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A REVIEW STUDY OF SEVERAL ADSORPTION TECHNIQUES FOR REMOVING OF HEAVY METAL IONS FROM WATER

Authors: Azad Kumar*, Durgesh Chauhan;

A REVIEW STUDY OF SEVERAL ADSORPTION TECHNIQUES FOR REMOVING OF HEAVY METAL IONS FROM WATER

Abstract

Abstract: - Water pollution has become a critical issue all over the world, and heavy metals, organic and inorganic compounds, and bio-organisms all contribute significantly to water contamination. The use of nanomaterials (NMs) to remove contaminants from water has received a lot of attention. Heavy metals such as Cd, Cr, As, Pb, Hg, and others pose a great risk to humans, animals, and plants due to their poisonous and harmful effects. It has an impact on human health due to precipitation, adsorption, and accumulation in the food chain. Its inability to degrade poses a major threat to the environment. Many conventional strategies for removing heavy metals from water have been proposed, but their applicability is limited in terms of cost, efficiency, and adaptability. Adsorption technology at the nanoscale dimension is seen to be the most promising for removing heavy metal ions. Because of their high surface area to mass ratio, selectivity, specificity, and adsorption capabilities, Nano sorbents are a particularly effective separation medium for hazardous metals from waste water, loments such as nanotechnology and bio-strategy, for which a number of reviews exist focusing on conventional methods, transitional metal/metal oxide nanoparticles, carbon nanotubes, graphene, and so on.

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Keywords: Adsorption, Adsorbent, Carbon nanotube, chitosan, bio-sorbents, nanocomposites

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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