Statistical techniques for the optimization of cesium removal from aqueous solutions onto iron-based nanoparticle-zeolit
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RESEARCH ARTICLE
Statistical techniques for the optimization of cesium removal from aqueous solutions onto iron-based nanoparticle-zeolite composites Md. Matiar Rahman 1,2,3 & Shamal Chandra Karmaker 1,2,3 & Animesh Pal 4 & Osama Eljamal 5 & Bidyut Baran Saha 1,2 Received: 22 June 2020 / Accepted: 13 October 2020 # Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract Statistical optimization of performance determining factors is essential for the development of a cesium removal system from aqueous solutions. Therefore, factorial experimental design and multiple regression techniques were employed to assess the primary and interaction effects of the pH, initial concentration, and contact time in the cesium removal process using nanoscale zero-valent iron-zeolite (nZVI-Z) and nano-Fe/Cu-zeolite (nFe/Cu-Z) as an adsorbent. The optimum region of cesium removal was identified by constructing a contour plot. The study revealed that initial concentration was the most significant factor followed by contact time. The study also suggested that maximum cesium removal occurred at pH, initial concentration, and contact time of 6, 200 mg/L, and 30 min, respectively. Moreover, the statistically significant interaction effect was observed between contact time and initial concentration. The experimental data were also fitted with Tόth, Langmuir, Dubinin-Astakhov (D-A), Freundlich, and Hill models and found that the Tόth model fitted better compared with the other four models based on Akaike information criterion (AIC) and root-mean-square deviation (RMSD). The findings of this paper can undoubtedly contribute to constructing the optimum statistical process of removing hazardous pollutants from the water, which significantly impacts on human health and the environment.
Keywords ANOVA . Cesium removal . Composites . Factorial experiment . Interaction effect . Statistical techniques Nomenclature A Level of pH (−) a0 Lower level of pH (−) a1 Higher level of pH (−)
AB AC ABC
Responsible Editor: Tito Roberto Cadaval Jr * Bidyut Baran Saha [email protected] 1
Mechanical Engineering Department, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka 819-0395, Japan
2
International Institute for Carbon-Neutral Energy Research (WPI-I2CNER), Kyushu University, 744 Motooka, Nishi-ku, Fukuoka 819-0395, Japan
3
Department of Statistics, University of Dhaka, Dhaka 1000, Bangladesh
4
Department of Nuclear Engineering, University of Dhaka, Dhaka 1000, Bangladesh
5
Interdisciplinary Graduate School of Engineering Sciences, Kyushu University, 6-1 Kasuga-Koen Kasuga, Fukuoka 816-8580, Japan
B b0 b0t b1 BC C c0 c1 Ce E KD Kf KL n
Interaction effect between pH (−) and initial concentration (mg/L) Interaction effect between pH (−) and contact time (min) Interaction effect among pH (−), initial concentration (mg/L), and contact time (min) Initial concentration (mg/L) Lower level of initial concentration (mg/L) Equilibrium constant of Tόth model (L/mg) Higher level of initial concentration (mg/L) Interaction ef
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