Using the hydrophobic subtraction model to choose orthogonal columns for online comprehensive two-dimensional liquid chromatography

• A new method for choosing orthogonal RP-columns is proposed (SADCOD).
• SADCOD uses the sample characteristics to predict column orthogonality.
• SADCOD predicts accurately for samples with different characteristics.
• The SADCOD predictions were validated with LC × LC.

A method for choosing orthogonal columns for a specific sample set in on-line comprehensive two-dimensional liquid chromatography (LC × LC) was developed on the basis of the hydrophobic subtraction model. The method takes into account the properties of the sample analytes by estimating new F-weights for the prediction of orthogonality. We compared sets of F-weights and used these F-weights to predict orthogonal column combinations: (1) the standard F-weights determined by Gilroy et al. [1], (2) F-weights determined from the retention of sample analytes, and the same procedure of calculation as described by Gilroy et al. [1], (3) F-weights determined from the retention of sample analytes but using principal component analysis (PCA) for the estimation, and (4) the Gilroy F-weights modified by excluding the C-term in the hydrophobic subtraction model, as suggested by Dolan and Snyder [2]. The retention of 13 neutral and 4 acidic oxygenated polycyclic aromatic compounds (PACs) and 3 nitrogen-containing PAC bases was measured isocratically on 12 columns. The isocratic runs were used to determine the hydrophobic subtraction model analyte parameters, and these were used to estimate new F-weights and predict orthogonal column combinations. LC × LC-DAD analysis was then performed on a test mix using these column sets. We found that the column combination predicted from the new F-weights provide a more orthogonal separation of the PACs than those predicted using the standard F-weights and the F-weights modified by excluding the C-term. This emphasizes the necessity of considering the nature of the sample when choosing orthogonal columns.