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Enhanced Removal of Salbutamol in Water Solution Using Cu-Based Magnetic Designed Metal–Organic Frameworks: Kinetics and Isothermal Models and Statistical Analysis

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Abstract

Clean water quality is dependent on the absence or complete removal of polar ionic micropollutant molecules and their associated products from the water. Utilizing copper Isonicotinate metal–organic frameworks ([Cu (INA)-MOF) a modified copper-based magnetic composite metal–organic framework ([Cu (INA)2]-MOF@Fe3O4) is mechanically synthesized under environmentally friendly conditions, and an adsorptive removal of salbutamol in water was successfully achieved in both synthesized materials. Characterization toward the materials has been carried out using X-ray diffraction, Brunauer–Emmett–Teller, field emission scanning microscopy, scanning electron microscopy, thermogravimetric analysis, and Fourier transform infrared spectroscopy. Our synthesized ([Cu (INA)2]-MOF@Fe3O4 used as an adsorbent in water showed enhanced performance in the removal of the model salbutamol within a shorter contact time (40 min) with the pseudo-second-order and Langmuir models providing the most accurate statistical descriptions of the process’s kinetics and isotherms, respectively, while thermodynamic studies indicated that the process was endothermic, spontaneous, and the material demonstrated very good reusability and regeneration with a very good percentage recovery even after the fifth cycle.

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Acknowledgements

The authors would like to thank University Malaysia Terengganu (UMT), Postgraduate Research Grant (PG-RG Vot: 55202), Faculty of Science and Marine Environment for the facilities provided throughout this study. The authors would also like to thank the Centre for Functional Materials and Nanotechnology, Institute of Science, Universiti Teknologi MARA, Shah Alam, Malaysia, for their support in completing this work.

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Armaya’u, U., Ariffin, M.M., Loh, S.H. et al. Enhanced Removal of Salbutamol in Water Solution Using Cu-Based Magnetic Designed Metal–Organic Frameworks: Kinetics and Isothermal Models and Statistical Analysis. Arab J Sci Eng 49, 439–458 (2024). https://doi.org/10.1007/s13369-023-08167-z

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