Optimizing and control of effective synthesize parameters for Fe3O4 nanoparticles using response surface methodology

Abstract

To control Fe3O4 nanoparticles (Fe3O4 NPs) size, different molar ratio of Fe2+ and Fe3+ as well as ammonium hydroxide (pH) was used to synthesize Fe3O4 NPs through co-precipitation method. The Box–Behnken design was selected to explore the interaction between process parameters (factors) such as Fe2+ molar ion, Fe3+ molar ion and pH on the final size. The interactive effect between the process variables was evaluated by analysis of variance (ANOVA). The quadratic model predicted by the Box–Behnken design was significant with a P value of < 0.0001. The optimum synthesis conditions were predicted by the model indicating optimum size obtained using 1.00 mol Fe2+ ion with 3.00 mol Fe3+ ion with pH at 12.00. From the experiment, the particle size was 10 ± 2 nm at optimum conditions, while the model predicted a particle size of 6.80 nm. The magnetic properties of Fe3O4 NPs were displayed typical ferromagnetic behavior with saturation magnetization value to be 49.729 emu/g. Finally, the optimized Fe3O4 NPs showed about 80% removal of Congo red (CR) dye, which confirms their applicability in adsorption process for future applications.

Removal of Cr(VI) from aqueous solution using ball mill modified biochar: multivariate modeling, optimization and experimental study

“…In order to evaluate the reliability of the quadratic model, the F value in the S9 analysis of variance (ANOVA) in the SI table was used for analysis. The F value of the model was 39, and the p value was < 0.001, indicating that the model had a significant effect on the response 71 . Table 5 showed that the R 2 value of the model was 0.9701, indicating that 97.01% of the model was consistent with the experimental data, and only 2.99% of the data did not match the model.…”