Bacterial alginate-based hydrogels reinforced with polysaccharide nanocrystals for water and wastewater decontamination
Year: 2025
Type: article
Abstract: The textile industry is a major driver of water pollution, releasing vast amounts of heavy metals, toxic dyes, and organic and inorganic contaminants, which severely harm the environment. Pollution remediation remains a major challenge, highlighting the need for efficient and cost-effective solutions. Biopolymer-based technologies provide a sustainable, efficient, and eco-friendly solution for industrial dye removal. Incorporating nanomaterials can enhance the adsorption capacity of these materials due to their high specific surface area. This study compares the effectiveness of nanomaterials such as cellulose nanocrystals (NCC), chitin nanocrystals (NCChit), and oxidized chitin nanocrystals (NCChit-ox). The results indicate that NCChit-ox is the most effective sorbent, exhibiting the highest Langmuir constant (KL) and a maximum adsorption capacity for methylene blue (MB) of 96.5 mg/g, with a removal efficiency exceeding 92.5 % across all concentrations, as confirmed by molecular modeling. These nanomaterials were incorporated into bacterial alginate-based hydrogels for MB adsorption. The effects of temperature, contact time, pH, and dye concentration were studied. Among the evaluated isotherms, the adsorption experimental data best fit the Langmuir model (R² = 0.9547). Kinetic data suggest that the adsorption process follows a second-order mechanism (R² = 0.977). The hydrogel demonstrates excellent reusability, maintaining high adsorption efficiency across multiple cycles.
Source: Results in Engineering
Institutions: Laboratoire de Glycochimie, des Antimicrobiens et des Agroressources, Université de Picardie Jules Verne, Institut Mines-Télécom, Université de Lille, JUNIA, Laboratoire de Génie Civil et Géo-Environnement, Université d'Artois, Centre National de la Recherche Scientifique, Enzyme and Cell Engineering - Molecular Recognition and Biocatalysis, Pontificia Universidad Católica de Valparaíso
Language: English
Subfield: Water Science and Technology
Field: Environmental Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,940
Award: Mastering AI Applications
OpenAlex ID: W7117295535
