Efficient encapsulation of toxic dye from wastewater using biodegradable polymeric adsorbent

By K. Kubra, M. Salman, Hussein Znad, M. Hasan. 2021

253 citations recorded by the source corpus.

Abstract The water pollution caused by industrial effluents of pollutant dyes has been harmfully affected to the human health and environment. Therefore, it is important for considerable attention to remove them from industrial wastewater before being discharged to the surface water. The natural polymer-based carbohydrate adsorbent with specific functional groups can be enhanced their potential applications toward the notorious dyes removal from wastewater. In this regard, we selected natural adsorbent of graham flour (GF) as an effective adsorbent to remove cationic crystal violet (CyV) dye by the adsorption method. The morphology and structure of GF was characterized in systematic manner by several instrumentations. The several influencing factors such as solution pH, contact time, dose amount, maximum adsorption capacity, competing metal ions effect and reuses behavior were systematically measured. The effective pH range for CyV adsorption was neutral pH region and the maximum adsorption capacity of the GF adsorbent was as high as 162.33 mg/g. The data also clarified that the polymeric GF adsorbent was selectively removed the CyV dye from synthetic polluted sample even in the presence of high concentration of diverse competing ions. The adsorbed CyV dye was eluted with ethanol and simultaneously regenerated into initial form for the next adsorption operations after rinsing with water. Importantly, the natural GF adsorbent was retaining functionality in spite of many steps during adsorption-elution-regeneration cycles. Therefore, the present study revealed that such a low-cost natural polymeric carbohydrate adsorbent could be used as potential adsorbent for the selective dye molecules from wastewater streams.

Subfields: Industrial and Manufacturing Engineering, Inorganic Chemistry, Water Science and Technology

View Paper: https://www.semanticscholar.org/paper/f4540df456a5f62fd2e8ae0fe6880e2066634bc5