Designing of a proficient macro porous metallo-polymer of iron with anion functionality: A sustainable approach for arsenic remediation from water

• Published in: Desalination and water treatment Vol. 320; p. 100816
• Main Authors: Joshi, Vipin C., Shukla, Shraddha, Sharma, Saroj
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.10.2024
• Subjects: 4-Vinyl benzyl chloride; ANN; Arsenic; Ferric(III) methacrylate; Hexamethylenetetramine; Metallo-polymer; ANN; Hexamethylenetetramine; Arsenic; 4-Vinyl benzyl chloride; Ferric(III) methacrylate; Metallo-polymer
• ISSN: 1944-3986
• DOI: 10.1016/j.dwt.2024.100816

In this study, a novel porous metallo-polymeric network named poly(Ferric trimethacrylate-co-4-Vinyl benzyl chloride), incorporating an iron moiety, was developed for arsenic remediation from water. The synthesis of crosslinked q(pFeVBC) was carried out via suspension polymerization and functionalizing it with hexamethylenetetramine, resulting in a porous three-dimensional structure. Characterization using FTIR, FESEM, XPS, XRD, and BET-SA analysis confirmed its properties. Various monomer ratios were tested to optimize q(pFeVBC) for arsenic removal. The q(pFeVBC) exhibited significant adsorption capacities (qe max exp) of 8.33 mg g−1 for As(V) and 7.9 mg g−1 for As (III), owe to its unique architecture (integrated iron moiety and anion functionality) and porous texture (SA: 112 m2 g−1, pore size: 1.27–2.07 µm), which is close to the capacity calculated by Langmuir model (qe max theo) 8.719 mg g−1 for As (V) and 8.463 mg g−1 for As (III). The PSO kinetic model showed excellent fitting for both arsenic forms. Thermodynamic studies indicated a spontaneous and endothermic adsorption process. Additionally, a 4:10:1 ANN model accurately predicted adsorption behavior. [Display omitted] •Fabricating amine functionalised iron metallopolymer for remediation of arsenic.•Maximum sorption capacities of 8.33 mg g−1 As(V) and 7.9 mg g−1 As(III) were achieved.•In the presence of co-ions and over a broad pH range, high As adsorption was accomplished.•The PSO model for kinetics and the Langmuir model for adsorption isotherm fit well (R2 > 0.99).•The trained ANN model performed batch adsorption data reasonably well.