1 to 4 of 4 Results
Oct 31, 2023 - SFB 1333 C4 - Kästner group, ITheoC
Gugeler, Katrin; Kästner, Johannes, 2023, "Replication data of Kästner group for: "Tethering chiral Rh diene complexes inside mesoporous solids: experimental and theoretical study of substituent, pore and linker effects on asymmetric catalysis"", https://doi.org/10.18419/darus-3561, DaRUS, V1
In this dataset, all simulation data are listed. That includes all geometry optimizations and single-point calculations and files from the conformational sampling. Furthermore, the spreadsheet with the collected data and the figures with the visualizations of the structures are l... |
Oct 19, 2023 - SFB 1333 C4 - Kästner group, ITheoC
Klostermann, Sina; Kästner, Johannes, 2023, "Replication data of Kästner group for: "How Solid Surfaces Control Stability and Interactions of Supported Cationic Cu^I(dppf) Complexes - A Solid-State NMR Study"", https://doi.org/10.18419/darus-3668, DaRUS, V1
In this dataset, all simulation data are listed. That includes all geometry optimizations and single-point calculations and solid-state NMR calculations. The folders with the data are named similar to the nomenclature in the publication. All structures are named "*.xyz" and the i... |
Oct 19, 2023 - SFB 1333 A3 - Schlaich group, ICP
Yang, Jie; Kondrat, Svyatoslav; Lian, Cheng; Liu, Honglai; Schlaich, Alexander; Holm, Christian, 2023, "Replication Data for: Solvent Effects on Structure and Screening in Confined Electrolytes", https://doi.org/10.18419/darus-3743, DaRUS, V1, UNF:6:KtlgApor9/WXUtTKp63TBw== [fileUNF]
This is the repository holding the data and python scripts we used for creating the corresponding figures in the publication. Tabular files include the ion and solvent (for solvent-explicit simulations) densiies for a hard-sphere primitive electrolyte model confined between two c... |
May 26, 2023 - Materials Design
Gubaev, Konstantin; Zaverkin, Viktor; Srinivasan, Prashanth; Duff, Andrew; Kästner, Johannes; Grabowski, Blazej, 2023, "Data for: Performance of two complementary machine-learned potentials in modelling chemically complex systems", https://doi.org/10.18419/darus-3516, DaRUS, V1
Data for the publication "Performance of two complementary machine-learned potentials in modelling chemically complex systems", npj. Comp. Mat. This data set contains the datasets of structures in cfg and npz formats INCAR file which was used for VASP calculations python script f... |