Thermal Conductivity of Real Substances from Excess Entropy Scaling Using PCP-SAFT

被引:79
|
作者
Hopp, Madlen [1 ]
Gross, Joachim [1 ]
机构
[1] Univ Stuttgart, Inst Thermodynam & Thermal Proc Engn, Pfaffenwaldring 9, D-70569 Stuttgart, Germany
关键词
FLUID TRANSPORT-COEFFICIENTS; VISCOSITY MODEL; CORRESPONDING-STATES; DYNAMIC PROPERTIES; PREDICTION; ANOMALIES; LIQUID; ARGON; DIFFUSIVITY; EQUATIONS;
D O I
10.1021/acs.iecr.6b04289
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
Entropy scaling is an intriguingly simple approach for correlating and predicting transport properties of real substances and mixtures. It is convincingly documented in the literature that entropy scaling is indeed a firm concept for the shear viscosity of real substances, including hydrogen bonding species and strongly nonspherical species. We investigate whether entropy scaling is applicable for thermal conductivity. It is shown that the dimensionless thermal conductivity (thermal conductivity divided by a reference thermal conductivity) does not show a single-variable dependence on residual entropy, for obvious choices of a reference thermal conductivity. We perform a detailed analysis of experimental data and propose a reference thermal conductivity that is itself a simple function of the residual entropy. We then obtain good scaling behavior for the entire fluid region for water and 147 organic substances from various chemical families: linear and branched alkanes, alkenes, aldehydes, aromatics, ethers, esters, ketones, alcohols, and acids. The residual entropy is calculated from the Perturbed Chain Polar Statistical Associating Fluid Theory equation of state. The correlation of experimental data requires two parameters for pure substances with scarce experimental data and up to five parameters for experimentally well-characterized species. The correlation results for all substances lead to average relative deviations of 4.2% to experimental data. To further assess the approach, we analyze extrapolations to states not covered by experimental data and find very satisfying results.
引用
收藏
页码:4527 / 4538
页数:12
相关论文
共 50 条
  • [31] Thermal Conductivity via Entropy Scaling: An Approach That Captures the Effect of Intramolecular Degrees of Freedom
    Hopp, Madlen
    Mele, Julia
    Hellmann, Robert
    Gross, Joachim
    INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2019, 58 (39) : 18432 - 18438
  • [32] Multi-objective optimization of PC-SAFT parameters for ionic liquids from density and viscosity data using entropy scaling
    Melfi, Diego T.
    Scurto, Aaron M.
    FLUID PHASE EQUILIBRIA, 2025, 595
  • [33] Transport properties of HFC and HFO based refrigerants using an excess entropy scaling approach
    Fouad, Wael A.
    Vega, Lourdes F.
    JOURNAL OF SUPERCRITICAL FLUIDS, 2018, 131 : 106 - 116
  • [34] Evaluation on Excess Entropy Scaling Method Predicting Thermal Transport Properties of Liquid HFC/HFO Refrigerants
    Wang, Xuehui
    Wright, Edward
    Gao, Neng
    Li, Ying
    JOURNAL OF THERMAL SCIENCE, 2022, 31 (05) : 1465 - 1475
  • [35] Evaluation on Excess Entropy Scaling Method Predicting Thermal Transport Properties of Liquid HFC/HFO Refrigerants
    Xuehui Wang
    Edward Wright
    Neng Gao
    Ying Li
    Journal of Thermal Science, 2022, 31 : 1465 - 1475
  • [36] Evaluation on Excess Entropy Scaling Method Predicting Thermal Transport Properties of Liquid HFC/HFO Refrigerants
    WANG Xuehui
    WRIGHT Edward
    GAO Neng
    LI Ying
    JournalofThermalScience, 2022, 31 (05) : 1465 - 1475
  • [37] Aviation Turbine Fuel Thermal Conductivity: A Predictive Approach Using Entropy Scaling-Guided Machine Learning with Experimental Validation
    Malatesta, William Anthony
    Yang, Bao
    ACS OMEGA, 2021, 6 (43): : 28579 - 28586
  • [38] Estimation of Thermal Conductivities for Binary and Ternary Liquid Mixtures Using Excess Thermal Conductivity Model
    Hiroyuki Matsuda
    Katsumi Tochigi
    Kiyofumi Kurihara
    Toshitaka Funazukuri
    Journal of Solution Chemistry, 2023, 52 : 105 - 133
  • [39] General method for prediction of thermal conductivity for well-characterized hydrocarbon mixtures and fuels up to extreme conditions using entropy scaling
    Rokni, Houman B.
    Moore, Joshua D.
    Gupta, Ashutosh
    McHugh, Mark A.
    Mallepally, Rajendar R.
    Gavaises, Manolis
    FUEL, 2019, 245 (594-604) : 594 - 604
  • [40] Estimation of Thermal Conductivities for Binary and Ternary Liquid Mixtures Using Excess Thermal Conductivity Model
    Matsuda, Hiroyuki
    Tochigi, Katsumi
    Kurihara, Kiyofumi
    Funazukuri, Toshitaka
    JOURNAL OF SOLUTION CHEMISTRY, 2023, 52 (01) : 105 - 133