Publikationen von Luca M. Ghiringhelli

Speckhard, D.; Carbogno, C.; Ghiringhelli, L. M.; Lubeck, S.; Scheffler, M.; Draxl, C.: Extrapolation to the complete basis-set limit in density-functional theory using statistical learning. Physical Review Materials 9 (1), 013801 (2025)

Bauer, S.; Benner, P.; Bereau, T.; Blum, V.; Boley, M.; Carbogno, C.; Catlow, C. R. A.; Dehm, G.; Eibl, S.; Ernstorfer, R. et al.; Fekete, A.; Foppa, L.; Fratzl, P.; Freysoldt, C.; Gault, B.; Ghiringhelli, L. M.; Giri, S. K.; Gladyshev, A.; Goyal, P.; Hattrick-Simpers, J.; Kabalan, L.; Karpov, P.; Khorrami, M. S.; Koch, C.; Kokott, S.; Kosch, T.; Kowalec, I.; Kremer, K.; Leitherer, A.; Li, Y.; Liebscher, C. H.; Logsdail, A. J.; Lu, Z.; Luong, F.; Marek, A.; Merz, F.; Mianroodi, J. R.; Neugebauer, J.; Pei, Z.; Purcell, T.; Raabe, D.; Rampp, M.; Rossi, M.; Rost, J.-M.; Saal, J. E.; Saalmann, U.; Sasidhar, K. N.; Saxena, A.; Sbailo, L.; Scheidgen, M.; Schloz, M.; Schmidt, D. F.; Teshuva, S.; Trunschke, A.; Wei, Y.; Weikum, G.; Xian, R. P.; Yao, Y.; Yin, J.; Zhao, M.; Scheffler, M.: Roadmap on data-centric materials science. Modelling and Simulation in Materials Science and Engineering 32 (6), 063301 (2024)

Leitherer, A.; Yeo, B. C.; Liebscher, C. H.; Ghiringhelli, L. M.: Automatic identification of crystal structures and interfaces via artificial-intelligence-based electron microscopy. npj Computational Materials 9, 179 (2023)

Purcell, T.; Scheffler, M.; Ghiringhelli, L. M.: Recent advances in the SISSO method and their implementation in the SISSO++ Code. The Journal of Chemical Physics 159 (11), 114110 (2023)

Purcell, T.; Scheffler, M.; Ghiringhelli, L. M.; Carbogno, C.: Accelerating materials-space exploration for thermal insulators by mapping materials properties via artificial intelligence. npj Computational Materials 9, 112 (2023)

Sbailò, L.; Fekete, Á.; Ghiringhelli, L. M.; Scheffler, M.: The NOMAD Artificial-Intelligence Toolkit: Turning materials-science data into knowledge and understanding. npj Computational Materials 8, 250 (2022)

Regler, B.; Scheffler, M.; Ghiringhelli, L. M.: TCMI: a non-parametric mutual-dependence estimator for multivariate continuous distributions. Data Mining and Knowledge Discovery (5), S. 1815 - 1864 (2022)

Kulik, H. J.; Hammerschmidt, T.; Schmidt, J.; Botti, S.; Marques, M. A. L.; Boley, M.; Scheffler, M.; Todorović, M.; Rinke, P.; Oses, C. et al.; Smolyanyuk, A.; Curtarolo, S.; Tkatchenko, A.; Bartók, A. P.; Manzhos, S.; Ihara, M.; Carrington, T.; Behler, J.; Isayev, O.; Veit, M.; Grisafi, A.; Nigam, J.; Ceriotti, M.; Schütt, K. T.; Westermayr, J.; Gastegger, M.; Maurer, R. J.; Kalita, B.; Burke, K.; Nagai, R.; Akashi, R.; Sugino, O.; Hermann, J.; Noé, F.; Pilati, S.; Draxl, C.; Kuban, M.; Rigamonti, S.; Scheidgen, M.; Esters, M.; Hicks, D.; Toher, C.; Balachandran, P. V.; Tamblyn, I.; Whitelam, S.; Bellinger, C.; Ghiringhelli, L. M.: Roadmap on Machine learning in electronic structure. Electronic Structure 4 (2), 023004 (2022)

Foppa, L.; Purcell, T.; Levchenko, S. V.; Scheffler, M.; Ghiringhelli, L. M.: Hierarchical Symbolic Regression for Identifying Key Physical Parameters Correlated with Bulk Properties of Perovskites. Physical Review Letters 129 (5), 0545301 (2022)

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

Carbogno, C.; Thygesen, K. S.; Bieniek, B.; Draxl, C.; Ghiringhelli, L. M.; Gulans, A.; Hofmann, O. T.; Jacobsen, K. W.; Lubeck, S.; Mortensen, J. J. et al.; Strange, M.; Wruss, E.; Scheffler, M.: Numerical quality control for DFT-based materials databases. npj Computational Materials 8, 69 (2022)

Liu, X.; Wang, X.; Gao, S.; Chang, V.; Tom, R.; Yu, M.; Ghiringhelli, L. M.; Marom, N.: Finding predictive models for singlet fission by machine learning. npj Computational Materials 8, 70 (2022)

Purcell, T.; Scheffler, M.; Carbogno, C.; Ghiringhelli, L. M.: SISSO++: A C++ Implementation of the Sure-Independence Screening and Sparisifying Operator Approach. The Journal of Open Source Software 7 (71), 3960 (2022)

Foppa, L.; Sutton, C. A.; Ghiringhelli, L. M.; De, S.; Löser, P.; Schunk, S. A.; Schäfer, A.; Scheffler, M.: Learning Design Rules for Selective Oxidation Catalysts from High-Throughput Experimentation and Artificial Intelligence. ACS Catalysis 12 (4), S. 2233 - 2232 (2022)

Foppa, L.; Ghiringhelli, L. M.: Identifying Outstanding Transition‑Metal‑Alloy Heterogeneous Catalysts for the Oxygen Reduction and Evolution Reactions via Subgroup Discovery. Topics in Catalysis 65 (1-4), S. 196 - 206 (2022)

Foppa, L.; Ghiringhelli, L. M.: 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), S. 207 - 207 (2022)

Mazheika, A.; Wang, Y.; Valero, R.; Viñes, F.; Illas, F.; Ghiringhelli, L. M.; Levchenko, S. V.; Scheffler, M.: Artificial-intelligence-driven discovery of catalyst genes with application to CO₂ activation on semiconductor oxides. Nature Communications 13, 419 (2022)

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

Leitherer, A.; Ziletti, A.; Ghiringhelli, L. M.: Robust recognition and exploratory analysis of crystal structures via Bayesian deep learning. Nature Communications 12 (1), 6234 (2021)

Talirz, L.; Ghiringhelli, L. M.; Smit, B.: Trends in Atomistic Simulation Software Usage [Articlev1.0]. Living Journal of Computational Molecular Science 3 (1), S. 1 - 12 (2021)