Efficient Removal of 2,4-DCP by Nano Zero-Valent Iron-Reduced Graphene Oxide: Statistical Modeling and Process Optimization Using RSM-BBD Approach

In this study, nano zero-valent iron-reduced graphene oxide (NZVI-rGO) composites were synthesized to remove 2,4-dichlorophenol (2,4-DCP) as an efficient adsorbent. Scanning electron microscopy (SEM) and X-ray diffraction (XRD) indicated that NZVI particles were successfully loaded and dispersed uni...

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Autores principales:	Qi Jing, Shuo Qiao, Wenyu Xiao, Le Tong, Zhongyu Ren
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi - SAGE Publishing 2021
Materias:	Physical and theoretical chemistry QD450-801
Acceso en línea:	https://doaj.org/article/3f183546adfc4c7f84852827ddf698b7
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spelling	oai:doaj.org-article:3f183546adfc4c7f84852827ddf698b72021-11-22T01:11:16ZEfficient Removal of 2,4-DCP by Nano Zero-Valent Iron-Reduced Graphene Oxide: Statistical Modeling and Process Optimization Using RSM-BBD Approach2048-403810.1155/2021/7130581https://doaj.org/article/3f183546adfc4c7f84852827ddf698b72021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/7130581https://doaj.org/toc/2048-4038In this study, nano zero-valent iron-reduced graphene oxide (NZVI-rGO) composites were synthesized to remove 2,4-dichlorophenol (2,4-DCP) as an efficient adsorbent. Scanning electron microscopy (SEM) and X-ray diffraction (XRD) indicated that NZVI particles were successfully loaded and dispersed uniformly on rGO nanosheets. Fourier transform infrared spectroscopy (FTIR) analysis showed that the interaction between NZVI-rGO and 2,4-DCP promoted the adsorption process. A three-level, four-factor Box-Behnken design (BBD) of the response surface methodology (RSM) was used to optimize the influencing factors including NZVI-rGO dosage, 2,4-DCP initial concentration, reaction time and initial pH. A statistically significant, well-fitting quadratic regression model was successfully constructed to predict 2,4-DCP removal rate. The high F value (15.95), very low P value (<0.0001), nonsignificant lack of fit, and appropriate coefficient of determination (R2=0.941) demonstrate a good correlation between the experimental and predicted values of the proposed model. The analyses of variance reveal that NZVI-rGO dosage and reaction time have a positive effect on 2,4-DCP removal, whereas the increase of contaminant concentration and initial pH inhibit the removal, whereas the effect of contaminant concentration and initial pH is in reverse, where the change of NZVI-rGO dosage has the greatest effect. The optimum condition is1.215 g/L of NZVI-rGO dosage, 20.856 mg/L of 2,4-DCP concentration, 4.115 of pH, and 8.157 min of reaction time. It is verified by parallel experiments under the optimum condition, achieving the removal efficiency of100%.Qi JingShuo QiaoWenyu XiaoLe TongZhongyu RenHindawi - SAGE PublishingarticlePhysical and theoretical chemistryQD450-801ENAdsorption Science & Technology, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Physical and theoretical chemistry QD450-801
spellingShingle	Physical and theoretical chemistry QD450-801 Qi Jing Shuo Qiao Wenyu Xiao Le Tong Zhongyu Ren Efficient Removal of 2,4-DCP by Nano Zero-Valent Iron-Reduced Graphene Oxide: Statistical Modeling and Process Optimization Using RSM-BBD Approach
description	In this study, nano zero-valent iron-reduced graphene oxide (NZVI-rGO) composites were synthesized to remove 2,4-dichlorophenol (2,4-DCP) as an efficient adsorbent. Scanning electron microscopy (SEM) and X-ray diffraction (XRD) indicated that NZVI particles were successfully loaded and dispersed uniformly on rGO nanosheets. Fourier transform infrared spectroscopy (FTIR) analysis showed that the interaction between NZVI-rGO and 2,4-DCP promoted the adsorption process. A three-level, four-factor Box-Behnken design (BBD) of the response surface methodology (RSM) was used to optimize the influencing factors including NZVI-rGO dosage, 2,4-DCP initial concentration, reaction time and initial pH. A statistically significant, well-fitting quadratic regression model was successfully constructed to predict 2,4-DCP removal rate. The high F value (15.95), very low P value (<0.0001), nonsignificant lack of fit, and appropriate coefficient of determination (R2=0.941) demonstrate a good correlation between the experimental and predicted values of the proposed model. The analyses of variance reveal that NZVI-rGO dosage and reaction time have a positive effect on 2,4-DCP removal, whereas the increase of contaminant concentration and initial pH inhibit the removal, whereas the effect of contaminant concentration and initial pH is in reverse, where the change of NZVI-rGO dosage has the greatest effect. The optimum condition is1.215 g/L of NZVI-rGO dosage, 20.856 mg/L of 2,4-DCP concentration, 4.115 of pH, and 8.157 min of reaction time. It is verified by parallel experiments under the optimum condition, achieving the removal efficiency of100%.
format	article
author	Qi Jing Shuo Qiao Wenyu Xiao Le Tong Zhongyu Ren
author_facet	Qi Jing Shuo Qiao Wenyu Xiao Le Tong Zhongyu Ren
author_sort	Qi Jing
title	Efficient Removal of 2,4-DCP by Nano Zero-Valent Iron-Reduced Graphene Oxide: Statistical Modeling and Process Optimization Using RSM-BBD Approach
title_short	Efficient Removal of 2,4-DCP by Nano Zero-Valent Iron-Reduced Graphene Oxide: Statistical Modeling and Process Optimization Using RSM-BBD Approach
title_full	Efficient Removal of 2,4-DCP by Nano Zero-Valent Iron-Reduced Graphene Oxide: Statistical Modeling and Process Optimization Using RSM-BBD Approach
title_fullStr	Efficient Removal of 2,4-DCP by Nano Zero-Valent Iron-Reduced Graphene Oxide: Statistical Modeling and Process Optimization Using RSM-BBD Approach
title_full_unstemmed	Efficient Removal of 2,4-DCP by Nano Zero-Valent Iron-Reduced Graphene Oxide: Statistical Modeling and Process Optimization Using RSM-BBD Approach
title_sort	efficient removal of 2,4-dcp by nano zero-valent iron-reduced graphene oxide: statistical modeling and process optimization using rsm-bbd approach
publisher	Hindawi - SAGE Publishing
publishDate	2021
url	https://doaj.org/article/3f183546adfc4c7f84852827ddf698b7
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Efficient Removal of 2,4-DCP by Nano Zero-Valent Iron-Reduced Graphene Oxide: Statistical Modeling and Process Optimization Using RSM-BBD Approach

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