Linear solvation energy relationships in normal phase chromatography based on gradient separations

Area of Science:

• Analytical Chemistry
• Chromatography

Background:

• Linear solvation energy relationships (LSER) are crucial for understanding chromatographic separations.
• Developing LSER models typically requires numerous experiments using isocratic conditions.

Purpose of the Study:

• To develop a gradient method for building LSER models in normal phase chromatography.
• To compare the efficiency and accuracy of gradient-derived LSER models with isocratic methods.

Main Methods:

• Coupling the modified Soczewiñski model with a single gradient run.
• Testing the gradient method on dinitroanilinopropyl (DNAP) and silica columns using hexane/dichloromethane (DCM) mobile phases.

Main Results:

• LSER models derived from gradient separation showed agreement with those from isocratic separations.
• Gradient-based LSER models exhibited similar coefficients and goodness of fit compared to isocratic models.
• The gradient method required fewer experimental trials for LSER model development.

Conclusions:

• A gradient-based approach is a viable and more efficient alternative for developing LSER models in normal phase chromatography.
• This method reduces experimental workload without compromising model accuracy.