Modeling and Optimization for Production of Rice Husk Activated Carbon and Adsorption of Phenol

Modeling of adsorption process establishes mathematical relationship between the interacting process variables and process optimization is important in determining the values of factors for which the response is at maximum. In this paper, response surface methodology was employed for the modeling an...

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Main Authors: Y. S. Mohammad, E. M. Shaibu-Imodagbe, S. B. Igboro, A. Giwa, C. A. Okuofu
Format: Article
Language:English
Published: Hindawi Limited 2014-01-01
Series:Journal of Engineering
Online Access:http://dx.doi.org/10.1155/2014/278075
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spelling doaj-0aff576492cf4297993014cc67f286702020-11-24T21:57:47ZengHindawi LimitedJournal of Engineering2314-49042314-49122014-01-01201410.1155/2014/278075278075Modeling and Optimization for Production of Rice Husk Activated Carbon and Adsorption of PhenolY. S. Mohammad0E. M. Shaibu-Imodagbe1S. B. Igboro2A. Giwa3C. A. Okuofu4Department of Water Resources and Environmental Engineering, ABU, Zaria, NigeriaSamaru College of Agriculture, Division of Agricultural Colleges, ABU, Zaria, NigeriaDepartment of Water Resources and Environmental Engineering, ABU, Zaria, NigeriaDepartment of Textile Science and Technology, ABU, Zaria, NigeriaDepartment of Water Resources and Environmental Engineering, ABU, Zaria, NigeriaModeling of adsorption process establishes mathematical relationship between the interacting process variables and process optimization is important in determining the values of factors for which the response is at maximum. In this paper, response surface methodology was employed for the modeling and optimization of adsorption of phenol onto rice husk activated carbon. Among the action variables considered are activated carbon pretreatment temperature, adsorbent dosage, and initial concentration of phenol, while the response variables are removal efficiency and adsorption capacity. Regression analysis was used to analyze the models developed. The outcome of this research showed that 99.79% and 99.81% of the variations in removal efficiency and adsorption capacity, respectively, are attributed to the three process variables considered, that is, pretreatment temperature, adsorbent dosage, and initial phenol concentration. Therefore, the models can be used to predict the interaction of the process variables. Optimization tests showed that the optimum operating conditions for the adsorption process occurred at initial solute concentration of 40.61 mg/L, pretreatment temperature of 441.46°C, adsorbent dosage 4 g, adsorption capacity of 0.9595 mg/g, and removal efficiency of 97.16%. These optimum operating conditions were experimentally validated.http://dx.doi.org/10.1155/2014/278075
collection DOAJ
language English
format Article
sources DOAJ
author Y. S. Mohammad
E. M. Shaibu-Imodagbe
S. B. Igboro
A. Giwa
C. A. Okuofu
spellingShingle Y. S. Mohammad
E. M. Shaibu-Imodagbe
S. B. Igboro
A. Giwa
C. A. Okuofu
Modeling and Optimization for Production of Rice Husk Activated Carbon and Adsorption of Phenol
Journal of Engineering
author_facet Y. S. Mohammad
E. M. Shaibu-Imodagbe
S. B. Igboro
A. Giwa
C. A. Okuofu
author_sort Y. S. Mohammad
title Modeling and Optimization for Production of Rice Husk Activated Carbon and Adsorption of Phenol
title_short Modeling and Optimization for Production of Rice Husk Activated Carbon and Adsorption of Phenol
title_full Modeling and Optimization for Production of Rice Husk Activated Carbon and Adsorption of Phenol
title_fullStr Modeling and Optimization for Production of Rice Husk Activated Carbon and Adsorption of Phenol
title_full_unstemmed Modeling and Optimization for Production of Rice Husk Activated Carbon and Adsorption of Phenol
title_sort modeling and optimization for production of rice husk activated carbon and adsorption of phenol
publisher Hindawi Limited
series Journal of Engineering
issn 2314-4904
2314-4912
publishDate 2014-01-01
description Modeling of adsorption process establishes mathematical relationship between the interacting process variables and process optimization is important in determining the values of factors for which the response is at maximum. In this paper, response surface methodology was employed for the modeling and optimization of adsorption of phenol onto rice husk activated carbon. Among the action variables considered are activated carbon pretreatment temperature, adsorbent dosage, and initial concentration of phenol, while the response variables are removal efficiency and adsorption capacity. Regression analysis was used to analyze the models developed. The outcome of this research showed that 99.79% and 99.81% of the variations in removal efficiency and adsorption capacity, respectively, are attributed to the three process variables considered, that is, pretreatment temperature, adsorbent dosage, and initial phenol concentration. Therefore, the models can be used to predict the interaction of the process variables. Optimization tests showed that the optimum operating conditions for the adsorption process occurred at initial solute concentration of 40.61 mg/L, pretreatment temperature of 441.46°C, adsorbent dosage 4 g, adsorption capacity of 0.9595 mg/g, and removal efficiency of 97.16%. These optimum operating conditions were experimentally validated.
url http://dx.doi.org/10.1155/2014/278075
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