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• W4313169623 abstract "With an ever-increasing population, the water crisis is increasing day by day due to limited water resources. Even with limited resources, water pollution aggravates this situation even more. Treatment of polluted water is one of the key areas of focus to make it reusable. Heavy metal treatment of contaminated water is being pursued with various technologies available, ranging from zeolites to membranes. These technologies are often expensive and demand huge resources for any new experiment. A comprehensive computational analysis of any proposed experimentation can provide early warnings as well as insights into it. Here, we are doing a comprehensive study to choose the suitable adsorbent for the concerned adsorbate and effective functionalization of the membrane for preferential passing using atomistic simulation. These atomistic simulations use density functional theory-based packages such as Quantum Espresso, Gaussian, VASP, and many more. Once the thermodynamic study is established, we move on to the kinetics of the flow in various situations such as adsorption, osmosis, and trapping using molecular dynamics. Along with this, some systems can contain biological or polymeric membranes for the effective removal of heavy metal ions, which increases the computational cost drastically. To have an effective insight into these systems, coarse-grained molecular dynamics simulations have been proposed. A comprehensive study using these techniques can provide us with a very accurate mimicking of an actual metal removal system and serve as a feedback system. Thus, multiscale simulation tools can be helpful in the design and development of efficient water purification systems. This bottom-up design approach helps in designing the systems to the precision level required by safety standards prescribed for the treated water. At the nanoscale, the particle-interaction as well as molecular dynamics provide control over selectivity and flow rate of the system, while coarse-grained simulations will provide the tolerance required at macro level." @default.
• W4313169623 created "2023-01-06" @default.
• W4313169623 creator A5006570988 @default.
• W4313169623 creator A5060023479 @default.
• W4313169623 date "2022-01-01" @default.
• W4313169623 modified "2023-10-13" @default.
• W4313169623 title "Multiscale modeling approach for removal of heavy metal ions from water: A review" @default.
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• W4313169623 doi "https://doi.org/10.1016/b978-0-323-85378-1.00022-2" @default.
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