Person
Dr. Luca Ghiringhelli
Member since 06/2009
Phone: +49 30 8413 4802
Room: T 1.08
Email: luca.ghiringhelli@fau.de
RESEARCH TOPICS
RESEARCH GROUP: Big-Data Analytics for Materials Science
- Configurational sampling of transition metal nanoclusters and comparison with experiments via vibrational analysis
- Development of accelerated schemes for the efficient sampling of the configurational space of atomic clusters
METHODS
- Density functional theory
- Generalized parallel tempering (replica exchange)
2024
Articles
S. Bauer, P. Benner, T. Bereau, V. Blum, M. Boley, C. Carbogno, C. R. A. Catlow, G. Dehm, S. Eibl, R. Ernstorfer, Á. Fekete, L. Foppa, P. Fratzl, C. Freysoldt, B. Gault, L. M. Ghiringhelli, S. K. Giri, A. Gladyshev, P. Goyal, J. Hattrick-Simpers, L. Kabalan, P. Karpov, M. S. Khorrami, C. Koch, S. Kokott, T. Kosch, I. Kowalec, K. Kremer, A. Leitherer, Y. Li, C. H. Liebscher, A. J. Logsdail, Z. Lu, F. Luong, A. Marek, F. Merz, J. R. Mianroodi, J. Neugebauer, T. A. R. Purcell, D. Raabe, M. Rampp, M. Rossi, J.-M. Rost, U. Saalmann, A. Saxena, L. Sbailo, M. Scheffler, M. Scheidgen, M. Schloz, D. F. Schmidt, S. Teshuva, A. Trunschke, Y. Wei, G. Weikum, R. P. Xian, Y. Yao, M. Zhao,
Roadmap on Data-Centric Materials Science.
submitted to Modelling Simul. Mater. Sci. Eng., January 15, 2024; https://doi.org/10.48550/arXiv.2402.10932
Preprint Download (2024): arXivS. Lu, L. M. Ghiringhelli, C. Carbogno, J. Wang, M. Scheffler,
On the Uncertainty Estimates of Equivariant-Neural-Network-Ensembles Interatomic Potentials.
submitted for publication September 1, 2023; https://doi.org/10.48550/arXiv.2309.00195
Preprint Download (2023): arXiv
2023
Articles
L. M. Ghiringhelli, C. Baldauf, T. Bereau, S. Brockhauser, C. Carbogno, J. Chamanara, S. Cozzini, S. Curtarolo, C. Draxl, S. Dwaraknath, Á. Fekete, J. Kermode, C. T. Koch, M. Kühbach, A. N. Ladines, P. Lambrix, M.-O. Lenz-Himmer, S. Levchenko, M. Oliveira, A. Michalchuk, R. Miller, B. Onat, P. Pavone, G. Pizzi, B. Regler, G.-M. Rignanese, J. Schaarschmidt, M. Scheidgen, A. Schneidewind, T. Sheveleva, C. Su, D. Usvyat, O. Valsson, C. Wöll, and M. Scheffler,
Shared Metadata for Data-Centric Materials Science.
Scientific Data 10, 626 (2023); https://doi.org/10.1038/s41597-023-02501-8
Download: pdfA. Leitherer, B. C. Yeo, C. H. Liebscher, and L. M. Ghiringhelli,
Automatic Identification of Crystal Structures and Interfaces via Artificial-Intelligence-based Electron Microscopy.
npj Computational Materials 9, 17 (2023); https://doi.org/10.1038/s41524-023-01133-1
Download: pdfM. Scheidgen, L. Himanen, A. N. Ladines, D. Sikter, M. Nakhaee, Á. Fekete, T. Chang, A. Golparvar, J. A. Márquez, S. Brockhauser, S. Brückner, L. M. Ghiringhelli, F. Dietrich, D. Lehmberg, T. Denell, A. Albino, H. Näsström, S. Shabih, F. Dobener, M. Kühbach, R. Mozumder, J. Rudzinski, N. Daelman, J. M. Pizarro, M. Kuban, P. Ondračka, H.-J. Bungartz, and C. Draxl,
NOMAD: A distributed web-based platform for managing materials science research data.
