Publications of Carsten Staacke

Staacke, C.; Huss, T.; Margraf, J.; Reuter, K.; Scheurer, C.: Tackling Structural Complexity in Li₂ S-P₂S₅ Solid-State Electrolytes Using Machine Learning Potentials. Nanomaterials 12 (17), 2950 (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)

Timmermann, J.; Lee, Y.; Staacke, C.; Margraf, J.; Scheurer, C.; Reuter, K.: Data-Efficient Iterative Training of Gaussian Approximation Potentials: Application to Surface Structure Determination of Rutile IrO₂ and RuO₂. The Journal of Chemical Physics 155 (24), 244107 (2021)

Staacke, C.; Heenen, H.; Scheurer, C.; Csányi , G.; Reuter, K.; Margraf, J.: On the Role of Long-Range Electrostatics in Machine-Learned Interatomic Potentials for Complex Battery Materials. ACS Applied Energy Materials 4 (11), pp. 12562 - 12569 (2021)

Staacke, C.: The Electrostatic Gap: Combining Electrostatic Models with Machine Learning Potentials. Dissertation, Technische Universität, München (2022)