Publications of Matthias Scheffler

Foppa, L., Rüther Frederik, M. Geske, G. Koch, F. Girgsdies, P. Kube, S. Carey, M. Hävecker, O. Timpe, A. Tarasov, M. Scheffler, F. Rosowski, 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).

Knoop, F., 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).

Purcell, T., 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).

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

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 and 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 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).

Foppa, L., C.A. Sutton, L.M. Ghiringhelli, S. De, P. Löser, S.A. Schunk, A. Schäfer and 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 and 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 and 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 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).

Purcell, T., 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).

Regler, B., 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).

Sbailò, L., Á. Fekete, 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).

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 and C. Draxl: FAIR data enabling new horizons for materials research. Nature 604 (7907), 635–642 (2022).

Zhou, Y., C. Zhu, M. Scheffler and 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 and 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 and 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 and 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 and M. Scheffler: All-electron periodic G₀W₀ implementation with numerical atomic orbital basis functions: Algorithm and benchmarks. Physical Review Materials 5 (1), 013807 (2021).