Journal of Open Source Software, 8 (90), 5388; https://doi.org/10.21105/joss.05388
Download: pdfT. A. R. Purcell, M. Scheffler, L. M. Ghiringhelli, C. Carbogno,
Accelerating Materials-Space Exploration by Mapping Materials Properties via Artificial Intelligence: The Case of the Lattice Thermal Conductivity.
npj Computational Materials 9 (1), 112 (2023); https://doi.org/10.1038/s41524-023-01063-y
Download: pdfT. A. R. Purcell, M. Scheffler, L. M. Ghiringhelli,
Recent advances in the SISSO method and their implementation in the SISSO++ code.
J. Chem. Phys. 159, 114110 (2023); https://doi.org/10.1063/5.0156620
Download (2023): pdf
2022
Articles
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); https://doi.org/10.1038/s41524-022-00744-4
Download: pdf- L. Foppa, T. A. R. 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, 55301 (2022); https://doi.org/10.1103/PhysRevLett.129.055301
Download: pdf - L. Foppa, C. 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, 2223 (2022); https://doi.org/10.1021/acscatal.1c04793
Download: ACS Publications L. M. Ghiringhelli,
Interpretability of machine-learning models in physical sciences.
Roadmap on Machine learning in electronic structure, ed. by Silvana Botti and Miguel Marques,
H J Kulik et al 2022 Electron. Struct. 4 023004, https://doi.org/10.1088/2516-1075/ac572f
Download: pdfA. Mazheika, Y. Wang, R. Valero, F. Vines, F. Illas, L. Ghiringhelli, S. Levchenko, and M. Scheffler,
Artificial-intelligence-driven discovery of catalyst “genes” with application to CO2 activation on semiconductor oxides.
Nature Communications 13, 419 (2022); https://doi.org/10.1038/s41467-022-28042-z
Download: pdfB. Regler, M. Scheffler, and L.M. Ghiringhelli,
TCMI: a non-parametric mutual-dependence estimator for multivariate continuous distributions. Data Min Knowl Disc 36, 1815–1864 (2022); https://doi.org/10.1007/s10618-022-00847-y
Download: pdfL. Sbailò, Á. Fekete, L. M. Ghiringhelli, and M. Scheffler
The NOMAD Artificial-Intelligence Toolkit: turning materials-science data into knowledge and understanding.
npj Computational Materials 8, 250 (2022); https://doi.org/10.1038/s41524-022-00935-z
Download: pdfT. A. R. Purcell, M. Scheffler, C. Carbogno, and L.M. Ghiringhelli,
SISSO++: A C++ Implementation of the Sure-Independence Screening and Sparsifying Operator Approach.
Journal of Open Source Software 7 (71), 3960 (2022); https://doi.org/10.21105/joss.03960
Download: pdfY. 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 Letter 128, 246101 (2022); https:/doi.org/10.1103/PhysRevLett.128.246101
Download: pdf
2021
Articles
- 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); https://doi.org/10.1063/5.0053931
Download: pdf - 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); https://doi.org/10.1063/5.0061875
Download: pdf - 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 (2021); https://doi.org/10.1557/s43577-021-00165-6
Download: pdf - 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, published online 02. September 2021; https://doi.org/10.1007/s11244-021-01502-4
Download: pdf - L. M. Ghiringhelli,
An AI-toolkit to develop and share research into new materials.
Nature Review Physics 3, 724 (2021); https://doi.org/10.1038/s42254-021-00373-8
Download: pdf - A. Leitherer, A. Ziletti, and L.M. Ghiringhelli,
Robust recognition and exploratory analysis of crystal structures via Bayesian deep learning.
Nature Communications 12, 6234 (2021); https://doi.org/10.1038/s41467-021-26511-5
Download: pdf - A. Mazheika, S.V. Levchenko, L.M. Ghiringhelli and M. Scheffler,
Materials for turning greenhouse gases into useful chemicals and fuels: a route identified by high-throughput calculations and artificial intelligence.
In: High-Performance Computing and Data Science in the Max Planck Society. Max Planck Computing and Data Facility, Garching, 44–46 (2021).
