Record link: 
http://hdl.handle.net/20.500.12708/227596
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Title: 
Training Machine Learning Interatomic Potentials for CuGa alloys active in CO2 Hydrogenation
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Citation: 
Eseroglou, C., Erhard, L. C., & Comas-Vives, A. (2025). Training Machine Learning Interatomic Potentials for CuGa alloys active in CO2 Hydrogenation. In Science Days TCH 2025 Book of Abstracts (pp. 11–11).
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Publication Type: 
Inproceedings - Abstract Book Contribution
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Language: 
English
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Authors: 
Eseroglou, Christoforos 
Erhard, Linus Carl 
Comas-Vives, Aleix 
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Organisational Unit: 
E165-03-1 - Forschungsgruppe Theoretische Materialchemie 
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Published in: 
Science Days TCH 2025 Book of Abstracts 
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Date (published): 
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: 
CO2 Hydrogenation; CuGa; Active Learning; Machine Learning Interatomic Potentials; DFT Calculations
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Research facilities: 
Vienna Scientific Cluster 
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Project title: 
Dynamische Modellierung v. Sites in der heterogenen Katalyze: PAT3175423 (FWF - Österr. Wissenschaftsfonds) 
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Research Areas: 
Quantum Modeling and Simulation: 50%
Computational Materials Science: 50%
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Science Branch: 
1040 - Chemie: 75%
1030 - Physik, Astronomie: 25%
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Appears in Collections:
Conference Paper

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