PREDICTION OF NORMAL BOILING POINTS OF HYDROCARBONS FROM MOLECULAR-STRUCTURE

Computer assisted methods are used to investigate the relationship between normal boiling point and molecular structure for a set of hydrocarbons. Multiple linear regression methods are used to develop a six-variable. linear model with a low root mean square (rms) error. The six descriptors in the linear model are also used to develop a computational neural network model with a significantly lower rms error. The methodology used in this study is also compared to Joback's group contribution method to estimate physical properties. The methods used here are found to be superior to Joback's method. However, when one additional variable encoding the square root of the molecular weight is added to Joback's groups, an excellent model is developed.