Quantifiable combinatorial materials science approach applied to perpendicular magnetic recording media.

Autor: Svedberg, Erik B., van de Veerdonk, Rene J. M., Howard, Kent J., Madsen, Lynnette D.
Předmět:
Zdroj: Journal of Applied Physics; 5/1/2003, Vol. 93 Issue 9, p5519, 8p, 1 Black and White Photograph, 3 Charts, 6 Graphs
Abstrakt: Deposition of films with controlled gradients across the wafer in terms of both composition and thickness were used together with statistical experimental design methodologies to explore large parameter spaces relevant to the optimization of perpendicular magnetic recording media. With this approach, thickness and composition of the media and the interdependencies of these variables were efficiently investigated and correlated to the coercivity of the material and the squareness of the hysteresis loops. To determine dependencies and codependencies between additives to CoCr alloys on the magnetic properties, this method was used to study magnetic layers of CoCrPt, CoCrPtTa, CoCrPtTi, and CoCrTiTa. The best models associated with each alloy had the same terms for the three magnetic parameters measured (H[sub c], S, and θ[sub k,perp]). Additions to the CoCr alloy introduced dependencies on the Cr and cross-term dependencies with Cr (i.e., CrTa, CrPt, or CrTi). In some cases, thickness became an important parameter and for the CoCrPtTa case, the Pt concentration directly influenced the magnetic properties. These findings, obtained in a concise manner with fully descriptive empirical models, agree with the bulk of published literature. In this study, the variables are tightly controlled and variables such as temperature and residual gas concentrations are identical for all data points used within each alloy system generating an accurate transfer function. Once the transfer function between the input and output parameters is established, the sensitivity or stability to changes in the different factors can easily be investigated. © 2003 American Institute of Physics. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index