Magnification inferred curvature for real-time curvature monitoring

Abstract The in situ and real-time measurement of curvature changes of optically reflecting surfaces is a key element to better control bottom-up fabrication processes in the semiconductor industry, but also to follow or adjust mirror deformations during fabrication and use for space or optics indus...

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Auteurs principaux: Alexandre Arnoult, Jonathan Colin
Format: article
Langue:EN
Publié: Nature Portfolio 2021
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Accès en ligne:https://doaj.org/article/70043f881fba4b61bd17f230cd26d878
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spelling oai:doaj.org-article:70043f881fba4b61bd17f230cd26d8782021-12-02T13:41:00ZMagnification inferred curvature for real-time curvature monitoring10.1038/s41598-021-88722-62045-2322https://doaj.org/article/70043f881fba4b61bd17f230cd26d8782021-04-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-88722-6https://doaj.org/toc/2045-2322Abstract The in situ and real-time measurement of curvature changes of optically reflecting surfaces is a key element to better control bottom-up fabrication processes in the semiconductor industry, but also to follow or adjust mirror deformations during fabrication and use for space or optics industries. Despite progresses made in the last two decades thanks to laser deflectometry-based techniques, the community lacks an instrument, easy to use, robust to tough environments and easily compatible with a large range of fabrication processes. We describe here a new method, called magnification inferred curvature (MIC), based on the determination of the magnification factor of the virtual image size of a known object created by a reflecting curved surface (the substrate) acting as a spherical mirror. The optical formalism, design, and proof of concept are presented. The precision, accuracy, and advantages of the MIC method are illustrated from selected examples taken from real-time growth monitoring and compared with state-of-the-art laser deflectometry-based instruments.Alexandre ArnoultJonathan ColinNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
institution DOAJ
collection DOAJ
language EN
topic Medicine
R
Science
Q
spellingShingle Medicine
R
Science
Q
Alexandre Arnoult
Jonathan Colin
Magnification inferred curvature for real-time curvature monitoring
description Abstract The in situ and real-time measurement of curvature changes of optically reflecting surfaces is a key element to better control bottom-up fabrication processes in the semiconductor industry, but also to follow or adjust mirror deformations during fabrication and use for space or optics industries. Despite progresses made in the last two decades thanks to laser deflectometry-based techniques, the community lacks an instrument, easy to use, robust to tough environments and easily compatible with a large range of fabrication processes. We describe here a new method, called magnification inferred curvature (MIC), based on the determination of the magnification factor of the virtual image size of a known object created by a reflecting curved surface (the substrate) acting as a spherical mirror. The optical formalism, design, and proof of concept are presented. The precision, accuracy, and advantages of the MIC method are illustrated from selected examples taken from real-time growth monitoring and compared with state-of-the-art laser deflectometry-based instruments.
format article
author Alexandre Arnoult
Jonathan Colin
author_facet Alexandre Arnoult
Jonathan Colin
author_sort Alexandre Arnoult
title Magnification inferred curvature for real-time curvature monitoring
title_short Magnification inferred curvature for real-time curvature monitoring
title_full Magnification inferred curvature for real-time curvature monitoring
title_fullStr Magnification inferred curvature for real-time curvature monitoring
title_full_unstemmed Magnification inferred curvature for real-time curvature monitoring
title_sort magnification inferred curvature for real-time curvature monitoring
publisher Nature Portfolio
publishDate 2021
url https://doaj.org/article/70043f881fba4b61bd17f230cd26d878
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