Publications of Matthias Scheffler

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), pp. 5433 - 5444 (2024)

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

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)

Regler, B.; Scheffler, M.; Ghiringhelli, L. M.: TCMI: a non-parametric mutual-dependence estimator for multivariate continuous distributions. Data Mining and Knowledge Discovery (5), pp. 1815 - 1864 (2022)

Scheffler, M.; Aeschlimann, M.; Albrecht, M.; Bereau, T.; Bungartz, H.-J.; Felser, C.; Greiner, M.; Groß, A.; Koch, C. T.; Kremer, K. et al.; Nagel, W. E.; Scheidgen, M.; Wöll, C.; Draxl, C.: FAIR data enabling new horizons for materials research. Nature 604 (7907), pp. 635 - 642 (2022)

Andersen, C. W.; Armiento, R.; Blokhin, E.; Conduit, G. J.; Dwaraknath, S.; Evans, M. L.; Fekete, Á.; Gopakumar, A.; Gražulis, S.; Merkys, A. et al.; Mohamed, F. R.; Oses, C.; Pizzi, G.; Rignanese, G.-M.; Scheidgen, M.; Talirz, L.; Toher, C.; Winston, D.; Aversa, R.; Choudhary, K.; Colinet, P.; Curtarolo, S.; Di Stefano, D.; Draxl, C.; Er, S.; Esters, M.; Fornari, M.; Giantomassi, M.; Govoni, M.; Hautier, G.; Hegde, V.; Horton, M. K.; Huck, P.; Huhs, G.; Hummelshøj, J.; Kariryaa, A.; Kozinsky, B.; Kumbhar, S.; Liu, M.; Marzari, N.; Morris, A. J.; Mostofi, A. A.; Persson, K. A.; Petretto, G.; Purcell, T.; Ricci, F.; Rose, F.; Scheffler, M.; Speckhard, D.; Uhrin, M.; Vaitkus, A.; Villars, P.; Waroquiers, D.; Wolverton, C.; Wu, M.; Yang, X.: OPTIMADE, an API for exchanging materials data. Scientific Data 8, 217 (2021)

Cao, G.; Ouyang, R.; Ghiringhelli, L. M.; Scheffler, M.; Liu, H.; Carbogno, C.; Zhang, Z.: Artificial intelligence for high-throughput discovery of topological insulators: The example of alloyed tetradymites. Physical Review Materials 4 (3), 034204 (2020)

Knoop, F.; Purcell, T.; Scheffler, M.; Carbogno, C.: Anharmonicity measure for materials. Physical Review Materials 4 (8), 083809 (2020)

Knoop, F.; Purcell, T.; Scheffler, M.; Carbogno, C.: FHI-vibes: Ab Initio Vibrational Simulations. The Journal of Open Source Software 5 (56), 2671 (2020)

Sutton, C. A.; Boley, M.; Ghiringhelli, L. M.; Rupp, M.; Vreeken, J.; Scheffler, M.: Identifying domains of applicability of machine learning models for materials science. Nature Communications 11, 4428 (2020)

Zacharias, M.; Scheffler, M.; Carbogno, C.: Fully anharmonic nonperturbative theory of vibronically renormalized electronic band structures. Physical Review B 102 (4), 045126 (2020)

Bartel, C. J.; Sutton, C. A.; Goldsmith, B. R.; Ouyang, R.; Musgrave, C. B.; Ghiringhelli, L. M.; Scheffler, M.: New tolerance factor to predict the stability of perovskite oxides and halides. Science Advances 5 (2), eaav0693 (2019)

Draxl, C.; Scheffler, M.: The NOMAD Laboratory: From Data Sharing to Artificial Intelligence. JPhys Materials 2 (3), 036001 (2019)

Goldsmith, B.; Florian, J.; Liu, J.-X.; Grüne, P.; Lyon, J. T.; Rayner, D. M.; Fielicke, A.; Scheffler, M.; Ghiringhelli, L. M.: Two-to-three dimensional transition in neutral gold clusters: The crucial role of van der Waals interactions and temperature. Physical Review Materials 3 (1), 016002 (2019)

Lenz, M.-O.; Purcell, T.; Hicks, D.; Curtarolo, S.; Scheffler, M.; Carbogno, C.: Parametrically constrained geometry relaxations for high-throughput materials science. npj Computational Materials 5, 123 (2019)

Ouyang, R.; Ahmetcik, E.; Carbogno, C.; Scheffler, M.; Ghiringhelli, L. M.: Simultaneous learning of several materials properties from incomplete databases with multi-task SISSO. JPhys Materials 2 (2), 024002 (2019)

Draxl, C.; Scheffler, M.: NOMAD: The FAIR concept for big data-driven materials science. MRS Bulletin 43 (9), pp. 676 - 682 (2018)

Ouyang, R.; Curtarolo, S.; Ahmetcik, E.; Scheffler, M.; Ghiringhelli, L. M.: SISSO: a compressed-sensing method for identifying the best low-dimensional descriptor in an immensity of offered candidates. Physical Review Materials 2 (08), 083802 (2018)

Shang, H.; Raimbault, N.; Rinke, P.; Scheffler, M.; Rossi, M.; Carbogno, C.: All-electron, real-space perturbation theory for homogeneous electric fields: theory, implementation, and application within DFT. New Journal of Physics 20 (7), 073040 (2018)