Issue 15, 2025

Unraveling the adsorption potential of Zr dithiol (MOF-DSH) through experimentation and neural network modeling

Abstract

In this study, an aqueous-stable metal–organic framework with two thiol groups was synthesized using Zr as the metal centre and dimercaptosuccinic acid as the ligand through a conventional heating method for the removal of Cd(II) from aqueous solution. Different characterization tools, including XRD, FT-IR, BET, SEM, TGA, and XPS, were employed. XRD results showed a characteristic pattern of a hexa-cluster, which was in agreement with the simulated MOF-801, and the corresponding vibrational peaks were observed in the FT-IR spectra. The synthesized MOF was thermally stable up to 300 °C, as demonstrated by TGA, and exhibited a specific surface area of 290 m2 g−1. Cadmium adsorption studies performed at different pH values showed a maximum adsorption capacity of 91.5 mg g−1 at pH 6. The adsorption behavior was well described by the Langmuir model and the pseudo-second order (PSO) kinetics, confirming the involvement of a monolayer with chemisorption as the dominant mode of adsorption. The synthesized MOF could be reused at least 4 times while retaining ∼80% of its initial adsorption capacity. FT-IR, XPS, and pH studies after Cd(II) adsorption revealed that the predominant mode of interaction of Cd(II) with the MOF is an ion-exchange mechanism. An artificial neural network-based (ANN) methodology was employed to model the adsorption capacity of Cd(II) and predict the adsorption capacity as a function of Cd(II) concentration, time of contact, and pH of the medium. The model demonstrated excellent results, with an average error of 2.3% and precision of 3.0%. The outcomes of these studies were consistent with the experimental results.

Graphical abstract: Unraveling the adsorption potential of Zr dithiol (MOF-DSH) through experimentation and neural network modeling

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Article information

Article type
Paper
Submitted
01 Jan 2025
Accepted
31 Mar 2025
First published
15 Apr 2025
This article is Open Access
Creative Commons BY license

RSC Adv., 2025,15, 11811-11825

Unraveling the adsorption potential of Zr dithiol (MOF-DSH) through experimentation and neural network modeling

N. Gumber, B. Kanrar, J. Singh, J. Bahadur and R. V. Pai, RSC Adv., 2025, 15, 11811 DOI: 10.1039/D5RA00002E

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