Optimization of Sodium Alginate?Graphene Nanoplate?Kaolin Bio?composite Adsorbents in Heavy Metal Adsorption by Response Surface Methodology (RSM)

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Tarih

2022

Dergi Başlığı

Dergi ISSN

Cilt Başlığı

Yayıncı

Springer

Erişim Hakkı

info:eu-repo/semantics/closedAccess

Özet

In this study, graphene nanoplate-kaolin-sodium alginate (GKS) bio-composite adsorbent was prepared, and the copper removal from wastewater by the adsorption method was investigated. Characterization of adsorbent was carried out using a scanning electron microscope, Fourier transforms infrared spectroscopy, and thermo-gravimetric analysis methods. In addition to the parametric adsorption studies, experimental optimization was also applied with parameters determined by the central composite design of response surface methodology (RSM). Effects of copper concentration (from 10 to 50 ppm), pH (from 3 to 7), and adsorption dosage (from 0.05 to 0.15 g/L) were investigated to determine the optimum design points. In order to determine the efficiency of heavy metal adsorption, four experimental parameters (adsorbent dosage, metal concentration, pH, and contact time) were evaluated. As a result, the highest removal of 92.12% was obtained when the heavy metal concentration was 10 mg/L, the adsorbent dosage was 0.15 g, the solution pH was 7, and the contact time was 180 min. Adsorption isotherm studies were also carried out. The appropriate adsorption isotherm for copper removal using GKS was determined as Langmuir isotherm. According to the optimization results, the quadratic model with an R2 of 0.9946 was found to be the most suitable model.

Açıklama

Anahtar Kelimeler

Batch Adsorption, Bio-Composite Adsorbent, Experimental Design, Heavy Metal Removal

Kaynak

Arabian Journal for Science and Engineering

WoS Q Değeri

Q3

Scopus Q Değeri

Cilt

47

Sayı

5

Künye

Ünügül, T., & Nigiz, F. U. (2022). Optimization of Sodium Alginate-Graphene Nanoplate-Kaolin Bio-composite Adsorbents in Heavy Metal Adsorption by Response Surface Methodology (RSM). Arabian Journal for Science and Engineering, 47(5), 6001–6012. https://doi.org/10.1007/s13369-021-05905-z