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%0 Journal Article
%1 born2021geometry
%A Born, Daniel
%A Kästner, Johannes
%D 2021
%I American Chemical Society
%J Journal of chemical theory and computation
%K
%N 9
%P 5955-5967
%R 10.1021/acs.jctc.1c00517
%T Geometry Optimization in Internal Coordinates Based on Gaussian Process Regression : Comparison of Two Approaches
%V 17
@article{born2021geometry,
added-at = {2023-08-31T16:21:30.000+0200},
affiliation = {Kastner, J (Corresponding Author), Univ Stuttgart, Inst Theoret Chem, D-70569 Stuttgart, Germany.
Born, Daniel; Kaestner, Johannes, Univ Stuttgart, Inst Theoret Chem, D-70569 Stuttgart, Germany.},
author = {Born, Daniel and Kästner, Johannes},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/20489d1406d95943be9bf9e8a941e9097/puma-wartung},
doi = {10.1021/acs.jctc.1c00517},
interhash = {634d44e57dbba9053fe3d83d38f0e50d},
intrahash = {0489d1406d95943be9bf9e8a941e9097},
issn = {{1549-9618} and {1549-9626}},
journal = {Journal of chemical theory and computation},
keywords = {},
language = {eng},
number = 9,
orcid-numbers = {Kastner, Johannes/0000-0001-6178-7669},
pages = {5955-5967},
publisher = {American Chemical Society},
research-areas = {Chemistry; Physics},
timestamp = {2023-08-31T14:21:30.000+0200},
title = {Geometry Optimization in Internal Coordinates Based on Gaussian Process Regression : Comparison of Two Approaches},
unique-id = {WOS:000696556000040},
volume = 17,
year = 2021
}
