Improved Estimates of the Critical Point Constants for Large <i>n</i>‑Alkanes Using Gibbs Ensemble Monte Carlo Simulations

In this work, we present improved estimates of the critical temperature (<i>T</i>_c), critical density (ρ_c), critical pressure (<i>P</i>_c), and critical compressibility factor (<i>Z</i>_c) for <i>n</i>-alkanes with chain lengths as large as C₄₈. These are obtained for several different force field models with Gibbs ensemble Monte Carlo simulations. We implement a recently proposed data analysis method designed to reduce the uncertainty in <i>T</i>_c, ρ_c, <i>P</i>_c, and <i>Z</i>_c when predicted with molecular simulation. The results show a large reduction in the uncertainties compared to the simulation literature with the greatest reduction found for ρ_c, <i>P</i>_c, and <i>Z</i>_c. Previously, even the most computationally intensive molecular simulation studies have not been able to elucidate the <i>n</i>-alkane <i>P</i>_c trend with respect to larger carbon numbers. The results of this study are significant because the uncertainty in <i>P</i>_c is small enough to discern between conflicting experimental data sets and prediction models for large <i>n</i>-alkanes. Furthermore, the results for <i>T</i>_c resolve a discrepancy in the simulation literature with respect to the correct <i>T</i>_c trend for large <i>n</i>-alkanes. In addition, the <i>Z</i>_c results are reliable enough to determine the most accurate prediction trend for <i>Z</i>_c. Finally, finite-size effects are shown to not be significant even for the relatively small system sizes required for efficient simulation of longer chain lengths

New Vapor-Pressure Prediction with Improved Thermodynamic Consistency using the Riedel Equation

Vapor pressure, heat of vaporization, liquid heat capacity, and ideal-gas heat capacity for pure compounds between the triple point and critical point are important properties for process design and optimization. These thermophysical properties are related to each other through temperature derivatives of thermodynamic relationships stemming from a temperature-dependent vapor-pressure correlation. The Riedel equation has been considered to be an excellent and simple choice among vapor-pressure correlating equations [Velasco et al. J. Chem. Thermodyn. 2008, 40 (5), 789−797] but requires modification of the final coefficient to provide thermodynamic consistency with thermal data [Hogge et al. Fluid Phase Equilib. 2016, 429, 149−165]. New predictive correlations with final coefficients in integer steps from 1 to 6 have been created for compounds with limited or no vapor-pressure data, based on the methodology used originally by Riedel [Chem. Ing. Tech. 1954, 26 (2), 83−89]. Liquid heat capacity was predicted using these vapor-pressure correlations, and the best final coefficient values were chosen based on the ability to simultaneously represent vapor pressure and liquid heat capacity. This procedure improves the fit to liquid heat-capacity data by 5–10% (average absolute deviation), while maintaining the fit of vapor-pressure data similar to those of other prediction methods. Additionally, low-temperature vapor-pressure predictions were improved by relying on liquid heat-capacity data