Download: pdf - 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); https://doi.org/10.33011/livecoms.3.1.1483
Download: pdf
2020
Articles
- 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. Phys. Rev. Mater. 4, 034204 (2020); https://doi.org/10.1103/PhysRevMaterials.4.034204
Reprint download: pdf, Arxiv - A. Dutta, J. Vreeken, L. M. Ghiringhelli, and T. Bereau,
Data-driven equation for drug-membrane permeability across drugs and membranes. J. Chem. Phys. 154, 244114 (2021); https://doi.org/10.1063/5.0053931
Reprint download: pdf C. Sutton, M. Boley, L.M. Ghiringhelli, M. Rupp, J. Vreeken, and M. Scheffler,
Identifying domains of applicability of machine learning models for materials science. Nat. Commun. 11, 4428 (2020); https://doi.org/10.1038/s41467-020-17112-9
Reprint download: pdf- A. Trunschke, G. Bellini, M. Boniface, S. J. 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, Ch. 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, 1683 (2020); https://doi.org/10.1007/s11244-020-01380-2
Reprint download: pdf - C. Wouters, C. Sutton, L. M. Ghiringhelli, T. Markurt, 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. Phys. Rev. Materials 4, 125001 (2020); https://doi.org/10.1103/PhysRevMaterials.4.125001
Reprint download: pdf,
2019
Articles
- C.J. Bartel, C. Sutton, B.R. Goldsmith, R. Ouyang, C.B. Musgrave, L.M. Ghiringhelli, and M. Scheffler,
New Tolerance Factor to Predict the Stability of Perovskite Oxides and Halides. Sci. Adv. 5, eaav0693 (2019); https://doi.org/10.1126/sciadv.aav0693
Reprint download: pdf, Supplementary material: pdf F. Belviso, V.E.P. Claerbout, A. Comas-Vives, N.S. Dalal, F.-R. Fan, A. Filippetti, V. Fiorentini, L. Foppa, C. Franchini, B. Geisler, L.M. Ghiringhelli, A. Groß, S. Hu, J. Íñiguez, S.K. Kauwe, J.L. Musfeldt, P. Nicolini, R. Pentcheva, T. Polcar, W. Ren, F. Ricci, F. Ricci, H.S. Sen, J.M. Skelton, T.D. Sparks, A. Stroppa, A. Urru, M. Vandichel, P. Vavassori, H. Wu, K. Yang, H.J. Zhao, D. Puggioni, R. Cortese and A. Cammarata,
Viewpoint: Atomic-Scale Design Protocols toward Energy, Electronic, Catalysis, and Sensing Applications. Inorganic Chemistry 58 (22), 14939 (2019); https://doi.org/10.1021/acs.inorgchem.9b01785
Reprint download: pdf- B.R. Goldsmith, J. Florian, J.-X. Liu, Ph. Gruene, J.T. Lyon, D.M. Rayner, A. Fielicke, M. Scheffler, and L.M. Ghiringhelli,
Two-to-three dimensional transition in neutral gold clusters: The crucial role of van der Waals interactions and temperature. Phys. Rev. Mat. 3, 016002 (2019); https://doi.org/10.1103/PhysRevMaterials.3.016002
Reprint download: pdf - D. Guedes-Sobrinho, W. Wang, I. Hamilton, J.L.F. Da Silva, and L.M. Ghiringhelli,
(Meta-)stability and Core-Shell Dynamics of Gold Nanoclusters at Finite Temperature. J. Phys. Chem. Lett. 10, 685-692 (2019); https://doi.org/10.1021/acs.jpclett.8b03397
Reprint download: pdf, Supplementary material: pdf R. Ouyang, E. Ahmetcik, C. Carbogno, M. Scheffler, and L. M. Ghiringhelli,
Simultaneous Learning of Several Materials Properties from Incomplete Databases with Multi-Task SISSO. J. Phys. Mater. 2, 024002 (2019); https://doi.org/10.1088/2515-7639/ab077bC. Sutton, L.M. Ghiringhelli, T. Yamamoto, Y. Lysogorskiy, L. Blumenthal, T. Hammerschmidt, J. Golebiowski, X. Liu, A. Ziletti, and M. Scheffler,
Crowd-sourcing materials-science challenges with the NOMAD 2018 Kaggle competition. npj Computational Materials 5, 111 (2019); https://doi.org/10.1038/s41524-019-0239-3I.-Y. Zhang, A.J. Logsdail, X. Ren, S.V. Levchenko, L.M. Ghiringhelli, and M. Scheffler,
Main-group test set for materials science and engineering with user-friendly graphical tools for error analysis: Systematic benchmark of the numerical and intrinsic errors in state-of-the-art electronic-structure approximations. New J. Phys. 21, 013025 (2019); https://doi.org/10.1088/1367-2630/aaf751Y. Zhou, M. Scheffler, and L.M.Ghiringhelli,
Determining Surface Phase Diagrams Including Anharmonic Effects. Phys. Rev. B 100, 174106 (2019); https://doi.org/10.1103/PhysRevB.100.174106
2018
Articles
- R. Ouyang, S. Curtarolo, E. Ahmetcik, M. Scheffler, and L.M. Ghiringhelli,
SISSO: a compressed-sensing method for identifying the best low-dimensional descriptor in an immensity of offered candidates . Phys. Rev. Mat. 2, 083802 (2018).
