Publikationen von Matthias Scheffler

Zeitschriftenartikel (591)

2024
Zeitschriftenartikel
Bi, S., C. Carbogno, I.Y. Zhang und M. Scheffler: Self-interaction corrected SCAN functional for molecules and solids in the numeric atom-center orbital framework. The Journal of Chemical Physics 160 (3), 034106 (2024).
Zeitschriftenartikel
Miyazaki, R., K.S. Belthle, H. Tüysüz, L. Foppa und M. Scheffler: Materials Genes of CO2 Hydrogenation on Supported Cobalt Catalysts: An Artificial Intelligence Approach Integrating Theoretical and Experimental Data. Journal of the American Chemical Society 146 (8), 5433–5444 (2024).
2023
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Dean, J., M. Scheffler, T. Purcell, S.V. Barabash, R. Bhowmik und T. Bazhirov: Interpretable Machine Learning for Materials Design. Journal of Materials Research 38 (20), 4477–4496 (2023).
Zeitschriftenartikel
Foppa, L., Rüther Frederik, M. Geske, G. Koch, F. Girgsdies, P. Kube, S. Carey, M. Hävecker, O. Timpe, A. Tarasov, M. Scheffler, F. Rosowski, R. Schlögl und A. Trunschke: Data-Centric Heterogeneous Catalysis: Identifying Rules and Materials Genes of Alkane Selective Oxidation. Journal of the American Chemical Society 145 (6), 3427–3442 (2023).
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Knoop, F., T. Purcell, M. Scheffler und C. Carbogno: Anharmonicity in Thermal Insulators: An Analysis from First Principles. Physical Review Letters 130 (23), 236301 (2023).
Zeitschriftenartikel
Knoop, F., M. Scheffler und C. Carbogno: Ab initio Green-Kubo simulations of heat transport in solids: Method and implementation. Physical Review B 107 (22), 224304 (2023).
Zeitschriftenartikel
Langer, M.F., F. Knoop, C. Carbogno, M. Scheffler und M. Rupp: Heat flux for semilocal machine-learning potentials. Physical Review B 108 (10), L100302 (2023).
Zeitschriftenartikel
Purcell, T., M. Scheffler und L.M. Ghiringhelli: Recent advances in the SISSO method and their implementation in the SISSO++ Code. The Journal of Chemical Physics 159 (11), 114110 (2023).
Zeitschriftenartikel
Purcell, T., M. Scheffler, L.M. Ghiringhelli und C. Carbogno: Accelerating materials-space exploration for thermal insulators by mapping materials properties via artificial intelligence. npj Computational Materials 9, 112 (2023).
2022
Zeitschriftenartikel
Bowker, M., S. DeBeer, N.F. Dummer, G.J. Hutchings, M. Scheffler, F. Schüth, S.H. Taylor und H. Tüysüz: Advancing Critical Chemical Processes for a Sustainable Future: Challenges for Industry and the Max Planck–Cardiff Centre on the Fundamentals of Heterogeneous Catalysis (FUNCAT). Angewandte Chemie 134 (50), e202209016 (2022).
Zeitschriftenartikel
Bowker, M., S. DeBeer, N.F. Dummer, G.J. Hutchings, M. Scheffler, F. Schüth, S.H. Taylor und H. Tüysüz: Advancing Critical Chemical Processes for a Sustainable Future: Challenges for Industry and the Max Planck–Cardiff Centre on the Fundamentals of Heterogeneous Catalysis (FUNCAT). Angewandte Chemie International Edition 61 (50), e202209016 (2022).
Zeitschriftenartikel
Carbogno, C., K.S. Thygesen, B. Bieniek, C. Draxl, L.M. Ghiringhelli, A. Gulans, O.T. Hofmann, K.W. Jacobsen, S. Lubeck, J.J. Mortensen, M. Strange, E. Wruss und M. Scheffler: Numerical quality control for DFT-based materials databases. npj Computational Materials 8, 69 (2022).
Zeitschriftenartikel
Foppa, L., T. Purcell, S.V. Levchenko, M. Scheffler und L.M. Ghiringhelli: Hierarchical Symbolic Regression for Identifying Key Physical Parameters Correlated with Bulk Properties of Perovskites. Physical Review Letters 129 (5), 0545301 (2022).
Zeitschriftenartikel
Foppa, L., C.A. Sutton, L.M. Ghiringhelli, S. De, P. Löser, S.A. Schunk, A. Schäfer und M. Scheffler: Learning Design Rules for Selective Oxidation Catalysts from High-Throughput Experimentation and Artificial Intelligence. ACS Catalysis 12 (4), 2233–2232 (2022).
Zeitschriftenartikel
Kulik, H.J., T. Hammerschmidt, J. Schmidt, S. Botti, M.A.L. Marques, M. Boley, M. Scheffler, M. Todorović, P. Rinke, C. Oses, A. Smolyanyuk, S. Curtarolo, A. Tkatchenko, A.P. Bartók, S. Manzhos, M. Ihara, T. Carrington, J. Behler, O. Isayev, M. Veit, A. Grisafi, J. Nigam, M. Ceriotti, K.T. Schütt, J. Westermayr, M. Gastegger, R.J. Maurer, B. Kalita, K. Burke, R. Nagai, R. Akashi, O. Sugino, J. Hermann, F. Noé, S. Pilati, C. Draxl, M. Kuban, S. Rigamonti, M. Scheidgen, M. Esters, D. Hicks, C. Toher, P.V. Balachandran, I. Tamblyn, S. Whitelam, C. Bellinger und L.M. Ghiringhelli: Roadmap on Machine learning in electronic structure. Electronic Structure 4 (2), 023004 (2022).
Zeitschriftenartikel
Mazheika, A., Y. Wang, R. Valero, F. Viñes, F. Illas, L.M. Ghiringhelli, S.V. Levchenko und M. Scheffler: Artificial-intelligence-driven discovery of catalyst genes with application to CO2 activation on semiconductor oxides. Nature Communications 13, 419 (2022).
Zeitschriftenartikel
Moerman, E., F. Hummel, A. Grüneis, A. Irmler und M. Scheffler: Interface to high-performance periodic coupled-cluster theory calculations with atom-centered, localized basis functions. The Journal of Open Source Software 7 (4), 4040 (2022).
Zeitschriftenartikel
Purcell, T., M. Scheffler, C. Carbogno und L.M. Ghiringhelli: SISSO++: A C++ Implementation of the Sure-Independence Screening and Sparisifying Operator Approach. The Journal of Open Source Software 7 (71), 3960 (2022).
Zeitschriftenartikel
Regler, B., M. Scheffler und L.M. Ghiringhelli: TCMI: a non-parametric mutual-dependence estimator for multivariate continuous distributions. Data Mining and Knowledge Discovery (5), 1815–1864 (2022).
Zeitschriftenartikel
Sbailò, L., Á. Fekete, L.M. Ghiringhelli und M. Scheffler: The NOMAD Artificial-Intelligence Toolkit: Turning materials-science data into knowledge and understanding. npj Computational Materials 8, 250 (2022).
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