Electronic properties of Si(111)-<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:mn>7</mml:mn><mml:mo>×</mml:mo><mml:mn>7</mml:mn></mml:mrow></mml:math>and related reconstructions: Density functional theory calculations
Bibliographic record
Abstract
The $7\ifmmode\times\else\texttimes\fi{}7$ reconstruction of Si(111) has the interesting property of being metallic despite bulk Si being a semiconductor. This surface has a complex reconstruction that takes on a dimer-adatom stacking fault (DAS) structure composed of adatoms, rest atoms, and several other key features. It is believed that the dangling bonds of the adatoms play a crucial role in the high conductivity and that this is predominantly a surface-state band effect. To elucidate the details of this mechanism, we investigate a set of related Si(111) reconstructions of increasing complexity in order to resolve the effect of the different DAS features on the electronic and transport properties of the Si(111)-$7\ifmmode\times\else\texttimes\fi{}7$ surface. Density functional theory calculations are carried out on the $\sqrt{3}\ifmmode\times\else\texttimes\fi{}\sqrt{3}$-R30${}^{\ensuremath{\circ}}$, $2\ifmmode\times\else\texttimes\fi{}2$, $5\ifmmode\times\else\texttimes\fi{}5$, and $7\ifmmode\times\else\texttimes\fi{}7$ reconstructions of Si(111). Since these surfaces are modeled as two-dimensional slabs, a careful investigation is carried out to determine the slab thickness needed to capture the structural and electronic properties of these systems. The densities of states (DOSs) projected on different atoms in these surfaces are then compared, revealing that the $\sqrt{3}\ifmmode\times\else\texttimes\fi{}\sqrt{3}$, $5\ifmmode\times\else\texttimes\fi{}5$, and $7\ifmmode\times\else\texttimes\fi{}7$ surfaces are metallic, while the $2\ifmmode\times\else\texttimes\fi{}2$ surface is semiconducting. Finally, the DOSs for Si(111)-$7\ifmmode\times\else\texttimes\fi{}7$ are related to scanning tunneling microscope data to offer an explanation for different adatom prominence trends depending on Si sample doping.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".