PHOTOCATALYTIC DEGRADATION OF ACID YELLOW DYE USING ZINC NITRATE HEPTAHYDRATE DOPED EGGSHELL AND ITS OPTIMIZATION OF USING RESPONSE SURFACE METHODOLOGY AND ARTIFICIAL NEURAL NETWORK

ABSTRACT

Interest in this experiment was borne out of the need to treat water colorant so as to preserve life and protect the environment. Dye is a common waste in textile industry and there is a need to find a suitable effective means to degrade the dye. In this research work, zinc nitrate doped eggshell sourced from locations within the University of Benin. Egg shell ash was gotten from grinding the egg shell to about 50mm and then sieved before calcining to about 900ºC for four hours. This ash was then doped with zinc nitrate hexahydrate salt and washed then dried to produce a photocatalytic material useful in degrading acid yellow dye. Experimental procedures were carried out to under three main factoring conditions; irradiation time, dye concentration and catalyst loading. The use of Response Surface Methodology (RSM) and Artificial Neural Network (ANN) were then considered in choosing the best fit optimization tool taking into consideration the amount of degradation that occurred after different runs were made while altering the three factoring conditions. All three factors investigated for the purpose of determining the optimum operating conditions of the catalyst, significantly influenced the dye removal efficiency. It was determined that the quadratic core model obtained was significant and able to predict the removal efficiency (p<0.05) with RSM having a R² value of 0.9984, which was lower than ANN R² value of 0.99986. Hence, ANN is a better optimization tool than RSM.