Publications of Karsten Reuter

Zhang, D.; Li, H.; Lu, H.; Yin, Z.; Fusco, Z.; Riaz, A.; Reuter, K.; Catchpole, K.; Karuturi, S.: Unlocking the performance of ternary metal (hydro)oxide amorphous catalysts via data-driven active-site engineering. Energy & Environmental Science 16 (11), pp. 5065 - 5075 (2023)

Stocker, S.; Jung, H.; Csányi, G.; Goldsmith, C. F.; Reuter, K.; Margraf, J.: Estimating Free Energy Barriers for Heterogeneous Catalytic Reactions with Machine Learning Potentials and Umbrella Integration. Journal of Chemical Theory and Computation 19 (19), pp. 6796 - 6804 (2023)

Gelžinytė, E.; Wengert, S.; Stenczel, T. K.; Heenen, H.; Reuter, K.; Csányi, G.; Bernstein, N.: wfl Python toolkit for creating machine learning interatomic potentials and related atomistic simulation workflows. The Journal of Chemical Physics 159 (12), 124801 (2023)

Dudzinski, A.; Diesen, E.; Heenen, H.; Bukas, V. J.; Reuter, K.: First Step of the Oxygen Reduction Reaction on Au(111): A Computational Study of O₂ Adsorption at the Electrified Metal/Water Interface. ACS Catalysis 13 (18), pp. 12074 - 12081 (2023)

Dupuy, R.; Filser, J.; Richter, C.; Seidel, R.; Trinter, F.; Buttersack, T.; Nicolas, C.; Bozek, J.; Hergenhahn, U.; Oberhofer, H. et al.; Winter, B.; Reuter, K.; Bluhm, H.: Correction: Photoelectron angular distributions as sensitive probes of surfactant layer structure at the liquid-vapor interface. Physical Chemistry Chemical Physics 25 (33), p. 22538 - 22538 (2023)

Lee, Y.; Timmermann, J.; Panosetti, C.; Scheurer, C.; Reuter, K.: 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), pp. 17599 - 17608 (2023)

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

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

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

Ghan, S.; Diesen, E.; Kunkel, C.; Reuter, K.; Oberhofer, H.: 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.; Kunkel, C.; Cheng, B.; Reuter, K.; Margraf, J.: Physics-inspired machine learning of localized intensive properties. Chemical Science 14 (18), pp. 4913 - 4922 (2023)

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

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

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

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

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

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

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

Türk, H.; Götsch, T.; Schmidt, F.; Hammud, A.; Ivanov, D.; de Haart, J. L. G. (.; Vinke, I. C.; Eichel, R.-A.; Schlögl, R.; Reuter, K. et al.; Knop-Gericke, A.; Lunkenbein, T.; Scheurer, C.: 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.; Huss, T.; Margraf, J.; Reuter, K.; Scheurer, C.: Tackling Structural Complexity in Li₂ S-P₂S₅ Solid-State Electrolytes Using Machine Learning Potentials. Nanomaterials 12 (17), 2950 (2022)