relation: https://khub.utp.edu.my/scholars/15865/
title: Removal of 4-chloro-2-methylphenoxyacetic acid from water by MIL-101(Cr) metal-organic framework: Kinetics, isotherms and statistical models
creator: Isiyaka, H.A.
creator: Jumbri, K.
creator: Sambudi, N.S.
creator: Zango, Z.U.
creator: Saad, B.
creator: Mustapha, A.
description: Effective removal of 4-chloro-2-methylphenoxyacetic acid (MCPA), an emerging agrochemical contaminant in water with carcinogenic and mutagenic health effects has been reported using hydrothermally synthesized MIL-101(Cr) metal-organic framework (MOF). The properties of the MOF were ascertained using powdered X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, thermal gravimetric analysis (TGA), field emission scanning electron microscopy (FESEM) and surface area and porosimetry (SAP). The BET surface area and pore volume of the MOF were 1439 m2 g-1 and 0.77 cm3 g-1, respectively. Artificial neural network (ANN) model was significantly employed for the accurate prediction of the experimental adsorption capacity (qe) values with minimal error. A rapid removal of the pollutant (99) was recorded within short time (approx. 25 min), and the reusability of the MOF (20 mg) was achieved up to six cycles with over 90 removal efficiency. The kinetics, isotherm and thermodynamics of the process were described by the pseudo-second-order, Freundlich and endothermic adsorption, respectively. The adsorption process is spontaneous based on the negative Gibbs free energy values. The significant correlation between the experimental findings and simulation results suggests the great potential of MIL-101(Cr) for the remediation of MCPA from water matrices. © 2021 The Authors.
publisher: Royal Society Publishing
date: 2021
type: Article
type: PeerReviewed
identifier:   Isiyaka, H.A. and Jumbri, K. and Sambudi, N.S. and Zango, Z.U. and Saad, B. and Mustapha, A.  (2021) Removal of 4-chloro-2-methylphenoxyacetic acid from water by MIL-101(Cr) metal-organic framework: Kinetics, isotherms and statistical models.  Royal Society Open Science, 8 (1).   ISSN 20545703     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85100913392&doi=10.1098%2frsos.201553&partnerID=40&md5=0656d36a8f653b3008cfb1a2705badae
relation: 10.1098/rsos.201553
identifier: 10.1098/rsos.201553