Publikationen von Karsten Reuter

Gehrke, R.: First-principles basin-hopping for the structure determination of atomic clusters. Dissertation, Freie Universität, Berlin (2009)

Zhang, Y.: First-principles statistical mechanics approach to step decoration at solid surfaces. Dissertation, Freie Universität, Berlin (2008)

Rogal, J.: Stability, composition and function of palladium surfaces in oxidizing environments: A first-principles statistical mechanics approach. Dissertation, Freie Universität, Berlin (2006)

Reuter, K.: First-principles statistical mechanics for oxidation catalysis. Habilitation, Freie Universität Berlin, Berlin (2005)

Huss, T.: Towards a universal machine learning interatomic potential for the xLi₂S-(100 - x)P₂S₅ material class. Master, Technische Universität, München (2022)

König, P.: Generative Adversarial Networks (GANs) for inverse design of RuO₂ surfaces. Master, Technische Universität, München (2022)

Sauerland, L.: Machine-learned interatomic potentials for the syngas conversion on Rhodium. Master, Ludwig-Maximilians-Universität, München (2021)

Bergmann, N.: Investigation of oxidized Cu surfaces using Gaussian Approximation Potentials. Master, Technische Universität, München (2021)

Belova, V.; Gao, H.; Sghaier, W.; Manikas, A.; Saedi, M.; Heenen, H.; Galiotis, C.; Renaud, G.; Konovalov, O. V.; Groot, I. M. N. et al.; Reuter, K.; Jankowski, M.: Operando Characterization and Molecular Simulations Reveal the Growth Kinetics of Graphene on Liquid Copper during Chemical Vapor Deposition. (2024)

Landini, E.; Reuter, K.; Oberhofer, H.: Machine-learning Based Screening of Lead-free Halide Double Perovskites for Photovoltaic Applications. (2022)

Neumann, F.; Margraf, J.; Reuter, K.; Bruix, A.: Interplay between shape and composition in bimetallic nanoparticles revealed by an efficient optimal-exchange optimization algorithm. (2021)