Retention-time prediction for polycyclic aromatic compounds in reversed-phase capillary electro-chromatography

Area of Science:

• Analytical Chemistry
• Separation Science
• Computational Chemistry

Background:

• Log Po/w based models are standard for retention time prediction in reversed-phase liquid chromatography.
• Capillary electro-chromatography (CEC) offers unique separation capabilities.
• Investigating predictive model applicability in CEC is crucial for method development.

Purpose of the Study:

• To assess the accuracy of log Po/w based retention time predictions in CEC.
• To compare different predictive modeling approaches for CEC separations.
• To identify factors influencing retention time prediction accuracy in CEC.

Main Methods:

• Separation of five polycyclic aromatic hydrocarbons using two stationary and three mobile phases in CEC.
• Correlation of experimental retention times with experimental and calculated log Po/w values.
• Application of quantitative structure-property relationship (QSPR) and molecular dynamics (MD) methods, including linear interaction energy (LIE) and Bennett acceptance ratio (BAR).

Main Results:

• Rigorous simulation models demonstrated the capability to accurately reproduce experimental CEC results.
• Significant deviations in retention time prediction were observed due to the electrophoretic mobility of analytes.
• Both experimental and calculated log Po/w values showed varying degrees of correlation with retention times.

Conclusions:

• Log Po/w based predictions require adjustments for CEC due to electrophoretic mobility effects.
• Advanced simulation methods like LIE and BAR show promise for accurate CEC retention time prediction.
• Further refinement of models is needed to fully account for electrokinetic phenomena in CEC predictions.