Case study of media noise mechanisms in longitudinal recording

Abstract

A comprehensive study (TEM, MFM, AFM, XRD, Recording Performance and Magnetometry) of media noise mechanisms and their relation to grain structure is reported for model, high noise contrast, CoCrPtTa thin films. The CoCrPtTa media were sputtered on to either CrMn or NiAIKrMn underlayers causing a change in media noise power of 9dB. The changes in media noise are not related to the topography of the underlayer(s) or due to interaction effects, which the 6M technique suggests are negligible in these model samples. A quantitative correlation is obtained between magnetic cluster size and media noise using an analytical first approximation of Zhou and Bertram's micromagnetic model.

Signal-to-noise ratio definition for magnetic recording channels with transition noise

“…We propose the following SNR definition to handle mixed noise channels: (5) where is twice the average energy 2 of the medium noise associated with each transition, , and denotes 1 Ryan used the notation E to denote the energy in the isolated transition response, but we use the subscript t to emphasize it is the energy in the isolated transition response rather than isolated dibit response. Also, note that h(t) here is the response to a full magnetization step, whereas the transition response in [1] is the half magnetization step, leading to the relationship: E = 4E .…”

“…This assumption will hold for any recording systems in which the total integrated medium noise power increases linearly with (i.e., where the intrinsic medium noise power per transition remains the same as the symbol pattern or density changes). This condition is met with well-designed media that do not exhibit supralinear noise increase with density (see, for example, [5]). …”

Micromagnetic torque studies of the intergranular exchange coupling and magnetocrystalline anisotropy in longitudinal recording media

“…2 and the inset, the low-noise sample 15B has a relatively narrow Gaussian distribution of H k values with dispersion value s ¼ 1:1: In contrast, the high-noise sample shows a significantly broader distribution of H k following a lognormal dependence with dispersion value s ¼ 0:3: Both results reflect the distributions of grain size, which are drastically different for the two samples. Low-noise 15B has an average size of 17 nm (as detected by TEM [1]) with a dispersion of 10%, whereas the high-noise sample 15A has very irregular shaped grains ranging in size between 20 and 200 nm:…”

“…The samples have been previously characterised by a range of techniques including TEM, FMR, Vector VSM, Delta-M and Delta-T [1][2][3][4], which gave us an initial range of parameters for the analysis of the torque data. Here we use micromagnetic modelling of torque [4] to simulate experimental data from the two samples and extract parameters of the anisotropy field H k ; exchange coupling C Ã and anisotropy field distribution.…”

Micromagnetic modelling of SANS in longitudinal recording media

“…Typically, these are moderately regular systems containing low dispersion nanomagnetic grains segregated within a magnetically passive layer (e.g. CoPtCrTa [6]). A characteristic feature of longitudinal media is that the anisotropy of the grains is randomly oriented, but confined to the film plane.…”