To overcome global water scarcity and pollution, nanomaterials have emerged as revolutionary tools for water remediation owing to their unique physicochemical properties, in particular, their ultrahigh specific surface area and programmable interface for molecular recognition. This review integrates multifaceted perspectives on contaminant treatment and compares the relative performance strength of nanomaterials for diverse contaminants, surpassing fragmented assessments focused on single contaminants. We taxonomize nanomaterial classes and highlight their recent advances across four domains: heavy metals removal, critical metals recovery, microbial contamination control, and emerging organic contaminants degradation. For each domain, we dissect scalability bottlenecks and define future research priorities, including database integration, graph neural networks, machine learning, and artificial intelligence. We provide design principles for high-performance water remediation by synthesizing cutting-edge materials using cross-disciplinary strategies. We describe eco-safe nanomaterials that guide industrial water management toward sustainable transformation, propelling global water remediation toward green, intelligent, and resource-recycling models.
Ling et al. (Mon,) studied this question.
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