使用上方视图SEM-EDX与电子束模拟和机器学习一起测量薄膜厚度的新技术
Tahsinul Huq1, Yew Hoong Wong1, Joon Huang Chuah2
1Department of Mechanical Engineering, Faculty of Engineering, Universiti Malaya, 50603 Kuala Lumpur, Malaysia.
Ultramicroscopy
|September 16, 2025
概括
一种新方法使用扫描电子显微镜和能量分散式X射线光谱 (EDX) 的机器学习来测量薄膜厚度. 这种技术避免了基质比较,为各种底层材料提供了更高的准确性.
科学领域:
- 材料科学 材料科学 材料科学
- 纳米技术纳米技术
- 分析化学 分析化学
背景情况:
- 精确测量薄膜厚度对于微电子设备制造至关重要.
- 现有的方法往往需要特定的参考样品或基质信号,限制了它们的适用性.
研究的目的:
- 开发一种新的,多功能方法来确定薄膜厚度.
- 利用机器学习和EDX信号比率来提高测量准确度.
主要方法:
- 利用电子束模拟来生成机器学习算法的训练数据.
- 在三个加速电压下使用EDX特征X射线计数的比例.
- 专注于顶部视图扫描电子显微镜 (SEM) 和EDX测量.
主要成果:
- 实现了高预测准确度,对于40nm以上的厚度,平均误差低于10%.
- 证明了该方法与基质材料特性之间的独立性.
- 识别了较高加速电压的横向电子束分散的增加,影响了最小可测量的特征大小.
结论:
- 开发的方法为薄膜厚度的确定提供了一个强大的方法,适用于各种基板.
- 限制包括需要使用作为顶层,并仔细控制实验参数.
- 需要进一步优化,以解决特定厚度范围的错误,并提高测量灵活性.
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