Prediction of Kovats retention indices of some aliphatic aldehydes and ketones on some stationary phases at different temperatures using artificial neural network.

In this work, the Kovats retention indices of aliphatic ketones and aldehydes on four stationary phases at different temperatures are predicted. The data set consists of retention indices of 35 aldehydes and ketones on HP-1, HP-50, DB-210, and HP-Innowax stationary phase. The molecular descriptors that appear in this model are: path one connectivity index, fractional atomic charge weighted by partial positive surface area, and dipole moment, which are selected by stepwise multiple linear regression (MLR).