| Optimization of Magnetite Using Statistical Based Experimental Design for Arsenic Removal | ||
| Soh Fong Lim1, Shuaiwen Zou2, Yuming Zheng2 and j. Paul Chen3, (1)Chemical and Biomolecular Engineering Department, National University of Singapore (NUS), 1 Engineering Dr 2, E2-05-05, Singapore, 117576, Singapore, (2)Division of Environmental Science and Engineering, National University of Singapore, 10 kent ridge, singapore, Singapore, (3)Env Sci Eng, National University of Singapore, 10 kent ridge, singapore, Singapore The effect of magnetite fabrication parameters on the sorption of arsenic was studied and optimized by statistically based design of experiments using response surface model (RSM). RSM is a new rallying cry for robust design parameter optimization in the laboratory experiment. Three factors considered in this study were temperature, heating duration, and PEG concentration. A 33 design using specific Box-Behnken response model was used to accommodate the three factors of the fabrication parameters. It was shown that the statistical experimental design was an effective way in optimizing the sorbent fabrication parameters. This systematic and efficient approach enabled to generate a satisfactory polynomial relationship between the factors and responses across the experiment region. The polynomial equation showed that there was significant interaction on arsenic sorption capacity between temperature, heating duration, and PEG concentration which implying that the three factors were interdependent. Extended Abstract Status: File Uploaded | ||