Bias dependence and defect analysis of Bi on Si(111) <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msqrt><mml:mn>3</mml:mn></mml:msqrt><mml:mo>×</mml:mo><mml:msqrt><mml:mn>3</mml:mn></mml:msqrt><mml:mspace width="4pt"/><mml:mi>β</mml:mi></mml:mrow></mml:math>-phase
Bibliographic record
Abstract
We investigate the Bi on Si(111) $\sqrt{3}\ifmmode\times\else\texttimes\fi{}\sqrt{3}\phantom{\rule{4pt}{0ex}}\ensuremath{\beta}$-phase surface reconstruction using scanning tunneling microscopy. Details of the bias-dependent images of both the reconstruction and defects are presented. Combining our experimental data with density-functional theory calculations, it is confirmed that the honeycomb pattern at low-bias empty states and hexagonal closest-packed pattern at high-bias empty states originate from the Bi ${p}_{x}, {p}_{y}$ states and Bi, Si overlapped states outside bulk band gap, respectively. Analysis of the defect images and their associated densities of states provides further insight into the electronic structure of the surface. In particular, we note the presence of a quantum-dotlike localized state associated with an $\ensuremath{\alpha}$-phase defect structure. These results pave the way for further development of surface structures based on Bi on Si(111) surface with unique electronic properties such as sizable spin-orbit coupling, which might be suitable candidates for spintronic applications.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".