Deconvolution of overlapping spectral polymer signals in size exclusion separation-diode array detection separations...

Area of Science:

• Polymer Chemistry
• Analytical Chemistry
• Chemometrics

Background:

• Size exclusion chromatography (SEC) often yields overlapping peaks due to polymer dispersity.
• Improving peak separation by reducing flow rate increases analysis time, which is often undesirable.
• Quantifying individual components in polymer mixtures with overlapping signals is challenging.

Purpose of the Study:

• To develop and validate a chemometric deconvolution method for analyzing overlapping peaks in SEC.
• To enable accurate qualitative and quantitative analysis of polymer mixtures.
• To provide an alternative to reducing flow rates for improved peak resolution.

Main Methods:

• Utilized a chemometric deconvolution approach with an in-house MATLAB script.
• Differentiated compounds based on UV spectra and retention time using 3D retention time UV-spectrum data.
• Applied the method to mixtures of polystyrene, poly(methyl methacrylate), and poly(ethoxyethyl acrylate).

Main Results:

• Successfully deconvoluted overlapping peaks in SEC chromatograms.
• Obtained accurate chromatograms and UV spectra for individual polymer components.
• Demonstrated the ability to perform both qualitative identification and quantitative analysis.
• Showed that alternating concentrations of adjacent peaks did not significantly impact accuracy.

Conclusions:

• The developed chemometric deconvolution method effectively resolves overlapping peaks in SEC.
• This approach allows for accurate qualitative and quantitative analysis of complex polymer mixtures.
• The method offers a valuable tool for analyzing copolymers and polymer blends without compromising analysis time.