Orthogonality measurements for multidimensional chromatography in three and higher dimensional separations

Area of Science:

• Analytical Chemistry
• Chromatography
• Chemometrics

Background:

• Orthogonality metrics (OMs) are crucial for evaluating zone utilization in two-dimensional (2D) separations.
• Extending these metrics to three and higher dimensions is essential for analyzing complex chromatographic data.

Purpose of the Study:

• To propose and validate new orthogonality metrics (OMs) for three and higher dimensional separations.
• To assess the zone utilization and molecular diversity in multi-dimensional chromatographic techniques.
• To re-evaluate existing experimental datasets using the novel OMs.

Main Methods:

• Development of OMs including correlation coefficients, dimensionality, information theory metrics, and convex-hull metrics for higher dimensions.
• Application of these OMs to analyze 3D peptide data and a comprehensive 3D chromatogram.
• Comparison of lower-dimensional subspace metrics with higher-dimensional ones.
• Introduction of a new information theory metric for orthogonality assessment.

Main Results:

• The proposed OMs successfully evaluated zone utilization in 3D chromatographic data.
• Good orthogonality values were observed in the Moore and Jorgenson chromatogram, but discretization-based OMs were sensitive to binning parameters.
• Geometric and harmonic means of 2D OMs correlated well with 3D OMs for the Gilar peptide data.
• A new information theory metric was proposed, showing improved or equal performance compared to the original 2D metric (%O).

Conclusions:

• Orthogonality metrics are vital for understanding complex multi-dimensional separations.
• Sufficient data points are critical for accurate OMs, especially with discretization methods.
• The geometric/harmonic means of lower-dimensional OMs can predict higher-dimensional performance.
• The newly proposed information theory metric offers a robust approach to orthogonality assessment in higher dimensions.