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Matthias Scheffler

Affiliations: 
2009- Theory  Fritz-Haber-Institut der Max-Planck-Gesellschaft, Berlin, Berlin, Germany 
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"Matthias Scheffler"
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Parents

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Kyozaburo Kambe grad student 1978 TU Berlin
Sokrates T. Pantelides post-doc IBM Thomas J. Watson Research Center

Children

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Jie Yu grad student (Chemistry Tree)
Nikolaj Moll grad student 1993-1998 Fritz-Haber-Institut der Max-Planck-Gesellschaft, Berlin
Jörg Behler grad student 2000-2004 Fritz Haber Institute (Chemistry Tree)
Biswajit Santra grad student 2006-2010 Fritz-Haber-Institut der Max-Planck-Gesellschaft, Berlin
Qimin Yan grad student 2007-2012 Fritz Haber Institute of the Max Planck Society
Karsten Reuter post-doc Fritz Haber Institute of the Max Planck Society
Vincenzo Fiorentini post-doc 1992-1993
Shobhana Narasimhan post-doc 1994-1996 Fritz Haber Institute of the Max Planck Society
Suljo Linic post-doc 2003-2004 Fritz-Haber-Institut der Max-Planck-Gesellschaft, Berlin (Chemistry Tree)
Alexandre Tkatchenko post-doc 2007-2010 Fritz Haber Institut der Max-Planck-Gesellschaft (Chemistry Tree)
Aloysius Soon post-doc 2009-2010 Fritz-Haber-Institut der Max-Planck-Gesellschaft, Berlin
Yong Xu post-doc 2010-2013
Saswata Bhattacharya post-doc 2011-2015 Fritz Haber Institute of the Max Planck Society
Amrita Bhattacharya post-doc 2013-2016 Fritz Haber Institute of the Max Planck Society
Bryan Richard Goldsmith post-doc 2015-2017 Fritz Haber Institute of the Max Planck Society (Neurotree)
Debalaya Sarker post-doc 2017-2019 Fritz Haber Institute of the Max Planck Society
Christopher A. Sutton post-doc 2015-2020 Fritz Haber Institut der Max-Planck-Gesellschaft (Chemistry Tree)
Steven C. Erwin research scientist 1998-1999
Volker Blum research scientist 2004-2013 Fritz Haber Institut der Max-Planck-Gesellschaft (Chemistry Tree)
Sergey V. Levchenko research scientist 2008-2018 Fritz Haber Institute of the Max Planck Society (Chemistry Tree)

Collaborators

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Michiel Jan van Setten collaborator 2010-2018 (Chemistry Tree)
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Publications

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Kokott S, Merz F, Yao Y, et al. (2024) Efficient all-electron hybrid density functionals for atomistic simulations beyond 10 000 atoms. The Journal of Chemical Physics. 161
Ghiringhelli LM, Baldauf C, Bereau T, et al. (2023) Shared metadata for data-centric materials science. Scientific Data. 10: 626
Teale AM, Helgaker T, Savin A, et al. (2022) DFT exchange: sharing perspectives on the workhorse of quantum chemistry and materials science. Physical Chemistry Chemical Physics : Pccp
Foppa L, Purcell TAR, Levchenko SV, et al. (2022) Hierarchical Symbolic Regression for Identifying Key Physical Parameters Correlated with Bulk Properties of Perovskites. Physical Review Letters. 129: 055301
Foppa L, Sutton C, Ghiringhelli LM, et al. (2022) Learning Design Rules for Selective Oxidation Catalysts from High-Throughput Experimentation and Artificial Intelligence. Acs Catalysis. 12: 2223-2232
Mazheika A, Wang YG, Valero R, et al. (2022) Artificial-intelligence-driven discovery of catalyst genes with application to CO activation on semiconductor oxides. Nature Communications. 13: 419
Andersen CW, Armiento R, Blokhin E, et al. (2021) OPTIMADE, an API for exchanging materials data. Scientific Data. 8: 217
Sutton C, Boley M, Ghiringhelli LM, et al. (2020) Identifying domains of applicability of machine learning models for materials science. Nature Communications. 11: 4428
Knoop F, Purcell TAR, Scheffler M, et al. (2020) Anharmonicity Measure for Materials Physical Review Materials. 4
Zacharias M, Scheffler M, Carbogno C. (2020) Fully anharmonic nonperturbative theory of vibronically renormalized electronic band structures Physical Review B. 102: 45126
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