Publikationen von Matthias Scheffler

Moerman, E.; Gallo, A.; Irmler, A.; Schäfer, T.; Hummel, F.; Grüneis, A.; Scheffler, M.: Finite-Size Effects in Periodic EOM-CCSD for Ionization Energies and Electron Affinities: Convergence Rate and Extrapolation to the Thermodynamic Limit. Journal of Chemical Theory and Computation 21 (4), S. 1865 - 1878 (2025)

Bellini, G.; Koch, G.; Girgsdies, F.; Dong, J.; Carey, S.; Timpe, O.; Auffermann, G.; Scheffler, M.; Schlögl, R.; Foppa, L. et al.; Trunschke, A.: CO Oxidation Catalyzed by Perovskites: The Role of Crystallographic Distortions Highlighted by Systematic Experiments and Artificial Intelligence. Angewandte Chemie International Edition 64 (6), e202417812 (2025)

Speckhard, D.; Carbogno, C.; Ghiringhelli, L. M.; Lubeck, S.; Scheffler, M.; Draxl, C.: Extrapolation to the complete basis-set limit in density-functional theory using statistical learning. Physical Review Materials 9 (1), 013801 (2025)

Miyazaki, R.; Faraji, S.; Levchenko, S. V.; Foppa, L.; Scheffler, M.: Vibrational frequencies utilized for the assessment of exchange-correlation functionals in the description of metal-adsorbate systems: C₂H₂ and C₂H₄ on transition-metal surfaces. Catalysis Science & Technology 14 (23), S. 6924 - 6933 (2024)

Quan, J.; Carbogno, C.; Scheffler, M.: Carrier Mobility of Strongly Anharmonic Materials from First Principles. Physical Review B 110 (23), 235202 (2024)

Bauer, S.; Benner, P.; Bereau, T.; Blum, V.; Boley, M.; Carbogno, C.; Catlow, C. R. A.; Dehm, G.; Eibl, S.; Ernstorfer, R. et al.; Fekete, A.; Foppa, L.; Fratzl, P.; Freysoldt, C.; Gault, B.; Ghiringhelli, L. M.; Giri, S. K.; Gladyshev, A.; Goyal, P.; Hattrick-Simpers, J.; Kabalan, L.; Karpov, P.; Khorrami, M. S.; Koch, C.; Kokott, S.; Kosch, T.; Kowalec, I.; Kremer, K.; Leitherer, A.; Li, Y.; Liebscher, C. H.; Logsdail, A. J.; Lu, Z.; Luong, F.; Marek, A.; Merz, F.; Mianroodi, J. R.; Neugebauer, J.; Pei, Z.; Purcell, T.; Raabe, D.; Rampp, M.; Rossi, M.; Rost, J.-M.; Saal, J. E.; Saalmann, U.; Sasidhar, K. N.; Saxena, A.; Sbailo, L.; Scheidgen, M.; Schloz, M.; Schmidt, D. F.; Teshuva, S.; Trunschke, A.; Wei, Y.; Weikum, G.; Xian, R. P.; Yao, Y.; Yin, J.; Zhao, M.; Scheffler, M.: Roadmap on data-centric materials science. Modelling and Simulation in Materials Science and Engineering 32 (6), 063301 (2024)

Kokott, S.; Merz, F.; Yao, Y.; Carbogno, C.; Rossi, M.; Havu, V.; Rampp, M.; Scheffler, M.; Blum, V.: Efficient all-electron hybrid density functionals for atomistic simulations beyond 10 000 atoms. The Journal of Chemical Physics 161 (2), 024112 (2024)

Miyazaki, R.; Belthle, K. S.; Tüysüz, H.; Foppa, L.; Scheffler, M.: 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), S. 5433 - 5444 (2024)

Bi, S.; Carbogno, C.; Zhang, I. Y.; Scheffler, M.: 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)

Dean, J.; Scheffler, M.; Purcell, T.; Barabash, S. V.; Bhowmik, R.; Bazhirov, T.: Interpretable Machine Learning for Materials Design. Journal of Materials Research 38 (20), S. 4477 - 4496 (2023)

Purcell, T.; Scheffler, M.; Ghiringhelli, L. M.: Recent advances in the SISSO method and their implementation in the SISSO++ Code. The Journal of Chemical Physics 159 (11), 114110 (2023)

Gavini, V.; Baroni, S.; Blum, V.; Bowler, D. R.; Buccheri, A.; Chelikowsky, J. R.; Das, S.; Dawson, W.; Delugas, P.; Dogan, M. et al.; Draxl, C.; Galli, G.; Genovese, L.; Giannozzi, P.; Giantomassi, M.; Gonze, X.; Govoni, M.; Gygi, F.; Gulans, A.; Herbert, J. M.; Kokott, S.; Kühne, T. D.; Liou, K.-H.; Miyazaki, T.; Motamarri, P.; Nakata, A.; Pask, J. E.; Plessl, C.; Ratcliff, L. E.; Richard, R. M.; Rossi, M.; Schade, R.; Scheffler, M.; Schütt, O.; Suryanarayana, P.; Torrent, M.; Truflandier, L.; Windus, T. L.; Xu, Q.; Yu, V. W. -.; Perez, D.: Roadmap on electronic structure codes in the exascale era. Modelling and Simulation in Materials Science and Engineering 31 (6), 063301 (2023)

Langer, M. F.; Knoop, F.; Carbogno, C.; Scheffler, M.; Rupp, M.: Heat flux for semilocal machine-learning potentials. Physical Review B 108 (10), L100302 (2023)

Purcell, T.; Scheffler, M.; Ghiringhelli, L. M.; Carbogno, C.: Accelerating materials-space exploration for thermal insulators by mapping materials properties via artificial intelligence. npj Computational Materials 9, 112 (2023)

Knoop, F.; Purcell, T.; Scheffler, M.; Carbogno, C.: Anharmonicity in Thermal Insulators: An Analysis from First Principles. Physical Review Letters 130 (23), 236301 (2023)

Knoop, F.; Scheffler, M.; Carbogno, C.: Ab initio Green-Kubo simulations of heat transport in solids: Method and implementation. Physical Review B 107 (22), 224304 (2023)

Foppa, L.; Rüther, F.; Geske, M.; Koch, G.; Girgsdies, F.; Kube, P.; Carey, S.; Hävecker, M.; Timpe, O.; Tarasov, A. et al.; Scheffler, M.; Rosowski, F.; Schlögl, R.; Trunschke, A.: Data-Centric Heterogeneous Catalysis: Identifying Rules and Materials Genes of Alkane Selective Oxidation. Journal of the American Chemical Society 145 (6), S. 3427 - 3442 (2023)

Bowker, M.; DeBeer, S.; Dummer, N. F.; Hutchings, G. J.; Scheffler, M.; Schüth, F.; Taylor, S. H.; Tüysüz, H.: 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)

Bowker, M.; DeBeer, S.; Dummer, N. F.; Hutchings, G. J.; Scheffler, M.; Schüth, F.; Taylor, S. H.; Tüysüz, H.: 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)

Sbailò, L.; Fekete, Á.; Ghiringhelli, L. M.; Scheffler, M.: The NOMAD Artificial-Intelligence Toolkit: Turning materials-science data into knowledge and understanding. npj Computational Materials 8, 250 (2022)