Publications
Showing entries 101 - 120 out of 628
2021
Kilaj A, Wang J, Stranak P, Schwilk M, Rivero U, Xu L et al. Conformer-specific polar cycloaddition of dibromobutadiene with trapped propene ions. Nature Communications. 2021 Oct 18;12(1):6047. doi: 10.1038/s41467-021-26309-5
Hahn T, Nagaosa N, Franchini C, Mishchenko AS. Diagrammatic quantum Monte Carlo study of an acoustic lattice polaron. Physical Review B. 2021 Oct 15;104(16):L161111. doi: 10.1103/PhysRevB.104.L161111
Turiansky ME, Alkauskas A, Engel M, Kresse G, Wickramaratne D, Shen JX et al. Nonrad: Computing nonradiative capture coefficients from first principles. Computer Physics Communications. 2021 Oct;267:108056. doi: 10.1016/j.cpc.2021.108056
Bokdam M, Lahnsteiner J, Sarma DD. Exploring Librational Pathways with on-the-Fly Machine-Learning Force Fields: Methylammonium Molecules in MAPbX(3) (X = I, Br, Cl) Perovskites. Journal of Physical Chemistry C. 2021 Sept 30;125(38):21077-21086. doi: 10.1021/acs.jpcc.1c06835
Verdi C, Karsai F, Liu P, Jinnouchi R, Kresse G. Thermal transport and phase transitions of zirconia by on-the-fly machine-learned interatomic potentials. npj Computational Materials. 2021 Sept 30;7(1):156. doi: 10.1038/s41524-021-00630-5
Huang B, von Lilienfeld OA. Ab Initio Machine Learning in Chemical Compound Space. Chemical Reviews. 2021 Aug 25;121(16):10001-10036. doi: 10.1021/acs.chemrev.0c01303
Ceriotti M, Clementi C, von Lilienfeld OA. Introduction: Machine Learning at the Atomic Scale. Chemical Reviews. 2021 Aug 25;121(16):9719-9721. doi: 10.1021/acs.chemrev.1c00598
Heinen S, von Rudorff GF, von Lilienfeld OA. Toward the design of chemical reactions: Machine learning barriers of competing mechanisms in reactant space. Journal of Chemical Physics. 2021 Aug 14;155(6):064105. doi: 10.1063/5.0059742
Ebad-Allah J, Rojewski S, Vöst M, Eickerling G, Scherer W, Uykur E et al. Pressure-Induced Excitations in the Out-of-Plane Optical Response of the Nodal-Line Semimetal ZrSiS. Physical Review Letters. 2021 Aug 11;127(7):076402. doi: 10.1103/PhysRevLett.127.076402
Bakowies D, von Lilienfeld OA. Density Functional Geometries and Zero-Point Energies in Ab Initio Thermochemical Treatments of Compounds with First-Row Atoms (H, C, N, O, F). Journal of Chemical Theory and Computation. 2021 Aug 10;17(8):4872-4890. doi: 10.1021/acs.jctc.1c00474
Lemm D, von Rudorff GF, von Lilienfeld OA. Machine learning based energy-free structure predictions of molecules, transition states, and solids. Nature Communications. 2021 Jul 22;12(1):4468. doi: 10.1038/s41467-021-24525-7
Averyanov DV, Liu P, Sokolov IS, Parfenov OE, Karateev IA, Di Sante D et al. Nanoscale synthesis of ionic analogues of bilayer silicene with high carrier mobility. Journal of Materials Chemistry C. 2021 Jul 21;9(27):8545-8551 . Epub 2021 May 24. doi: 10.1039/d1tc01951a
Varrassi L, Liu P, Ergönenc Yavas Z, Bokdam M, Kresse G, Franchini C. Optical and excitonic properties of transition metal oxide perovskites by the Bethe-Salpeter equation. Physical Review Materials. 2021 Jul 9;5(7):074601. doi: 10.1103/PhysRevMaterials.5.074601
Franchini C, Reticcioli M, Setvín M, Diebold U. Polarons in materials. Nature Reviews Materials. 2021 Jul;6(7):560–586. Epub 2021 Mar 19. doi: 10.1038/s41578-021-00289-w
Dirnberger D, Kresse G, Franchini C, Reticcioli M. Electronic State Unfolding for Plane Waves: Energy Bands, Fermi Surfaces, and Spectral Functions. Journal of Physical Chemistry C. 2021 Jun 17;125(23):12921–12928. doi: 10.1021/acs.jpcc.1c02318
Tapavicza E, von Rudorff GF, De Haan DO, Contin M, George C, Riva M et al. Elucidating an Atmospheric Brown Carbon Species-Toward Supplanting Chemical Intuition with Exhaustive Enumeration and Machine Learning. Environmental Science & Technology. 2021 Jun 15;55(12):8447-8457. doi: 10.1021/acs.est.1c00885
Liu P, Verdi C, Karsai F, Kresse G. α−β phase transition of zirconium predicted by on-the-fly machine-learned force field. Physical Review Materials. 2021 May 24;5(5):053804. doi: 10.1103/PhysRevMaterials.5.053804
Veliz JCSV, Koner D, Schwilk M, Bemish RJ, Meuwly M. The C(
3P) + O
2(
3Σ
g
-) → CO
2↔ CO(
1Σ
+) + O(
1D)/O(
3P) reaction: thermal and vibrational relaxation rates from 15 K to 20 000 K. Physical Chemistry Chemical Physics. 2021 May 21;23(19):11251–11263. Epub 2021 Apr 12. doi: 10.1039/d1cp01101d
von Rudorff GF, von Lilienfeld OA. Simplifying inverse materials design problems for fixed lattices with alchemical chirality. Science Advances. 2021 May 19;7(21). doi: 10.1126/sciadv.abf1173
Ceriotti M, Clementi C, Anatole von Lilienfeld O. Machine learning meets chemical physics. Journal of Chemical Physics. 2021 Apr 28;154(16):160401. Epub 2021 Apr 23. doi: 10.1063/5.0051418
Showing entries 101 - 120 out of 628