Prediction of Triple-Point Temperature of Pure Components Using their Chemical Structures

A quantitative structure property relationship study was performed to develop a model for the prediction of triple-point temperature of pure components. For developing this model, 638 pure components were used, and, for whichever, 1664 molecular descriptors were determined. As a standard tool for subset variable selection, genetic algorithm-based multivariate linear regression (GA-MLR) technique was used. The obtained model is a seven parameters multilinear equation that has a squared correlation coefficient of 0.9410 (R2 = 0.9410).