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Lookup NU author(s): Professor David XieORCiD
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).
A fitting method combined with a linear correlation function was developed as an improved approach for the SAXS analysis of the semicrystalline lamellae of starch granules. Using a power-law function with two Gaussian plus Lorentz functions, the SAXS pattern was resolved into sub-patterns of the net lamellar peak and the power-law scattering plus scattering background (PL + B). The ratio of the net lamellar peak area (Apeak) to the total scattering area (Atotal) was proposed equal to the proportion of the lamellae within the starch granule (PSL). Along with this fitting method, we obtained a better profile of linear correlation function, with the elimination of the interference of non-lamellar amorphous starch (i.e., amorphous growth rings). Then, we could accurately calculate the lamellar parameters, e.g., PSL, the thicknesses of semicrystalline (d), crystalline (dc) and amorphous (da) lamellae, and the volume fraction (φc) of crystalline lamellae within semicrystalline lamellae. Quantitative analysis revealed that PSL was positively correlated with the crystallinity (Xc) of starch. It was confirmed that the distribution of lamellar thickness was more important than the starch botanical origin in affecting the validity of the developed fitting method. We also proposed a criterion to test the validity of the proposed method. Specifically, the total SAXS pattern should be mostly tangent to the profile of PL + B at a high q tail (close to 0.2 Å−1).
Author(s): Zhang B, Xie F, Wang DK, Qiao D, Zhao S, Niu M, Xiong S, Jiang F, Zhu J, Yu L
Publication type: Article
Publication status: Published
Journal: Carbohydrate Polymers
Year: 2017
Volume: 158
Pages: 29-36
Print publication date: 20/02/2017
Online publication date: 02/12/2016
Acceptance date: 01/12/2016
Date deposited: 31/08/2023
ISSN (print): 0144-8617
ISSN (electronic): 1879-1344
Publisher: Elsevier
URL: https://doi.org/10.1016/j.carbpol.2016.12.002
DOI: 10.1016/j.carbpol.2016.12.002
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