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Geometry Optimization in Internal Coordinates Based on Gaussian Process Regression: Comparison of Two Approaches

, and . J. Chem. Theory Comput., 17 (9): 5955-5967 (2021)
DOI: 10.1021/acs.jctc.1c00517

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Geometry Optimization in Internal Coordinates Based on Gaussian Process Regression : Comparison of Two Approaches, and . Journal of chemical theory and computation, 17 (9): 5955-5967 (2021)Geometry Optimization in Internal Coordinates Based on Gaussian Process Regression: Comparison of Two Approaches, and . J. Chem. Theory Comput., 17 (9): 5955-5967 (2021)Positioning of grid points for spanning potential energy surfaces : How much effort is really needed?, , , and . The journal of chemical physics, 158 (14): 144118 (2023)Publication data for: "Evaporation and Fragmentation of Organic Molecules in Strong Electric Fields Simulated with DFT" - data from Kästner group, , , , , and . Dataset, (2021)Related to: Carolin A. Dietrich, Robin Schuldt, Daniel Born, Helena Solodenko, Guido Schmitz, and Johannes Kästner "Evaporation and Fragmentation of Organic Molecules in Strong Electric Fields Simulated with DFT" The Journal of Physical Chemistry A, 2020 124 (41), 8633-8642. doi: 10.1021/acs.jpca.0c06887.Positioning of grid points for spanning potential energy surfaces–How much effort is really needed?, , , and . J. Chem. Phys., 158 (14): 144118 (2023)Machine-learning techniques for geometry optimization. Universität Stuttgart, Stuttgart, Dissertation, (2023)Evaporation and Fragmentation of Organic Molecules in Strong Electric Fields Simulated with DFT, , , , , and . J. Phys. Chem. A, (2020)Evaporation and Fragmentation of Organic Molecules in Strong Electric Fields Simulated with DFT, , , , , and . The journal of physical chemistry. A, Molecules, spectroscopy, kinetics, environment & general theory, 124 (41): 8633-8642 (2020)