Record link: 
http://hdl.handle.net/20.500.12708/222997
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Title: 
How Realistic are Idealized Copper Surfaces? A Machine Learning Study of Rough Copper-Water Interfaces
en
Citation: 
Erhard, L. C., Schörghuber, J., Comas-Vives, A., & Madsen, G. K. H. (2025). How Realistic are Idealized Copper Surfaces? A Machine Learning Study of Rough Copper-Water Interfaces. In Science Days TCH 2025 : Book of Abstracts (pp. 46–46).
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Publication Type: 
Inproceedings - Abstract Book Contribution
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Language: 
English
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Authors: 
Erhard, Linus Carl 
Schörghuber, Johannes 
Comas-Vives, Aleix 
Madsen, Georg Kent Hellerup 
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Organisational Unit: 
E165-03-1 - Forschungsgruppe Theoretische Materialchemie 
E056-04 - Fachbereich TU-DX: Towards Applications of 2D Materials 
E056-23 - Fachbereich Innovative Combinations and Applications of AI and ML (iCAIML) 
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Published in: 
Science Days TCH 2025 : Book of Abstracts 
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Date (published): 
Jun-2025
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Event name: 
TCH Science Days 2025 
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Event date: 
17-Jun-2025 - 18-Jun-2025
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Event place: 
Wien, Austria
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Number of Pages: 
1
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Keywords: 
Copper-water interface; Machine Learning Interatomic Potentials (ML-IAPs)
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Research Areas: 
Modeling and Simulation: 50%
Computational Materials Science: 50%
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Science Branch: 
1040 - Chemie: 100%
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Appears in Collections:
Conference Paper

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