Over the last few decades, researchers have developed a number of empirical and theoretical models for the correlation and prediction of the thermophysical properties of pure fluids and mixtures treated as pseudo-pure fluids. In this paper, a survey of all the state-of-the-art formulations of thermophysical properties is presented. The most-accurate thermodynamic properties are obtained from multiparameter Helmholtz-energy-explicit-type formulations. For the transport properties, a wider range of methods has been employed, including the extended corresponding states method. All of the thermophysical property correlations described here have been implemented into CoolProp, an open-source thermophysical property library. This library is written in C++, with wrappers available for the majority of programming languages and platforms of technical interest. As of publication, 110 pure and pseudo-pure fluids are included in the library, as well as properties of 40 incompressible fluids and humid air. The source code for the CoolProp library is included as an electronic annex.

Rosenfeld proposed two different scaling approaches to model the transport properties of fluids, separated by 22 years, one valid in the dilute gas, and another in the liquid phase. In this work, we demonstrate that these two limiting cases can be connected through the use of a novel approach to scaling transport properties and a bridging function. This approach, which is empirical and not derived from theory, is used to generate reference correlations for the transport properties of the Lennard-Jones 12-6 fluid of viscosity, thermal conductivity, and self-diffusion. This approach, with a very simple functional form, allows for the reproduction of the most accurate simulation data to within nearly their statistical uncertainty. The correlations are used to confirm that for the Lennard-Jones fluid the appropriately scaled transport properties are nearly monovariate functions of the excess entropy from low-density gases into the supercooled phase and up to extreme temperatures. This study represents the most comprehensive metastudy of the transport properties of the Lennard-Jones fluid to date.

The NIST REFPROP software program is a powerful tool for calculating thermophysical properties of industrially important fluids, and this manuscript describes the models implemented in, and features of, this software. REFPROP implements the most accurate models available for selected pure fluids and their mixtures that are valid over the entire fluid range including gas, liquid, and supercritical states, with the goal of uncertainties approaching the level of the underlying experimental data. The equations of state for thermodynamic properties are primarily of the Helmholtz energy form; a variety of models are implemented for the transport properties. We document the models for the 147 fluids included in the current version. A graphical user interface generates tables and provides extensive plotting capabilities. Properties can also be accessed through third-party apps or user-written code via the core property subroutines compiled into a shared library. REFPROP disseminates international standards in both the natural gas and refrigeration industries, as well as standards for water/steam.

This work investigates the link between residual entropy and viscosity based on wide-ranging, highly accurate experimental and simulation data. This link was originally postulated by Rosenfeld in 1977, and it is shown that this scaling results in an approximately monovariate relationship between residual entropy and reduced viscosity for a wide range of molecular fluids (argon, methane, CO 2 , SF 6 , refrigerant R-134a (1,1,1,2-tetrafluoroethane), refrigerant R-125 (pentafluoroethane), methanol, and water), and a range of model poten-arXiv:1809.05682v1 [physics.chem-ph]

The residual entropy scaling of viscosity was applied to pure refrigerants, including natural refrigerants, hydrofluoroolefins, hydrochlorofluoroolefins, perfluorocarbons, hydrofluorocarbons, chlorofluorocarbons, and hydrochlorofluorocarbons and their mixtures. Experimental temperature, pressure, and viscosity data of 39 pure refrigerants, including more than 15,000 experimental data values from more than 400 literature sources, were used to build a univariate correlation function between the reduced residual viscosity and the dimensionless residual entropy. The correlation function contains only four fitted parameters and a fluid-specific scaling factor. Approximately, 80.0% of the experimental data are predicted within 5.0% when the fluid-specific fitted parameters are used. About 80.0% of the experimental data collapse onto one single curve within 7.9% when the global fitted parameters and the fluid-specific scaling factor were adopted for the correlation function. The correlation function is able to predict mixture viscosity without any additional empirical parameters. Approximately, 80.0% of the experimental data of 27 binary or multi-component mixtures composed by the investigated pure components, encompassing 2890 experimental values from more than 20 literature sources, agree with the correlation function within 7.9%, which is as good as the comparison for pure fluids. The commonly used extended corresponding states model has as many as four more parameters for each pair of components and has been optimized for some of the binaries; therefore, it generally yields better agreement than the proposed correlation function for binary mixtures but similar performance for multi-component mixtures.