Study of the training effect in exchange bias using the domain state model

Abstract

The most common product of the storage industry is the well known hard disk, based on the magnetic recording and reading of data. The research of magnetic materials is enhanced by the establishment of hard disks as a recording media. Given the current trend toward nanostructured materials and complex materials design, the understanding of the origins of magnetic phenomenology at the atomistic level has become necessary. In this thesis, we focus on the aging effects of magnetic materials. The systems that are investigated are bilayer thin films comprised of two materials with different magnetic order. The so called exchange bias systems are comprised of a ferromagnetic layer in contact with an antiferromagetic layer. Exchange bias systems are part of the current read-heads, which utilise the phenomenon of Giant Magnetoresistance discovered by A. Fert and P. Grünberg, who were awarded a Nobel prize in 2007 for this discovery. The most wellknown characteristic of the exchange bias systems is the shift of the hysteresis loop along the horizontal axis. The reduction of this shift with consecutive hysteresis cycles is called the training effect. The current research focused on the dependence of the training effect on various exchange bias system parameters using the well established domain state model. A novel analysis was developed for the study of the antiferromagnet during consecutive hysteresis loops. A special focus was given to the response of training effect on temperature. Several characteristics of the system were varied to investigate the physics of the training effect, such as the antiferromagnetic thickness and dilution with non-magnetic defects. The reversal modes of the ferromagnet were also investigated varying the anisotropies of the system as well the angle of the magnetic field. New characteristics were added to the domain state model increasing the realism of this model. The interface roughness was introduced in the model, as more representative of realistic exchange bias systems. Furthermore, different crystallographic structures such as body-centered cubic and hexagonal-close packed, were investigated as in these structures the coupling between the ferromagnet and the antiferromagnet increases. In these structures, in addition to the interface roughness, the enhance coupling is shown to give rise to complex trends of the exchange bias and the training effect