https://ifp.hal.science/hal-03436849Liu, HangtaoHangtaoLiuTHU - Tsinghua University [Beijing]Yang, FufangFufangYangTHU - Tsinghua University [Beijing]DTU - Danmarks Tekniske Universitet = Technical University of DenmarkIFPEN - IFP Energies nouvelles - IFPEN - IFP Energies nouvellesYang, XiaoxianXiaoxianYangUWA - The University of Western AustraliaYang, ZhenZhenYangTHU - Tsinghua University [Beijing]Duan, YuanyuanYuanyuanDuanTHU - Tsinghua University [Beijing]Modeling the Thermal Conductivity of Hydrofluorocarbons, Hydrofluoroolefins and their Binary Mixtures using Residual Entropy Scaling and Cubic-plus Association Equation of StateHAL CCSD2021Residual entropy scalingCubic-plus-association equation of stateThermal conductivityHydrofluorocarbonHydrofluoroolefin[PHYS] Physics [physics][SDE] Environmental SciencesBelli, Catherine2021-11-19 15:20:022022-08-05 12:38:202021-11-22 13:19:23enJournal articleshttps://ifp.hal.science/hal-03436849/document10.1021/acs.organomet.0c00709application/pdf1Thermal conductivity strongly impacts heat transfer, and thus is an important thermophysical property for refrigeration and medium-low-temperature heat utilization systems. In this work, the residual entropy scaling incorporating cubic-plus-association equation of state, as a convenient and robust modeling approach for the transport properties of pure and mixture fluids of which the experimental data are scarce or unavailable, is extended to the thermal conductivity of hydrofluorocarbons, hydrofluoroolefins, and their binary mixtures. For all the investigated pure and mixture fluids, the dependence of the thermal conductivity on the thermodynamic state is reduced to a â€˜universalâ€™ univariate function of the rescaled residual entropy with one adjustable parameter for each pure fluid and no further adjustable parameter for mixtures. A new formulation of the reference thermal conductivity is proposed to improve the accuracy for the binary mixtures. The model reproduces the thermal conductivity of the investigated pure and mixture fluids with the root mean square deviation of 2.9% in gas, liquid, and supercritical regions. The lack or uneven distribution of the data is overcome based on the residual entropy scaling with the extensive data of R134a as a reference.