Simulation and Analysis of Co-Pt Based Granular Magnetic Recording Media Near the Curie Temperature
Bibliographic record
Abstract
Heat-assisted magnetic recording (HAMR) has been shown to satisfy modern data storage of hard disk drives by enabling the writing of high-anisotropy materials such as Fe-Pt. Modelling the magnetization dynamics near the Curie temperature (Tc) is crucial when predicting the limits of HAMR or any technology that relies on fast, high temperature magnetization control. However, there are some differences in how magnetic grains behave under conditions important to HAMR, such as cooling rate and magnetic field angle. Such differences arise from how thermal fluctuations are modeled in the stochastic Landau-Lifshitz-Gilbert equation. Therefore, it is important to benchmark these results against experiments to validate theoretical models. Here, we model the switching probability of granular Co-Pt media with VAMPIRE’s atomistic simulator as preparation for experiments. Unlike Fe-Pt, Co-Pt thin-films serve as a good benchmark due to their tunable composition, allowing us to generously change parameters like saturation magnetization, anisotropy and Tc.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".