Optimisation of chromatographic resolution using objective functions including both time and spectral information

Area of Science:

• Analytical Chemistry
• Chromatography
• Spectroscopy

Background:

• Traditional high-performance liquid chromatography (HPLC) resolution optimization relies solely on time information.
• Unresolved peak pairs can still be resolved using deconvolution, especially with spectral data.
• Existing methods lack sensitivity to spectral differences in coeluting compounds.

Purpose of the Study:

• To develop and test two-way chromatographic objective functions (COFs) integrating time and spectral information.
• To identify experimental conditions that maximize the success of deconvolution for complex mixtures.
• To evaluate COFs based on peak purity and multivariate selectivity for improved resolution.

Main Methods:

• Tested two-way COFs incorporating peak purity and multivariate selectivity.
• Applied the best-performing COF (two-way multivariate selectivity) to a real-world mixture.
• Utilized diode-array detection for spectral information acquisition.
• Performed peak deconvolution using orthogonal projection approach and alternating least squares.

Main Results:

• Two-way COFs effectively identified conditions where spectral differences aid deconvolution.
• Two-way multivariate selectivity demonstrated superior performance in optimizing resolution.
• Successfully deconvoluted a mixture of 25 phenolic compounds unresolved by chromatographic order alone.
• Demonstrated the utility of spectral information in overcoming coelution challenges.

Conclusions:

• Integrating spectral information into COFs significantly enhances chromatographic resolution optimization.
• Two-way multivariate selectivity is a powerful tool for improving deconvolution success.
• The developed methods offer a robust approach for analyzing complex mixtures in HPLC.