Introduction

A quantitative treatment of the correlation between the microstructure and magnetic properties in nanostructured materials requires numerical and computational techniques. These techniques, in many senses, are complimentary to the experimental ones, especially in understanding of the magnetization reversal mechanisms, which define the nano-structured material performance. The experimental studies, such as magnetic imaging, have serious difficulties in controlling the magnetic properties down to several nanometers scale in space or down to nanosecond scale in time. At the same time, the modeling of reversal modes propagation both in space and time in this scale is possible. The use of computational techniques such as micromagnetics provides a way to obtain a realistic relation between the microstructure and magnetic properties in many cases.

By using this technique, the magnetic properties of a nanostructured material, relevant to its application, such as coercivity and remanence, dynamical switching time, and thermal stability could be predicted qualitatively in relation to nanostructure. The rapid variation of many extrinsic and intrinsic parameters is accessible by using numerical techniques and is useful in understanding the qualitative tendency in the material behavior when one constitutes the design of materials with determined properties. As an example, the micromagnetic simulations have been shown to be extremely useful techniques in the study of the performance of magnetic media used for magnetic recording.

In general, many factors influence the magnetic properties of a nanocrystalline magnetic film, e.g., the grain size and shape, anisotropy distribution, the grain boundary properties, magnetic impurities, etc. The potential of an analytical approach is limited to a small number of very simplified cases. The simulations represent the only alternative to experimental techniques. At the same time, the micromagnetic simulations require an input of the intrinsic media parameters in the micromagnetic code from measurements. However, in many cases and especially in granular materials, the experimental techniques are unable to provide the knowledge of the microstructure with the desired details. This is especially true for the treatment of the grain boundary in nanostructured materials where normally there is no detailed knowledge of many intrinsic parameters such as exchange or anisotropy. This limits the potential accuracy of micromagnetic predictions. For example, the coer-civity value, which is a result of very complicated interplay between intrinsic and extrinsic magnetic medium parameters, calculated numerically, rarely coincides with the experimental value. At the same time, this also constitutes a strong point of the numerical simulations since it allows the flexibility and control in varying the intrinsic parameters (such as different intergrain boundary models), which are not accessible by experimental techniques, with the aim of a final comparison of the results with the experimental measurements.

We ? will describe the principle utilities and results of the so-called micromagnetic simulations in relation to the magnetization reversal processes in nanostructured magnetic materials. Section 4.2 will describe briefly the classical micromagnetics. In Sections 4.3 to 4.5, we present results on the role of zero-temperature micromagnetic simulations in understanding the magnetization reversal processes in nanostructured magnetic materials. Section 4.6 is devoted to simulations of magnetic recording medium performance. In Section 4.7, we present the results of the micromagnetic simulation guiding the optimization of magnetic behavior of nanocomposite (soft-hard) magnetic materials. Finally, Sections 4.8 and 4.9 are devoted to "nonclassical" micromag-netics, i.e., to the dynamical behavior of the nanostructured media and to the effects of temperature.

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