PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
June 3, 20260 citations

A theoretical study to understand the photophysical properties of a fluorescent compound (HINA)

View Full Paper
RSRituparna SahaPMPratap MukherjeeDBDebosreeta Bose

Key Points

  • This study aims to understand the photophysical properties of the fluorescent compound HINA using theoretical models.
  • Theoretical investigation using Hartree-Fock and density functional theory models.
  • Calculations performed using the 6-311++G(d,p) basis set in gas phase.
  • Time-Dependent Density Functional Theory (TD-DFT) used for excited-state geometry analysis.
  • Ground-state and excited-state geometries calculated and analyzed.
  • Photophysical properties correlated with optimized structures.
  • Computed findings validated against experimental data.

Abstract

The photophysical properties of fluorescent molecules are investigated theoretically using computational methods, including Hartree-Fock and density functional theory (HF/DFT) models. The observed UV-Visible spectra and related photophysical properties are interpreted using energy values from the ground-state geometry. From the optimized structure excited-state geometry is calculated for further analysis. The structure-property relationship of the fluorescent molecule is analyzed, and theoretical data will be validated against the experimental data. In our present study, the photophysical properties of 3-hydroxy-4-pyridine carboxaldehyde (HINA) are studied theoretically in the gas phase. Using DFT calculation with 6-311++G(d,p) basis set, the ground state geometry and potential energy surface are calculated. In addition, the Time-Dependent Density Functional Theory (TD-DFT) method is used to calculate the excited state geometry of the molecule, and finally, the computed results are compared with experimental data.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Saha et al. (2026) studied this question.

synapsesocial.com/papers/6a1fc530dee9eb8c0dce6965https://doi.org/10.1051/epjconf/202637001022/pdf
Ask AI
Helpful
Bookmark
Share
View Full Paper