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.