Statistical optimization of effective parameters on saturation magnetization of nanomagnetite particles

In this study, nanomagnetite particles have been successfully prepared via the coprecipitation method. The effect of the key explanatory variables on the saturation magnetization of synthetic nanomagnetite particles was investigated using the response surface methodology (RSM). The correlation of the involved parameters with the growth process was examined by employing the central composite design method through designating set up experiments that will determine the interaction of the variables. The vibrating sample magnetometer (VSM) was used to confirm the statistical analysis. Furthermore, the regression analysis monitors the priority of the variables' influence on the saturation magnetization of nanomagnetite particles by developing the statistical model of the saturation magnetization. According to the investigated model, the highest interaction of variable belongs to the pH and temperature with the optimized condition of 9-11, and 75-85 °C, respectively. The response obtained by VSM suggests that the saturation magnetization of nanomagnetite particles can be controlled by restricting the effective parameters.