Publications of Matthias Scheffler

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.; 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), pp. 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)

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)

Kulik, H. J.; Hammerschmidt, T.; Schmidt, J.; Botti, S.; Marques, M. A. L.; Boley, M.; Scheffler, M.; Todorović, M.; Rinke, P.; Oses, C. et al.; Smolyanyuk, A.; Curtarolo, S.; Tkatchenko, A.; Bartók, A. P.; Manzhos, S.; Ihara, M.; Carrington, T.; Behler, J.; Isayev, O.; Veit, M.; Grisafi, A.; Nigam, J.; Ceriotti, M.; Schütt, K. T.; Westermayr, J.; Gastegger, M.; Maurer, R. J.; Kalita, B.; Burke, K.; Nagai, R.; Akashi, R.; Sugino, O.; Hermann, J.; Noé, F.; Pilati, S.; Draxl, C.; Kuban, M.; Rigamonti, S.; Scheidgen, M.; Esters, M.; Hicks, D.; Toher, C.; Balachandran, P. V.; Tamblyn, I.; Whitelam, S.; Bellinger, C.; Ghiringhelli, L. M.: Roadmap on Machine learning in electronic structure. Electronic Structure 4 (2), 023004 (2022)

Foppa, L.; Purcell, T.; Levchenko, S. V.; Scheffler, M.; Ghiringhelli, L. M.: Hierarchical Symbolic Regression for Identifying Key Physical Parameters Correlated with Bulk Properties of Perovskites. Physical Review Letters 129 (5), 0545301 (2022)

Moerman, E.; Hummel, F.; Grüneis, A.; Irmler, A.; Scheffler, M.: 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)

Zhou, Y.; Zhu, C.; Scheffler, M.; Ghiringhelli, L. M.: Ab Initio Approach for Thermodynamic Surface Phases with Full Consideration of Anharmonic Effects: The Example of Hydrogen at Si(100). Physical Review Letters 128 (24), 246101 (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)

Carbogno, C.; Thygesen, K. S.; Bieniek, B.; Draxl, C.; Ghiringhelli, L. M.; Gulans, A.; Hofmann, O. T.; Jacobsen, K. W.; Lubeck, S.; Mortensen, J. J. et al.; Strange, M.; Wruss, E.; Scheffler, M.: Numerical quality control for DFT-based materials databases. npj Computational Materials 8, 69 (2022)

Purcell, T.; Scheffler, M.; Carbogno, C.; Ghiringhelli, L. M.: SISSO++: A C++ Implementation of the Sure-Independence Screening and Sparisifying Operator Approach. The Journal of Open Source Software 7 (71), 3960 (2022)

Foppa, L.; Sutton, C. A.; Ghiringhelli, L. M.; De, S.; Löser, P.; Schunk, S. A.; Schäfer, A.; Scheffler, M.: Learning Design Rules for Selective Oxidation Catalysts from High-Throughput Experimentation and Artificial Intelligence. ACS Catalysis 12 (4), pp. 2233 - 2232 (2022)

Mazheika, A.; Wang, Y.; Valero, R.; Viñes, F.; Illas, F.; Ghiringhelli, L. M.; Levchenko, S. V.; Scheffler, M.: Artificial-intelligence-driven discovery of catalyst genes with application to CO₂ activation on semiconductor oxides. Nature Communications 13, 419 (2022)

Foppa, L.; Ghiringhelli, L. M.; Girgsdies, F.; Hashagen, M.; Kube, P.; Hävecker, M.; Carey, S.; Tarasov, A.; Kraus, P.; Rosowski, F. et al.; Schlögl, R.; Trunschke, A.; Scheffler, M.: Materials genes of heterogeneous catalysis from clean experiments and artificial intelligence. MRS Bulletin 46 (11), pp. 1016 - 1026 (2021)

Schmidt-Mende, L.; Dyakonov, V.; Olthof, S.; Ünlü, F.; Lê, K. M. T.; Mathur, S.; Karabanov, A. D.; Lupascu, D. C.; Herz, L. M.; Hinderhofer, A. et al.; Schreiber, F.; Chernikov, A.; Egger, D. A.; Shargaieva, O.; Cocchi, C.; Unger, E.; Saliba, M.; Byranvand, M. M.; Kroll, M.; Nehm, F.; Leo, K.; Redinger, A.; Höcker, J.; Kirchartz, T.; Warby, J.; Gutierrez-Partida, E.; Neher, D.; Stolterfoht, M.; Würfel, U.; Unmüssig, M.; Herterich, J.; Baretzky, C.; Mohanraj, J.; Thelakkat, M.; Maheu, C.; Jaegermann, W.; Mayer, T.; Rieger, J.; Fauster, T.; Niesner, D.; Yang, F.; Albrecht, S.; Riedl, T.; Fakharuddin, A.; Vasilopoulou, M.; Vaynzof, Y.; Moia, D.; Maier, J.; Franckevičius, M.; Gulbinas, V.; Kerner, R. A.; Zhao, L.; Rand, B. P.; Glück, N.; Bein, T.; Matteocci, F.; Castriotta, L. A.; Carlo, A. D.; Scheffler, M.; Draxl, C.: Roadmap on organic–inorganic hybrid perovskite semiconductors and devices. APL Materials 9 (10), 109202 (2021)

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)

Ren, X.; Merz, F.; Jiang, H.; Yao, Y.; Rampp, M.; Lederer, H.; Blum, V.; Scheffler, M.: All-electron periodic G₀W₀ implementation with numerical atomic orbital basis functions: Algorithm and benchmarks. Physical Review Materials 5 (1), 013807 (2021)