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Reliability of DFT and multiscale modelling for prediction of emission properties of blue TADF luminophores

Donor-acceptor molecules exhibiting TADF are in the heart of third-generation OLEDs. In this study, we apply (TD)DFT and multiscale modelling to assess the reliability of these approaches for prediction of the emission properties of carbazole-triazine (Cz-TRZ) based TADF luminophores. We found that...

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Bibliographic Details
Published in:Optical materials 2024-11, Vol.157, p.116244, Article 116244
Main Authors: Dubinets, N.O., Dominskiy, D.I., Tukachev, N.V., Sosorev, A. Yu
Format: Article
Language:English
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Summary:Donor-acceptor molecules exhibiting TADF are in the heart of third-generation OLEDs. In this study, we apply (TD)DFT and multiscale modelling to assess the reliability of these approaches for prediction of the emission properties of carbazole-triazine (Cz-TRZ) based TADF luminophores. We found that a series of hybrid and doubly hybrid functionals reproduce the experimentally observed trend in the S1→S0 transition energy for single molecules of Cz-TRZ series, verifying the use of these calculations for the emission wavelength prediction. Considering molecular environment of luminophores within QM/MM and QM/EFP methods allowed us to model inhomogeneous broadening of the emission spectra; impact of long-range corrected functionals was revealed. The results obtained provide useful tips for computational studying of the structure-property relationships for TADF luminophores and semiquantitative prediction of their properties. We anticipate that it will stimulate rational design of promising TADF luminophores for doped and non-doped OLEDs. •Reliability of DFT and multiscale methods for prediction of the emission properties of Cz-TRZ TADF fluorophores is studied.•Various functionals reproduce the experimentally observed trend in the emission wavelength for these molecules.•DFT functionals with/without LR correction behave differently in multiscale modelling of the emission spectra broadening.
ISSN:0925-3467
DOI:10.1016/j.optmat.2024.116244