Three-Dimensional Modeling of Organic Light-Emitting Diodes Containing Molecules with Large Electric Dipole Moments

R. Coehoorn (Corresponding author), X. Lin, C.H.L. Weijtens, S. Gottardi, H. van Eersel

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We present the results of a three-dimensional kinetic Monte Carlo (3D KMC) simulation study of the current density and efficiency of a prototypical green phosphorescent organic light-emitting diode within which the TPBi [2,2′,2″-(1,3,5-benzinetriyl)-tris(1-phenyl-1-H-benzimidazole)] molecules that comprise the electron transport layer have a large (7 D) static dipole moment. By explicitly calculating the dipole-induced electrostatic field distribution the additional energetic disorder and the additional internal electrostatic field due to the small net dipole-moment orientation in TPBi are included in a mechanistic manner. The simulation results are compared with the results of an experimental study by B. Sim et al. [ACS Appl. Mater. Interf. 8, 33010 (2016)]. Using a set of simulation parameters that provides a fair agreement with the experimental voltage-dependent current density, external quantum efficiency, and emission profiles, the simulations are used to study the sensitivity to the size and net orientation of the dipole moments. We show how the dipole-induced disorder and the dipole orientation affect the current density, the electron injection efficiency, the blocking of holes by the TPBi layer, the shape of the emission profile, and the quantum efficiency. A key element of the validation of the simulations is a comparison with measured emission profiles, which Sim et al. obtained from sense layer experiments. Explicit KMC simulations of these experiments are used to investigate the expected accuracy with which the emission profiles are probed.

Original languageEnglish
Article number034048
Number of pages18
JournalPhysical Review Applied
Issue number3
Publication statusPublished - Sept 2021

Bibliographical note

Funding Information:
This work is supported by the National Key Research and Development Program of China (Grant No. 2017YFB0404404), the leading talents of Guangdong Province Program (Grant No. 00201504), and the Guangdong Innovative Research Team Program (Grant No. 2013C102).


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