Publikationen von Matthias Scheffler

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).

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).

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).

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).

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).

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).

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).

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).

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).

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

Zhou, Y., C. Zhu, M. Scheffler und L.M. Ghiringhelli: 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).

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

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

Kokott, S., I. Hurtado, C. Vorwerk, C. Draxl, V. Blum und M. Scheffler: GIMS: Graphical Interface for Materials Simulations. The Journal of Open Source Software 6 (57), 2767 (2021).

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

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

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

Janke, S.M., M. Rossi, S.V. Levchenko, S. Kokott, M. Scheffler und V. Blum: Pentacene and Tetracene Molecules and Films on H/Si(111): Level Alignment from Hybrid Density Functional Theory. Electronic Structure 2 (3), 035002 (2020).

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

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