Publikationen von Christian Kunkel

Felsen, F.; Kunkel, C.; Reuter, K.; Scheurer, C.: Adaptive designs for the exploration of reaction kinetic phase transitions. Chemical Engineering Journal Advances 22, 100746 (2025)

Li, Z.; Öztuna, E.; Skorupska, K.; Vinogradova, O.; Jamshaid, A.; Steigert, A.; Rohner, C.; Dimitrakopoulou, M.; Prieto, M.; Kunkel, C. et al.; Stredansky, M.; Kube, P.; Götte, M.; Dudzinski, A.; Girgsdies, F.; Wrabetz, S.; Frandsen, W.; Blume, R.; Zeller, P.; Muske, M.; Delgado Muñoz, D.; Jiang, S.; Schmidt, F.; Köchler, T.; Arztmann, M.; Efimenko, A.; Frisch, J.; Kokumai, T.; Garcia-Diez, R.; Bär, M.; Hammud, A.; Kröhnert, J.; Trunschke, A.; Scheurer, C.; Schmidt, T.; Lunkenbein, T.; Amkreutz, D.; Kuhlenbeck, H.; Bukas, V. J.; Knop-Gericke, A.; Schlatmann, R.; Reuter, K.; Roldan Cuenya, B.; Schlögl, R.: Rationally Designed Laterally-Condensed-Catalysts Deliver Robust Activity and Selectivity for Ethylene Production in Acetylene Hydrogenation. Nature Communications 15, 10660 (2024)

Kunkel, C.; Rüther, F.; Felsen, F.; Pare, C. W. P.; Terzi, A.; Baumgarten, R.; Gioria, E.; d’Alnoncourt, R. N.; Scheurer, C.; Rosowski, F. et al.; Reuter, K.: Systematic Exploration of a Multi-Promoter Catalyst Composition Space with Limited Experiments: Non-Oxidative Propane Dehydrogenation to Propylene. ACS Catalysis 14 (11), S. 9008 - 9017 (2024)

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), S. 4913 - 4922 (2023)

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

Chen, K.; Kunkel, C.; Reuter, K.; Margraf, J.: Reorganization energies of flexible organic molecules as a challenging target for machine learning enhanced virtual screening. Digital Discovery 1 (2), S. 147 - 157 (2022)

Staacke, C.; Wengert, S.; Kunkel, C.; Csányi, G.; Reuter, K.; Margraf, J.: Kernel charge equilibration: efficient and accurate prediction of molecular dipole moments with a machine-learning enhanced electron density model. Machine Learning: Science and Technology 3 (1), 015032 (2022)

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)

Kunkel, C.: Data-driven Organic Semiconductor Discovery. Dissertation, Technische Universität, München (2021)