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Water scarcity and escalating pollution have placed approximately three-quarters of the global population under water security pressure. Among various contaminants, heavy metal ions (HMs) pose severe risks to ecosystems and human health owing to their persistence, high toxicity, and non-biodegradability. Compared with conventional water treatment technologies, adsorption is widely regarded as an effective strategy for HMs remediation because of its high removal efficiency, operational simplicity, and cost-effectiveness. Hydrogels, featuring three-dimensional interconnected networks, abundant functional groups, and highly tunable architectures, provide versatile platforms for overcoming the limitations of conventional adsorbents. This review systematically summarizes recent advances in hydrogel-based adsorbents for HMs removal and elucidates adsorption mechanisms arising from synergistic physicochemical interactions. Quantitative analysis indicates that reported hydrogel adsorbents can achieve adsorption capacities of up to 1743.4 mg g −1 (dry-basis), with equilibrium times ranging from approximately 30 min to 48 h, while structurally reinforced or functionalized hydrogels can retain over 90% of their initial adsorption performance after multiple regeneration cycles. To address the multi-dimensional adsorption demands in practical applications, a systematic performance-enhancement framework is established encompassing accelerated kinetics, enhanced adsorption capacity, selective recognition, environmental adaptability, and long-term durability. Conventional chemical regeneration and emerging green desorption-regeneration strategies are further compared. Furthermore, the applications in integrated adsorption-sensing systems, agricultural soil and water remediation, HMs removal from food and beverages, and human health protection are discussed. Finally, key challenges in complex water matrices, multi-metal systems, long-term operation, and scale-up are identified, and future directions toward structure-property-application integration are proposed.
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Zhang et al. (2026) studied this question.
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