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      Efficient removal of methylene blue dye from wastewater specimen using polystyrene coated nanoparticles of silica

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          Adsorption isotherm models: Classification, physical meaning, application and solving method

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            Insight into the adsorption kinetics models for the removal of contaminants from aqueous solutions

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              Graphene and graphene oxide as effective adsorbents toward anionic and cationic dyes.

              In the present study, exfoliated graphene oxide (EGO) and reduced graphene oxide (rGO) have been used for the adsorption of various charged dyes such as methylene blue, methyl violet, rhodamine B, and orange G from aqueous solutions. EGO consists of single layer of graphite decorated with oxygen containing functional groups such as carboxyl, epoxy, ketone, and hydroxyl groups in its basal and edge planes. Consequently, the large negative charge density available in aqueous solutions helps in the effective adsorption of cationic dyes on EGO while the adsorption is negligible for anionic dyes. On the other hand, rGO that has high surface area does not possess as high a negative charge and is found to be very good adsorbent for anionic dyes. The adsorption process is followed using UV-Visible spectroscopy, while the material before and after adsorption has been characterized using physicochemical and spectroscopic techniques. Various isotherms have been used to fit the data, and kinetic parameters were evaluated. Raman and FT-IR spectroscopic data yield information on the interactions of dyes with the adsorbent. Copyright © 2011 Elsevier Inc. All rights reserved.
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                Author and article information

                Journal
                Inorganic Chemistry Communications
                Inorganic Chemistry Communications
                Elsevier BV
                13877003
                February 2024
                February 2024
                : 160
                : 112018
                Article
                10.1016/j.inoche.2024.112018
                ed17c944-7b67-40da-b8db-bef0117f42ca
                © 2024

                https://www.elsevier.com/tdm/userlicense/1.0/

                https://doi.org/10.15223/policy-017

                https://doi.org/10.15223/policy-037

                https://doi.org/10.15223/policy-012

                https://doi.org/10.15223/policy-029

                https://doi.org/10.15223/policy-004

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