Removal of Rhodamine B dye in aqueous solution using raw timber wood sawdust as adsorbent

Utilising agricultural waste, raw timber wood sawdust as adsorbent for the removal of Rhodamine B (RB) dye is a good alternative as it is a cost effective way. The adsorption process is used because it is found to be more economical and effective compared to other dye removal methods. Fourier Transf...

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Bibliographic Details
Main Author: Utheyakumaran, Thepadarsini
Format: Undergraduate Final Project Report
Published: 2020
Online Access:http://discol.umk.edu.my/id/eprint/4378/
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Summary:Utilising agricultural waste, raw timber wood sawdust as adsorbent for the removal of Rhodamine B (RB) dye is a good alternative as it is a cost effective way. The adsorption process is used because it is found to be more economical and effective compared to other dye removal methods. Fourier Transform Infrared spectroscopy (FTIR) analysis revealed that functional groups such as OH and amine groups on timber wood sawdust proved that it can be used as adsorbent for removal of RB dye. Various parameters such as particle size, adsorbent dosage, initial dye concentration versus contact time, and pH were investigated. The optimum adsorption of Rhodamine B dye using raw timber wood sawdust as bio-sorbent were found to be at 0.355 mm of particle size which is worked best on 4.0 gram of adsorbent dosage in 24 hours at pH 3 with 5 minutes of agitation time at room temperature. Adsorption isotherm was studied by using Langmuir and Freundlich isotherm. The best fit line model favoured the Langmuir isotherm with R2 of 0.9998. Langmuir best fit graph indicates that the adsorption that took place is a monolayer adsorption. The highest percentage removal of RB dye was found at 98.86% at pH 3 and it is proven that raw timber wood sawdust is potential to remove Rhodamine B dye. Kinetic Modelling study was conducted with pseudo-first order and pseudo-second-order to evaluate the rate of adsorption of adsorbent. The adsorption process follows pseudo-second-order model which is a better fit for the experimental data than the pseudo-first-order model.