A Facile Precipitation Synthesis and Magnetic Investigation of Fe3O4 Nanoparticles and Modeling for Predicting the Particle Size, Using Artificial Neural Network (ANN)
پذیرفته شده برای ارائه شفاهی
عنوان دوره: اولین همایش ملی توسعه فناوری نانو در علوم پایه و مهندسی
کد مقاله : 1054-DNBSE
نویسندگان
1دانشگاه اراک
2دانشگاه صنعتی اراک
چکیده
Magnetic nanoparticles have been one of the most popular topics in science and engineering during the two last decades. Magnetite nanoparticles were prepared by a simple precipitation method between FeCl3.6H2O and FeCl2.4H2O. X-ray diffraction (XRD) and scanning electron microscopy (SEM) were used to study the structural and physical properties of magnetite nanoparticles. The magnetic properties of the product were also investigated using a vibrating sample magnetometer (VSM). The Fe3O4 nanoparticles exhibit ferrimagnetic behaviour at room temperature, with a saturation magnetization of 31 emu/g and a coercivity of 2 Oe. Artificial neural network (ANN) models can be able to eliminate the need for expensive experimental investigation in various areas such as manufacturing processes and estimation including the casting methods. In this research, we used various parameters such as ppm of a solution, temperature and reaction time to prediction the average size of Fe3O4 nanoparticles.
کلیدواژه ها
موضوعات
فیلم ارائه