Use of the N–O Bonds in N-Mesyloxyamides and N-Mesyloxyimides To Gain Access to 5-Alkoxy-3,4-dialkyloxazol-2-ones and 3-Hetero-Substituted Succinimides: A Combined Experimental and Theoretical Study. Synthesis, (55)26:2460-2472, 2023. [PUMA: chemie from:kgugeler kaestner pn3 pn3-4(II) kästner theoretische EXC2075 stuttgart theochem]
Performance of two complementary machine-learned potentials in modelling chemically complex systems. Npj Comput. Mater., (9):129, 2023. [PUMA: chemie from:kgugeler pn6-a1 kaestner kästner pn6 theoretische EXC2075 stuttgart theochem] URL
Reaction dynamics on amorphous solid water surfaces using interatomic machine-learned potentials - Microscopic energy partition revealed from the P + H → PH reaction. Astron. Astrophys., (673):A51, 2023. [PUMA: EXC2075 chemie from:kgugeler kaestner kästner pn3 stuttgart theochem theoretische]
Positioning of grid points for spanning potential energy surfaces–How much effort is really needed?. J. Chem. Phys., (158)14:144118, 2023. [PUMA: myown theoretische EXC2075 stuttgart from:danielborn chemie kaestner pn3 kästner rauhut theochem] URL
Transfer learning for chemically accurate interatomic neural network potentials. Phys. Chem. Chem. Phys., (25)7:5383-5396, 2023. [PUMA: chemie kaestner kästner pn6 theoretische EXC2075 stuttgart from:danielborn theochem]
MolecuSense: Using Force-Feedback Gloves for Creating and Interacting with Ball-and-Stick Molecules in VR. Proceedings of the 15th International Symposium on Visual Information Communication and Interaction, 1–5, Association for Computing Machinery, New York, NY, USA, 2022. [PUMA: chemie koehn myown from:akoehn köhn theoretische EXC2075 stuttgart] URL
Capabilities and limits of the unitary coupled-cluster approach with generalized two-body cluster operators. J. Chem. Phys., (157)12:124110, 2022. [PUMA: chemie koehn myown from:akoehn köhn theoretische EXC2075] URL
Exploring chemical and conformational spaces by batch mode deep active learning. Digital Discovery, (1):605-620, 2022. [PUMA: chemie kaestner kästner pn6 theoretische EXC2075 stuttgart from:danielborn theochem]
Desorption of organic molecules from interstellar ices, combining experiments and computer simulations: Acetaldehyde as a case study. Astron. Astrophys., (664):A169, 2022. [PUMA: chemie kaestner pn3 kästner theoretische EXC2075 stuttgart from:danielborn theochem]
Hydrogen abstraction reactions in formic and thioformic acid isomers by hydrogen and deuterium atoms. Astron. Astrophys., (663):A41, 2022. [PUMA: EXC2075 chemie from:danielborn kaestner kästner pn3 stuttgart theochem theoretische]
Neural-network assisted study of nitrogen atom dynamics on amorphous solid water – II. Diffusion. Mon. Not. R. Astron. Soc., (510)2:3063-3070, 2022. [PUMA: theoretische EXC2075 stuttgart from:danielborn chemie kaestner kästner pn6 theochem] URL
Thermally Averaged Magnetic Anisotropy Tensors via Machine Learning Based on Gaussian Moments. J. Chem. Theory Comput., (18):1-12, 2022. [PUMA: EXC2075 chemie from:danielborn kaestner koehn kästner köhn pn6 stuttgart theochem theoretische] URL
Neural-network assisted study of nitrogen atom dynamics on amorphous solid water – II. Diffusion. Mon. Not. R. Astron. Soc., (510)2:3063-3070, 2021. [PUMA: theoretische EXC2075 stuttgart from:danielborn chemie kaestner kästner pn6 theochem] URL
Strategies for the construction of machine-learning potentials for accurate and efficient atomic-scale simulations. Mach. Learn.: Sci. Technol., (2):031001, 2021. [PUMA: EXC2075 chemie from:danielborn kaestner kästner pn6 stuttgart theochem theoretische] URL
Computational Study of the Hydrogenation Sequence of the Phosphorous Atom on Interstellar Dust Grains. Astrophys. J., (910):55, 2021. [PUMA: theoretische EXC2075 stuttgart from:danielborn chemie kaestner pn3 kästner theochem] URL
Neural-network assisted study of nitrogen atom dynamics on amorphous solid water – I. adsorption and desorption. Mon. Not. R. Astron. Soc., (499):1373-1384, 2020. [PUMA: EXC2075 chemie from:danielborn kaestner kästner pn6 stuttgart theochem theoretische] URL
Gaussian Moments as Physically Inspired Molecular Descriptors for Accurate and Scalable Machine Learning Potentials. J. Chem. Theory Comput., (16):5410-5421, 2020. [PUMA: EXC2075 chemie from:danielborn kaestner kästner pn6 stuttgart theochem theoretische] URL
Gaussian Process Regression for Minimum Energy Path Optimization and Transition State Search. J. Phys. Chem. A, (123)44:9600-9611, 2019. [PUMA: EXC2075 chemie from:alexanderdenzel kaestner kästner pn3 stuttgart theochem theoretische] URL