Publications of Karsten Reuter

Li, H., Y. Liu, K. Chen, J. Margraf, Y. Li and K. Reuter: Subgroup Discovery Points to the Prominent Role of Charge Transfer in Breaking Nitrogen Scaling Relations at Single-Atom Catalysts on VS₂. ACS Catalysis 11 (13), 7906–7914 (2021).

Andersen, M. and K. Reuter: Adsorption Enthalpies for Catalysis Modeling through Machine-Learned Descriptors. Accounts of Chemical Research 54 (12), 2741–2749 (2021).

Kunkel, C., J.T. Margraf, K. Chen, H. Oberhofer and K. Reuter: Active discovery of organic semiconductors. Nature Communications 12, 2422 (2021).

Weindl, R., R. Khare, L. Kovarik, A. Jentys, K. Reuter, H. Shi and J.A. Lercher: Zeolite-Stabilized Di- and Tetranuclear Molybdenum Sulfide Clusters Form Stable Catalytic Hydrogenation Sites. Angewandte Chemie International Edition 60 (17), 9301–9305 (2021).

Griesser, C., H. Li, E.-M. Werning, D. Winkler, N.S. Nia, T. Mairegger, T. Götsch, T. Schachinger, A. Steiger-Thirsfeld, S. Penner, D. Wielend, D. Egger, C. Scheurer, K. Reuter and J. Kunze-Liebhäuser: True Nature of the Transition-Metal Carbide/Liquid Interface Determines Its Reactivity. ACS Catalysis 11 (8), 4920–4928 (2021).

Wengert, S., G. Csányi, K. Reuter and J. Margraf: Data-efficient machine learning for molecular crystal structure prediction. Chemical Science 12 (12), 4536–4546 (2021).

Hörmann, N. and K. Reuter: Thermodynamic Cyclic Voltammograms Based on Ab Initio Calculations: Ag(111) in Halide-Containing Solutions. Journal of Chemical Theory and Computation 17 (3), 1782–1794 (2021).

Xu, W., M. Andersen and K. Reuter: Data-Driven Descriptor Engineering and Refined Scaling Relations for Predicting Transition Metal Oxide Reactivity. ACS Catalysis 11 (2), 734–742 (2021).

Margraf, J.T. and K. Reuter: Pure non-local machine-learned density functional theory for electron correlation. Nature Communications 12, 344 (2021).

Götsch, T., H. Türk, F. Schmidt, I.C. Vinke, L.G.J. De Haart, R. Schlögl, K. Reuter, R.-A. Eichel, A. Knop-Gericke, C. Scheurer and T. Lunkenbein: Visualizing the Atomic Structure Between YSZ and LSM: An Interface Stabilized by Complexions? ECS Transactions 103 (1), 1331–1337 (2021).

Ghan, S., C. Kunkel, K. Reuter and H. Oberhofer: Improved Projection-Operator Diabatization Schemes for the Calculation of Electronic Coupling Values. Journal of Chemical Theory and Computation 16 (12), 7431–7443 (2020).

Deimel, M., K. Reuter and M. Andersen: Active Site Representation in First-Principles Microkinetic Models: Data-Enhanced Computational Screening for Improved Methanation Catalysts. ACS Catalysis 10 (22), 13729–13736 (2020).

Timmermann, J., F. Kraushofer, N. Resch, P. Li, Y. Wang, Z. Mao, M. Riva, Y. Lee, C. Staacke, M. Schmid, C. Scheurer, G.S. Parkinson, U. Diebold and K. Reuter: IrO₂ Surface Complexions Identified through Machine Learning and Surface Investigations. Physical Review Letters 125 (20), 206101 (2020).

Auer, A., M. Andersen, E.-M. Werning, N.G. Hörmann, N. Buller, K. Reuter and J. Kunze-Liebhäuser: Self-activation of copper electrodes during CO electro-oxidation in alkaline electrolyte. Nature Catalysis 3 (10), 797–803 (2020).

Stocker, S., G. Csányi, K. Reuter and J.T. Margaf: Machine learning in chemical reaction space. Nature Communications 11, 5505 (2020).

Li, H. and K. Reuter: Active-Site Computational Screening: Role of Structural and Compositional Diversity for the Electrochemical CO₂ Reduction at Mo Carbide Catalysts. ACS Catalysis 10 (20), 11814–11821 (2020).

Cheng, B., R.-R. Griffiths, S. Wengert, C. Kunkel, T. Stenczel, B. Zhu, V.L. Deringer, N. Bernstein, J.T. Margraf, K. Reuter and G. Csanyi: Mapping Materials and Molecules. Accounts of Chemical Research 53 (9), 1981–1991 (2020).

Hörmann, N.G., N. Marzari and K. Reuter: Electrosorption at metal surfaces from first principles. npj Computational Materials 6, 136 (2020).

Cingolani, J.S., M. Deimel, S. Köcher, C. Scheurer, K. Reuter and M. Andersen: Interface between graphene and liquid Cu from molecular dynamics simulations. The Journal of Chemical Physics 153 (7), 074702 (2020).

Jung, H., S. Stocker, C. Kunkel, H. Oberhofer, B. Han, K. Reuter and J.T. Margraf: Size-Extensive Molecular Machine Learning with Global Representations. ChemSystemsChem 2 (4), e1900052 (2020).