Implementing a multivariate curve resolution method optimized by alternating least square (MCR-ALS) to deconvolute overlapping spectral polymer signals in SEC-DAD separations

摘要

Peaks eluting from a size exclusion separation are often not completely baseline-separated, due to the inherent polydispersity of the polymer and low efficiency of the separation mechanism. Chemometrical deconvolution provides the possibility of calculating the contribution of each peak separately from the recorded spectrum1. Herefore, an in house developed MATLAB script dis-criminates between the different compounds based on their difference in UV-spectrum and retention time, using the entire 3D retention time-UV spectrum. The output of the script provides the calculated chromatograms of each compound as well as their respective UV-spectrum2. The latter can be used for peak identification, while quantitative calculations can be performed on the chromatographical peaks. This aproach allows for overlap in both rentention time as UV-spectrum, speeding up the analyses and extending the separation power of SEC separations. The applicability (both qualitative as quantitative) has been demonstrated on a mixture of three different polymer types.