时间域热反射技术使用多个延迟探针脉冲进行高通量数据采集和分析
Hiroto Arima1, Yuichiro Yamashita1, Takashi Yagi1
1National Metrology Institute of Japan (NMIJ), National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, Japan.
Science and technology of advanced materials
|July 16, 2025
概括
一种新的高通量时域热反射 (HT-TDTR) 技术快速测量材料的热物理性质. 机器学习进一步加快了这个过程,使得快速而准确的热特性.
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
- 热力工程是热力工程中的一个.
背景情况:
- 了解微观热传输对于推进热控制和设备性能至关重要.
- 目前用于测量热物理性质的方法可能耗时.
研究的目的:
- 开发一种高通量时域热反射 (HT-TDTR) 技术,用于加速测量热物理性质.
- 展示机器学习用于快速材料表征的应用.
主要方法:
- 通过将超连续光分解成多个延迟探针脉冲来同时获取信号,开发了HT-TDTR.
- 应用皮秒脉冲光来加热石英玻璃,SrTiO3和蓝宝石.
- 利用机器学习算法,以最小的延迟点分析热反射数据.
主要成果:
- 同时测量多次延迟时间的时间温度下降.
- 分析了热度,显示与文献价值一致.
- 证明了机器学习在不到一秒的时间内从最小的数据中预测热流量的能力.
结论:
- 通过HT-TDTR,可以快速准确地测量热物理性质.
- 机器学习显著提高了使用热放松动态的材料表征的效率.
- 开发的技术有助于更高效的表征,改善了热管理.
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