Jonathan Schmidt

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	Toate	Din 2020
Referințe bibliografice	3379	3302
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i10-index	18	18

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Miguel Alexandre Lopes MarquesRC-FEMS, ICAMS, and Faculty of Mechanical Engineering, Ruhr University BochumAdresă de e-mail confirmată pe rub.de
Silvana BottiRC-FEMS and Faculty of Physics, Ruhr University Bochum, GermanyAdresă de e-mail confirmată pe rub.de
Pedro BorlidoUniversity of CoimbraAdresă de e-mail confirmată pe uc.pt
Tiago CerqueiraUniversity of CoimbraAdresă de e-mail confirmată pe uc.pt
Carlos L. Benavides-RiverosMarie Skłodowska-Curie fellow, University of TrentoAdresă de e-mail confirmată pe unitn.it
Liming ChenProfesseur des Universités, Ecole Centrale de LyonAdresă de e-mail confirmată pe ec-lyon.fr
Jingming ShiJiangsu Normal UniversityAdresă de e-mail confirmată pe jsnu.edu.cn
Fabien TranAdresă de e-mail confirmată pe tuwien.ac.at
Ahmad W. HuranPhD student, Institut für Physik MLUAdresă de e-mail confirmată pe physik.uni-halle.de
Pedro J.M.A CarriçoAdresă de e-mail confirmată pe ua.pt
Claudio VerdozziLund UniversityAdresă de e-mail confirmată pe teorfys.lu.se
Aldo Humberto RomeroWest Virginia UniversityAdresă de e-mail confirmată pe mail.wvu.edu
Jack WetherellR&D Imagineer with Disney Research at Walt Disney ImagineeringAdresă de e-mail confirmată pe polytechnique.edu
Matthew J. P. HodgsonLecturer at the University of YorkAdresă de e-mail confirmată pe york.ac.uk
Matteo FadelETH ZürichAdresă de e-mail confirmată pe phys.ethz.ch
Antonio SannaMax Plank Institute of microstructure physicsAdresă de e-mail confirmată pe mpi-halle.mpg.de
Ludger WirtzProfessor of Physics, University of LuxembourgAdresă de e-mail confirmată pe uni.lu
Nicola SpaldinProfessor for Materials Theory, ETH ZurichAdresă de e-mail confirmată pe mat.ethz.ch

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Jonathan Schmidt

ETH Zurich

Adresă de e-mail confirmată pe mat.ethz.ch

Machine Learning Materials Science Condensed Matter Density Functional Theory


Titlu Sortați după descrierea bibliografică Sortați după an Sortați după titlu	Citat de Citat de	Anul
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	2030	2019
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	350	2017
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	274	2020
Roadmap on Machine Learning in Electronic Structure H Kulik, T Hammerschmidt, J Schmidt, S Botti, MAL Marques, M Boley, ... Electronic Structure, 2022	153	2022
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	112	2021
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	96	2019
Machine-learning-assisted determination of the global zero-temperature phase diagram of materials. J Schmidt, N Hoffmann, HC Wang, P Borlido, PJMA Carriço, ... Advanced Materials, e2210788-e2210788, 2023	58*	2023
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), 2018	50	2018
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	34	2021
Reduced density matrix functional theory for superconductors J Schmidt, CL Benavides-Riveros, MAL Marques Physical Review B 99 (22), 224502, 2019	32	2019
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	29	2022
High-throughput study of oxynitride, oxyfluoride and nitrofluoride perovskites H Wang, J Schmidt, S Botti, MAL Marques Journal of Materials Chemistry A, 2021	28	2021
Superconductivity in antiperovskites N Hoffmann, T Cerqueira, J Schmidt, M Marques npj Computational Materials 8 (1), 2022	24	2022
Improving machine-learning models in materials science through large datasets J Schmidt, TFT Cerqueira, AH Romero, A Loew, F Jäger, HC Wang, ... Materials Today Physics, 101560, 2024	18	2024
Machine learning universal bosonic functionals J Schmidt, M Fadel, CL Benavides-Riveros Physical Review Research 3 (3), L032063, 2021	18	2021
Transfer learning on large datasets for the accurate prediction of material properties N Hoffmann, J Schmidt, S Botti, MAL Marques Digital Discovery, 2023	14	2023
Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange M Evans, J Bergsma, A Merkys, C Andersen, OB Andersson, D Beltrán, ... Digital Discovery, 2024	12	2024
Machine-learning correction to density-functional crystal structure optimization R Hussein, J Schmidt, T Barros, MAL Marques, S Botti MRS Bulletin 47 (8), 765-771, 2022	12	2022
Searching for ductile superconducting Heusler X2YZ compounds N Hoffmann, TFT Cerqueira, P Borlido, A Sanna, J Schmidt, MAL Marques npJ computational materials 9 (138), 2023	8	2023
Symmetry-based computational search for novel binary and ternary 2D materials HC Wang, J Schmidt, MAL Marques, L Wirtz, AH Romero 2D Materials 10 (3), 035007, 2023	7	2023

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