Publikationen von Karsten Reuter

Gehrke, R.: First-principles basin-hopping for the structure determination of atomic clusters. Freie Universität Berlin

Zhang, Y.: First-principles statistical mechanics approach to step decoration at solid surfaces. Freie Universität Berlin

Rogal, J.: Stability, composition and function of palladium surfaces in oxidizing environments: A first-principles statistical mechanics approach. Freie Universität Berlin

Reuter, K.: First-principles statistical mechanics for oxidation catalysis. Freie Universität Berlin Berlin

Huss, T.: Towards a universal machine learning interatomic potential for the xLi₂S-(100 - x)P₂S₅ material class. Technische Universität München

König, P.: Generative Adversarial Networks (GANs) for inverse design of RuO₂ surfaces. Technische Universität München

Bergmann, N.: Investigation of oxidized Cu surfaces using Gaussian Approximation Potentials. Technische Universität München

Sauerland, L.: Machine-learned interatomic potentials for the syngas conversion on Rhodium. Ludwig-Maximilians-Universität München

Belova, V., H. Gao, W. Sghaier, A. Manikas, M. Saedi, H. Heenen, C. Galiotis, G. Renaud, O.V. Konovalov, I.M.N. Groot, K. Reuter und M. Jankowski: Operando Characterization and Molecular Simulations Reveal the Growth Kinetics of Graphene on Liquid Copper during Chemical Vapor Deposition., im Druck.

Landini, E., K. Reuter und H. Oberhofer: Machine-learning Based Screening of Lead-free Halide Double Perovskites for Photovoltaic Applications., im Druck.

Neumann, F., J. Margraf, K. Reuter und A. Bruix: Interplay between shape and composition in bimetallic nanoparticles revealed by an efficient optimal-exchange optimization algorithm., im Druck.