Predicting Accurate Fluorescent Spectra For High Molecular Weight Polycyclic Aromatic Hydrocarbons Using Density Functional Theory

Keywords

Density functional theory; Fluorescence; Polarized continuum model; Polycyclic aromatic hydrocarbons; Shpol'skii

Abstract

The ability of density functional theory (DFT) methods to predict accurate fluorescence spectra for polycyclic aromatic hydrocarbons (PAHs) is explored. Two methods, PBE0 and CAM-B3LYP, are evaluated both in the gas phase and in solution. Spectra for several of the most toxic PAHs are predicted and compared to experiment, including three isomers of C24H14 and a PAH containing heteroatoms. Unusually high-resolution experimental spectra are obtained for comparison by analyzing each PAH at 4.2 K in an n-alkane matrix. All theoretical spectra visually conform to the profiles of the experimental data but are systematically offset by a small amount. Specifically, when solvent is included the PBE0 functional overestimates peaks by 16.1 ± 6.6 nm while CAM-B3LYP underestimates the same transitions by 14.5 ± 7.6 nm. These calculated spectra can be empirically corrected to decrease the uncertainties to 6.5 ± 5.1 and 5.7 ± 5.1 nm for the PBE0 and CAM-B3LYP methods, respectively. A comparison of computed spectra in the gas phase indicates that the inclusion of n-octane shifts peaks by +11 nm on average and this change is roughly equivalent for PBE0 and CAM-B3LYP. An automated approach for comparing spectra is also described that minimizes residuals between a given theoretical spectrum and all available experimental spectra. This approach identifies the correct spectrum in all cases and excludes approximately 80% of the incorrect spectra, demonstrating that an automated search of theoretical libraries of spectra may eventually become feasible.

Publication Date

10-1-2016

Publication Title

Journal of Molecular Spectroscopy

Volume

328

Number of Pages

37-45

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1016/j.jms.2016.06.015

Socpus ID

84979261619 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84979261619

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