The beneficial polyphenol gallic acid (GA) is often loaded in polymeric systems to improve its poor bioavailability and low stability, therefore quantifying its concentration is mandatory. Chromatography is expensive, time long and non-ecological; partial least square-based near-infrared technique requires interpretative chemometrics tools; ultraviolet/visible (UV-Vis) method is non-specific and destructive. Herein, using Fourier transform infrared (FTIR) spectroscopy, a fast, low-cost, ecological and conservative method for quantifying GA in polymer matrices was developed, by acquiring spectra of GA solutions at different GA concentrations (CGAs). Selected spectral data and CGAs were used to build a linear regression model by least squares approach, subsequently validated adopting samples of three different GA polymer formulations, as validation sets. Test samples were analyzed by FTIR technique and the model was used to determine CGAs, which were predicted with minimal absolute errors (0.01-0.03). This method is robust and extendable also to other precious polymeric matrices or valuable substances.

Development of a Fast, Low‐Cost, Conservative and Ecological Method for Quantifying Gallic Acid in Polymeric Formulations by FTIR Spectroscopy in Solution

Alfei, Silvana;Marengo, Barbara;Domenicotti, Cinzia
2020-01-01

Abstract

The beneficial polyphenol gallic acid (GA) is often loaded in polymeric systems to improve its poor bioavailability and low stability, therefore quantifying its concentration is mandatory. Chromatography is expensive, time long and non-ecological; partial least square-based near-infrared technique requires interpretative chemometrics tools; ultraviolet/visible (UV-Vis) method is non-specific and destructive. Herein, using Fourier transform infrared (FTIR) spectroscopy, a fast, low-cost, ecological and conservative method for quantifying GA in polymer matrices was developed, by acquiring spectra of GA solutions at different GA concentrations (CGAs). Selected spectral data and CGAs were used to build a linear regression model by least squares approach, subsequently validated adopting samples of three different GA polymer formulations, as validation sets. Test samples were analyzed by FTIR technique and the model was used to determine CGAs, which were predicted with minimal absolute errors (0.01-0.03). This method is robust and extendable also to other precious polymeric matrices or valuable substances.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1006087
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