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A Modeling Approach for Orthogonality of Comprehensive Two-Dimensional Separations
A novel
method is developed for orthogonality evaluation of comprehensive
two-dimensional separations (C2DS). Utilization of efficiency measures
such as peak capacity (<i>n</i><sub>c</sub>) can be critically
evaluated for C2DS analysis to describe an orthogonal separation of
the analytes in a 2D plane. Unlike most previous methods focusing
on “bin coverage” over 2D space, rather than taking
into account the distribution based on accurate peak retention, in
the proposed method, the separation orthogonality of C2DS is divided
into two parts (i.e., <i>C</i><sub>pert</sub> and <i>C</i><sub>peaks</sub>). These correspond to peak coverage percent,
and 2D distribution correlation of compounds, respectively. Bin occupation
and a simple-linear regression model, on the basis of normalized retention
times in 2D separation space (<sup>1</sup><i>t</i><sub>R</sub> and <sup>2</sup><i>t</i><sub>R</sub>), are further introduced
to quantitatively define the two terms. Orthogonality ranges from
0 to 1 correspond to perfectly correlated and orthogonal separations,
respectively, which are presented based on both <i>C</i><sub>pert</sub> and <i>C</i><sub>peaks</sub> considerations.
The advantage of this method is the use of separation properties of
C2DS to characterize practical 2D peak distribution and does not rely
on assumptions or any imposed limitations. Simulation of comprehensive
two-dimensional gas chromatography (GC × GC) was achieved by
using the Abraham solvation parameter model, and applied to generate
examples for orthogonality assessment. In this work, 225 compounds
comprising a range of chemical classes were simulated for separation
on two column set pairs comprising low polarity/polar and moderately
polar/polar combinations. Results illustrate that the proposed method
applied to GC × GC provides a reasonable assessment of 2D separation
performance and may be used to derive optimal experimental conditions
when used with an experimental design strategy