This study proposes a model for self-diffusion
coefficients of
pure substances from entropy scaling using the perturbed-chain polar
statistical associating fluid theory (PCP-SAFT) equation of state.
In accordance with the entropy scaling approach proposed by Y. Rosenfeld
[RosenfeldY.
Rosenfeld, Y.
Phys. Rev. A1977152545–2549], we observe that the self-diffusion
coefficient of real substances, once made dimensionless with an appropriate
expression, only depends on residual entropy. The proposed model requires
3 parameters for each pure substance. For substances with scarce experimental
data, however, a scheme is proposed to estimate one or two of these
parameters. We study 133 substances from more than 14 different chemical
families and find the average absolute deviation of 8.2% between the
proposed model and experimental data (9992 data points). The model
shows satisfying robustness for extrapolating self-diffusion coefficients
to conditions rather distant from the state points where experimental
data are available.
The thermal conductivity of gases depends strongly on the vibrational and rotational degrees of freedom of the molecule under consideration. Entropy scaling is based on the residual entropy, which does not capture the intramolecular and rotational contributions. This study proposes a model for the thermal conductivity that accounts for these degrees of freedom. We use the Chapman− Cowling approximation, where contributions of internal degrees of freedom to the thermal conductivity of an ideal gas are related to the self-diffusion coefficient. A resulting expression for the thermal conductivity is used as a reference in entropy scaling. We find experimental values for thermal conductivities in the entire fluid range to be (to good approximation) a function of residual entropy only. This study shows that entropy scaling is a strong approximation also for thermal conductivity, provided a suitable expression is chosen for the reference thermal conductivity.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.