INTEC   05402
INSTITUTO DE DESARROLLO TECNOLOGICO PARA LA INDUSTRIA QUIMICA
Unidad Ejecutora - UE
artículos
Título:
Molar Mass Distributions of Linear Homopolymers by Size Exclusion Chromatography with Light Scattering Detection: A Method for Automatic Band Broadening Correction
Autor/es:
YOSSEN, MARIANA M.; CLEMENTI, LUIS A.; VEGA, JORGE R.
Revista:
JOURNAL OF CHROMATOGRAPHY - A
Editorial:
ELSEVIER SCIENCE BV
Referencias:
Lugar: Amsterdam; Año: 2019 p. 136 - 143
ISSN:
0021-9673
Resumen:
Size exclusion chromatography (SEC) equipped with a differential refractometer (DR) and a light scattering (LS) detector is a well-known technique for determining the molar mass distribution (MMD) of many polymers. In the case of narrow polymers, correction of the band broadening (BB) effect is necessary; but unfortunately, the available BB correction methods are rather impractical for most SEC users. This work proposes an automatic BB correction method for determining the MMD of narrow linear homopolymers(or multimodal homopolymers that include narrow modes) on the basis of SEC/(DR + LS) measurements. The required data are: the baseline-corrected DR and LS chromatograms, the inter-detector volume (IDV), and a molar mass calibration independently determined from narrow standards. In comparison to other available alternatives for BB correction, the here-proposed method has the following key advantages: a) no previous knowledge on the BB function is required; b) the detectors gain constants are unnecessary; and c) no numerical regularization method is required. Moreover, if the IDV is unknown, then the proposed method could also be used for estimating the IDV from the knowledge of the dispersity index of a narrow homopolymer. The proposal was experimentally assessed by analyzing narrow standards of poly(styrene) and poly(methyl-methacrylate). The proposed method estimated the dispersity indexes of the standards with errors lower than 0.9% with respect to values reported by manufacturers (between 1.015 and 1.044); while the classical approaches based on SEC/DR and SEC/(DR + LS), produced errors of up to -11% and 3%, respectively.