Reprint download: pdf, Supplementary material: pdf A. Ziletti, D. Kumar, M. Scheffler, and L.M. Ghiringhelli,
Insightful classification of crystal structures using deep learning. Nat. Commun. 9 , 2775 (2018); https:/doi.org/10.1038/s41467-018-05169-6
2017
Articles
- S. Bhattacharya, D. Berger, K. Reuter, L.M. Ghiringhelli, and S.V. Levchenko,
Theoretical evidence for unexpected O-rich phases at corners of MgO surfaces. Phys. Rev. Materials 1, 071601(R) (2017) .
Reprint download: pdf, Supplementary material: pdf DOI: 10.1103/PhysRevMaterials.1.071601. - M. Boley, B.R. Goldsmith, L.M. Ghiringhelli, and J. Vreeken,
Identifying consistent statements about numerical data with dispersion-corrected subgroup discovery. Data Min. Knowl. Disc. 31, 1391 (2017).
Reprint download: pdf DOI: 10.1007/s10618-017-0520-3. - L.M. Ghiringhelli, C. Carbogno, S.V. Levchenko, F. Mohamed, G. Huhs, M. Lueders, M. Oliveira, and M. Scheffler,
Towards efficient data exchange and sharing for big-data driven materials science: metadata and data formats. npj Computational Materials 3, 46 (2017).
Reprint download: pdf, Supplementary material: pdf DOI: 10.1038/s41524-017-0048-5. - L.M. Ghiringhelli, J. Vybiral, E. Ahmetcik, R. Ouyang, S.V. Levchenko, C. Draxl, and M. Scheffler,
Learning physical descriptors for materials science by compressed sensing. New J. Phys. 19, 023017 (2017).
Reprint download: pdf DOI: 10.1088/1367-2630/aa57bf. - B.R. Goldsmith, M. Boley, J. Vreeken, M. Scheffler, and L.M. Ghiringhelli,
Uncovering structure-property relationships of materials by subgroup discovery. New J. Phys. 19, 013031 (2017).
Reprint download: pdf, Supplementary material: pdf DOI: 10.1088/1367-2630/aa57c2. - C. Yu, W. Harbich, L. Sementa, L. Ghiringhelli, E. Aprá, M. Stener, A. Fortunelli, and H. Brune,
Intense fluorescence of Au20. J. Chem. Phys. 147, 074301 (2017).
Reprint download: pdf
2016
Articles
- L.M. Ghiringhelli, C. Carbogno, S. Levchenko, F. Mohamed, G. Huhs, M. Lueders, M. Oliveira, and M. Scheffler,
Towards a Common Format for Computational Materials Science Data. Published as "Ψk Scientific Highlight of the Month", n. 131 (July 2016).
Reprint download: pdf
2015
Articles
- S. Bhattacharya, B. Sonin, C.J. Jumonville, L.M. Ghiringhelli, and N. Marom,
Computational Design of Nanoclusters by Property-Based Genetic Algorithms: Tuning the Electronic Properties of (TiO2)n Clusters. Phys. Rev. B 91, 241115 (2015).
Reprint download: pdf, Supplementary material: pdf - L.M. Ghiringhelli and S.V. Levchenko,
Strengthening gold-gold bonds by complexing gold clusters with noble gases. Inor. Chem. Comm. 55, 153-156 (2015).
Reprint download: pdf, Supplementary material: pdf - L.M. Ghiringhelli, J. Vybiral, S.V. Levchenko, C. Draxl, and M. Scheffler,
Big Data of Materials Science: Critical Role of the Descriptor. Phys. Rev. Lett. 114, 105503 (2015).
