Atomistic study of magnetite thin film interfaces and defects for Spintronic applications \n
Bibliographic record
Abstract
Fe3O4 is a candidate material for future spintronic device applications due to its predicted half metallicity, high Curie temperature and lattice match with current oxide barrier materials. There have been numerous studies on Fe3O4(001)/MgO(001) heterostructures and devices in recent years which show structural defect formation has a significant influence on the properties of the grown layers and device performance. In this work I seek to advance our understanding of defect formation and heterostructure interfaces of epitaxially grown Fe3O4 layers on a range of substrates. Atomically resolved (S)TEM/EELS has been used as a main experimental techniques to determine the atomic structure of the defects and interfaces in order to model their effect of the functional properties of the thin films magnetite. \nFirstly we investigate the MBE growth of (111) oriented Fe3O4/MgO thin films. This creates highly ordered, atomically sharp APB defect boundaries rather than the random-like fractal geometry defects which have previously been observed in (001) oriented growth. This has enabled us to undertake atomistic modelling and begin to understand the APBs effect on the magnetic properties of grown films. We show that all APB defects exhibit a high density of high angle Fe-O-Fe bonds with antiferromagnetic coupling. \n The Fe3O4/MgO structure produces a high density of APB defects, and consequently anomalous properties of the grown films such as negative magnetoresistance and high saturating magnetic fields. In order to avoid crystal symmetry as an origin of APBs we undertook a MBE growth of Fe3O4/MgAl2O4 a spinel-spinel growth system. However, the presence of the APBs was still observed and their formation was discussed in terms of strain and 3D film growth. \nTo reduce the density of defects in Fe3O4 we employed pulsed laser deposition with subsequent film annealing in a CO/CO2 atmosphere. This is shown to produce films with bulk like transport properties after a high temperature annealing process. Residual defects including twins were observed. These defects have a low density and the effect on overall film properties is small. \nFinally, using the spinel/perovskite model structure of Fe3O4/SrTiO3 we show the ability to produce atomically sharp oxide/oxide interfaces which open up the possibility of performing atomic level engineering to tailor potential oxide-oxide device functionality. \n
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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".