Abstract

The toxicity, bioaccumulation, and persistence of heavy metals, especially copper (Cu 2+ ), in ecosystems make their poisoning of water supplies a serious environmental and public health risk. Numerous treatment processes, such as ion exchange, membrane filtering, chemical precipitation, and electrochemical methods, have been developed to remove copper from wastewater. However, these technologies often face challenges related to high operational costs, energy consumption, and the generation of secondary waste. In this regard, adsorption has become a viable, economical, and environmentally sustainable heavy metal removal method. This paper offers a thorough examination of Cu 2+ adsorption with bio-adsorbents, natural clays, and modified clays (organoclays Key adsorption parameters examined included pH, metal concentration, temperature, contact time, and adsorbent dosage. With their increased surface area and adsorption capacity, modified and functionalized clays and bio-adsorbents demonstrated superior performance. While functionalized biochar and organoclay composites were experimentally shown to have the highest adsorption capacity, while most natural and modified adsorbents demonstrated substantial removal efficiencies. Both monolayer and multilayer adsorption were indicated by the adsorption isotherms fit well to the Langmuir and Freundlich models. For the majority of adsorbents, kinetic investigations showed that the most accurately described the adsorption behavior. These findings suggest that due to their high cation exchange capacity (CEC) and large surface area, natural and modified adsorbents can be employed to remove Cu 2+ from wastewater.

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Year
2025
Type
article
Volume
1172
Pages
57-70
Citations
0
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Closed

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Cite This

Mohamed Bahouch, Nouhaila Hadoudi, Abdellah Yousfi et al. (2025). A Comprehensive Review of Organoclays and Bio-Adsorbents for Effective Copper Removal. Materials science forum , 1172 , 57-70. https://doi.org/10.4028/p-lv8sv1

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DOI
10.4028/p-lv8sv1

Data Quality

Data completeness: 72%