Karsten Reuter, Prof. Dr.

Affiliations: 
Chemistry Technical University Munich, Germany, München, Bayern, Germany 
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Stefan Ringe grad student
Jörg Behler grad student 2000-2004 Fritz Haber Institute of the Max Planck Society (Chemistry Tree)
Reinhard J Maurer grad student 2010-2014 (Chemistry Tree)
Johannes T. Margraf research scientist (Chemistry Tree)
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Publications

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Xu W, Diesen E, He T, et al. (2024) Discovering High Entropy Alloy Electrocatalysts in Vast Composition Spaces with Multiobjective Optimization. Journal of the American Chemical Society. 146: 7698-7707
Stocker S, Jung H, Csányi G, et al. (2023) Estimating Free Energy Barriers for Heterogeneous Catalytic Reactions with Machine Learning Potentials and Umbrella Integration. Journal of Chemical Theory and Computation. 19: 6796-6804
Vondrák M, Reuter K, Margraf JT. (2023) q-pac: A Python package for machine learned charge equilibration models. The Journal of Chemical Physics. 159
Chen K, Kunkel C, Cheng B, et al. (2023) Physics-inspired machine learning of localized intensive properties. Chemical Science. 14: 4913-4922
Kube P, Dong J, Bastardo NS, et al. (2022) Green synthesis of propylene oxide directly from propane. Nature Communications. 13: 7504
Staacke CG, Huss T, Margraf JT, et al. (2022) Tackling Structural Complexity in LiS-PS Solid-State Electrolytes Using Machine Learning Potentials. Nanomaterials (Basel, Switzerland). 12
Wengert S, Csányi G, Reuter K, et al. (2022) A Hybrid Machine Learning Approach for Structure Stability Prediction in Molecular Co-crystal Screenings. Journal of Chemical Theory and Computation
Keller E, Tsatsoulis T, Reuter K, et al. (2022) Regularized second-order correlation methods for extended systems. The Journal of Chemical Physics. 156: 024106
Levin N, Margraf JT, Lengyel J, et al. (2022) CO-Activation by size-selected tantalum cluster cations (Ta): thermalization governing reaction selectivity. Physical Chemistry Chemical Physics : Pccp. 24: 2623-2629
Timmermann J, Lee Y, Staacke CG, et al. (2021) Data-efficient iterative training of Gaussian approximation potentials: Application to surface structure determination of rutile IrO and RuO. The Journal of Chemical Physics. 155: 244107
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