Ab initio search of polymer crystals with high thermal conductivity

Ab initio search of polymer crystals with high thermal conductivity
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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
*Kenta Hongo
中科院分区:
材料科学2区
文献类型:
--
作者:
*Keishu Utimula;Tom Ichibha;Ryo Maezono;*Kenta Hongo

文献摘要

相似文献

我们研究了聚合物基因组库中一组聚合物晶体的晶格热导率,以探索高晶格热导率的聚合物体系。在三阶微扰理论和密度泛函理论相结合的情况下,我们用第一性原理方法计算了声子寿命,然后求解了单模驰豫时间近似为计算寿命的线性化Boltzmann输运方程。对典型的高低温聚合物体系,即聚乙烯(PE)晶体和纤维,进行了基准测试,以验证我们的方法。除了PE,我们还评估了聚苯硫醚(PPS)和聚对苯二甲酸乙二酯(PET)的LTC,因为尽管它们的实验LTC值不是从它们的“完美”晶体中获得的,但它们大多是可用的。我们的模拟再现了实验观察到的低温有序化(PE、≫、PPS&>PET)。首次将我们的方案应用于一些聚合物晶体,我们发现在所有考虑的情况中,聚偏氟乙烯(PVDF-β)晶体的β相在低温下具有最高的低温转变温度。我们还发现LTC与能量-体积图的曲率有关。这一曲率可以作为构建现代机器学习模型的描述符之一,以通过数据驱动的方法来进一步探索高LTC聚合物晶体,而不是基于人类的方法。
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.