التفاصيل البيبلوغرافية
العنوان: |
Highly selective reusable nanolayered sorbent for the elution of hazardous As (III) from environmental samples. |
المؤلفون: |
Aravind, Archana, Sebastian, Maria, Nair, Vinayakan Ramachandran |
المصدر: |
Polymer Bulletin; Aug2024, Vol. 81 Issue 13, p11911-11929, 19p |
مصطلحات موضوعية: |
ENVIRONMENTAL sampling, MULTIWALLED carbon nanotubes, IMPRINTED polymers, METHACRYLIC acid, INSECTICIDES, ARSENIC removal (Water purification), HUMAN ecology |
مستخلص: |
Arsenic (As), a hazardous and carcinogenic heavy metal, poses a significant threat to both human health and the environment. Given its toxicity even at low concentrations, there is a pressing need for a low-cost technology for arsenic removal from environmental samples. In this study, a highly selective and reusable ion-imprinted polymer was synthesized to efficiently remove As from various environmental samples. The synthesis involved using methacrylic acid as a functional monomer, As(III) as a template, and multi-walled carbon nanotubes as a supporting material (MWCNT-IIP). To confirm the specificity of MWCNT-IIP for As(III), three other types of sorbents were also prepared: IIP, MWCNT-NIP, and NIP (non-imprinted polymer). Various parameters, including the initial concentration of metal ions, time, pH, and solvent medium, were systematically checked and optimized. In the adsorption study, the total capacity of the developed system for As(III) reached a linear range of 1–5 ppm, with an adsorption capacity of 27.14 mg/g. At pH 5, with a 40 min binding time, MWCNT-IIP demonstrated itself as an effective sorbent with a high percentage of removal efficiency. Inter- and intrachain interactions of the fabricated sorbents were calculated using the Equilibrium Water Content (EWC) method. In conclusion, MWCNT-IIP presents itself as an excellent alternative approach for removing As(III) from various environmental samples, including those collected from lakes, pigments, mining, and insecticides. [ABSTRACT FROM AUTHOR] |
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قاعدة البيانات: |
Complementary Index |