Publications of Matthias Scheffler
All genres
Journal Article (591)
2024
Journal Article
S. Bi, C. Carbogno, and 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).
Journal Article
R. Miyazaki, , , L. Foppa and 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
Journal Article
M. Scheffler, T. Purcell, , and : Interpretable Machine Learning for Materials Design. , Journal of Materials Research 38 (20), 4477–4496 (2023).
Journal Article
L. Foppa, , , G. Koch, F. Girgsdies, P. Kube, S. Carey, M. Hävecker, O. Timpe, A. Tarasov, M. Scheffler, , R. Schlögl and 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).
Journal Article
F. Knoop, T. Purcell, M. Scheffler and C. Carbogno: Anharmonicity in Thermal Insulators: An Analysis from First Principles. Physical Review Letters 130 (23), 236301 (2023).
Journal Article
F. Knoop, M. Scheffler and C. Carbogno: Ab initio Green-Kubo simulations of heat transport in solids: Method and implementation. Physical Review B 107 (22), 224304 (2023).
Journal Article
M.F. Langer, F. Knoop, C. Carbogno, M. Scheffler and M. Rupp: Heat flux for semilocal machine-learning potentials. Physical Review B 108 (10), L100302 (2023).
Journal Article
T. Purcell, M. Scheffler and 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).
Journal Article
T. Purcell, M. Scheffler, L.M. Ghiringhelli and C. Carbogno: Accelerating materials-space exploration for thermal insulators by mapping materials properties via artificial intelligence. npj Computational Materials 9, 112 (2023).
2022
Journal Article
M. Scheffler, , and : 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).
Journal Article
M. Scheffler, , and : 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).
Journal Article
C. Carbogno, , B. Bieniek, C. Draxl, L.M. Ghiringhelli, , , , , , , and M. Scheffler: Numerical quality control for DFT-based materials databases. npj Computational Materials 8, 69 (2022).
Journal Article
L. Foppa, T. Purcell, , M. Scheffler and L.M. Ghiringhelli: Hierarchical Symbolic Regression for Identifying Key Physical Parameters Correlated with Bulk Properties of Perovskites. Physical Review Letters 129 (5), 0545301 (2022).
Journal Article
L. Foppa, C.A. Sutton, L.M. Ghiringhelli, , , , and M. Scheffler: Learning Design Rules for Selective Oxidation Catalysts from High-Throughput Experimentation and Artificial Intelligence. ACS Catalysis 12 (4), 2233–2232 (2022).
Journal Article
M. Scheffler, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , and L.M. Ghiringhelli: Roadmap on Machine learning in electronic structure. , , , , , , Electronic Structure 4 (2), 023004 (2022).
Journal Article
A. Mazheika, Y. Wang, , , , L.M. Ghiringhelli, and M. Scheffler: Artificial-intelligence-driven discovery of catalyst genes with application to CO2 activation on semiconductor oxides. Nature Communications 13, 419 (2022).
Journal Article
E. Moerman, , , and 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).
Journal Article
T. Purcell, M. Scheffler, C. Carbogno and 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).
Journal Article
B. Regler, M. Scheffler and L.M. Ghiringhelli: TCMI: a non-parametric mutual-dependence estimator for multivariate continuous distributions. Data Mining and Knowledge Discovery (5), 1815–1864 (2022).
Journal Article
L.M. Ghiringhelli and M. Scheffler: The NOMAD Artificial-Intelligence Toolkit: Turning materials-science data into knowledge and understanding. , , npj Computational Materials 8, 250 (2022).