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DOI 10.1021/acs.jctc.6c00071

Медицинская библиотека · Journal of chemical theory and computation · 2026

Efficient and Accurate Modeling of Anisotropic Electrostatic Landscapes in Amorphous Organic Semiconductor Films.

Kim Yoonki, Son Jiho, Moon Geongi, Choi Hyeonsik, Gil Jaeyoung, Lee Jay-Hak, Jung YounJoon

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Аннотация

Precise modeling of the energetic landscape is a prerequisite for predicting the charge transport properties of organic light-emitting diodes (OLEDs). However, a significant gap remains between highly accurate but computationally prohibitive self-consistent field (SCF) calculations and efficient but often oversimplified models. In this work, we propose an accurate and effective electrostatic framework with high computational efficiency that encompasses these complex polarization effects through an anisotropically screened dielectric function augmented by a position-dependent background potential. Optimized for the archetypal host material 4,4'-Bis(N-carbazolyl)-1,1'-biphenyl (CBP), our model accurately reproduces the microscopic details, including the polarization-induced stabilization and the surface-reduced energetic disorder, while maintaining high transferability across independent morphological realizations and film thicknesses down to D ≈ 4 nm. Kinetic Monte Carlo (KMC) simulations further confirm that the model faithfully replicates the reference mean squared displacement (MSD) and current-voltage (JV) characteristics, whereas simple image charge models significantly underestimate the current density by failing to describe the downhill gradient at the interface. This framework offers a practical pathway for generating realistic energy distributions for large-scale device simulations, effectively bridging the tradeoff between physical accuracy and computational efficiency.

Для цитирования: Kim Yoonki, Son Jiho, Moon Geongi, Choi Hyeonsik, Gil Jaeyoung, Lee Jay-Hak, Jung YounJoon. Efficient and Accurate Modeling of Anisotropic Electrostatic Landscapes in Amorphous Organic Semiconductor Films.. Journal of chemical theory and computation. 2026. DOI: 10.1021/acs.jctc.6c00071.
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