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To address this, we implemented machine learning algorithms to establish quantitative structure-property relationship models, predicting key optoelectronic characteristics, such as full width at half maximum (FWHM) and main peak wavelength, for deep-blue MR candidates. Using these methodologies, we crafted \u03bd-DABNA-O-xy and developed deep-blue organic light-emitting diodes featuring a Commission Internationale de l\u2019Eclairage y of 0.07 and an FWHM of 19 nm. The maximum external quantum efficiency reached ca. 27.5% with a binary emission layer, which increased to 41.3% with the hyperfluorescent architecture, effectively mitigating efficiency roll-off. 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