Showing entries 1 - 20 out of 599


Birschitzky VC, Sokolovic I, Prezzi M, Palotas K, Setvin M, Diebold U et al. Machine Learning Based Prediction of Polaron-Vacancy Patterns on the TiO2(110) Surface. arXiv. 2024 Jan 22.

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


Karandashev K, Weinreich J, Heinen S, Arismendi Arrieta DJ, von Rudorff GF, Hermansson K et al. Evolutionary Monte Carlo of QM Properties in Chemical Space: Electrolyte Design. Journal of Chemical Theory and Computation. 2023 Dec 12;19(23):8861-8870. doi: 10.48550/arXiv.2307.15563, 10.1021/acs.jctc.3c00822

Lemm D, Falk von Rudorff G, Anatole von Lilienfeld O. Improved decision making with similarity based machine learning: applications in chemistry. Machine Learning: Science and Technology. 2023 Dec 1;4(4):045043. doi: 10.1088/2632-2153/ad0fa3, 10.1088/2632-2153/ad0fa3

Celiberti L, Varrassi L, Franchini C. Pb9Cu(PO4)6O is a charge-transfer semiconductor. Physical Review B. 2023 Nov 15;108(20):L201117. Epub 2023 Aug 22. doi: 10.1103/PhysRevB.108.L201117

Riemelmoser S, Verdi C, Kaltak M, Kresse G. Machine Learning Density Functionals from the Random-Phase Approximation. Journal of Chemical Theory and Computation. 2023 Oct 24;19(20):7287-7299. doi: 10.48550/arXiv.2308.00665, 10.1021/acs.jctc.3c00848

Puntscher L, Sombut P, Wang C, Ulreich M, Pavelec J, Rafsanjani-Abbasi A et al. A Multitechnique Study of C2H4 Adsorption on Fe3O4(001). Journal of Physical Chemistry C. 2023 Sep 21;127(37):18378-18388. Epub 2023 Sep 11. doi: 10.1021/acs.jpcc.3c03684

Cai X, Wei SH, Deák P, Franchini C, Li SS, Deng HX. Band-gap trend of corundum oxides α - M2O3 (M = Co, Rh, Ir): An ab initio study. Physical Review B. 2023 Aug 15;108(7):075137. doi: 10.1103/PhysRevB.108.075137

Sukurma Z, Schlipf M, Humer M, Taheridehkordi A, Kresse G. Benchmark Phaseless Auxiliary-Field Quantum Monte Carlo Method for Small Molecules: Journal of Chemical Theory and Computation. Journal of Chemical Theory and Computation. 2023 Aug 8;19(15):4921–4934. Epub 2023 Jul. doi:, 10.1021/acs.jctc.3c00322

Cong R, Garcia E, Forino PC, Tassetti A, Allodi G, Reyes AP et al. Effects of charge doping on Mott insulator with strong spin-orbit coupling, Ba2Na1−xCaxOsO6. Physical Review Materials. 2023 Aug;7(8):084409. doi: 10.1103/PhysRevMaterials.7.084409

Taheridehkordi A, Schlipf M, Sukurma Z, Humer M, Grüneis A, Kresse G. Phaseless auxiliary field quantum Monte Carlo with projector-augmented wave method for solids. Journal of Chemical Physics. 2023 Jul 28;159(4):044109. doi: 10.48550/arXiv.2304.14029, 10.1063/5.0156657

Huang B, von Rudorff GF, von Lilienfeld OA. The central role of density functional theory in the AI age. Science. 2023 Jul 14;381(6654):170-175. doi: 10.1126/science.abn3445

Ellinger F, Shafiq M, Ahmad I, Reticcioli M, Franchini C. Small Polaron Formation on the Nb-doped SrTiO3(001) Surface. Physical Review Materials. 2023 Jun 28;7:064602. doi: 10.48550/arXiv.2208.10624, 10.1103/PhysRevMaterials.7.064602

Celiberti L, Mosca DF, Allodi G, Pourovskii LV, Tassetti A, Forino PC et al. Spin-orbital Jahn-Teller bipolarons. 2023 Jun 27.

Weinreich J, Rudorff GFV, Lilienfeld OAV. Encrypted machine learning of molecular quantum properties. Machine Learning: Science and Technology. 2023 Jun;4(2):025017. doi: 10.48550/arXiv.2212.04322, 10.1088/2632-2153/acc928

Showing entries 1 - 20 out of 599