A new metric for relating macroscopic chromatograms to microscopic surface dynamics: the distribution function ratio...

Area of Science:

• Analytical Chemistry
• Chromatography
• Surface Science

Background:

• Chromatographic tailing, caused by heterogeneous stationary phase chemistry, reduces separation efficiency and complicates mobile phase optimization.
• Model-free metrics are useful for assessing separation conditions but often fail to identify the mechanisms causing tailing, such as heterogeneous retention modes.

Purpose of the Study:

• To introduce a novel metric, the Distribution Function Ratio (DFR), for quantifying heterogeneous retention modes in chromatography.
• To demonstrate the DFR's ability to correlate with ground truth surface dynamics and outperform existing metrics like asymmetry factor and skewness.

Main Methods:

• Development of the Distribution Function Ratio (DFR) metric through graphical comparison of chromatograms and Gaussian cumulative distribution functions.
• Utilizing a Monte Carlo framework to validate the DFR's predictive power for heterogeneous retention modes.
• Comparing DFR performance against asymmetry factor and skewness using ground truth surface dynamics.

Main Results:

• The DFR accurately predicts the prevalence of heterogeneous retention modes when the relative desorption rate between modes is known.
• The DFR demonstrates a one-to-one correspondence with heterogeneous retention mode prevalence, outperforming asymmetry factor and skewness.
• Combining DFR with asymmetry factor and skewness allows for the estimation of microscopic surface dynamics.

Conclusions:

• The DFR provides a powerful, model-free method for assessing chromatographic separation efficiency and understanding surface chemistry.
• This new metric enhances insights into surface dynamics using existing chromatographic instrumentation.
• The DFR establishes a chemistry-driven approach for advancing chromatographic separations.