%0 Journal Article
%1 zav22
%A Zaverkin, Viktor
%A Netz, Julia
%A Zills, Fabian
%A Köhn, Andreas
%A Kästner, Johannes
%D 2022
%J J. Chem. Theory Comput.
%K myown
%P 1-12
%R 10.1021/acs.jctc.1c00853
%T Thermally Averaged Magnetic Anisotropy Tensors via Machine Learning Based on Gaussian Moments
%U http://dx.doi.org/10.1021/acs.jctc.1c00853
%V 18
@article{zav22,
added-at = {2023-10-04T14:49:43.000+0200},
author = {Zaverkin, Viktor and Netz, Julia and Zills, Fabian and Köhn, Andreas and K\"astner, Johannes},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2d85395aa51c2ef610be16a94ebb002f5/jkaestner},
doi = {10.1021/acs.jctc.1c00853},
interhash = {8eb27e841bbc9c87f7553410f92e8039},
intrahash = {d85395aa51c2ef610be16a94ebb002f5},
journal = {J. Chem. Theory Comput.},
keywords = {myown},
pages = {1-12},
timestamp = {2023-10-04T14:49:43.000+0200},
title = {Thermally Averaged Magnetic Anisotropy Tensors via Machine Learning Based on Gaussian Moments},
url = {http://dx.doi.org/10.1021/acs.jctc.1c00853},
volume = 18,
year = 2022
}