Publikationen von Luca M. Ghiringhelli

Ghiringhelli, L. M.: (Meta)stability and dynamics of metal clusters in realistic atmosphere from first principles. International Workshop on Frontiers in Computational Material Science, Ringberg Castle, Germany (2012)

Ghiringhelli, L. M.: Ab initio free energy: interface PLUMED / FHI-aims and application to fluxional metal clusters and beyond. First PLUMED meeting, Trieste, Italy (2012)

Ghiringhelli, L. M.: Towards catalysis by gold clusters: reaction cycles and poisons. Colloquium at Oak Ridge National Laboratory (ORNL), Tennessee, USA (2012)

Ghiringhelli, L. M.: Free-energy calculation for molecules and condensed phases. jDPG Theoretikerworkshop (Theorist’s workshop of the Young German Physical Society), Burg Breuberg, Germany (2012)

Ghiringhelli, L. M.: Towards catalysis by gold clusters: allowed reaction cycles and poisons. Sustainable Energy Workshop, Taipei, Taiwan (2011)

Ghiringhelli, L. M.: Towards catalysis by gold clusters: allowed reaction cycles and poisons. Workshop on the Physics and Chemistry of Energy Conversion at Interfaces, Dalian, China (2011)

Ahmetcik, E.: Machine Learning of the Stability of Octet Binaries. Master, Technische Universität, Berlin (2016)

Lu, S.; Ghiringhelli, L. M.; Carbogno, C.; Wang, J.; Scheffler, M.: On the Uncertainty Estimates of Equivariant-Neural-Network-Ensembles Interatomic Potentials. (2023)

Speckhard, D.; Carbogno, C.; Ghiringhelli, L. M.; Lubeck, S.; Scheffler, M.; Draxl, C.: Extrapolation to complete basis-set limit in density-functional theory by quantile random-forest models. (2023)

Ghiringhelli, L. M.: Interpretability of machine-learning models in physical sciences. (2021)

Mazheika, A.; Wang, Y.; Valero, R.; Ghiringhelli, L. M.; Vines, F.; Illas, F.; Levchenko, S. V.; Scheffler, M.: Ab initio data-analytics study of carbon-dioxide activation on semiconductor oxide surfaces. (2019)

Acosta, C. M.; Ouyang, R.; Fazzio, A.; Scheffler, M.; Ghiringhelli, L. M.; Carbogno, C.: Analysis of Topological Transitions in Two-dimensional Materials by Compressed Sensing. (2018)

Ghiringhelli, L. M.; Carbogno, C.; Levchenko, S. V.; Mohamed, F. R.; Huhs, G.; Lüders, M.; Oliveira, M.; Scheffler, M.: Towards a Common Format for Computational Materials Science Data. Psi-k Scientific Highlight Of The Month (131) S. 1 - 16 (2016), 16 S.

Ghiringhelli, L. M.; Baldauf, C.; Bereau, T.; Brockhauser, S.; Carbogno, C.; Chamanara, J.; Cozzini, S.; Curtarolo, S.; Draxl, C.; Dwaraknath, S. et al.; Fekete, Á.; Kermode, J.; Koch, C. T.; Kühbach, M.; Ladines, A. N.; Lambrix, P.; Himmer, M.-O. L.; Levchenko, S. V.; Oliveira, M.; Michalchuk, A.; Miller, R.; Onat, B.; Pavone, P.; Pizzi, G.; Regler, B.; Rignanese, G.-M.; Schaarschmidt, J.; Scheidgen, M.; Schneidewind, A.; Sheveleva, T.; Su, C.; Usvyat, D.; Valsson, O.; Wöll, C.; Scheffler, M.: Shared Metadata for Data-Centric Materials Science. Scientific Data 10, 626 (2023)

Ghiringhelli, L. M.: An AI-toolkit to develop and share research into new material. Nature Reviews Physics 3, 724 (2021)