Ultrasound-aided rapid and enhanced adsorption of anionic dyes from binary dye matrix onto novel hematite/polyaniline nanocomposite: Response surface methodology optimization

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Abstract

In recent times, polyaniline (PANI), a conducting polymer, has been studied widely for environmental remediation application due to its controllable electric conductivity with high surface area, which makes it a suitable adsorbent material. But lower mechanical stability of PANI is considered to be a serious drawback for its large-scale industrial application. To improve the mechanical strength of PANI, in this study, hematite nanoparticles were impregnated onto PANI by oxidative polymerization method in order to fabricate a novel organometallic nanocomposite (hematite-PANI-NC). The hematite-PANI-NC was used as adsorbent for removal of methyl orange (MO) and eosin yellow (EY) dye from binary dye matrix under ultrasonic-assisted adsorption. Excellent MO and EY dye removal (more than 98%) was observed from binary matrix at a wide solution pH from 2.0 to 6.0, and under ultrasound wave the adsorption equilibrium was achieved within 15 min only. Both MO and EY dyes adsorption experimental data strictly followed Langmuir isotherm, and maximum monolayer adsorption capacity of 126.58 mg/g and 112.36 mg/g was observed for MO and EY dye, respectively. The uptake mechanism of MO and EY dyes onto hematite-PANI-NC is governed by electrostatic interaction, π-π bonding and hydrogen bonding between dye molecules and nanocomposite. Response surface methodology analysis reveals maximum MO and EY removal of 98.43% and 99.35% at optimum experimental conditions. This study implies that the hybrid organometallic material hematite-PANI-NC has high potential for quick and enhanced sono-assisted uptake of anionic dyes from water near neutral solution pH.

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Deb, A., Debnath, A., & Saha, B. (2020). Ultrasound-aided rapid and enhanced adsorption of anionic dyes from binary dye matrix onto novel hematite/polyaniline nanocomposite: Response surface methodology optimization. Applied Organometallic Chemistry, 34(2). https://doi.org/10.1002/aoc.5353

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