Dataset for: "Quantification of Geometric Errors Made Simple: Application to Main-Group Molecular Structures"

• Published in: The Journal of Physical Chemistry A
• Main Author: Stefan
• Format: Other/Unknown Material
• Language: unknown
• Published: Zenodo 2023
• Subjects: DFT; computantional chemistry; molecular structures; molecular geometries; errors in geometries; Orca
• Online Access: https://doi.org/10.1021/acs.jpca.1c10688

This dataset contains geometric energy offset (GEO') values for a set of density functional theory (DFT) methods for the B2se set of molecular structures. The data was generated as part of a research project aimed at quantifying geometric errors in main-group molecular structures. The dataset is in XLSX format created with MS Excel (version 16.69), and contains multiple worksheets with GEO' values for different basis sets and DFT methods. The worksheet headings, such as "AVQZ AVTZ AVDZ VQZ VTZ VDZ" represent different basis sets of Dunning theory, and the naming convention "(A)VnZ = aug-cc-pVnZ" is being used to label the worksheets. The data is organized in columns, with the first column providing the molecular ID and the names of the DFT methods specified in the first row of each worksheet. The molecular structures corresponding to each of these IDs can be found in Figure S1 of the supplementary information of the underlying publication [ https://pubs.acs.org/doi/suppl/10.1021/acs.jpca.1c10688/suppl_file/jp1c10688_si_001.pdf ]. The data have been generated from quantum-chemical calculations from the G16 and ORCA 5.0.0 packages, with further computational details, methodology, and data validation strategies (e.g., comparisons with higher-level quantum-chemical calculations) given in the supplementary information of the underlying publication[ J. Phys. Chem. A 2022, 126, 7, 1300–1311] and its supporting information[ https://pubs.acs.org/doi/suppl/10.1021/acs.jpca.1c10688/suppl_file/jp1c10688_si_001.pdf ]. The dataset is expected to be useful to researchers in the field of computational chemistry and materials science. All values are given in kcal/mol. The data is generated by the authors of the underlying publication and it is shared under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. The data is expected to be re-usable and the quality of the data is assured by the authors. The size of the data is 71 KB.