Inversion model for extracting chemically resolved depth profiles across liquid interfaces of various configurations from XPS data: PROPHESY

PROPHESY, a technique for the reconstruction of surface-depth profiles from X-ray photoelectron spectroscopy data, is introduced. The inversion methodology is based on a Bayesian framework and primal-dual convex optimization. The acquisition model is developed for several geometries representing dif...

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Detalles Bibliográficos
Autores principales: Ozon, Matthew, Tumashevich, Konstantin, Lin, Jack J., Prisle, Nønne L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Union of Crystallography 2023
Materias:
Research Papers
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10481271/
https://www.ncbi.nlm.nih.gov/pubmed/37610342
http://dx.doi.org/10.1107/S1600577523006124
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author Ozon, Matthew
Tumashevich, Konstantin
Lin, Jack J.
Prisle, Nønne L.
author_facet Ozon, Matthew
Tumashevich, Konstantin
Lin, Jack J.
Prisle, Nønne L.
author_sort Ozon, Matthew
collection PubMed
description PROPHESY, a technique for the reconstruction of surface-depth profiles from X-ray photoelectron spectroscopy data, is introduced. The inversion methodology is based on a Bayesian framework and primal-dual convex optimization. The acquisition model is developed for several geometries representing different sample types: plane (bulk sample), cylinder (liquid microjet) and sphere (droplet). The methodology is tested and characterized with respect to simulated data as a proof of concept. Possible limitations of the method due to uncertainty in the attenuation length of the photo-emitted electron are illustrated.
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spelling pubmed-104812712023-09-07 Inversion model for extracting chemically resolved depth profiles across liquid interfaces of various configurations from XPS data: PROPHESY Ozon, Matthew Tumashevich, Konstantin Lin, Jack J. Prisle, Nønne L. J Synchrotron Radiat Research Papers PROPHESY, a technique for the reconstruction of surface-depth profiles from X-ray photoelectron spectroscopy data, is introduced. The inversion methodology is based on a Bayesian framework and primal-dual convex optimization. The acquisition model is developed for several geometries representing different sample types: plane (bulk sample), cylinder (liquid microjet) and sphere (droplet). The methodology is tested and characterized with respect to simulated data as a proof of concept. Possible limitations of the method due to uncertainty in the attenuation length of the photo-emitted electron are illustrated. International Union of Crystallography 2023-08-23 /pmc/articles/PMC10481271/ /pubmed/37610342 http://dx.doi.org/10.1107/S1600577523006124 Text en © Matthew Ozon et al. 2023 https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution (CC-BY) Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are cited.
spellingShingle Research Papers
Ozon, Matthew
Tumashevich, Konstantin
Lin, Jack J.
Prisle, Nønne L.
Inversion model for extracting chemically resolved depth profiles across liquid interfaces of various configurations from XPS data: PROPHESY
title Inversion model for extracting chemically resolved depth profiles across liquid interfaces of various configurations from XPS data: PROPHESY
title_full Inversion model for extracting chemically resolved depth profiles across liquid interfaces of various configurations from XPS data: PROPHESY
title_fullStr Inversion model for extracting chemically resolved depth profiles across liquid interfaces of various configurations from XPS data: PROPHESY
title_full_unstemmed Inversion model for extracting chemically resolved depth profiles across liquid interfaces of various configurations from XPS data: PROPHESY
title_short Inversion model for extracting chemically resolved depth profiles across liquid interfaces of various configurations from XPS data: PROPHESY
title_sort inversion model for extracting chemically resolved depth profiles across liquid interfaces of various configurations from xps data: prophesy
topic Research Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10481271/
https://www.ncbi.nlm.nih.gov/pubmed/37610342
http://dx.doi.org/10.1107/S1600577523006124
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AT linjackj inversionmodelforextractingchemicallyresolveddepthprofilesacrossliquidinterfacesofvariousconfigurationsfromxpsdataprophesy
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