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Jonathan Schmidt
Jonathan Schmidt
Verified email at student.uni-halle.de
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Cited by
Year
Recent advances and applications of machine learning in solid-state materials science
J Schmidt, MRG Marques, S Botti, MAL Marques
npj Computational Materials 5 (1), 1-36, 2019
9602019
Predicting the thermodynamic stability of solids combining density functional theory and machine learning
J Schmidt, J Shi, P Borlido, L Chen, S Botti, MAL Marques
Chemistry of Materials 29 (12), 5090-5103, 2017
2082017
Exchange-correlation functionals for band gaps of solids: benchmark, reparametrization and machine learning
P Borlido, J Schmidt, AW Huran, F Tran, MAL Marques, S Botti
npj Computational Materials 6 (1), 1-17, 2020
992020
Machine Learning the Physical Nonlocal Exchange–Correlation Functional of Density-Functional Theory
J Schmidt, CL Benavides-Riveros, MAL Marques
Journal of Physical Chemistry Letters, 2019
512019
Predicting the stability of ternary intermetallics with density functional theory and machine learning
J Schmidt, L Chen, S Botti, MAL Marques
The Journal of chemical physics 148 (24), 241728, 2018
262018
Reduced density matrix functional theory for superconductors
J Schmidt, CL Benavides-Riveros, MAL Marques
Physical Review B 99 (22), 224502, 2019
162019
High-throughput study of oxynitride, oxyfluoride and nitrofluoride perovskites
H Wang, J Schmidt, S Botti, MAL Marques
Journal of Materials Chemistry A, 2021
132021
Crystal graph attention networks for the prediction of stable materials
J Schmidt, L Pettersson, C Verdozzi, S Botti, MAL Marques
Science Advances 7 (49), eabi7948, 2021
92021
Roadmap on Machine Learning in Electronic Structure
H Kulik, T Hammerschmidt, J Schmidt, S Botti, MAL Marques, M Boley, ...
Electronic Structure, 2022
82022
Machine learning the derivative discontinuity of density-functional theory
J Gedeon, J Schmidt, MJP Hodgson, J Wetherell, CL Benavides-Riveros, ...
Machine Learning: Science and Technology 3 (1), 015011, 2021
72021
Machine learning universal bosonic functionals
J Schmidt, M Fadel, CL Benavides-Riveros
Physical Review Research 3 (3), L032063, 2021
52021
Representability problem of density functional theory for superconductors
J Schmidt, CL Benavides-Riveros, MAL Marques
Physical Review B 99 (2), 024502, 2019
52019
A dataset of 175k stable and metastable materials calculated with the PBEsol and SCAN functionals
J Schmidt, HC Wang, TFT Cerqueira, MAL Marques
Scientific Data 9 (64), 2022
32022
Machine-learning correction to density-functional crystal structure optimization
R Hussein, J Schmidt, T Barros, MAL Marques, S Botti
MRS Bulletin, 1-7, 2022
12022
Machine Learning guided high-throughput search of non-oxide garnets
J Schmidt, H Wang, G Schmidt, M Marques
arXiv:2208.13742, 2022
2022
Computational screening of materials with extreme gap deformation potentials
P Borlido, J Schmidt, HC Wang, S Botti, MAL Marques
npj Computational Materials 8 (1), 1-10, 2022
2022
Superconductivity in antiperovskites
N Hoffmann, T Cerqueira, J Schmidt, M Marques
npj Computational Materials 8 (1), 2022
2022
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Articles 1–17