1,451 to 1,460 of 1,480 Results
Nov 3, 2025 -
Replication Data for: A symmetry-preserving and transferable representation for learning the Kohn-Sham density matrix
Gzip Archive - 18.3 GB -
MD5: 4bc6371605d3bf8ecb589d8dbb7d5ab5
Two datasets for m-toluidine obtained with larger basis set. The dataset for 2-Propanol missing in the previous version. |
Nov 3, 2025 -
Replication Data for: A symmetry-preserving and transferable representation for learning the Kohn-Sham density matrix
TAR Archive - 14.6 MB -
MD5: 9606969dc781aa2a3eee9c304e52ba4b
Collection of archives (one for each molecule) containing the Gaussian input files used for the generation of the datasets. |
Nov 3, 2025 -
Replication Data for: A symmetry-preserving and transferable representation for learning the Kohn-Sham density matrix
Gzip Archive - 1.9 KB -
MD5: e0b15c81e8740610cbdeb019cc1ed15e
Scripts for generating Gaussian matrix element files containing the predicted density. |
Nov 3, 2025 -
Replication Data for: A symmetry-preserving and transferable representation for learning the Kohn-Sham density matrix
Plain Text - 3.8 KB -
MD5: 8f184f64b50930c659e93369f120cc94
README file. |
May 20, 2025
Barthwal, Rahul; Rohde, Christian; Wang, Yue, 2025, "Software for "A generalized Riemann problem solver for a hyperbolic model governing two-layer thin film flow"", https://doi.org/10.18419/DARUS-5052, DaRUS, V1
In this project, we developed a Generalized Riemann solver for a hyperbolic model which governs first order dynamics of two-layer thin film flow under the influence of an anti-surfactant. The solver is a one-dimensional spatial-temporal coupled second-order finite-volume solver and can be utilized for further development. |
May 20, 2025 -
Software for "A generalized Riemann problem solver for a hyperbolic model governing two-layer thin film flow"
XZ Archive - 106.3 MB -
MD5: db780a0fa3a8dfb7f3418f105e59d439
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May 20, 2025 -
Software for "A generalized Riemann problem solver for a hyperbolic model governing two-layer thin film flow"
Markdown Text - 1.9 KB -
MD5: 5c87ab5a08fb75e721d568595586a9c7
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Mar 24, 2025 -
Replication Data for: A symmetry-preserving and transferable representation for learning the Kohn-Sham density matrix
Gzip Archive - 37.5 GB -
MD5: 15a906244ec76d846dc661664dc4235c
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Oct 9, 2024
Askarpour, Zahra; Nottoli, Michele; Stamm, Benjamin, 2024, "Replication Data for: Grassmann Extrapolation for Accelerating Geometry Optimization", https://doi.org/10.18419/DARUS-4470, DaRUS, V1
Data for reproducibility of the numerical simulations of the research paper: Grassmann Extrapolation for Accelerating Geometry Optimization |
Gzip Archive - 94.2 MB -
MD5: 7c744146fb39365ea1d6a2b4c160d27d
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