Publications of Luca M. Ghiringhelli

Journal Article (57)

Journal Article
H.J. Kulik, 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
L. Foppa, 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
B. Regler, 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
Y. Zhou, 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).
Journal Article
C. Carbogno, 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
X. Liu, 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
T. Purcell, 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
L. Foppa, 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
L. Foppa 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
L. Foppa and L.M. Ghiringhelli: Correction to: Identifying Outstanding Transition-Metal-Alloy Heterogeneous Catalysts for the Oxygen Reduction and Evolution Reactions via Subgroup Discovery. Topics in Catalysis 65 (1-4), 207–207 (2022).
Journal Article
A. Mazheika, 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
L. Foppa, 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).
Journal Article
A. Leitherer, A. Ziletti and L.M. Ghiringhelli: Robust recognition and exploratory analysis of crystal structures via Bayesian deep learning. Nature Communications 12 (1), 6234 (2021).
Journal Article
L. Talirz, L.M. Ghiringhelli and B. Smit: Trends in Atomistic Simulation Software Usage [Articlev1.0]. Living Journal of Computational Molecular Science 3 (1), 1–12 (2021).
Journal Article
A. Dutta, J. Vreeken, L.M. Ghiringhelli and T. Bereau: Publisher's Note: "Data-driven equation for drug-membrane permeability across drugs and membranes" [J. J. chem. Phys. 154, 244114 (2021)]. The Journal of Chemical Physics 155 (3), 039901 (2021).
Journal Article
A. Dutta, J. Vreeken, L.M. Ghiringhelli and T. Bereau: Data-driven equation for drug-membrane permeability across drugs and membranes. The Journal of Chemical Physics 154 (24), 244114 (2021).
Journal Article
C. Wouters, C.A. Sutton, L.M. Ghiringhelli, T. Markut, R. Schewski, A. Hassa, H. Von Wenckstern, M. Grundmann, M. Scheffler and M. Albrecht: Investigating the ranges of (meta)stable phase formation in (InxGa1−x)2O3: Impact of the cation coordination. Physical Review Materials 4 (12), 125001 (2020).
Journal Article
A. Trunschke, G. Bellini, M. Boniface, S. Carey, J. Dong, E. Erdem, L. Foppa, W. Frandsen, M. Geske, L.M. Ghiringhelli, F. Girgsdies, R. Hanna, M. Hashagen, M. Hävecker, G. Huff, A. Knop-Gericke, G. Koch, P. Kraus, J. Kröhnert, P. Kube, S. Lohr, T. Lunkenbein, L. Masliuk, R. Naumann d’Alnoncourt, T. Omojola, C. Pratsch, S. Richter, C. Rohner, F. Rosowski, F. Rüther, M. Scheffler, R. Schlögl, A. Tarasov, D. Teschner, O. Timpe, P. Trunschke, Y. Wang and S. Wrabetz: Towards Experimental Handbooks in Catalysis. Topics in Catalysis 63 (19-20), 1683–1699 (2020).
Journal Article
C.A. Sutton, M. Boley, L.M. Ghiringhelli, M. Rupp, J. Vreeken and M. Scheffler: Identifying domains of applicability of machine learning models for materials science. Nature Communications 11, 4428 (2020).
Journal Article
G. Cao, R. Ouyang, L.M. Ghiringhelli, M. Scheffler, H. Liu, C. Carbogno and Z. Zhang: Artificial intelligence for high-throughput discovery of topological insulators: The example of alloyed tetradymites. Physical Review Materials 4 (3), 034204 (2020).
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