Predictive Molecular Simulation Studies on the Vapor–Liquid Equilibria of 10 Binary Mixtures Containing Different Hydrofluoroolefins

IF 2 3区 工程技术 Q3 CHEMISTRY, MULTIDISCIPLINARY
Gabriele Raabe*, 
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引用次数: 0

Abstract

In this work, predictions from Gibbs Ensemble Monte Carlo simulations on the vapor liquid phase equilibria properties of 10 different binary mixtures of the components, carbon dioxide, 2,3,3,3-tetrafluoropropene (R-1234yf), cis-and trans-1,3,3,3-tetrafluoropropene [R-1234ze(Z/E)], cis- and trans-1,1,1,4,4,4-hexafluorobut-2-ene [R-1336mzz(Z/E)], and trans-1-chloro-3,3,3-trifluoroprop-1-ene [R-1233zd(E)], are presented. For seven of these mixtures, the simulation results represent the first information on their phase behavior, addressing gaps in the existing data on potential HFO-based refrigerant blends. The simulation results together with available experimental data were then used to derive parameters for the multifluid modeling of these mixtures. Different variants of the multifluid model, i.e., predictive mixing rules as well as different parametrizations of the adjustable parameters, are evaluated by assessing their performance in reproducing bubble and dew point lines, as well as saturated densities.

对含有不同氢氟烯烃的 10 种二元混合物的汽液平衡进行预测性分子模拟研究
介绍了顺式和反式-1,3,3,3-四氟丙烯[R-1234ze(Z/E)]、顺式和反式-1,1,1,4,4,4-六氟丁烯-2-烯[R-1336mzz(Z/E)]以及反式-1-氯-3,3,3-三氟丙烯-1-烯[R-1233zd(E)]的 10 种不同的二元混合物的相平衡特性。对于其中的七种混合物,模拟结果代表了有关其相行为的第一手信息,弥补了有关基于 HFO 的潜在制冷剂混合物的现有数据的不足。模拟结果和可用的实验数据随后被用于推导这些混合物的多流体模型参数。多流体模型的不同变体,即预测混合规则以及可调参数的不同参数化,通过评估它们在再现气泡和露点线以及饱和密度方面的性能进行了评估。
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来源期刊
Journal of Chemical & Engineering Data
Journal of Chemical & Engineering Data 工程技术-工程:化工
CiteScore
5.20
自引率
19.20%
发文量
324
审稿时长
2.2 months
期刊介绍: The Journal of Chemical & Engineering Data is a monthly journal devoted to the publication of data obtained from both experiment and computation, which are viewed as complementary. It is the only American Chemical Society journal primarily concerned with articles containing data on the phase behavior and the physical, thermodynamic, and transport properties of well-defined materials, including complex mixtures of known compositions. While environmental and biological samples are of interest, their compositions must be known and reproducible. As a result, adsorption on natural product materials does not generally fit within the scope of Journal of Chemical & Engineering Data.
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