TD-DFT Benchmark Data for Camphorquinone Photoabsorption

Computational inputs and outputs for benchmarking four time-dependent density functional theory (TD-DFT) functionals against the experimental photoabsorption peak of camphorquinone near 468 nm. It includes optimized ground-state geometries, TD-DFT excitation calculations, and Natural Transition Orbital (NTO) data for a clinically established dental photoinitiator. The data supports reproducibility and methodological comparison for quantum-chemical studies of carbonyl-based photoinitiators.

Use Cases

• Compare computed absorption maxima from B3LYP, PBE0, CAM-B3LYP, and ωB97XD TD-DFT functionals against the experimental benchmark of 468 nm.
• Analyze Natural Transition Orbital (NTO) data to characterize the excitation as a localized carbonyl-centered n(O) → π*(C=O) transition.
• Reproduce ground-state geometries optimized with the B3LYP functional and a 6-31G(d) basis set under an implicit solvent model (ε = 4.0).
• Use the provided computational outputs for in silico screening of related carbonyl-based photoinitiators in dental resin applications.

Strengths

• Includes data for benchmarking four distinct TD-DFT functionals (B3LYP, PBE0, CAM-B3LYP, ωB97XD) under consistent methodological conditions.
• Provides Natural Transition Orbital (NTO) data to support assignment of the excitation character.
• Ground-state optimization was performed with a specific basis set (6-31G(d)) and an implicit solvent model representing a resin-relevant dielectric environment (ε = 4.0).

Limitations

• The scope is explicitly limited to vertical excitation benchmarking under an implicit solvent model and does not imply general functional transferability beyond the studied system.
• The dataset is focused on a single molecule (camphorquinone) and its lowest optically allowed singlet excitation, limiting broader chemical applicability.
• Sample data, file formats, and dataset size are unknown, which may complicate initial assessment of data structure and volume.

Provenance

Source

Harvard Dataverse, authored by Bugude, Shiva Shankar.

Collection Method

Computational data generated via density functional theory (DFT) and time-dependent DFT (TD-DFT) calculations.

Freshness

Last updated on 2026-01-26.