PREDICTION OF NORMAL BOILING POINTS OF HYDROCARBONS FROM MOLECULAR-STRUCTURE

Computer assisted methods are used to investigate the relationship bet ween normal boiling point and molecular structure for a set of hydroca rbons. Multiple linear regression methods are used to develop a six-va riable. linear model with a low root mean square (rms) error. The six descriptors in the linear model are also used to develop a computation al neural network model with a significantly lower rms error. The meth odology used in this study is also compared to Joback's group contribu tion 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.