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Experimental Analysis and Neural Network Modeling of the Rheological Behavior of Xanthan Gum and Its Derivatives

Lookup NU author(s): Dr Jie ZhangORCiD



This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


© 2023 by the authors.The main objective of this study was to create a mathematical tool that could be used with experimental data to predict the rheological flow behavior of functionalized xanthan gum according to the types of chemical groups grafted onto its backbone. Different rheological and physicochemical analyses were applied to assess six derivatives synthesized via the etherification of xanthan gum by hydrophobic benzylation with benzyl chloride and carboxymethylation with monochloroacetic acid at three (regent/polymer) ratios R equal to 2.4 and 6. Results from the FTIR study verified that xanthan gum had been modified. The degree of substitution (DS) values varying between 0.2 and 2.9 for carboxymethylxanthan gum derivatives were found to be higher than that of hydrophobically modified benzyl xanthan gum for which the DS ranged from 0.5 to 1. The molecular weights of all the derivatives were found to be less than that of xanthan gum for the two types of derivatives, decreasing further as the degree of substitution (DS) increased. However, the benzyl xanthan gum derivatives presented higher molecular weights varying between 1,373,146 (g/mol) and 1,262,227 (g/mol) than carboxymethylxanthan gum derivatives (1,326,722–1,015,544) (g/mol). A shear-thinning behavior was observed in the derivatives, and the derivatives’ viscosity was found to decrease with increasing DS. The second objective of this research was to create an ANN model to predict one of the rheological properties (the apparent viscosity). The significance of the ANN model (R2 = 0.99998 and MSE = 5.95 × 10−3) was validated by comparing experimental results with the predicted ones. The results showed that the model was an efficient tool for predicting rheological flow behavior.

Publication metadata

Author(s): Yahoum MM, Toumi S, Hentabli S, Tahraoui H, Lefnaoui S, Hadjsadok A, Amrane A, Kebir M, Moula N, Assadi AA, Zhang J, Mouni L

Publication type: Article

Publication status: Published

Journal: Materials

Year: 2023

Volume: 16

Issue: 7

Print publication date: 01/04/2023

Online publication date: 23/03/2023

Acceptance date: 18/03/2023

Date deposited: 04/05/2023

ISSN (electronic): 1996-1944

Publisher: MDPI


DOI: 10.3390/ma16072565


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