Analytical Determination of Heavy Metals in Water Using Carbon-Based Materials

2025

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DOI 10.3390/molecules31010005
Data confidence 70 medium
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Abstract

This review presents a critical and comparative analysis of carbon-based electrochemical sensing platforms for the determination of heavy metal ions in water, with emphasis on Pb2+, Cd2+, and Hg2+. The growing discharge of industrial and mining effluents has led to persistent contamination of aquatic environments by toxic metals, creating an urgent need for sensitive, rapid, and field-deployable analytical technologies. Carbon-based nanomaterials, including graphene, carbon nanotubes (CNTs), and MXene, have emerged as key functional components in modern electrochemical sensors due to their high electrical conductivity, large surface area, and tunable surface chemistry. Based on reported studies, typical detection limits for Pb2+ and Cd2+ using differential pulse voltammetry (DPV) on glassy carbon and thin-film electrodes are in the range of 0.4–1.2 µg/L. For integrated thin-film sensing systems, limits of detection of 0.8–1.2 µg/L are commonly achieved. MXene-based platforms further enhance sensitivity and enable Hg2+ detection with linear response ranges typically between 1 and 5 µg/L, accompanied by clear electrochemical or optical signals. Beyond conventional electrochemical detection, this review specifically highlights self-sustaining visual sensors based on MXene integrated with enzyme-driven bioelectrochemical systems, such as glucose oxidase (GOD) and Prussian blue (PB) assembled on ITO substrates. These systems convert chemical energy into measurable colorimetric signals without external power sources, enabling direct visual identification of Hg2+ ions. Under optimized conditions (e.g., 5 mg/mL GOD and 5 mM glucose), stable and distinguishable color responses are achieved for rapid on-site monitoring. Overall, this review not only summarizes current performance benchmarks of carbon-based sensors but also identifies key challenges, including long-term stability, selectivity under multi-ion interference, and large-scale device integration, while outlining future directions toward portable multisensor water-quality monitoring systems.