Ferromagnetic resonance damping mechanisms in CoFeB thin films with Cr substitution
Bibliographic record
Abstract
The substitution of iron atoms by chromium in CoFeB films has been proposed to reduce the critical current density ${J}_{c}$ for current-driven magnetization switching in spin transfer torque devices by reducing its magnetization. Yet the effect of Cr on the magnetic damping has remained elusive. Ferromagnetic resonance (FMR) measurements up to 110 GHz and 5 T, as well as angle-dependent FMR measurements at 9.5 and 17 GHz, are used to discriminate between different mechanisms of FMR damping in ${\mathrm{Co}}_{40}{\mathrm{Fe}}_{40\ensuremath{-}x}{\mathrm{Cr}}_{x}{\mathrm{B}}_{20}$ thin films ($x=0$, 4, 8, and 18). A constant isotropic Gilbert parameter is used to phenomenologically describe the magnetization damping for each composition, increasing from 0.005 to 0.022 as the amount of Cr increases from 0% to 18%. Two thirds of this contribution appear to be accounted for by intrinsic spin-orbit damping, and the balance is mostly due to extrinsic two-magnon scattering. While the introduction of Cr increases the spin-orbit damping, it nevertheless reduces the corresponding magnetic relaxation rate. The amorphous films with a high scattering rate exhibit a so-called conductivitylike damping at room temperature, in agreement with the breathing Fermi surface model. The presence of Cr also seems to inhibit internal fluctuations of the magnetization, reducing the two-magnon damping. The reduction of ${J}_{c}$ due to lower magnetization is partly mitigated by the overall increase in magnetic damping.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".