%0 Journal Article %1 zav22 %A Zaverkin, Viktor %A Netz, Julia %A Zills, Fabian %A Köhn, Andreas %A Kästner, Johannes %D 2022 %J Journal of Chemical Theory and Computation %K EXC2075 PN3 PN3-4 PN6 PN6A-1 unclear %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 = {2024-03-26T11:56:11.000+0100}, author = {Zaverkin, Viktor and Netz, Julia and Zills, Fabian and Köhn, Andreas and K\"astner, Johannes}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/29cd9fecab723dc9aa69a05151bbd85f0/testusersimtech}, doi = {10.1021/acs.jctc.1c00853}, interhash = {8eb27e841bbc9c87f7553410f92e8039}, intrahash = {9cd9fecab723dc9aa69a05151bbd85f0}, journal = {Journal of Chemical Theory and Computation}, keywords = {EXC2075 PN3 PN3-4 PN6 PN6A-1 unclear}, pages = {1-12}, timestamp = {2024-03-26T11:56:11.000+0100}, 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 }