Cross-Linked Starch as Media for Crystal Violet Elimination from Water: Modeling Batch Adsorption with Fuzzy Regression

Author:

Bahrami Mehdi12ORCID,Amiri Mohammad Javad12ORCID,Busquets Rosa34ORCID,Nematollahi Mohammad Javad5ORCID

Affiliation:

1. Department of Water Science and Engineering, Faculty of Agriculture, Fasa University, Fasa 74616-86131, Iran

2. Research Institute of Water Resources Management in Arid Region, Fasa University, Fasa 74616-86131, Iran

3. Department of Civil, Environmental and Geomatic Engineering, University College London, Gower St., Bloomsbury, London WC1E 6BT, UK

4. Faculty of Health, Science, Social Care and Education, School of Pharmacy and Chemistry, Kingston University, Penrhyn Road, Kingston Upon Thames KT1 2EE, UK

5. Department of Geology, Faculty of Sciences, Urmia University, Urmia 57561-51818, Iran

Abstract

A scalable and cost-effective solution for removing pollutants from water is to use biodegradable and eco-friendly sorbents that are readily available such as starch. The current research explored the removal of crystal violet (CV) dye from water using chemically modified potato starch. The adsorbent was prepared by cross-linking potato starch with sodium trimetaphosphate (STMP). The impact of various operating factors including pH, temperature, contact time, initial CV concentration, and adsorbent dosage on the removal of CV were investigated using batch experiments. The adsorption data were analyzed using a fuzzy regression approach, which provided a range-based representation of the model’s output. The cross-linked starch adsorbent was mesoporous, with a mean pore diameter of 9.8 nm and a specific surface area of 2.7 m2/g. The adsorption of CV by the STMP cross-linked potato starch was primarily influenced by the adsorbent dosage, followed by the solution pH, temperature, initial CV concentration, and contact time. The fuzzy regression model accurately predicted the independent experimental data of CV removal with an R2 of 0.985, demonstrating its value as a tool for the continuous monitoring of CV removal as well as optimizing water treatment conditions.

Publisher

MDPI AG

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