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Binary color adsorption by zinc@magnetite nanocomposites: Robust parametric optimization using Taguchi method

Vietnam Journal of Chemistry 2024 3 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 40 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Sangita Yadav, Subhash Chander, Neha Luhach, Sweta Kumari, Ankur Kashyap, Asha Gupta

Summary

Not relevant to microplastics — this study uses Taguchi design-of-experiments to optimize zinc-magnetite nanocomposite adsorbents for removing color (dye) from wastewater, with no connection to microplastic pollution.

Abstract The goal of the current study was to determine the optimal level (value) of adsorption process variables for the adsorption of color from binary aqueous solution. The impact of key adsorption factors, including adsorbent dose, initial color concentration, and contact time, on the color removal effectiveness of Zinc@magnetite nanocomposites (Zin@Fe 3 O 4 (ME) produced from bacterial extracts and Zin@Fe 3 O 4 (M) produced from bacterial cell mass), has been examined. Utilizing an L9 orthogonal array (OA), average values and the SN ratio for each variable at three diverse points are calculated. ANOVA has determined the most advantageous optimum conditions for raw and SN data. According to the study, the adsorbent dose is shown to be the most important parameter for color adsorption, while contact duration is determined to be the least important factor based on Pareto chart analysis. The percentage of color removal at optimal values for Zin@Fe 3 O 4 (M) and Zin@Fe 3 O 4 (ME) nanocomposites, respectively, was found to be 81% and 73%. The optimal parameters were found to be 12.5 mg of adsorbent, 125 mg/L initial dye concentration, and 90 min of contact time at pH 7, room temperature. The confirmatory experiments conducted under optimized conditions revealed a higher percentage of color eliminated than was optimized in each test run of the Taguchi design, proving the credibility of the process variables optimized within the designated experiments.

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