Record link: 
http://hdl.handle.net/20.500.12708/222338
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Title: 
Deep Learning for Chemical Reactions: Activation Energy Prediction
en
Citation: 
De Landsheere, J., Karwounopoulos, J., Gerhaher, A. C., Galustian, L., Kovar, M. P.-P., Zamyatin, A., Mark, K. A., Ganser, L., Gstöttenmayr, S., Teis Hannah, Zeller Benjamin, & Heid, E. C. (2025, September). Deep Learning for Chemical Reactions: Activation Energy Prediction [Poster Presentation]. AITHYRA Symposium “AI for Life Science” 2025, Wien, Austria.
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Publication Type: 
Presentation - Poster Presentation
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Language: 
English
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Authors: 
De Landsheere, Jasper 
Karwounopoulos, Johannes 
Gerhaher, Anna Charlotte 
Galustian, Leonard 
Kovar, Maximilian Peter-Paul 
Zamyatin, Anton 
Mark, Konstantin Alexander 
Ganser, Leon 
Gstöttenmayr, Stephanie 
Teis Hannah 
Zeller Benjamin 
Heid, Esther Carina 
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Organisational Unit: 
E165-03-1 - Forschungsgruppe Theoretische Materialchemie 
E056-23 - Fachbereich Innovative Combinations and Applications of AI and ML (iCAIML) 
E163-03-5 - Forschungsgruppe Nachhaltige organische Synthese und Katalyse 
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Date (published): 
Sep-2025
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Event name: 
AITHYRA Symposium “AI for Life Science” 2025 
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Event date: 
8-Sep-2025 - 10-Sep-2025
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Event place: 
Wien, Austria
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Keywords: 
Deep Learning; Chemical reactions; activation energy
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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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