Publications of Luca M. Ghiringhelli
All genres
Journal Article (57)
Journal Article
, , , , , , M. Scheffler, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , and L.M. Ghiringhelli: Roadmap on Machine learning in electronic structure. Electronic Structure 4 (2), 023004 (2022).
Journal Article
L. Foppa, T. Purcell, , 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, , B. Bieniek, C. Draxl, L.M. Ghiringhelli, , , , , , , and M. Scheffler: Numerical quality control for DFT-based materials databases. npj Computational Materials 8, 69 (2022).
Journal Article
, , , , , , L.M. Ghiringhelli and : 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, , , , 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, , , , L.M. Ghiringhelli, and M. Scheffler: Artificial-intelligence-driven discovery of catalyst genes with application to CO2 activation on semiconductor oxides. Nature Communications 13, 419 (2022).
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L. Foppa, L.M. Ghiringhelli, F. Girgsdies, M. Hashagen, P. Kube, , S. Carey, A. Tarasov, P. Kraus, , 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.M. Ghiringhelli and : Trends in Atomistic Simulation Software Usage [Articlev1.0]. Living Journal of Computational Molecular Science 3 (1), 1–12 (2021).
Journal Article
, , L.M. Ghiringhelli and : 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).
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, , L.M. Ghiringhelli and : Data-driven equation for drug-membrane permeability across drugs and membranes. The Journal of Chemical Physics 154 (24), 244114 (2021).
Journal Article
, C.A. Sutton, L.M. Ghiringhelli, , , , , , M. Scheffler and : 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, , L.M. Ghiringhelli, F. Girgsdies, R. Hanna, M. Hashagen, M. Hävecker, G. Huff, A. Knop-Gericke, G. Koch, P. Kraus, J. Kröhnert, P. Kube, , T. Lunkenbein, L. Masliuk, , T. Omojola, C. Pratsch, S. Richter, C. Rohner, , , M. Scheffler, R. Schlögl, A. Tarasov, D. Teschner, O. Timpe, , Y. Wang and S. Wrabetz: Towards Experimental Handbooks in Catalysis. Topics in Catalysis 63 (19-20), 1683–1699 (2020).
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C.A. Sutton, , L.M. Ghiringhelli, M. Rupp, 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, , C. Carbogno and : Artificial intelligence for high-throughput discovery of topological insulators: The example of alloyed tetradymites. Physical Review Materials 4 (3), 034204 (2020).