Prediction of the Superparamagnetic Limit for Magnetic Storage Medium Using Artificial Neural Networks

In this study, computational techniques based on artificial neural networks for three models were used for training sets, N & eacute;e l's relaxation time, particle Length and the decay of magnetization were used to perform superparamagnetic calculations for Co 3 Pt and FePt typical magnetic storage medium. The magnetic medium's magnetisation stability was studied using the thermal stability coefficient by determining the N & eacute;el relaxation time. The superparamagnetic limit was discovered to determine the size of the magnetic particle that can maintain its magnetization for over 10 years, larger particles (8 nm 3 for FePt and 64 nm 3 for Co 3 Pt) are required. The decay of magnetization occurs when the thermal stability factor exceeds 40. the effect of changing the neural network's parameters on its performance was examined. The results demonstrated the high sensitivity of the designed neural network's response, which relies on the backpropagation technique to change these parameters.