Publications of Karsten Reuter

S. Stegmaier: Working Interfaces in Solid-State Electrolytes: A Theoretical Approach towards Realistic Models. Technische Universität München

S. Stocker: Transferability in chemical machine learning. Technische Universität München

S. Wengert: Kernel-based machine learning for molecular crystal structure prediction. Technische Universität München

C. Grosu: Capturing ion dynamics in lithium intercalated graphite: bridging the gap between experiment and theory through advanced nuclear magnetic resonance and multiscale modeling. Technische Universität München

S. Döpking: Error aware analysis of multi-scale reactivity models for chemical surface reactions. Freie Universität Berlin

C. Kunkel: Data-driven Organic Semiconductor Discovery. Technische Universität München

H. Guhl: Density functional theory study of oxygen and water adsorption on SrTiO3(001). Humboldt-Universität Berlin

S. Matera: A First-Principles Based Multiscale Approach from the Electronic to the Continuum Regime: CO Oxidation at RuO2(110). Technische Universität Berlin Berlin

M. Rieger: First-principles based models for lateral interactions of adsorbates. Freie Universität Berlin

A.G. Sanfilippo: An ab-initio study of bilayer graphene using higher order quantum chemical methods. Freie Universität Berlin

E.R. McNellis: First-principles modeling of molecular switches at surfaces. Freie Universität Berlin

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

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

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

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

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

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

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

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

A. Samtsevych, Y. Song, T. van der Heide, B. Aradi, B. Hourahine, R.J. Maurer, K. Reuter, C. Scheurer and C. Panosetti: DSKO: dancing through DFTB parameterization., in press.