journal article·2023-10Open access

Advanced metal oxides nanostructures to recognize and eradicate water pollutants

Urmila Chakraborty, Gurpreet Kaur, Horst-Günter Rubahn, Ajeet Kaushik, Ganga Ram Chaudhary, Yogendra Kumar Mishra

Abstract

The excessive inlet of contaminants into water is affecting its quality adversely which is not recommended for quality health. Therefore, investigating economical, scalable, efficient, and faster approaches for water treatment is crucual. In this direction, nanostructures (NSs) due to easy fabrication and tailored properties are emerging technology for water quality management via detecting, monitoring, and removing the targeted water contaminants. Among several NSs, metal oxides (MO)-NSs have performed desired sensing and remediation of targeted water contaminants. Considering state-of-the-art, this review is a first-time attempt to explore the design and development of available smart MO-NSs investigated for water quality management. This comprehensive article presents a careful and critical discussion of a decade (2011 to 2022) of advancements based on MO-NSs for sensing (via electrochemical and optical signalling), eradication (via adsorption, photocatalytic degradation, ultrasound-assisted-catalytic degradation/adsorption, and ultrafiltration), simultaneous detection and eradication of water pollutants, and water disinfection. Moreover, the challenges associated with focused state-of-the-art technology for water quality management, alternative approaches, and possible future aspects are critically delineated. Finally, this review project MO-NSs-based futuristic approach as green technologies to deliver clean water to everyone and greatly contributes to the community concerned as per the United Nations Sustainable Development Goal 6 (SDG6).
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Advanced Nanomaterials in Catalysis · Biosensors and Analytical Detection · Water Quality Monitoring Technologies

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

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