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Computational hole mobilities in (pseudo-)amorphous organic semiconductors.
Manuel Pérez-Escribano1, Jesús Cerdá1, Enrique Ortí1
1Instituto de Ciencia Molecular (ICMol), Universitat de València, Paterna 46980, Spain.
Accurately modeling charge transport in organic semiconductors is challenging. This study introduces a multiscale computational method that accurately predicts hole mobilities by considering film morphology, crucial for designing new materials.
Area of Science:
- Materials Science
- Computational Chemistry
- Organic Electronics
Background:
- Accurate modeling of charge transport in organic semiconductors is crucial for device performance.
- Amorphous and pseudo-amorphous films in optoelectronic devices present modeling challenges.
- Understanding morphology's impact on charge transport is key for material design.
Purpose of the Study:
- To develop a multiscale computational protocol for predicting hole mobilities in non-crystalline organic semiconductors.
- To investigate the influence of different film morphologies on charge transport properties.
- To establish a framework for the rational design of next-generation organic semiconductors.
Main Methods:
- Integration of density functional theory (DFT), molecular dynamics (MD), docking, and kinetic Monte Carlo (KMC) simulations.
- Modeling of amorphous, pseudo-amorphous films, and docking aggregates.
- Prediction of hole mobilities for ten hole-transporting molecules.
Main Results:
- Achieved order-of-magnitude accuracy in predicting hole mobilities.
- Demonstrated that considering both amorphous disorder and molecular aggregates is essential for accurate predictions.
- Reproduced experimentally observed mobility trends, correlating them with molecular structure (planarity, π-conjugation).
Conclusions:
- The developed multiscale computational protocol provides a robust, morphology-aware framework.
- This approach enables the in silico design and optimization of organic semiconductors.
- Explicitly accounting for film morphology is critical for understanding and predicting charge transport in organic electronic materials.
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