Analysis of the flow patterns of liquid organic compounds between blade electrodes by classification models

The flow patterns of 20 organic liquids with diverse structures and functionalities between electrodes were measured under a dc electric field. The results clearly showed the existence of a strong relationship between the flow pattern of a compound and its molecular structure. On the basis of a variety of 23 molecular descriptors including those obtained by quantum-chemical calculations, multiple regression analysis and discriminant analysis were applied to identify the significant factors contributing to the flow patterns. For the flow rate dipole moment, nucleophilic delocalizability and lipophilicity as expressed by the 1-octanol/water partition coefficient were found to be the key factors as judged by a five-value regression model with a squared correlation coefficient (r2) of 0.881. For the direction of the flow, just two quantum-chemical parameters, namely, absolute hardness and the self-polarizability normalized by molecular volume, were identified as significant factors by using linear discriminant analysis. The numbers of misclassified compounds were only one and two for training and prediction (leave-one-out cross-validation), respectively, by the best discriminant model.