Machine learning powered ellipsometry

Jinchao Liu; Di Zhang; Dianqiang Yu; Mengxin Ren; Jingjun Xu

doi:10.1038/s41377-021-00482-0

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Machine learning powered ellipsometry

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- Machine learning powered ellipsometry
- Machine learning powered ellipsometry
- LSA 2021年10卷第4期页码：582-588
- Affiliations：
  
  1.The Key Laboratory of Weak-Light Nonlinear Photonics, Ministry of Education, School of Physics and TEDA Applied Physics Institute, Nankai University, Tianjin, 300071, China
  2.College of Artificial Intelligence, Nankai University, Tianjin, 300071, China
  3.Collaborative Innovation Center of Extreme Optics, Shanxi University, Taiyuan, Shanxi, 030006, China
- Author bio：
  
  Mengxin Ren (ren_mengxin@nankai.edu.cn)
  Jingjun Xu (jjxu@nankai.edu.cn)
- Funds：
- DOI：10.1038/s41377-021-00482-0
  中图分类号：
- 纸质出版日期：2021-04-30，
  
  网络出版日期：2021-03-12，
  
  收稿日期：2020-06-18，
  
  修回日期：2021-01-30，
  
  录用日期：2021-01-30
- Accepted：
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Machine learning powered ellipsometry[J]. LSA, 2021,10(4):582-588.

Liu, J. C. et al. Machine learning powered ellipsometry. Light: Science & Applications, 10, 582-588 (2021).
Machine learning powered ellipsometry[J]. LSA, 2021,10(4):582-588. DOI： 10.1038/s41377-021-00482-0.

Liu, J. C. et al. Machine learning powered ellipsometry. Light: Science & Applications, 10, 582-588 (2021). DOI： 10.1038/s41377-021-00482-0.

摘要

Abstract

Ellipsometry is a powerful method for determining both the optical constants and thickness of thin films. For decades

solutions to ill-posed inverse ellipsometric problems require substantial human-expert intervention and have become essentially human-in-the-loop trial-and-error processes that are not only tedious and time-consuming but also limit the applicability of ellipsometry. Here

we demonstrate a machine learning based approach for solving ellipsometric problems in an unambiguous and fully automatic manner while showing superior performance. The proposed approach is experimentally validated by using a broad range of films covering categories of metals

semiconductors

and dielectrics. This method is compatible with existing ellipsometers and paves the way for realizing the automatic

rapid

high-throughput optical characterization of films.

关键词

Keywords

references

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