4.6 Article

Fixed-Bed Adsorption of Phenol onto Microporous Activated Carbon Set from Rice Husk Using Chemical Activation

期刊

APPLIED SCIENCES-BASEL
卷 12, 期 9, 页码 -

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MDPI
DOI: 10.3390/app12094354

关键词

activated carbon; breakthrough curve; column study; phenol removal; rice husk

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  1. King Faisal University, Saudi Arabia [AN00048]

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In this study, the potential of activated carbon from rice husk as a medium for phenol removal from aqueous solution was investigated. It was found that the activated carbon had a porous structure with a large surface area and exhibited increased adsorption capacity with higher influent concentration and bed depth, while decreased adsorption capacity with higher feed flow rate. The regeneration of activated carbon column using sodium hydroxide was found to be effective.
In the course of this research, the potential of activated carbon from rice husk was examined as being a phenol removal medium from an aqueous solution in a fixed-bed adsorption column. The activated carbon was characterized through FESEM (Field-Emission Scanning Electron Microscopy) and BET (Brunauer-Emmett-Teller) surface area. According to the FESEM micrograph and BET surface area, RHAC (rice husk activated carbon) had a porous structure with a large surface area of 587 m(2)center dot g(-1) and mean diameter of pores of 2.06 nm. The concentration effects on the influent phenol (100-2000 mg center dot L-1), rate of flow (5-10 mL center dot min(-1)), and bed depth (8.5-15.3 cm) were examined. It was found that the capacity of bed adsorption increased according to the increase in the influent concentration and bed depth. However, the capacity of bed adsorption decreased according to the increase in the feed flow rate. The regeneration of activated carbon column using 0.1 M sodium hydroxide was found to be effective with a 75% regeneration efficiency after three regeneration cycles. Data on adsorption were observed to be in line with many well-established models (i.e., Yoon-Nelson and Adams-Bohart, as well as bed depth service time models).

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