MATHEMATICAL MODEL PREDICTING SECOND VIRIAL COEFFICIENT OF PURE ORGANIC COMPOUND THROUGH OYLE TEMPERATURE PREDICTION

摘要

PURPOSE: A mathematic model for predicting the second virial coefficient of a pure organic compound through a prediction of the Boyle temperature is provided to predict a reliable second virial coefficient even for organic compounds having unknown experimental values, thereby reducing time and cost for an experiment. CONSTITUTION: A molecule descriptor value about the Boyle temperature for an experimental data set of sample organic compounds is prepared. Experimental data is separated into a training set and a test set. An optimum MLRM(Multiple Linear Regression Model) for the training set is explored. The predicted performance of the optimum MLRM is tested. If the test is satisfied, a value of the Boyle temperature is obtained through the MLRM explored on the experimental data set.