Journal Article

Novel ZIF-67@Bentonite (ZIF-67@BNT) Nanocomposite for Aqueous Methyl Orange Removal

Onaizi, Sagheer A., Faheem, Kashif, Vohra, Muhammad S.

2025

Overview

The indiscriminate discharge of synthetic dyes into wastewater streams poses a severe threat to the environment as well as to human well-being. Among all these dyes, methyl orange (MO) attracts attention due to its widespread use and persistence in industrial effluents. This study investigated the use of zeolitic imidazolate framework and bentonite (ZIF-67@BNT) nanocomposite material for the removal of MO from the aqueous phase. Various characterization techniques were employed such as FTIR, XRD, and TGA to verify the successful synthesis of the ZIF-67@BNT adsorbent, which was subsequently utilized to investigate the adsorption of MO. Batch adsorption studies demonstrated a high MO adsorption capacity of 187 mg/g. A response surface methodology (RSM)-based modeling exercise was used to optimize the adsorption process. While assessing the impact of various operational factors, the initial MO concentration followed by ZIF-67@BNT dose were noted to be important. Adsorption kinetics and isotherm studies were also completed. The ZIF-67@BNT nanocomposite after adsorption analysis indicated multiple mechanisms facilitating MO uptake. Additionally, various machine learning (ML) models such ANN, SVR, RF, and GPR were also utilized to predict MO adsorption onto ZIF-67@BNT nanocomposite under a varying set of conditions.

• Publisher: MDPI AG
• Subject: Adsorbents / Adsorption / Aqueous solutions / Artificial intelligence / Azo compounds / Bentonite / Cobalt / Dyes / Fourier transforms / Machine learning / methyl orange / Nanocomposites / Neural networks / Nitrates / Pollutants / Porous materials / Protons / RSM and ML modeling / Variance analysis / Wastewater / Water treatment / ZIF-67@Bentonite