Effect of conjugated system extension on structural features and electron-density distribution in charge–transfer difluoroborates

Ośmiałowski, Borys; Dziuk, Błażej; Ejsmont, Krzysztof; Chęcińska, Lilianna; Dobrzańska, Liliana

doi:10.1107/s2053229621012249

Cited by 1 publication

(1 citation statement)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As stated above, the set of molecules ( Scheme 1 ) considered encompasses a wide range of structural features, i.e., (i) a rigid molecule ( A-4 ), (ii) molecules with an unsubstituted phenylene moiety having significant rotational freedom ( A-7 , B-1 , B-2 ), (iii) compounds with a donor–acceptor substituted phenylene moiety ( A-1 , B-2 , etc. ), (iv) derivatives with a vinylene linker that are prone to photoisomerization, which dramatically tunes the spectral signatures 99 ( C series), and (v) a molecule with two vinylene linkers 100 ( A-3 ). The structural variability present in the set leads to a wide range of charge-transfer properties for the lowest electronic excited states, as illustrated by the variable experimental absorption band widths (see Figures S1–S3 in the SI).…”

Section: Resultsmentioning

confidence: 99%

Cost-Effective Simulations of Vibrationally-Resolved Absorption Spectra of Fluorophores with Machine-Learning-Based Inhomogeneous Broadening

Petrusevich

Bousquet

Ośmiałowski

et al. 2023

J. Chem. Theory Comput.

Self Cite

View full text Add to dashboard Cite

The results of electronic and vibrational structure simulations are an invaluable support for interpreting experimental absorption/emission spectra, which stimulates the development of reliable and cost-effective computational protocols. In this work, we contribute to these efforts and propose an efficient first-principle protocol for simulating vibrationally-resolved absorption spectra, including nonempirical estimations of the inhomogeneous broadening. To this end, we analyze three key aspects: (i) a metric-based selection of density functional approximation (DFA) so to benefit from the computational efficiency of time-dependent density function theory (TD-DFT) while safeguarding the accuracy of the vibrationally-resolved spectra, (ii) an assessment of two vibrational structure schemes (vertical gradient and adiabatic Hessian) to compute the Franck–Condon factors, and (iii) the use of machine learning to speed up nonempirical estimations of the inhomogeneous broadening. In more detail, we predict the absorption band shapes for a set of 20 medium-sized fluorescent dyes, focusing on the bright ππ ★ S0 → S1 transition and using experimental results as references. We demonstrate that, for the studied 20-dye set which includes structures with large structural variability, the preselection of DFAs based on an easily accessible metric ensures accurate band shapes with respect to the reference approach and that range-separated functionals show the best performance when combined with the vertical gradient model. As far as band widths are concerned, we propose a new machine-learning-based approach for determining the inhomogeneous broadening induced by the solvent microenvironment. This approach is shown to be very robust offering inhomogeneous broadenings with errors as small as 2 cm–1 with respect to genuine electronic-structure calculations, with a total CPU time reduced by 98%.

show abstract

Section: Resultsmentioning

confidence: 99%