Publications of Karsten Reuter

Lee, Y., J. Timmermann, C. Panosetti, C. Scheurer and K. Reuter: Staged Training of Machine-Learning Potentials from Small to Large Surface Unit Cells: Efficient Global Structure Determination of the RuO₂(100)-c(2 × 2) Reconstruction and (410) Vicinal. The Journal of Physical Chemistry C 127 (35), 17599–17608 (2023).

Vondrák, M., K. Reuter and J. Margraf: q-pac: A Python package for machine learned charge equilibration models. The Journal of Chemical Physics 159 (5), 054109 (2023).

Lai, K.C., S. Matera, C. Scheurer and K. Reuter: A fuzzy classification framework to identify equivalent atoms in complex materials and molecules. The Journal of Chemical Physics 159 (2), 024129 (2023).

Jung, H., L. Sauerland, S. Stocker, K. Reuter and J. Margraf: Machine-learning driven global optimization of surface adsorbate geometries. npj Computational Materials 9, 114 (2023).

Ghan, S., E. Diesen, C. Kunkel, K. Reuter and H. Oberhofer: Interpreting ultrafast electron transfer on surfaces with a converged first-principles Newns–Anderson chemisorption function. The Journal of Chemical Physics 158 (23), 234103 (2023).

Chen, K., C. Kunkel, B. Cheng, K. Reuter and J. Margraf: Physics-inspired machine learning of localized intensive properties. Chemical Science 14 (18), 4913–4922 (2023).

Dupuy, R., J. Filser, C. Richter, T. Buttersack, F. Trinter, S. Gholami, R. Seidel, C. Nicolas, J. Bozek, D. Egger, H. Oberhofer, S. Thürmer, U. Hergenhahn, K. Reuter, B. Winter and H. Bluhm: Ångstrom-Depth Resolution with Chemical Specificity at the Liquid-Vapor Interface. Physical Review Letters 130 (15), 156901 (2023).

Mairegger, T., H. Li, C. Grießer, D. Winkler, J. Filser, N. Hörmann, K. Reuter and J. Kunze-Liebhäuser: Electroreduction of CO₂ in a Non-aqueous Electrolyte-The Generic Role of Acetonitrile. ACS Catalysis 13 (9), 5780–5786 (2023).

Margraf, J., H. Jung, C. Scheurer and K. Reuter: Exploring catalytic reaction networks with machine learning. Nature Catalysis 6 (2), 112–121 (2023).

Gao, H., V. Belova, F. La Porta, J.S. Cingolani, M. Andersen, M. Saedi, O.V. Konovalov, M. Jankowski, H. Heenen, I.M.N. Groot, G. Renaud and K. Reuter: Graphene at Liquid Copper Catalysts: Atomic-Scale Agreement of Experimental and First-Principles Adsorption Height. Advanced Science 9 (36), 2204684 (2022).

Kube, P., J. Dong, N. Sánchez Bastardo, H. Ruland, R. Schlögl, J. Margraf, K. Reuter and A. Trunschke: Green synthesis of propylene oxide directly from propane. Nature Communications 13, 7504 (2022).

Peng, J., D. Schwalbe-Koda, K. Akkiraju, T. Xie, L. Giordano, Y. Yu, C.J. Eom, J.R. Lunger, D.J. Zheng, R.R. Rao, S. Muy, J.C. Grossman, K. Reuter, R. Gómez-Bombarelli and Y. Shao-Horn: Human- and machine-centred designs of molecules and materials for sustainability and decarbonization. Nature Reviews Materials 7 (12), 991–1009 (2022).

Türk, H., E. Landini, C. Kunkel, J. Margraf and K. Reuter: Assessing Deep Generative Models in Chemical Composition Space. Chemistry of Materials 34 (21), 9455–9467 (2022).

Türk, H., T. Götsch, F. Schmidt, A. Hammud, D. Ivanov, (B.de H. J. L. G., I.C. Vinke, R.-A. Eichel, R. Schlögl, K. Reuter, A. Knop-Gericke, T. Lunkenbein and C. Scheurer: Sr Surface Enrichment in Solid Oxide Cells – Approaching the Limits of EDX Analysis by Multivariate Statistical Analysis and Simulations. ChemCatChem 14 (19), e202200300 (2022).

Staacke, C., T. Huss, J. Margraf, K. Reuter and C. Scheurer: Tackling Structural Complexity in Li₂ S-P₂S₅ Solid-State Electrolytes Using Machine Learning Potentials. Nanomaterials 12 (17), 2950 (2022).

Boix, V., W. Xu, G. D’Acunto, J. Stubbe, T. Gallo, M.D. Strømsheim, S. Zhu, M. Scardamaglia, A. Shavorskiy, K. Reuter, M. Andersen and J. Knudsen: Graphene as an Adsorption Template for Studying Double Bond Activation in Catalysis. The Journal of Physical Chemistry C 126 (33), 14116–14124 (2022).

Stegmaier, S., K. Reuter and C. Scheurer: Exploiting Nanoscale Complexion in LATP Solid-State Electrolyte via Interfacial Mg²⁺ Doping. Nanomaterials 12 (17), 2912 (2022).

Li, H. and K. Reuter: Ab Initio Thermodynamic Stability of Carbide Catalysts under Electrochemical Conditions. ACS Catalysis 12 (16), 10506–10513 (2022).

Xu, W., K. Reuter and M. Andersen: Predicting binding motifs of complex adsorbates using machine learning with a physics-inspired graph representation. Nature Computational Science 2 (7), 443–450 (2022).

Wengert, S., G. Csányi, K. Reuter and J. Margraf: A Hybrid Machine Learning Approach for Structure Stability Prediction in Molecular Co-crystal Screenings. Journal of Chemical Theory and Computation 18 (7), 4586–4593 (2022).