Rice husk derived silica and its application for treatment of fluoride containing wastewater: batch study and modeling using artificial neural network analysis

摘要

Fluoride contamination in water may create environmental hazards. In the present investigation, nano silica was synthesized from agricultural waste (rice husk) at high temperature in a tubular reactor and de-fluoridation capacity of the entire product was explored. The batch experiments were conducted at different conditions: adsorbent dose, temperature, and contact time to evaluate the fluoride removal performance. It was observed that the synthesized product have higher de-fluoridation efficiency than its pristine counterparts such as 70.86% (rice husk, RH), 88.69% (rice husk derived silica, Si-RH) respectively. The equilibrium data for de-fluoridation by rice husk(RH) and rice husk derived silica (Si-RH) were best fitted to the Langmuir isotherm model. The experimental results were applied to obtain training set for Artificial Neural Network (ANN) analysis. The results suggested that ANN model prediction shows a closer interaction between experimental and theoretical results. It may be concluded that rice husk and its derivatives could be an environmentally benign and economic option for de-fluoridation.