Prediction of Thermophysical Properties Using Polynomial Expansion Equation and Genetic Algorithm

摘要

Thermophysical properties are the data necessary for discussing the chemical processes. Such thermophysical properties will be commonly evaluated using corresponding-state principle or group contribution method. Recently chemoinformatic procedures like polynomial expansion equation and genetic algorithm has been used and developed for predicting thermophysical properties. This article reviews the predictive method of thermophysical properties. Firstly, the acentric factor, density, vapor pressure, latent heat of vaporization, viscosity, thermal conductivity and surface tension have been predicted using critical constants, normal boiling point and molecular weight as the molecular descriptors in the polynomial expansion equation. The predicted results have been then compared with those by the previous predicted methods. Secondary, the melting point, viscosity and ionic conductivity of ionic liquids, and thermal conductivity of CFC alternatives have been predicted using group, and molecular volume obtained by MOPAC as the molecular descriptors.