerland. OGM@zurich.ibm.com.
Scientific reports
|May 21, 2024
概括
二氧化瓦纳 (VO2) 显示出对人工智能硬件的承诺. 这项研究优化了上VO2膜的制造,为先进的计算应用提供可重现,低变量的振荡器.
科学领域:
- 材料科学 材料科学 材料科学
- 凝聚物质物理学 凝聚物质物理学
- 计算机工程 计算机工程
背景情况:
- 二氧化瓦纳 (VO2) 在室温附近表现出独特的电气和光学切换特性.
- VO2对于像振荡神经网络这样的非常规计算架构来说是一个有前途的材料.
- 在制造稳定,低可变性VO2器件在上进行大规模集成方面仍然存在挑战.
研究的目的:
- 为了研究化参数对VO2颗粒形成的影响.
- 为可重复的VO2设备制造开发一个最佳的基质堆.
- 提出一种创建稳定的VO2基于振荡器的配方,其变化最小.
主要方法:
- 氧化瓦纳的原子层沉积,然后采用三个回火方法:缓慢的热,闪光和快速的热回火.
- 制造的VO2片的材料和电气特性.
- 优化一个含有氧化 (HfO2) 介层的基质堆.
主要成果:
- 确定了VO2形成的最佳回火参数和基质配置.
- 展示了可重复的VO2振荡器制造的逐步配方.
- 在多个基于VO2的设备之间实现了低可变性.
结论:
- HfO2中间层对于稳定VO2和最大限度地减少设备变化至关重要.
- 开发的制造工艺使得能够创建高度可复制的VO2振荡器.
- 这项工作为人工智能应用的大规模VO2振荡神经网络铺平了道路.
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