Study of interaction effects in magnetic granular systems for recording media application

Magnetic nano-systems have a wide scope of applications ranging from data storage technologies to biomedicine. In data storage devices the information is encoded in the grain magnetisation corresponding to bit "0" and "1". The recording media industry is driven by increasing the areal density of stored data and decreasing cost, while in the same time maintaining the thermal stability and signal-to-noise ratio. For this, close-packed 2-dimensional granular systems are used, with nanometre grain size. The quality of such magnetic recording media depends on the intrinsic material properties and on the inter-granular coupling via exchange and magnetostatic interaction. The work presented here studies the effects of inter-granular coupling and investigates different approaches to extract intrinsic properties from the bulk measurements. Due to the irregular shape of the grains, the dipole approximation for magnetostatic interaction is inaccurate. For higher accuracy, a 5-fold numerical integral is required for each pair of grains. Analytical integration over the grains height is possible reducing the numerical calculation to a 3-fold integral. The competition between the exchange and magnetostatic interactions leads to complex magnetic structures and correlated behaviour, where groups of grains behave collectively. The effects are observed and studied here based on the magnetic radial correlation function which shows a damped oscillatory form as a function of grain separation. The correlation length increases with increasing exchange interaction. An important consequence of correlated behaviour is that it alters the intrinsic switching field distribution (SFD), leading to an effective SFD. The intrinsic SFD is a fundamental characteristic of granular magnetic materials, defined as the distribution of irreversible switching events of magnetic grains in the absence of inter-granular interactions. Separating the intrinsic SFD from the effective SFD remains a challenge. Two methods that have been widely used to extract the intrinsic SFDs from hysteresis based measurements, the so-called FORC method and the Delta H(M, Delta M)-method are compared. It is shown here that the FORC diagrams contain useful information about the interactions in the system, but the ability to extract the intrinsic SFD is limited to the system in which the magnetic correlations can be neglected. Identifying the SFD from hysteresis loop measurements in the parameter range relevant for applications, requires applying the inverse problem solving techniques such as the Delta H(M, Delta M)-method.