A Simple Model with Wide Applicability for the Determination of Binary Interaction Parameters for Mixtures of n-Alkanes with Carbon Dioxide and Nitrogen

Tao Yang, J. Ilja Siepmann, Jiangtao Wu

Research output: Contribution to journalArticlepeer-review

Abstract

Accurate modeling of the phase equilibria for mixtures containing hydrocarbons and dissolved gases is important for numerous industrial applications. Binary interaction coefficient models between dissolved gases with permanent quadrupoles (carbon dioxide, CO2, and nitrogen, N2) and long-chain hydrocarbons are essential for achieving the desired accuracy for the phase coexistence properties. In this work, binary interaction parameter (BIP), kij, correlations from the literature were reviewed, and four prototypical (Kordas, Avlonitis, Jaubert, and Li) models were chosen for further study. Then, the Peng-Robinson equation of state (PR EoS) was utilized to explore vapor-liquid phase equilibria in the high-pressure, high-temperature region for binary mixtures of (n-pentane, n-tetradecane, or n-octacosane) + (CO2 or N2). In addition, the binary phase equilibria were studied using configurational-bias Monte Carlo simulations in the isobaric-isothermal Gibbs ensemble (NpT-GEMC) with the interactions described by the Transferable Potential for Phase Equilibria (TraPPE) force field. Good agreement was observed between the experimental measurements, the PR EoS calculations, and the NpT-GEMC simulations which supports the predictive capabilities of the group contribution method embedded in the predictive PR model. To simplify the use of the group contribution method, a quadratic polynomial function with the carbon number and the reduced temperature of the dissolved gas as input parameters is proposed to determine kij for n-alkane + (CO2 or N2) mixtures over a wide temperature region, which provides specific guidance for future studies.

Original languageEnglish (US)
Article number2c00242
JournalIndustrial and Engineering Chemistry Research
DOIs
StateAccepted/In press - 2022

Bibliographical note

Funding Information:
The authors acknowledge the financial support of the National Natural Science Foundation of China (No. 51976164 and 51761135116) and the computer resources provided by the Minnesota Supercomputing Institute. J.I.S. acknowledges the generous support from the Nanostructural Materials and Processes program of IPRIME, an industry-university consortium at the University of Minnesota.

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