Molecular Dynamics Data for Optimization and Validation of Modeling Techniques for Predicting Structures and Charge Mobilities of P3HT

  • Evan Miller (Data Collector)
  • Matthew L. Jones (Data Collector)
  • Mike Henry (Data Collector)
  • Eric Jankowski (Data Collector)

Dataset

Description

The self-assembled active layer morphology strongly affects the performance of organic electronic devices. In this work, we present the development of an optimized OPLS-UA force-field for the benchmark donor polymer poly(3 -hexylthiophene). With this model, we perform molecular dynamic simulations to predict the self-assembled morphology at a variety of processing conditions - a total of ∼ 350 unique state points. We find that our optimized P3HT model is able to produce the most accurate structural predictions for self-assembled morphologies (as compared to experimental grazing incident X-ray scattering experiments) to-date, despite several assumptions in the interest of computational efficiency. In particular, we consider short oligomer chains, omit electrostatic contributions, treat the solvent implicitly, and equilibrate our systems at initially low thin-film densities. Our structural calculations predict that the highest degrees of order are obtained at low temperatures with good solvents.
Date made available14 Sep 2018

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