Assessment and Ranking of Difluoromethane (R32) and Pentafluoroethane (R125) Interatomic Potentials Using Several Thermophysical and Transport Properties Across Multiple State Points

B Agbodekhe and E Marin-Rimoldi and Y Zhang and AW Dowling and EJ Maginn, JOURNAL OF CHEMICAL AND ENGINEERING DATA, 69, 427-444 (2023).

DOI: 10.1021/acs.jced.3c00379

Difluoromethane (R32) and pentafluoroethane (R125) are two common hydrofluorocarbon refrigerants, often used in a mixture termed R410A. Many refrigerants, including R32 and especially R125, have high global warming potentials and so are being phased out. There is a desire to develop processes that can separate and recover these materials, which means that there is a need to determine the thermodynamic and transport properties of these fluids. In this work, we evaluate the ability of molecular dynamics simulations to determine the key thermodynamic and transport properties of these two fluids. We test whether classical interatomic force fields (FFs) parametrized against vapor-liquid equilibrium (VLE) data using a machine learning directed (MLD) approach can also yield accurate estimates of other key properties. The top- performing MLD FFs tuned against VLE data were nearly indistinguishable based on VLE results. This work seeks to investigate if these MLD-tuned FFs are transferable to other properties not used in tuning them and if they can be ranked to identify the "best" FFs. Literature FFs, one each for R32 and R125, are included in the study. A total of ten FFs were tested. Thermal conductivity (lambda), viscosity (eta), self-diffusivity (D), liquid density (rho), isobaric heat capacity (C-P), isochoric heat capacity (C-V), thermal expansivity (a(P)), thermal pressure coefficient ((gamma)rho), isothermal compressibility (beta(T)), speed of sound (c(sound)), Joule-Thomson coefficient (mu(JT)), and center of mass radial distribution functions (g(r)) were computed using molecular dynamics and compared with experiments when possible. Somewhat surprisingly, the MLD-tuned FFs are found to be transferable to a wide range of properties not used in tuning them. The MLD-tuned FFs were ranked. The FFs labeled R32(a) and R125(b) were found to be the "best" FFs for R32 and R125, respectively, across a broad range of properties. The MLD-tuned FFs were found to be superior to previously developed literature FFs.

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