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Optimisation of process variables by response surface methodology (RSM) for malachite green dye removal using spent tea leaves biochar


Citation

Nur Ir Imani Ishak (2019) Optimisation of process variables by response surface methodology (RSM) for malachite green dye removal using spent tea leaves biochar. Final Year Project thesis, Universiti Malaysia Kelantan. (Submitted)

Abstract

Due to simple preparation, spent tea leaves lead to disposing problem and causes accumulation of agricultural wastes. Conventional methods for the effluent treatment are expensive and have low removal efficiency. Hence, the utilisation of agricultural waste to an added value product which known as biosorbent is suggested due to its reliability and affordability. This study is aimed to use biochar derived from the Spent Tea Leaves (STL) as a biosorbent for Malachite Green (MG) dye removal and the application of Response Surface Methodology (RSM) to optimise the process variables. All analysis was successfully done by applying Central Composite Design (CCD). The adsorptive capacity of spent tea leaves biochar were investigated under combined effects of parameter such as adsorbent dosage, initial dye concentration and contact time. Maximum MG dye adsorption of 98.76 % was achieved using STL biochar. The statistical analysis was performed by ANOVA which indicated good correlation of experimental parameter with R2 of 0.9854. The experimental data was fitted to the empirical second-order polynomial model. Numerical optimisation showed the optimum operating conditions of adsorbent dosage was 0.18 g, 46.92 mg/L of initial dye concentration and contact time of 56.16 minutes with desirability of 1.000. Physical characterization of MG dye, STL powder and STL biochar was studied using FTIR and SEM analysis. Spent tea leaves biochar was found to be very effective for the removal of MG dye from aqueous solution.

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Additional Metadata

Item Type: Undergraduate Final Project Report
Collection Type: Final Year Project
Date: 2019
Call Number: SBT 2019 032
Supervisor: Dr. Mardawani Binti Mohamad
Programme: Bioindustrial Technology
Institution: Universiti Malaysia Kelantan
Faculty/Centre/Office: Faculty of Bioengineering and Technology
URI: http://discol.umk.edu.my/id/eprint/4700
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