Prediction of retention times in temperature programmed gas chromatography using the retention equation derived from crystallization behavior of polymer

Based on the enlightenment from the crystallization behavior of polymer, a novel retention equation constructed with only three pairs of isothermal retention data was proposed to predict retention times in temperature programmed gas chromatography (TPGC). The new retention equation worked beautifully in both the single- and the multiple-ramp temperature-programmed modes, yielding the average absolute relative errors of 0.65% for single-ramp TPGC across all the 18 analytes in 3 temperature programmed experiments and 0.30% for multiple-ramp TPGC across all the 8 analytes in 6 temperature programmed experiments tested in this work. Moreover, to compare with the new retention equation systematically and thoroughly, another 13 retention equations determined by two or three parameters were derived from a universal formula ln k = a0 + a1/T + a2/T2 + a3 ln T + a4T + a5T2 as a combination of the relationships between ln k and T with reference to four widely used retention equations in publications. Calculated by these 14 retention equations with the same experimental data, the absolute relative errors of prediction retention times for single-ramp TPGC mode were compared by means of statistical analysis. At a very high significance level of 1%, statistical evidences of paired t-test strictly implied that the new retention equation yielded the best prediction results among all of the 14 retention equations. In addition, remarkably, among the 13 retention equations, three seldom used in publications retention equations also worked nicely, yielding satisfactory average absolute relative errors of 0.78%, 0.81% and 0.84% for single-ramp TPGC.

► A novel retention equation for TPGC retention times predicting is proposed.
► The new retention equation is derived from the crystallinity formula of polymer.
► The new retention equation characterized as a simple nonlinear curve.
► The new retention equation yield satisfactory prediction results in TPGC.
► Statistical evidences significantly verify this new retention equation as the best.