A New Fast Estimation Method for Critical Pressure and Critical Temperature of Binary Mixture Based on the Modified Redlich–Kister Method

• Published in: Industrial & engineering chemistry research Vol. 63; no. 20; pp. 9236 - 9244
• Main Authors: Tang, Bo, Yao, Xiaoyu, Dong, Xueqiang, Zhao, Xiufang, Zhao, Yanxing, Gong, Maoqiong
• Format: Journal Article
• Language: English
• Published: American Chemical Society 22.05.2024
• Subjects: Thermodynamics, Transport, and Fluid Mechanics
• ISSN: 0888-5885; 1520-5045
• DOI: 10.1021/acs.iecr.4c00752

The vapor–liquid critical parameters of mixtures are important in the establishment of equations of state and mixing rules to predict thermophysical properties and develop next-generation, low-carbon working fluids. Obtaining critical parameters through experimental measurement is the most efficient and straightforward approach but it is a time-consuming and labor-intensive process, thus necessitating the use of theoretical prediction methods. There is currently no prediction model that can attain the same level of precision as experimental measurements, and the existing models are not easily accessible. In this paper, the nonideal effect of the acentric factor of the mixture and the median deviation term of the critical parameters are introduced into the Redlich–Kister model. The newly developed model surpasses current fast estimation methods in terms of its accurate predictions, minimal adjustable factors, lack of a requirement for critical volume data of pure substances, and consideration of molecular polarity. This new fast estimation model can be applied to hundreds of binary combinations consisting of methane-free alkanes, alkenes, alkynes, alicyclic hydrocarbons, benzene and its derivatives, NH3, CO2, halogenated hydrocarbons, N2O, Kr, Xe, sulfur compounds, and oxygen-containing organic compounds. The absolute average relative deviation (AARD) of this method in calculating the critical temperature and critical pressure of binary mixtures is 1.21% and 4.22%, based on 4116 critical temperature experimental data points (521 groups of binary mixtures) and 2882 critical pressure experimental data points (342 groups of binary mixtures), respectively.