GDB-9-Ex: Quantum chemical prediction of UV/Vis absorption spectra for GDB-9 molecules
Description
We performed calculations of electronic excitation energies and associated oscillator strengths based on the time-dependent density-functional tight-binding (TD-DFTB) method. The SMILES (Simplified molecular-input line-entry system) strings of the molecules from the GDB-9 database were converted to a 3D atomistic structure and stored in a PDB file after preliminary geometry optimization using the Merck Molecular Force Field (MMFF94) in RDKit. The primary information stored in the PDB file archive consists of Cartesian coordinates for each atom of the molecule in their 3D location in space, along with summary information about the structure, sequence, and experiment. We then performed molecular geometry optimization using the density-functional tight-binding (DFTB) method in the electronic ground state, followed by single-point excited states calculations, as described below. The computed excitation energies and associated oscillator strengths can be converted to predict UV/Vis absorption spectra, where excitation energies correspond to absorption peak positions, and oscillator strengths are a good measure of the probability of absorption of visible or UV light in transitions between electronic ground and excited states. Additional methodological information and references are provided in the dataset README file.
Funding Information
DOE Contract Number
DE-AC05-00OR22725Originating Research Organization
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)Sponsoring Organization
Office of Science (SC)Related Works
- IsSupplementedBy (DOI): https://doi.org/10.13139/OLCF/1985521
Details
Release Date
November 22, 2022Subject
MATERIALS SCIENCE, INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY, CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS, ATOMIC AND MOLECULAR PHYSICSKeywords
Python, GDB-9, Time-dependent density-functional tight-binding (TD-DFTB), Predicting Excited States Molecular PropertiesDataset
Dataset Type
ND Numeric DataCite This Dataset:
Lupo Pasini, M., Yoo, P., Mehta, K., Irle, S. (2022). GDB-9-Ex: Quantum chemical prediction of UV/Vis absorption spectra for GDB-9 molecules. Oak Ridge National Laboratory. https://doi.org/10.13139/OLCF/1890227.
Acknowledgements
This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Advanced Scientific Computing Research programs in the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725.