MULTI-OBJECTIVE OPTIMIZATION OF COBALT FERRITE NANOPARTICLE SYNTHESIS USING MICROREACTOR SYSTEM TENSION MEMBERS USING ANSYS TOOL

Abstract

A grey relational analysis was conducted to investigate the effect of process parameters on the crystallite size and magnetic properties of cobalt ferrite nanoparticles. The Taguchi statistical experiments were utilized, and an L9 orthogonal array was employed to conduct nine unique experiments with three different levels for each process parameter. The analysis showed that the optimal values for the parameters to achieve the desired crystallite size and magnetic properties were a heat treatment temperature of 1053 K, EDTA-to-metal ions molar ratio of 1.7, EG-to-metal ions molar ratio of 3, and pH value of 6.5. The Scherrer formula was used to calculate the crystallite size by analyzing the powder X-ray diffraction patterns. The results showed that the crystallite size ranged from 2-9 nm depending on the different levels of each parameter. The vibrating sample magnetometer (VSM) was utilized to analyze the magnetic properties of the samples, and magnetic parameters such as saturation magnetization (MS) and coercivity (HC) were obtained from the VSM data. This study demonstrated that the Microreactor process can be effectively optimized using the Taguchi statistical experiments and grey relational analysis to create nanostructured cobalt ferrite powders with desired crystallite size and magnetic properties. The findings of this research can be used as a basis for further optimization studies on other material systems.