Abstract
The uses of rice husk are constantly increasing since the last decay. Rice husk is a by-product attained from agricultural activities and has a potential use as a bio-sorbent for the adsorption of heavy metal ions, for example, lead removal from water and other aqueous solutions. The basic objective of this research is to synthesis environment-friendly adsorbent using rice husks. The study also investigated the effects of rice husk treatment on the elimination of Pb(II) ion from aqueous solutions. The results of adsorption capability also been related to the commercial activated carbon (CAC). Rice husks were treated in a few processes which were the pretreatment of raw rice husks, chemical activation, and carbonization process. Subsequently, it was characterized using X-ray diffraction (XRD) and SEM. The structure of the adsorbent using rice husks is found to be amorphous. Based on the treated rice husks characterization, the optimum carbonization temperature is found to be 600 degrees C. Temperature alteration showed 50-60% weight loss, with up to 3.475% removal. Artificial neural network modeling was applied to predict the experimental data sets using feed forward back-propagation neural network (FFBPNN) and Levenberg-Marquardt (L-M) training algorithm. The customized neural network was applied to emphasize the predicted adsorption capacity and removal/uptake percentage of the investigated bio-sorbents. The outcomes from the artificial neural network model showed high validity of the predicted data compared to the initially examined experimental data sets. The adsorption efficiency increases with the increment of carbon presence ratio in the adsorbent. The adsorption measurements are well presented by the Langmuir isotherm. The kinetic modelling revealed that the adsorption of Pb(II) ions followed the pseudo-second-order models. The reported results in this work can deliberate the rice husks as a potential alternative to commercial adsorbents with lower cost and better environmental aspects.