Efficient dye removal using fixed-bed process based on porous montmorillonite nanosheet/poly(acrylamide-co-acrylic acid)/sodium alginate hydrogel beads
Source abstract
Abstract
In this study, Montmorillonite nanosheet/poly(acrylamide- co -acrylic acid)/sodium alginate hydrogel beads with high handle capacity towards dyes effluent was investigated. Montmorillonite nanosheet cooperated with acrylamide and acrylic acid via hydrogen bond, amidation and polymerization interaction first, then crosslinked with sodium alginate by intertwining interaction to form 3D network structure, achieving free entrance and rapid adsorption for dye molecules. Batch adsorption tests revealed a multilayer and heterogeneous adsorption of methylene blue (MB) onto hydrogel beads according to pseudo two-order kinetic model and Freundlich isotherm model. The adsorption capacity of MB was controlled by the amount of adsorption sites in hydrogel beads, which could reach maximum of 530.7 mg/g. The adsorption mechanism is attributed to Ca ion-exchange and chemical bonding of COOH and OH groups with MB. Column tests showed an excellent dynamic adsorption performance of hydrogel beads towards MB wastewater compared with the traditional commercial adsorbents of granular active carbon and cation exchange resin, which achieved 380 bed volume (BV) of treated sewage to meet the emission standards using the single column. Moreover, 1625 BV and more treated dye effluent was achieved to be safety discharged via double column series in 5 circulation-regeneration, indicating the great potential of hydrogel beads in practical application. Such hydrogel realized the performance promotion of macromolecule polymers and nanoclay in materials design, and green application in water treatment.
Source: expertdata · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Adsorption and biosorption for pollutant removal · Membrane Separation Technologies · Nanomaterials for catalytic reactions
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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