Artificial Neural Network modeling of spin-transition behavior in two-dimensional molecular magnet: The learning by experiences analysis

Monte Carlo simulation was used to study dynamic spin-transition behavior via thermal hysteresis in two-dimensional molecular magnetic systems. The Ising model in Wajnflasz-Pick version with elastic interaction was used to investigate the thermal hysteresis behavior with varying the spin-state characteristic and field perturbation. The Artificial Neural Network modeling was then used in establishing the database of how relevant parameters quantitatively affect the hysteresis phenomena over broad ranges. Suggesting by good statistical accuracy, the ANN model and the obtained database are dependable, which confirming the ANN success in modeling spin-transition behavior in ultra-thin-film molecular magnet.