85‐2: Prediction of Triplet Harvesting Ability in Blue Fluorescent Organic Light‐Emitting Diodes Using Deep Learning.

In this paper, we implemented new time dependent exciton decay model based on exciton dynamics using transient electroluminescence profile of fluorescent triplet‐triplet annihilation (TTA) orgarnic light‐emitting diodes (OLEDs). The prompt and delayed components of fluorescent TTA OLED could be distinguished quantitatively and accurate TTA ratio analysis was achieved using the new TTA model. In addition, predictive model of kinetic coefficients and TTA ratio was established using neural network of multilayer perception, and it demonstrated nearly perfect prediction ability of TTA ratio (determination coefficient, R2 = 0.999). The results of this study would contribute to understand TTA mechanisms deeply with exact estimation of major parameters of TTA OLEDs and help future OLED research using deep learning predictive model. [ABSTRACT FROM AUTHOR]