Publications
Showing entries 21 - 40 out of 631
2024
Klimin SN, Tempere J, Houtput M, Ragni S, Hahn T, Franchini C et al. Analytic method for quadratic polarons in nonparabolic bands. Physical Review B. 2024 Aug 15;110(7):075107. doi: 10.48550/arXiv.2403.18019, 10.1103/PhysRevB.110.075107
Tresca C, Forcella PM, Angeletti A, Ranalli L, Franchini C, Reticcioli M et al. Molecular hydrogen in the N-doped LuH3 system as a possible path to superconductivity. Nature Communications. 2024 Aug;15(1):7283. doi: 10.1038/s41467-024-51348-z
Leoni L, Franchini C. Global sampling of Feynman's diagrams through normalizing flow. Physical Review Research. 2024 Jul;6(3):033041. doi: 10.48550/arXiv.2402.00736, 10.1103/PhysRevResearch.6.033041
Li Z, Varrassi L, Yang Y, Franchini C, Bellaiche L, He J. Ultrastrong Coupling between Polar Distortion and Optical Properties in Ferroelectric MoBr2O2. Journal of the American Chemical Society. 2024 Jun 5;146(22):15411–15419. Epub 2024 May 23. doi: 10.48550/arXiv.2402.15949, 10.1021/jacs.4c03296
Sukurma Z, Schlipf M, Humer M, Taheridehkordi A, Kresse G. Toward Large-Scale AFQMC Calculations: Large Time Step Auxiliary-Field Quantum Monte Carlo. Journal of Chemical Theory and Computation. 2024 May 28;20(10):4205–4217. Epub 2024 May 15. doi: 10.48550/arXiv.2403.02542, 10.1021/acs.jctc.4c00304
Jinnouchi R, Karsai F, Kresse G. Machine learning-aided first-principles calculations of redox potentials. npj Computational Materials. 2024 May 20;10(1):107. doi: 10.48550/arXiv.2309.13217, 10.1038/s41524-024-01295-6
Liu CY, Celiberti L, Decker R, Ruotsalainen K, Siewierska K, Kusch M et al. Orbital-overlap-driven hybridization in 3d-transition metal perovskite oxides LaMO3 (M = Ti-Ni) and La2CuO4. Communications Physics. 2024 May 14;7(1):156. doi: 10.1038/s42005-024-01642-5
Tal A, Marsman M, Kresse G, Anders A, Rodriguez S, Kim K et al. Solving Millions of Eigenvectors in Large-Scale Quantum-Many-Body-Theory Computations. In ISC High Performance 2024 Research Paper Proceedings (39th International Conference): Hamburg, Germany, May 12 - 16, 2024. Hamburg: Prometeus GmbH. 2024 doi: 10.23919/ISC.2024.10528945
Birschitzky VC, Sokolović I, Prezzi M, Palotás K, Setvín M, Diebold U et al. Machine learning-based prediction of polaron-vacancy patterns on the TiO2(110) surface. npj Computational Materials. 2024 May 6;10(1):89. Epub 2024 Jan 22. doi: 10.1038/s41524-024-01289-4
Wang C, Sombut P, Puntscher L, Jakub Z, Meier M, Pavelec J et al. CO-Induced Dimer Decay Responsible for Gem-Dicarbonyl Formation on a Model Single-Atom Catalyst. Angewandte Chemie - International Edition. 2024 Apr 15;63(16):e202317347. Epub 2024 Jan 31. doi: 10.1002/anie.202317347
Liu M, Wang J, Hu J, Liu P, Niu H, Yan X et al. Layer-by-layer phase transformation in Ti3O5 revealed by machine-learning molecular dynamics simulations. Nature Communications. 2024 Apr 9;15:3079. doi: 10.1038/s41467-024-47422-1
Domenichini G. Extending the definition of atomic basis sets to atoms with fractional nuclear charge. Journal of Chemical Physics. 2024 Mar 28;160(12):124107. Epub 2024 Mar 25. doi: 10.1063/5.0196383
Montero de Hijes P, Dellago C, Jinnouchi R, Schmiedmayer B, Kresse G. Comparing machine learning potentials for water: Kernel-based regression and Behler-Parrinello neural networks. Journal of Chemical Physics. 2024 Mar 21;160(11):114107. doi: 10.1063/5.0197105
Celiberti L, Fiore Mosca D, Allodi G, Pourovskii LV, Tassetti A, Forino PC et al. Spin-orbital Jahn-Teller bipolarons. Nature Communications. 2024 Mar 18;15:2429. Epub 2023 Jun 27. doi: 10.1038/s41467-024-46621-0
Varrassi L, Liu P, Franchini C. Quasiparticle and excitonic properties of monolayer SrTiO3. Physical Review Materials. 2024 Feb;8(2):024001. doi: 10.1103/PhysRevMaterials.8.024001
Fiore Mosca D, Schnait H, Celiberti L, Aichhorn M, Franchini C. The Mott transition in the 5d1 compound Ba2NaOsO6: a DFT+DMFT study with PAW spinor projectors. Computational Materials Science. 2024 Jan 30;233:112764. Epub 2023 Mar 29. doi: 10.1016/j.commatsci.2023.112764
Bosoni E, Beal L, Bercx M, Blaha P, Blügel S, Bröder J et al. How to verify the precision of density-functional-theory implementations via reproducible and universal workflows. Nature Reviews Physics. 2024 Jan;6:45–58. Epub 2023 Nov 14. doi: 10.1038/s42254-023-00655-3
Lemm D, von Rudorff GF, Anatole von Lilienfeld O. Impact of noise on inverse design: the case of NMR spectra matching. Digital Discovery. 2024 Jan;3(1):136-144. 136-144. Epub 2023 Oct 17. doi: 10.48550/arXiv.2307.03969, 10.1039/d3dd00132f
Coretti A, Falkner S, Weinreich J, Dellago C, von Lilienfeld-Toal OA. Boltzmann Generators and the New Frontier of Computational Sampling in Many-Body Systems. KIM Review. 2024;2:3. doi: 10.25950/bfa99422
2023
Kyvala L, Angeletti A, Franchini C, Dellago C. Diffusion and Coalescence of Phosphorene Monovacancies Studied Using High-Dimensional Neural Network Potentials. Journal of Physical Chemistry C. 2023 Dec 14;127(49):23743-23751. doi: 10.1021/acs.jpcc.3c05713