Wavelength-multiplexed multi-mode EUV reflection ptychography based on automatic differentiation

Yifeng Shao; Sven Weerdenburg; Jacob Seifert; H. Paul Urbach; Allard P. Mosk; Wim Coene

doi:10.1038/s41377-024-01558-3

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Wavelength-multiplexed multi-mode EUV reflection ptychography based on automatic differentiation

Original Articles

- Wavelength-multiplexed multi-mode EUV reflection ptychography based on automatic differentiation
- Wavelength-multiplexed multi-mode EUV reflection ptychography based on automatic differentiation
- LSA 2024年13卷第10期页码：2156-2167
- Affiliations：
  
  1.Imaging Physics Department, Applied Science Faculty, Delft University of Technology, Lorentzweg 1, Delft 2628 CJ, The Netherlands
  2.Nanophotonics, Debye Institute for Nanomaterials Science and Center for Extreme Matter and Emergent Phenomena, Utrecht University, P.O. Box 80000, Utrecht 3508 TA, The Netherlands
  3.Research Department, ASML Netherlands B.V, De Run 6501, Veldhoven 5504 DR, The Netherlands
- Author bio：
  
  Yifeng Shao (Y.Shao@tudelft.nl)
- Funds：
- DOI：10.1038/s41377-024-01558-3
  中图分类号：
- 收稿日期：2023-12-12，
  
  修回日期：2024-06-29，
  
  录用日期：2024-07-27，
  
  网络出版日期：2024-08-19，
  
  纸质出版日期：2024-10-31
- Accepted：
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Wavelength-multiplexed multi-mode EUV reflection ptychography based on automatic differentiation[J]. LSA, 2024,13(10):2156-2167.

Shao, Y. F. et al. Wavelength-multiplexed multi-mode EUV reflection ptychography based on automatic differentiation. Light: Science & Applications, 13, 2156-2167 (2024).
Wavelength-multiplexed multi-mode EUV reflection ptychography based on automatic differentiation[J]. LSA, 2024,13(10):2156-2167. DOI： 10.1038/s41377-024-01558-3.

Shao, Y. F. et al. Wavelength-multiplexed multi-mode EUV reflection ptychography based on automatic differentiation. Light: Science & Applications, 13, 2156-2167 (2024). DOI： 10.1038/s41377-024-01558-3.

摘要

Abstract

Ptychographic extreme ultraviolet (EUV) diffractive imaging has emerged as a promising candidate for the next generationmetrology solutions in the semiconductor industry

as it can image wafer samples in reflection geometry at the nanoscale. This technique has surged attention recently

owing to the significant progress in high-harmonic generation (HHG) EUV sources and advancements in both hardware and software for computation. In this study

a novel algorithm is introduced and tested

which enables wavelength-multiplexed reconstruction that enhances the measurement throughput and introduces data diversity

allowing the accurate characterisation of sample structures. To tackle the inherent instabilities of the HHG source

a modal approach was adopted

which represents the cross-density function of the illumination by a series of mutually incoherent and independent spatial modes. The proposed algorithm was implemented on a mainstream machine learning platform

which leverages automatic differentiation to manage the drastic growth in model complexity and expedites the computation using GPU acceleration. By optimising over 200 million parameters

we demonstrate the algorithm's capacity to accommodate experimental uncertainties and achieve a resolution approaching the diffraction limit in reflection geometry. The reconstruction of wafer samples with 20-nm high patterned gold structures on a silicon substrate highlights our ability to handle complex physical interrelations involving a multitude of parameters. These results establish ptychography as an efficient and accurate metrology tool.

关键词

Keywords

references

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