A Unified Correlation for Prediction of Pure Component Properties Based on Similarity of Molecular Descriptors of Various Compounds

A new approach for predicting a wide range of physical and thermodynamic properties is proposed. It involves calculation of the molecular descriptors of a target compound of unknown properties, followed by regression of this vector of molecular descriptors versus a database of compounds with known descriptors and measured properties. The regression model, obtained for the descriptors of a target compound in terms of those of predictive compounds and their weighting factors, is then used for prediction of properties of the target compound. The precision of the prediction can be estimated based on the standard deviation of the correlation and the known precision of the property data of the predictive compounds. The use of the proposed technique is demonstrated by using regression models of various precision and complexity to predict properties of n-tetradecane.