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journal article·2026-07-17Open access

A comparative review of the adsorption efficiency and performance variances of metal oxide nanoparticles and pristine carbon nanotubes for Pb2+ sequestration

Samuel Nnadi, Ifeanyi A. Ucheana, Stanley U. Nwoke

Discover Nano· Volume 21· Issue 1
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Abstract

Lead (Pb²⁺) contamination in aquatic systems poses a major threat to human health and environmental safety. Conventional remediation techniques such as chemical precipitation and ion exchange are often constrained by high operational costs, poor efficiency at trace concentrations, and secondary pollution. Nanotechnology has introduced materials like carbon nanotubes (CNTs) and metal oxide nanoparticles (MONPs) with superior physicochemical reactivity for Pb²⁺ removal. This review highlights recent advances (2002-2025) in adsorption-desorption behaviour of Pb²⁺ on MONPs and pristine CNTs, focusing on synthesis, surface properties, adsorption mechanisms, reusability, and toxicity. Reported findings reveal that MONPs, including Fe₃O₄, ZnO, MgO, and CuO, exhibit outstanding adsorption capacities (up to 1980 mg g⁻¹ for MgONPs), surpassing those of CNTs which usually range between 10 and 250 mg g-1 under comparable conditions. This performance is linked to the abundance of chemically active surface sites and electrostatic interactions, which dominate adsorption on MONPs. Desorption studies confirm both materials are reusable over multiple cycles, though MONPs demonstrate higher regeneration efficiency and lower toxicity. Overall, MONPs present more scalable and eco-friendly alternatives for Pb²⁺ remediation. Future research should refine regeneration strategies, assess environmental safety, and develop hybrid systems for sustainable water treatment.
Source: europepmc · Quality: candidate unverified · Source record ↗

Research context

Nanomaterials

OpenAlex topics: Adsorption and biosorption for pollutant removal · Chemical Synthesis and Characterization · Layered Double Hydroxides Synthesis and Applications

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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