Central composite design and genetic algorithm applied for the optimization of ultrasonic-assisted removal of malachite green by ZnO Nanorod-loaded activated carbon

被引：131

作者：

Ghaedi, M. ^{[1
]}

Azad, F. Nasiri ^{[1
]}

Dashtian, K. ^{[1
]}

Hajati, S. ^{[2
]}

Goudarzi, A. ^{[3
]}

Soylak, M. ^{[4
]}

机构：

[1] Univ Yasuj, Dept Chem, Yasuj 7591874831, Iran

[2] Univ Yasuj, Dept Phys, Yasuj 7591874831, Iran

[3] Golestan Univ, Dept Polymer Engn, Gorgan 4918888369, Iran

[4] Erciyes Univ, Dept Chem, TR-38039 Kayseri, Turkey

来源：

SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY | 2016年 / 167卷

基金：

美国国家科学基金会;

关键词：

Malachite green; Genetic algorithm; ZnO-Nanorods; Central composite design; RESPONSE-SURFACE METHODOLOGY; DIRECT YELLOW 12; AQUEOUS-SOLUTION; HYDROTHERMAL SYNTHESIS; DESIRABILITY FUNCTION; METHYLENE-BLUE; ORGANIC-DYES; ADSORPTION; ADSORBENT; ISOTHERM;

D O I：

10.1016/j.saa.2016.05.025

中图分类号：

O433 [光谱学];

学科分类号：

0703 ; 070302 ;

摘要：

Maximum malachite green (MG) adsorption onto ZnO Nanorod-loaded activated carbon (ZnO-NR-AC) was achieved following the optimization of conditions, while the mass transfer was accelerated by ultrasonic. The central composite design (CCD) and genetic algorithm (GA) were used to estimate the effect of individual variables and their mutual interactions on the MG adsorption as response and to optimize the adsorption process. The ZnO-NR-AC surface morphology and its properties were identified via FESEM, XRD and FTIR. The adsorption equilibrium isotherm and kinetic models investigation revealed the well fit of the experimental data to Langmuir isotherm and pseudo-second-order kinetic model, respectively. It was shown that a small amount of ZnO-NR-AC (with adsorption capacity of 20 mg g(-1)) is sufficient for the rapid removal of high amount of MG dye in short time (3.99 min). (C) 2016 Elsevier B.V. All rights reserved.

引用

页码：157 / 164

页数：8

共 50 条

[11] Optimization of the ultrasonic assisted removal of methylene blue by gold nanoparticles loaded on activated carbon using experimental design methodology
Roosta, M.
Ghaedi, M.
Daneshfar, A.
Sahraei, R.
Asghari, A.
ULTRASONICS SONOCHEMISTRY, 2014, 21 (01) : 242 - 252
[12] Experimental design based response surface methodology optimization of ultrasonic assisted adsorption of safaranin O by tin sulfide nanoparticle loaded on activated carbon
Roosta, M.
Ghaedi, M.
Daneshfar, A.
Sahraei, R.
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY, 2014, 122 : 223 - 231
[13] Simultaneous ultrasound-assisted removal of sunset yellow and erythrosine by ZnS:Ni nanoparticles loaded on activated carbon: Optimization by central composite design
Roosta, M.
Ghaedi, M.
Daneshfar, A.
Darafarin, S.
Sahraei, R.
Purkait, M. K.
ULTRASONICS SONOCHEMISTRY, 2014, 21 (04) : 1441 - 1450
[14] Optimization of ultrasonic-assisted copper ion removal from polluted water by a natural clinoptilolite nanostructure through a central composite design
Sheydaei, Mohsen
Gasemsoltanlu, Ali Balanejad
Beiraghi, Asadollah
CLAY MINERALS, 2019, 54 (04) : 339 - 347
[15] Ultrasonic enhancement of the simultaneous removal of quaternary toxic organic dyes by CuO nanoparticles loaded on activated carbon: Central composite design, kinetic and isotherm study
Dashamiri, Somayeh
Ghaedi, Mehrorang
Dashtian, Kheibar
Rahimi, Mahmood Reza
Goudarzi, Alireza
Jannesar, Ramin
ULTRASONICS SONOCHEMISTRY, 2016, 31 : 546 - +
[16] Multi-response optimization of ultrasound assisted competitive adsorption of dyes onto Cu (OH)2-nanoparticle loaded activated carbon: Central composite design
Dashamiri, Somayeh
Ghaedi, Mehrorang
Asfaram, Arash
Zare, Fahimeh
Wang, Shaobin
ULTRASONICS SONOCHEMISTRY, 2017, 34 : 343 - 353
[17] Ultrasonic-assisted synthesis of Fe3O4 nanoparticles-loaded sawdust carbon for malachite green removal from aquatic solutions
Ziaeddin Bonyadi
Fatemeh Sadat Khatibi
Fatemeh Alipour
Applied Water Science, 2022, 12
[18] Highly efficient simultaneous ultrasonic assisted adsorption of brilliant green and eosin B onto ZnS nanoparticles loaded activated carbon: Artificial neural network modeling and central composite design optimization
Jamshidi, M.
Ghaedi, M.
Dashtian, K.
Ghaedi, A. M.
Hajati, S.
Goudarzi, A.
Alipanahpour, E.
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY, 2016, 153 : 257 - 267
[19] A hybrid model of support vector regression with genetic algorithm for forecasting adsorption of malachite green onto multi-walled carbon nanotubes: central composite design optimization
Ghaedi, M.
Dashtian, K.
Ghaedi, A. M.
Dehghanian, N.
PHYSICAL CHEMISTRY CHEMICAL PHYSICS, 2016, 18 (19) : 13310 - 13321
[20] Comparative study of Central Composite and Box-Behnken design for the optimization of malachite green dye adsorption onto Sal seed activated char
Singh, V. K.
Soni, A. B.
Singh, R. K.
JOURNAL OF ENVIRONMENTAL BIOLOGY, 2017, 38 (05) : 849 - 858

← 1 2 3 4 5 →