Morphology Control in van der Waals Epitaxy of Bismuth Telluride Topological Insulators
Bibliographic record
Abstract
Bismuth telluride have regained significant attention as a prototype of topological insulator. Thin films of high quality have been investigated as a basic platform for novel spintronic devices. Low mobility of bismuth and high desorption coefficient of telluride compose a scenario where growth parameters have drastic effects on structural and electronic properties of the films. Recently [J. Phys. Chem. C 2019, 123, 24818-24825], a detailed investigation has been performed on the dynamics of defects in epitaxial films of this material, revealing the impact of film/substrate lattice misfit on the films' lateral coherence. Very small lattice misfit (<0.05%) are expected to have no influence on quality of epitaxial system with atomic layers weakly bonded to each other by van der Waals forces, contrarily to what was observed. In this work, we investigate the correlation between lattice misfit and size and morphology of the film crystalline domains. Three-dimensional reciprocal-space maps of film Bragg reflections obtained with synchrotron X-rays are used to visualize the spatial conformation of the crystallographic domains through film thickness, while atomic force microscopy images provide direct information of the domains morphology at the film surface.
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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) | 0.000 | 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".