Record link: 
http://hdl.handle.net/20.500.12708/218454
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Title: 
Artificial Intelligence for Surface-Sensitive Materials Characterization: A Transformer for High Throughput Quantitative X-ray Photoelectron Spectroscopy
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Citation: 
Simperl, F. (2025, August 21). Artificial Intelligence for Surface-Sensitive Materials Characterization: A Transformer for High Throughput Quantitative X-ray Photoelectron Spectroscopy [Presentation]. Joint Annual Meeting of ÖPG and SPS 2025, Wien, Austria.
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Publication Type: 
Presentation - Presentation
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Language: 
English
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Authors: 
Simperl, Florian 
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Organisational Unit: 
E134-03 - Forschungsbereich Atomic and Plasma Physics 
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Date (published): 
21-Aug-2025
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Event name: 
Joint Annual Meeting of ÖPG and SPS 2025 
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Event date: 
18-Aug-2025 - 22-Aug-2025
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Event place: 
Wien, Austria
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Keywords: 
Neuronale Netzwerke; Röntgenphotoelektronenspektroskopie; Monte-Carlo Simulation; Materialcharakterisierung
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Additional information: 
https://portal-cdn.scnat.ch/asset/57310e64-bdde-539c-87a6-8949997cb050/SPG-%C3%96PG-2025_Programmuebersicht.pdf?b=502dc2f5-b124-5559-9f39-f5348fd46683&v=e8cc6efe-fb97-5b17-9e62-21d4d1bc5c2c_0&s=F9wclF9y22dW7Qll7n9Q3JwDq0BLqDxbrQDuaVyPPNW2hakEZ25DO-mXvGUjgZYVXvbhoO-wVlgautqKLkKMEHcNcqH06yA999cBJwk4F3izq7TcLzb7Vt6yztV2QTjB7K0HNcRHeq4c58vY_L1QGB8JheYJz4K1ttYsl47PhR4
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Research Areas: 
Materials Characterization: 40%
Surfaces and Interfaces: 30%
Modeling and Simulation: 30%
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Science Branch: 
1030 - Physik, Astronomie: 100%
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Appears in Collections:
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