人工智能优化的氧化物多层,可提高20倍以上的博洛米特性能
Jin-Hyun Choi1, Hyoung-Taek Lee1,2, Jeonghoon Kim1
1Department of Physics, Ulsan National Institute of Science & Technology, Ulsan, Republic of Korea.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
|January 28, 2026
概括
研究人员使用机器学习开发了先进的WxV1-xOy薄膜,以创建线性,非歇斯底里的红外波力计. 这一突破克服了二氧化的局限性,显著提高了红外传感器的博洛米特性能.
科学领域:
- 材料科学 材料科学 材料科学
- 纳米技术纳米技术
- 传感器技术 传感器技术
背景情况:
- 像二氧化瓦纳 (VO2) 这样的相位过渡材料表现出非线性,歇斯底里性行为,限制了它们在红外波力度传感器中的使用.
- 非静电测量VOx在博洛米特中使用,但具有降解过渡和较低的温度电阻系数 (TCR).
- 实现高TCR和线性,非歇斯底里反应是微波仪技术的一个关键挑战.
研究的目的:
- 开发一种使用机器学习优化WxV1-xOy薄膜的多层方法,以实现具有高TCR的线性,非歇斯底里反应.
- 为了克服传统基于二氧化的红外传感器的局限性.
- 为了提高微波仪的性能,用于先进的红外探测.
主要方法:
- 使用多层薄膜沉积策略,在VxOy.中使用不同的 (W) 兴奋剂比率.
- 采用遗传算法优化来为所需的TCR配置文件量身定制膜特性,并减少歇斯底里.
- 在配合金属氧化物半导体 (CMOS) 兼容的条件下生长WxV1-xOy薄膜.
主要成果:
- 在多层WxV1-xOy系统中实现了量身定制的线性/平面TCR配置文件,并显著减少了hysteresis.
- 证明了同时高的TCR和低的电噪声.
- 报告说,与商业材料相比,通用博洛米特性能提高了23.6倍.
结论:
- 开发的多层WxV1-xOy薄膜为线性,高性能红外球计提供了可行的解决方案.
- 机器学习引导的方法为优化具有大,线性响应的材料提供了一般的方法.
- 这项工作对微波仪技术和其他刺激响应装置有广泛的影响.
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