Reprint download: pdf, Supplementary material: pdf - X. Zhao, X. Shao, Y. Fujimori, S. Bhattacharya, L.M. Ghiringhelli, H.-J. Freund, M. Sterrer, N. Nilius, and S.V. Levchenko,
Formation of Water Chains on CaO(001): What Drives the 1D Growth? J. Phys. Chem. Lett. 6, 1204-1208 (2015).
Reprint download: pdf
2014
Articles
- E.C. Beret, M. van Wijk, and L.M. Ghiringhelli,
Reaction cycles and poisoning in catalysis by gold clusters: a thermodynamics approach. Int. J. Quant. Chem. 114, 57-65 (2014).
Reprint download: pdf - S. Bhattacharya, S. Levchenko, L.M. Ghiringhelli and M. Scheffler,
Efficient ab initio schemes for finding thermodynamically stable and metastable atomic structures: Benchmark of cascade genetic algorithms. New J. Phys. 16, 123016 (2014).
Reprint download: pdf - L.M. Ghiringhelli,
Application to (Kohn-Sham) Density-Functional Theory to Real Materials.
In Many-Electron Approaches in Physics, Chemistry and Mathematics: A Multidisciplinary View., V. Bach and L. Delle Site Editors, Springer (2014).
Preprint download: pdf - R. Peköz, S. Wörner, L.M. Ghiringhelli, and D. Donadio,
Trends in the Adsorption and Dissociation of Water Clusters on Flat and Stepped Metallic Surfaces. J. Phys. Chem. C 118, 29990-29998 (2014).
Reprint download: pdf - Y. Peng, L.M. Ghiringhelli, and H. Appel,
A quantum reactive scattering perspective on electronic nonadiabaticity. Eur. Phys. J. B 87, 1-13 (2014).
Reprint download: pdf
2013
Articles
- S. Bhattacharya, S. Levchenko, L.M. Ghiringhelli, and M. Scheffler,
Stability and Metastability of Clusters in a Reactive Atmosphere: Theoretical Evidence for Unexpected Stoichiometries of MgMOx. Phys. Rev. Lett. 111, 135501 (2013).
Reprint download: pdf, Supplementary material: pdf - L. Delle Site, L.M. Ghiringhelli, and D.M. Ceperley
Electronic Energy Functionals: Levy-Lieb Principle within the Ground State Path Integral Quantum Monte Carlo. Int. J. Quant. Chem. 113, 155-160 (2013).
Reprint download: pdf. - L.M. Ghiringhelli, P. Gruene, J.T. Lyon, D.M. Rayner, G. Meijer, A. Fielicke, and M. Scheffler,
Not so loosely bound rare gas atoms: finite-temperature vibrational fingerprints of neutral gold-cluster complexes. New J. Phys. 15, 083003 (2013).
Reprint download: pdf
2012
Articles
- D. Donadio, L.M. Ghiringhelli, and L. Delle Site,
Autocatalytic and Cooperatively Stabilized Dissociation of Water on a Stepped Platinum Surface. J. Am. Chem. Soc. 134, 19217-19222 (2012).
Reprint download: pdf
2011
Articles
- E.C. Beret, L.M. Ghiringhelli, and M. Scheffler,
Free gold clusters: Beyond the static, mono-structure description. Faraday Discuss. 152 (1), 153-167 (2011).
Reprint download: pdf - J.M. Carlsson, L.M. Ghiringhelli, and A. Fasolino,
Theory and hierarchical calculations of the structure and energetics of [0001] tilt grain boundaries in graphene. Phys. Rev. B 84, 165423 (2011).
Reprint download: pdf - R. Scipioni, D. Donadio, L.M. Ghiringhelli, and L. Delle Site,
Proton Wires via One-Dimensional Water Chains Adsorbed on Metallic Steps. J. Chem. Theory and Comp. 7, 2681-2684 (2011).
Reprint download: pdf
2010
Articles
- L.M. Ghiringhelli and E.J. Meijer,
"Liquid Carbon: Freezing Line and Structure near Freezing". In: Computer-based modeling of novel carbon systems (other than nanotubes) and their properties. (Eds.) A. Fasolino and L. Colombo. Springer 2010, p. 1-36.
Reprint download: pdf
2009
Articles
- T. Li, D. Donadio, L.M. Ghiringhelli, and G. Galli,
"Surface-induced crystallization in supercooled tetrahedral liquids". Nature Materials 8, 726-730 (2009).
Reprint download: pdf
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