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A Sustainable Karaya Gum/Polyethylenimine Crosslinked Hydrogel for Anionic Dye Removal From Water: Adsorption Behavior and Machine Learning Prediction
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DOI：10.1002/app.71138.png)
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Abstract
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The release of anionic dyes from textile effluents threatens aquatic ecosystems and human health, creating a need for efficient and reusable adsorbents. In this study, a bio-based KG/PEI hydrogel was prepared by crosslinking Karaya gum (KG) with polyethylenimine (PEI) using glutaraldehyde. FTIR, XRD, SEM, and TGA confirmed successful crosslinking, enhanced thermal stability, and the formation of a porous, mostly amorphous network suitable for dye adsorption. Methyl orange (MO) was used as a model anionic dye to evaluate adsorption performance under different pH, contact time, dye concentration, and temperature conditions. The hydrogel showed higher adsorption capacity under acidic conditions due to protonation of PEI amine groups, which strengthened electrostatic attraction with MO sulfonate groups. The adsorption kinetics followed the pseudo-second-order model, while equilibrium data were best described by the Langmuir isotherm, giving a maximum experimental capacity of 284 mg/g and a theoretical monolayer capacity of 333 mg/g. Thermodynamic results indicated that adsorption was spontaneous and endothermic. The hydrogel retained about 73% of its initial efficiency after five reuse cycles. Machine-learning models further predicted adsorption capacity, with Gradient Boosting showing the best performance.
Keywords:
adsorption
anionic dye removal
biomaterials
Karaya gum
machine learning
polyethylenimine hydrogel
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