Optimizing the Removal of Rhodamine B in Aqueous Solutions by Reduced   Graphene Oxide-Supported Nanoscale Zerovalent Iron (nZVI/rGO) Using an   Artificial Neural Network-Genetic Algorithm (ANN-GA)

doi:10.3390/nano7060134

CORC > 北京大学 > 化学与分子工程学院

	Optimizing the Removal of Rhodamine B in Aqueous Solutions by Reduced Graphene Oxide-Supported Nanoscale Zerovalent Iron (nZVI/rGO) Using an Artificial Neural Network-Genetic Algorithm (ANN-GA)
	Shi, Xuedan ; Ruan, Wenqian ; Hu, Jiwei ; Fan, Mingyi ; Cao, Rensheng ; Wei, Xionghui
刊名	NANOMATERIALS
	2017
关键词	rhodamine B nanoscale zero-valent iron graphene RSM ANN-GA adsorption isotherm and kinetics ZERO-VALENT IRON RESPONSE-SURFACE METHODOLOGY SYNTHETIC DYES EXPERIMENTAL-DESIGN MECHANISTIC MODELS ACTIVATED CARBON PB(II) REMOVAL WATER ADSORPTION NANOPARTICLES
DOI	10.3390/nano7060134
英文摘要	Rhodamine B (Rh B) is a toxic dye that is harmful to the environment, humans, and animals, and thus the discharge of Rh B wastewater has become a critical concern. In the present study, reduced graphene oxide-supported nanoscale zero-valent iron (nZVI/rGO) was used to treat Rh B aqueous solutions. The nZVI/rGO composites were synthesized with the chemical deposition method and were characterized using scanning electron microscopy (SEM), X-ray diffraction (XRD), Raman spectroscopy, N-2-sorption, and X-ray photoelectron spectroscopy (XPS) analysis. The effects of several important parameters (initial pH, initial concentration, temperature, and contact time) on the removal of Rh B by nZVI/rGO were optimized by response surface methodology (RSM) and artificial neural network hybridized with genetic algorithm (ANN-GA). The results suggest that the ANN-GA model was more accurate than the RSM model. The predicted optimum value of Rh B removal efficiency (90.0%) was determined using the ANN-GA model, which was compatible with the experimental value (86.4%). Moreover, the Langmuir, Freundlich, and Temkin isotherm equations were applied to fit the adsorption equilibrium data, and the Freundlich isotherm was the most suitable model for describing the process for sorption of Rh B onto the nZVI/rGO composites. The maximum adsorption capacity based on the Langmuir isotherm was 87.72 mg/g. The removal process of Rh B could be completed within 20 min, which was well described by the pseudo-second order kinetic model.; National Natural Science Foundation of China [21667012]; SCI(E); ARTICLE; 6; 7
语种	英语
内容类型	期刊论文
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/473064]
专题	化学与分子工程学院
推荐引用方式 GB/T 7714	Shi, Xuedan,Ruan, Wenqian,Hu, Jiwei,et al. Optimizing the Removal of Rhodamine B in Aqueous Solutions by Reduced Graphene Oxide-Supported Nanoscale Zerovalent Iron (nZVI/rGO) Using an Artificial Neural Network-Genetic Algorithm (ANN-GA)[J]. NANOMATERIALS,2017.
APA	Shi, Xuedan,Ruan, Wenqian,Hu, Jiwei,Fan, Mingyi,Cao, Rensheng,&Wei, Xionghui.(2017).Optimizing the Removal of Rhodamine B in Aqueous Solutions by Reduced Graphene Oxide-Supported Nanoscale Zerovalent Iron (nZVI/rGO) Using an Artificial Neural Network-Genetic Algorithm (ANN-GA).NANOMATERIALS.
MLA	Shi, Xuedan,et al."Optimizing the Removal of Rhodamine B in Aqueous Solutions by Reduced Graphene Oxide-Supported Nanoscale Zerovalent Iron (nZVI/rGO) Using an Artificial Neural Network-Genetic Algorithm (ANN-GA)".NANOMATERIALS (2017).