Computational Characterization of Quantum-Dot Light-Emitting Diodes by Combinatorial Exciton Recombination Parameters and Photon Extraction Efficiency

Quantum-dot light-emitting diodes (QD-LEDs) have gained significant attention for next-generation display and lighting systems owing to their superior color selectivity and color purity. To maximize the efficiency of QD-LED devices, it is of great importance to identify the key factors that govern their electro-optical properties. The efficiency of QD-LED devices is strongly influenced by combinatorial processes, represented by the Shockley-Read-Hall rate A, Langevin strength B, and Auger probability C (ABC parameters) of quantum-dots (QDs), along with photon extraction efficiency of QD-LED devices. In this study, an integrated computational framework is proposed to accurately analyze the electro-optical properties of QD-LED devices. The experimental device properties are characterized by ABC and photon extraction efficiency parameters through an innovative numerical data-fitting procedure. Utilizing these parameters, a parametric analysis is performed based on a complete computational charge transport simulation model to explore the influence of the combinatorial exciton recombination processes. This computational framework aligns excellently with experimental results, showcasing its remarkable reliability and effectiveness in both quantitatively characterizing QD nanoparticles and in the detailed analysis of the electro-optical properties of QD-LED devices. Quantum-dot light-emitting diodes (QD-LEDs) have gained significant attention for next-generation display and lighting systems. Electro-optical properties of QD-LEDs are rigorously characterized by integrated computational frameworks with combinatorial QD material parameters for charge transport and ABC models. The computational framework shows reliable performances in quantitatively characterizing QD nanoparticles and in analyzing the electro-optical properties of the QD-LED devices. image