Ab initio search of polymer crystals with high thermal conductivity
Ab initio search of polymer crystals with high thermal conductivity
复制标题
高导热聚合物晶体的从头算研究
DOI:
10.1021/acs.chemmater.9b00020
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发表时间:
2019
期刊:
影响因子:
8.6
通讯作者:
*Kenta Hongo
中科院分区:
文献类型:
--
作者:
*Keishu Utimula;Tom Ichibha;Ryo Maezono;*Kenta Hongo
We investigated the lattice thermal conductivity (LTC) of a subset of polymer crystals from the polymer genome library to explore high LTC polymer systems. We employed a first-principles approach to evaluate the phonon lifetime within the third-order perturbation theory combined with density functional theory and then solved the linearized Boltzmann transport equation with a single-mode relaxation time approximated by the computed lifetime. Typical high LTC polymer systems, namely, polyethylene (PE) crystal and fiber, were benchmarked to validate our approach. In addition to PE, we evaluated the LTC of polyphenylene sulfide (PPS) and poly(ethylene terephthalate) (PET) because, although their experimental LTC values are not obtained from their “perfect” crystals, they are mostly available. Our simulations reproduced an experimentally observed LTC ordering (PE ≫ PPS > PET). Applying our scheme to a number of polymer crystals for the first time, we discovered that the β-phase of a poly(vinylidenesurely fluoride) (PVDF-β) crystal at low temperatures has the highest LTC among all of the cases considered. We also found the LTC correlating to the curvature of an energy–volume plot. This curvature can be used as one of the descriptors of constructing modern machine learning models to further explore high LTC polymer crystals by means of a data-driven approach beyond a human-based one.