A machine-learning-based approach for angular alignment of 2D multilayer Laue lenses for high-resolution hard x-ray microscopy

Wei Xu; Weihe Xu; Nathalie Bouet; Juan Zhou; Hanfei Yan; Xiaojing Huang; Lei Huang; Ming Lu; Maxim Zalalutdinov; Yong S. Chu; Evgeny Nazaretski

doi:10.1117/12.2673688

5 October 2023 A machine-learning-based approach for angular alignment of 2D multilayer Laue lenses for high-resolution hard x-ray microscopy

Wei Xu, Weihe Xu, Nathalie Bouet, Juan Zhou, Hanfei Yan, Xiaojing Huang, Lei Huang, Ming Lu, Maxim Zalalutdinov, Yong S. Chu, Evgeny Nazaretski

Author Affiliations +

Proceedings Volume 12698, X-Ray Nanoimaging: Instruments and Methods VI; 1269803 (2023) https://doi.org/10.1117/12.2673688
Event: SPIE Optical Engineering + Applications, 2023, San Diego, California, United States

Abstract

Multilayer Laue lenses (MLLs) are promising optics for high efficiency nano focusing in the hard x-ray regime. However, since MLLs are one-dimensional focusing elements, a pair of MLLs need to be orthogonally aligned with respect to each other to achieve point focusing. This involves eight independent motions with nanoscale resolutions. This requirement poses significant technical challenges for a microscopy system and requires a highly specialized and stable instrument. The development of monolithic 2D MLL nano focusing optics could greatly reduce the instrument complexity, increase focusing stability, and minimize the degrees of a nanoscale motion needed for operating the MLL optics. A critical step in building 2D MLL optics is to ensure the orthogonality between two MLLs during the alignment. In this work, we report our approach for precise angular alignment of 2D MLL optics. This process, by utilizing a machine learning algorithm on the interferometer data, can automatically and precisely detect the small orthogonality error of 2D MLL optics. It is easy to use, accurate, and robust, and remarkably simplifies the procedure of 2D MLL alignment.

Conference Presentation

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Wei Xu, Weihe Xu, Nathalie Bouet, Juan Zhou, Hanfei Yan, Xiaojing Huang, Lei Huang, Ming Lu, Maxim Zalalutdinov, Yong S. Chu, and Evgeny Nazaretski "A machine-learning-based approach for angular alignment of 2D multilayer Laue lenses for high-resolution hard x-ray microscopy", Proc. SPIE 12698, X-Ray Nanoimaging: Instruments and Methods VI, 1269803 (5 October 2023); https://doi.org/10.1117/12.2673688

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