Multi-Objective Optimization of the Electro-Optical Performances of Fluorescent OLEDs Based on Defect-State and ETL/HTL Thickness Analysis

In scientific research, the optimization of organic light-emitting diodes (OLEDs) is generally achieved through a lengthy and expensive experimental process as new ideas and configurations are tested on real devices. Electro-optical simulation allows for the rapid evaluation of key performance parameters of device structures, thus reducing manufacturing time and costs. This paper presents an original contribution to the electro-optical modeling and optimization of multilayer OLED devices using the Non-dominated Sorting Genetic Algorithm II (NSGA-II). This optimization explicitly incorporates defect states within the ITO/NPB/Alq3:C545T/Alq3/LiF-Al structure. The simulated model is calibrated using experimental data by fitting the trap state distribution. The Pareto front resulting from the multi-objective optimization identifies a set of non-dominated configurations, including an optimal intermediate structure defined by an electron transport layer (ETL) thickness of approximately 42 nm and a hole transport layer (HTL) thickness of approximately 53 nm. This configuration leads to a limited reduction of 1.75–2% in current efficiency (ηc) while offering a remarkable improvement of 23–30% in power efficiency (ηp) compared to the extreme configurations of the optimal Pareto set. Thus, this solution represents an optimal Pareto trade-off between high current efficiency and improved power efficiency. This paper shows that combining defect modeling and thickness optimization provides a reliable framework for the electro-optical optimization of OLED devices. Future work will extend this approach to spectral and colorimetric analysis.