Toward highly efficient hyperfluorescence-based emitters through excited-states alignment using novel optimally tuned...

Area of Science:

• Materials Science
• Computational Chemistry
• Organic Electronics

Background:

• Hyperfluorescence is a key strategy for high-performance organic light-emitting diodes (OLEDs), demanding precise excited-state alignment in fluorescent emitters (FEs).
• Accurate theoretical prediction of excited-state ordering in FEs is challenging but critical for efficient energy transfer from sensitizers (e.g., those with thermally activated delayed fluorescence - TADF) to FEs.

Purpose of the Study:

• To develop and validate advanced theoretical models for accurately describing the excited-state ordering in FEs for hyperfluorescence OLEDs.
• To investigate the influence of various computational parameters, including density functional approximations and exchange contributions, on excited-state alignment predictions.

Main Methods:

• Utilized optimally tuned range-separated hybrid functionals (OT-RSHs), including coupled versions with the polarizable continuum model (OT-RSHs-PCM) and screened versions (OT-SRSHs).
• Analyzed the impact of density functional approximations, short- and long-range Hartree-Fock (HF) exchange, and range-separation parameters on excited-state ordering.
• Validated models against experimentally known hyperfluorescence emitters.

Main Results:

• No single combination of parameters universally yielded correct excited-state ordering; a specific compromise is necessary.
• Generalized gradient approximation-based OT-RSHs-PCM with correct asymptotic behavior and low short-range HF exchange demonstrated superior performance.
• The developed models outperformed standard approximations and were used for computational design of novel FE candidates.

Conclusions:

• The proposed OT-RSHs-PCM models offer a reliable approach for theoretical modeling and experimental validation in hyperfluorescence OLED research.
• These models are essential for the rational design of efficient FEs for next-generation OLED devices.
• Accurate excited-state alignment prediction is paramount for advancing hyperfluorescence OLED technology.