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Nature Communications|January 10, 2017
Quantum-chemical insights from deep tensor neural networksKristof T Schütt, Farhad Arbabzadah, Stefan Chmiela, et al.The Journal of Chemical Physics|October 2, 2020
Molecular force fields with gradient-domain machine learning (GDML): Comparison and synergies with classical force fieldsHuziel E Sauceda, Michael Gastegger, Stefan Chmiela, et al.The Journal of Physical Chemistry Letters|December 13, 2021
Significance of the Chemical Environment of an Element in Nonadiabatic Molecular Dynamics: Feature Selection and Dimensionality Reduction with Machine LearningWei Bin How, Bipeng Wang, Weibin Chu, et al.Chemical Science|September 16, 2024
SpaiNN: equivariant message passing for excited-state nonadiabatic molecular dynamicsSascha Mausenberger, Carolin Müller, Alexandre Tkatchenko, et al.Physical Review Letters|March 10, 2012
New perspective on formation energies and energy levels of point defects in nonmetalsR Ramprasad, H Zhu, Patrick Rinke, et al.Clinical Hemorheology and Microcirculation|September 9, 2017
Microcirculation measurements: Barriers for use in clinical routineDietrich Henzler, Matthias Scheffler, Arne Westheider, et al.Physical Review Letters|July 13, 2004
First-principles study of ferromagnetism in epitaxial Si-Mn thin films on Si(001)Hua Wu, Mahbube Hortamani, Peter Kratzer, et al.Physical Review Letters|August 27, 2013
Thermodynamic equilibrium conditions of graphene films on SiCLydia Nemec, Volker Blum, Patrick Rinke, et al.The Journal of Physical Chemistry. A|January 11, 2014
Validation challenge of density-functional theory for peptides-example of Ac-Phe-Ala5-LysH(+)Mariana Rossi, Sucismita Chutia, Matthias Scheffler, et al.Faraday Discussions|March 30, 2012
Free gold clusters: beyond the static, monostructure descriptionElizabeth C Beret, Luca M Ghiringhelli, Matthias SchefflerPageof 37