Application of Taguchi method and response surface methodology into the removal of malachite green and auramine-O by NaX nanozeolites

Abstract In the present study, the simultaneous removal of malachite green (MG) and auramine-O (AO) dyes from the aqueous solution by NaX nanozeolites in a batch system is investigated. Taguchi method and response surface methodology (RSM) were used to optimize and model dye removal conditions. In o...

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Autores principales: Siroos Shojaei, Saeed Shojaei, Shahab S. Band, Amir Abbas Kazemzadeh Farizhandi, Milad Ghoroqi, Amir Mosavi
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/c8884f6607504f65a1dbe98d3b93a03c
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Sumario:Abstract In the present study, the simultaneous removal of malachite green (MG) and auramine-O (AO) dyes from the aqueous solution by NaX nanozeolites in a batch system is investigated. Taguchi method and response surface methodology (RSM) were used to optimize and model dye removal conditions. In order to do so, the effect of various factors (dyes concentration, sonication time, ionic strength, adsorbent dosage, temperature, and pH of the solution) on the amount of dye removal was evaluated by the Taguchi method. Then, the most important factors were chosen and modeled by the RSM method so as to reach the highest percentage of dye removal. The proposed quadratic models to remove both dyes were in good accordance with the actual experimental data. The maximum removal efficiencies of MG and AO dyes in optimal operating conditions were 99.07% and 99.61%, respectively. Also, the coefficients of determination (R2) for test data were 0.9983 and 0.9988 for MG and AO dyes, respectively. The reusability of NaX nanozeolites was evaluated during the adsorption process of MG and AO. The results showed that the adsorption efficiency decreases very little up to five cycles. Moreover, NaX nanozeolites were also applied as adsorbents to remove MG and AO from environmental water samples, and more than 98.1% of both dyes were removed from the solution in optimal conditions.