Sustainable removal of anionic azo dyes using amine-functionalized Cu-MOF: experimental and DFT analysis.

Authors

Sumaya Akhter, Tanveer Rasool, Leela Manohar Aeshala

Published in

Environmental science and pollution research international. Jul 14, 2026. Epub Jul 14, 2026.

Abstract

An amine-functionalized copper-based metal-organic framework (NH₂-Cu-MOF) was synthesized using a solvothermal route for the efficient removal of hazardous azo dyes, Congo red (CR), and methyl orange (MO) from aqueous solutions. High adsorption capacities of 463.4 mg g^-1 for Congo red and 37.5 mg g^-1 for methyl orange were achieved. CR followed the Langmuir model, MO the Freundlich model, and both dyes exhibited pseudo-second-order kinetics, indicating chemisorption-controlled adsorption. XRD and FT-IR results confirmed π-π stacking, hydrogen bonding, electrostatic interactions, and structural charges and indicated dye interaction into the NH₂-Cu-MOF lattice. Density functional theory (DFT) calculations further validated the mechanism, with CR showing stronger interaction (E_ads = -145.24 kJ mol^-1) than MO (E_ads = -90.0 kJ mol^-1). The reduced vertical distance (2.634 Å) between CR and NH₂-Cu-MOF indicated closer contact, whereas frontier molecular orbital (FMO) analysis showed greater structural stability for MO-NH₂-Cu-MOF due to a larger band gap (ΔE = 1.822 eV). The findings reveal a critical role of -NH₂ groups and copper sites in adsorption efficiency. Thermodynamic analysis revealed the adsorption to be spontaneous. The NH₂-Cu-MOF retained 85.7% and 85.1% of its initial capacity for CR and MO respectively after five regeneration cycles, demonstrating its excellent reusability and sustainable behaviour for dye removal. ANOVA analysis highlighted pH, dose, and concentration as the most critical factors governing adsorption efficiency, with CR showing stronger dependence than MO. Overall, NH₂-Cu-MOF proves to be a sustainable and highly effective adsorbent for the removal of anionic dyes from aqueous solution.

PMID:
42446799
Bibliographic data and abstract were imported from PubMed on 14 Jul 2026.

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