Prediction of Thermal Conductivity for Guiding Molecular Design of Liquids

Xiangyang Liu, Chengjie Wang, Tian Lan, Maogang He*, Ying Zhang

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

18 引用 (Scopus)

摘要

There is a need for molecular-structure-based predictive models that guide the molecular design of materials with desired properties. Herein, we developed a general model based on group-contribution (GC) theory and vibrational theory that predicts the thermal conductivity of different types of liquids which are used as working media in energy conversion and environmental protection, including three types of organic molecular liquids, ionic liquids, and their mixtures. We also derive the pressure dependencies of the thermal conductivities of these liquids for the first time. The GC model is extended to determining the thermal conductivities of mixtures by developing a group division method and mixing rules that operate without knowing the thermal conductivity of each component. The excellent performance of the presented model is verified by comparing the predicted thermal conductivities with experimental data and those from other models. On the basis of the developed model, group sequences are established according to their contributions to thermal conductivity, and the sensitivity of thermal conductivity to temperature and pressure is analyzed to guide the molecular design of liquids.

源语言英语
页(从-至)6022-6032
页数11
期刊ACS Sustainable Chemistry and Engineering
8
15
DOI
出版状态已出版 - 20 4月 2020
已对外发布

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