Multiscale modeling of charge transfer in polymers with flexible backbones
Literature Information
Masahiro Sato, Akiko Kumada, Kunihiko Hidaka
In order to evaluate the carrier transfer properties in polymers with flexible backbones, we have proposed a simplified multi-scale modeling approach combining molecular dynamics simulations, first-principles calculations and kinetic Monte Carlo simulations. Hole transfer in amorphous polyethylene (PE) is studied as a model system. It is shown that the characteristic length scale of hole localized states in PE is comparable to the Kuhn length of PE, which is the characteristic length scale in terms of the geometric structure. Because a PE oligomer whose length is equivalent to the Kuhn length (C12H26) has a similar electronic structure to amorphous PE, C12H26 is considered as an approximate model of amorphous PE. In line with experimental findings, computed hole mobility in the amorphous PE oligomer is several orders of magnitude smaller than that in crystalline PE. We show that this difference originates from strong hole localization and large site energy variation in amorphous PE due to the conformational disorder of PE oligomer chains. The agreement between experimental and calculated hole mobilities strongly supports the rationale of our modeling approach. The modeling approach proposed in this paper is considered capable of predicting carrier mobilities in polymers with flexible backbones with reasonable computational load.
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Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.














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