Publikationen von Karsten Reuter

de Andres, P. L.; Reuter, K.; Garcia-Vidal, F. J.; Sestovic, D.; Flores, F.: A theoretical analysis of ballistic electron emission microscopy: k-space distributions and spectroscopy. Applied Surface Science 123-124, S. 199 - 206 (1998)

Reuter, K.; Bernhardt, J.; Wedler, H.; Schardt, J.; Starke, U.; Heinz, K.: Holographic Image Reconstruction from Electron Diffraction Intensities of Ordered Superstructures. Physical Review Letters 79 (24), S. 4818 - 4821 (1997)

Reuter, K.; Wedler, H.; Ott, M.; Heinz, K.; Vamvakas, J. A.; Chen, X.; Saldin, D. K.: Influence of the data base and algorithmic parameters on the image quality in holographic diffuse LEED. Physical Review B 55 (8), S. 5344 - 5352 (1997)

de Andres, P.L.; Reuter, K.; Garcia-Vidal, F.J.; Flores, F.; Hohenester, U.; Kocevar, P.: A Theoretical Analysis of Ballistic Electron Emission Microscopy: Band Structure Effects and Attenuation Lengths. Acta Physica Polonica A 93 (2), S. 281 - 287 (1997)

Saldin, D. K.; Chen, X.; Vamvakas, J. A.; Ott, M.; Wedler, H.; Reuter, K.; Heinz, K.; Andres, P. L. D.: Holographic LEED: A Review of Recent Progress. Surface Review and Letters 4 (5), S. 991 - 1001 (1997)

Saldin, D. K.; Reuter, K.; Andres, P. L. D.; Wedler, H.; Chen, X.; Pendry, J. B.; Heinz, K.: Direct reconstruction of three-dimensional atomic adsorption sites by holographic LEED. Physical Review B 54 (11), S. 8172 - 8176 (1996)

Wengert, S.; Kunkel, C.; Margraf, J.; Reuter, K.: Accelerating molecular materials discovery with machine-learning. In: High-Performance Computing and Data Science in the Max Planck Society, S. 40 - 41. Max Planck Computing and Data Facility, Garching (2021)

Reuter, K.; Metiu, H.: A Decade of Computational Surface Catalysis. In: Handbook of Materials Modeling, 2. Ed. Aufl., S. 1309 - 1319 (Hg. Andreoni, W.; Yip, S.). Springer, Cham (2020)

Carbogno, C.; Groß, A.; Meyer, J.; Reuter, K.: O₂ Adsorption Dynamics at Metal Surfaces: Non-adiabatic Effects, Dissociation and Dissipation. In: Dynamics of Gas-Surface Interactions: Atomic-level Understanding of Scattering Processes at Surfaces, S. 389 - 419 (Hg. Díez Muiño, R.; Busnengo, H. F.). Springer, Berlin, Heidelberg (2013)

Reuter, K.: First-principles kinetic Monte Carlo simulations for heterogeneous catalysis: Concepts, status, and frontiers. In: Modeling and Simulation of Heterogeneous Catalytic Reactions: From the Molecular Process to the Technical System, S. 71 - 111 (Hg. Deutschmann, O.). Wiley-VCH, Weinheim (2012)

Reuter, K.: Nanometer and subnanometer thin oxide films at surfaces of late transition metals. In: Nanocatalysis, S. 343 - 376 (Hg. Heiz, U.; Landman, U.). Springer, Berlin (2006)

Reuter, K.; Stampfl, C.; Scheffler, M.: Ab initio atomistic thermodynamics and statistical mechanics of surface properties and functions. In: Handbook of Materials Modeling, S. 149 - 194 (Hg. Yip, S.). Springer, Dordrecht (2005)

Hermann, K.; Reuter, K.: Theoretische Bausteine zum Verständnis katalytischer Reaktionen an Übergangsmetall-Oxidoberflächen. In: MPG Jahrbuch. Max-Planck-Gesellschaft, Munich (2003)

Rogal, J.; Reuter, K.: Ab initio atomistic thermodynamics for surfaces: A primer. In: Experiment, Modeling and Simulation of Gas-Surface Interactions for Reactive Flows in Hypersonic Flights, S. 2-1 - 2-18. VT-142 RTO AVT/VKI Lecture Series, von Karman Institute, Rhode St. Genèse, Belgium, 06. Februar 2006 - 10. Februar 2006. NATO Research and Technology Organisation, Neuilly-sur-Seine (2007)

Reuter, K.: Machine Learning Accelerated Materials Discovery for Energy Conversion and Storage. CECAM Flagship Workshop, Machine Learning for Materials Discovery, ML4MD, Aalto, Finland (2025)

Reuter, K.: Machine Learning Accelerated Materials Discovery for Energy Conversion and Storage. Computation for Applied Catalysis Workshop 2025, Leeds, UK (2025)

Reuter, K.: Machine Learning Accelerated Materials Discovery for Energy Conversion and Storage. 58. Jahrestreffen Deutscher Katalytiker, Weimar, Germany (2025)

Reuter, K.: Machine Learning Accelerated Materials Discovery for Energy Conversion and Storage. ACS Spring Meeting 2025, San Diego, CA, USA (2025)

Reuter, K.: Machine Learning Accelerated Materials Discovery for Energy Conversion and Storage. 4th Annual Ph.D. Workshop, TAming COmplexity in Materials Modeling, TACO, Schladming, Austria (2025)

Reuter, K.: Machine Learning Accelerated Materials Discovery for Energy Conversion and Storage. COST18234 Workshop, ML with Computational Materials Science Data, Freiburg, Germany (2025)