Fabrication and characterization of Bismuth-Cerium composite iron garnet epitaxial films for magneto optical applications
Bibliographic record
Abstract
The BixCe3−xFe5O12 (x = 0.8) epitaxial films of high quality were grown by means of pulsed laser deposition on paramagnetic substrates of Gadolinium Gallium Garnet. We study the modifications of substitutions in the parent garnet Y3Fe5O12 that produces a higher magneto-optical response at communication wavelengths. These films displayed a strong in plane textures which are treated in argon as well as reduced atmosphere conditions. The elemental constituents of these films were confirmed by energy dispersive-X ray analysis, elastic recoil detection system, Rutherford backscattering spectroscopy, and X-ray photoelectron spectroscopy measurements. The transmittance spectra were measured and found these films exhibit good transmittance values. The transmittance-spectra were fitted with the theoretical model and the optical constants such as refractive index and absorption edge were evaluated. The highest (negative) Faraday rotation was found for these films treated in the environment of Ar + H2. A density matrix theory has been developed for the Faraday rotation and a good agreement between the theory and experiment is found. These epitaxial garnet films can be used in a wide range of frequencies from visible to infrared spectra making them ideal for many magneto optical applications. Therefore, these films may overcome many issues in fabricating all optical isolators which is the viable solution for integrated photonics.
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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".