Characterizing Intergranular Segregation in Co-based Magnetic Recording Media by AEM




Thin-film longitudinal magnetic recording media that provide the technological basis for modern personal computer hard drives are prototypical complex nanostructured materials. A combination of a complex multi-element Co-Cr-based composition with judicious selection of a host of processing variables is used to achieve a nanoscale domain structure, comprised of Co-rich grains a few tens of nanometers in size interspersed by Cr-enriched grain boundaries a few nanometers in width, that optimizes key performance criteria such as signal-to-noise and thermal stability. The intergranular segregation decouples the magnetic exchange between the nano-scale ferromagnetic grains and is a key microstructural effect that allows high data-density recording. In order to uncover the basic phenomena governing these complex materials, an intensive multi-year collaboration has been established to characterize these media by analytical electron microscopy (AEM) techniques. Preliminary efforts focussed on the development of quantitative elemental mapping of composition at ~1 nm resolution by energy-filtered transmission electron microscopy (EFTEM). These efforts have met with great success in correlating Cr concentration variation with media composition and processing, but only following the development of sophisticated treatments to mitigate the effects of diffraction contrast, specimen thickness variations, and closely spaced ionization edges. However, the mapping of common alloying additions are poorly suited to EFTEM characterization.






Analysis techniques have been developed for atom probe tomography (APT) data in order to identify and quantitatively characterize nanometer-scale features in materials. Statistical methods have been developed to identify whether variations in local composition at the nanometer or sub-nanometer scale constitute distinct microstructural features or whether these variations are consistent with statistical fluctuations in the matrix composition. The chemical short range ordering tendencies and nearest neighbor configurations of solute atoms in each phase and feature can then be statistically estimated. Although specifically developed for APT, these analysis methods are generally applicable to assemblages of atoms in a material, which may be either measured or simulated. The data analysis methods allow quantitative characteristics such as size, shape, number density, composition and atomic ordering to be determined in a robust manner, even for features with diffuse boundaries. These characteristics can then be used to construct structural models that provide a basis for interpreting indirect measurements of nanometer-scale features, such as small angle X-ray (SAXS) and neutron (SANS) scattering.

SHaRE program collaborative research by M. K. Miller (ORNL)







 Oak Ridge National Laboratory