Publications 2022 of the
Emeritus Group Prof. Scheffler

2022 | 2021 | 2020 | 2019

Journal Article (19)

2022
Journal Article
Aggoune, W., A. Eljarrat, D. Nabok, K. Irmscher, M. Zupancic, Z. Galazka, M. Albrecht, C. Koch and C. Draxl: A consistent picture of excitations in cubic BaSnO3 revealed by combining theory and experiment. Communications Materials 3, 12 (2022).
Journal Article
Boeri, L., R.G. Hennig, P.J. Hirschfeld, G. Profeta, A. Sanna, E. Zurek, W.E. Pickett, M. Amsler, R. Dias, M. Eremets, C. Heil, R. Hemley, H. Liu, Y. Ma, C. Pierleoni, A. Kolmogorov, N. Rybin, D. Novoselov, V.I. Anisimov, A.R. Oganov, C.J. Pickard, T. Bi, R. Arita, I. Errea, C. Pellegrini, R. Requist, E.K.U. Gross, E.R. Margine, S.R. Xie, Y. Quan, A. Hire, L. Fanfarillo, G.R. Stewart, J.J. Hamlin, V. Stanev, R.S. Gonnelli, E. Piatti, D. Romanin, D. Daghero and R. Valenti: The 2021 Room-Temperature Superconductivity Roadmap. Journal of Physics: Condensed Matter 34 (18), 183002 (2022).
Journal Article
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).
Journal Article
Foppa, L. and L.M. Ghiringhelli: Identifying Outstanding Transition‑Metal‑Alloy Heterogeneous Catalysts for the Oxygen Reduction and Evolution Reactions via Subgroup Discovery. Topics in Catalysis 65 (1-4), 196–206 (2022).
Journal Article
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).
Journal Article
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).
Journal Article
Kühbach, M.T., A.J. London, J. Wang, D.K. Schreiber, F. Mendez Martin, I. Ghamarian, H. Bilal and A.V. Ceguerra: Community-Driven Methods for Open and Reproducible Software Tools for Analyzing Datasets from Atom Probe Microscopy. Microscopy and Microanalysis 28 (4), 1038–1053 (2022).
Journal Article
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).
Journal Article
Langer, M.F., A. Goeßmann and M. Rupp: Representations of molecules and materials for interpolation of quantum-mechanical simulations via machine learning. npj Computational Materials 8, 41 (2022).
Journal Article
Liu, X., X. Wang, S. Gao, V. Chang, R. Tom, M. Yu, L.M. Ghiringhelli and N. Marom: Finding predictive models for singlet fission by machine learning. npj Computational Materials 8, 70 (2022).
Journal Article
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).
Journal Article
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).
Journal Article
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).
Journal Article
Qi, R., B. Zhu, Z.-K. Han and Y. Gao: High-Throughput Screening of Stable Single-Atom Catalysts in CO2 Reduction Reactions. ACS Catalysis 12 (14), 8269–8278 (2022).
Journal Article
Regler, B., M. Scheffler and L.M. Ghiringhelli: TCMI: a non-parametric mutual-dependence estimator for multivariate continuous distributions. Data Mining and Knowledge Discovery, in press.
Journal Article
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).
Journal Article
Tantardini, C., S. Kokott, X. Gonze, S.V. Levchenko and W.A. Saidi: “Self-trapping” in solar cell hybrid inorganic-organic perovskite absorbers. Applied Materials Today 26, 101380 (2022).
Journal Article
Zhou, X., Y. Wei, M.T. Kühbach, H. Zhao, F. Vogel, R.D. Kamachali, G.B. Thompson, D. Raabe and B. Gault: Revealing in-plane grain boundary composition features through machine learning from atom probe tomography data. Acta Materialia 226, 117633 (2022).
Journal Article
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).

Book (1)

2022
Book
Elsässer, T., M. Grötschel, M. Scheffler, J.H. Ullrich and F.von Blanckenburg: Open Research Data in Naturwissenschaften und Mathematik: Empfehlungen der mathematisch-naturwissenschaftlichen Klasse der BBAW. (Denkanstöße aus der Akademie: Eine Schriftenreihe der Berlin-Brandenburgischen Akademie der Wissenschaften, Vol. 10). Berlin-Brandenburgischen Akademie der Wissenschaften, Berlin (2022).

Thesis - PhD (6)

2022
Thesis - PhD
Ahmetcik, E.: Artificial intelligence for crystal structure prediction. Technische Universität Berlin
Thesis - PhD
Knoop, F.: Heat transport in strongly anharmonic solids from first principles. Humboldt-Universität zu Berlin
Thesis - PhD
Leitherer, A.: Robust recognition and exploratory analysis of crystal structures using machine learning. Humboldt Universität Berlin
Thesis - PhD
Lenz, M.-O.: Towards efficient novel materials discovery: Acceleration of high-throughput calculations and semantic management of big data using ontologies. Humboldt-Universität Berlin
Thesis - PhD
Regler, B.: Systematic identification of relevant features for the statistical modeling of materials properties of crystalline solids. Freie Universität Berlin
Thesis - PhD
Yuan, Z.: Electrical conductivity from first principles. Humboldt-Universität zu Berlin

Thesis - Master (2)

2022
Thesis - Master
Zhao, B.: Identifying descriptors for the in-silico, high-throughput discovery of the thermal insulators for thermoelectric applications. Technische Universität Darmstadt
Thesis - Master
Zhu, X.: Ab Initio green-kubo calculations for strongly anharmonic solids: a comparative benchmark of lattice thermal conductivities. Technische Universität Darmstadt
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