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使用超快速光声技术和人工智能对多层薄膜进行表征
Zhiheng Chen1, Hongyuan Zhao2, Yueying Hou2
1National Laboratory of Solid State Microstructures, Nanjing University, Nanjing, Jiangsu 210093, China; School of Materials Science and Intelligent Engineering, Nanjing University, Suzhou 215163, China.
Ultrasonics
|July 1, 2025
概括
本研究介绍了一种人工智能驱动的超快速光声学技术,用于精确的纳米级特征化多层膜. 这种先进的方法准确地测量了薄膜厚度和晶体方向,这对于微电子和生物医学至关重要.
科学领域:
- 材料科学 材料科学 材料科学
- 纳米技术纳米技术
- 人工智能的人工智能
背景情况:
- 高精度的纳米尺度表征对于微电子,光电子和生物医学领域的先进材料至关重要.
- 超快的光声学技术提供非接触式结构造型,分辨率低于纳米.
研究的目的:
- 开发基于人工智能的自动化方案,用于测量多层薄膜和超薄膜的厚度和晶体方向.
- 通过人工智能集成,提高超高速光声学技术的精度和适用性.
主要方法:
- 开发一个多层光声学理论模型数据集.
- 变化模式分解 (VMD) -反向传播神经网络 (BPNN) 和AlexNet的应用用于降低噪声和性能预测.
- 使用超快的光声学技术与人工智能算法相结合.
主要成果:
- 成功地自动测量SiO2,LiNbO3多层和GaAs/AlAs超级格子中的厚度和晶体方向.
- 与传统方法相比,在表征多层性质方面表现出更高的精度.
- 通过与理论模型相一致的实验结果验证基于AI的方案.
结论:
- 人工智能增强的超快速光声学方法为多层膜的纳米尺度表征提供了高精度的自动化方法.
- 这项技术可以对复杂的纳米结构进行断层检测,并对集成设备和生物医学成像进行实时监测.
- 该研究为先进的材料分析和设备监控建立了新的途径.
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