Temperature- and exposure-dependent study of the Ge(001)<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:mi>c</mml:mi><mml:mo stretchy="false">(</mml:mo><mml:mn>8</mml:mn><mml:mo>×</mml:mo><mml:mn>2</mml:mn><mml:mo stretchy="false">)</mml:mo></mml:mrow></mml:math>-Au surface
Bibliographic record
Abstract
Using scanning tunneling microscopy (STM), Auger electron spectroscopy, and low-energy electron diffraction, we have determined the optimal gold exposure for the Ge(001) $c$(8 \ifmmode\times\else\texttimes\fi{} 2)-Au surface. We find deposition of submonolayer (ML) gold onto a Ge(001) surface held at temperatures between 570 and 870 K produces a $c$(8 \ifmmode\times\else\texttimes\fi{} 2) surface reconstruction. The relative extent of $c$(8 \ifmmode\times\else\texttimes\fi{} 2) domains increases with Au exposure, and at 0.75 \ifmmode\pm\else\textpm\fi{} 0.05 ML the surface is entirely covered by $c$(8 \ifmmode\times\else\texttimes\fi{} 2) chains. The 0.75-ML exposure is equivalent to six gold atoms per unit cell. Beyond 0.75 ML, exposure to additional Au leaves the $c$(8 \ifmmode\times\else\texttimes\fi{} 2) domains intact, and extra Au is accommodated at three-dimensional islands on the surface. STM images of the $c$(8 \ifmmode\times\else\texttimes\fi{} 2) phase are dominated by bright chains running along the Ge{110} directions with an interchain spacing of 1.6 nm. At low coverage the domains are highly asymmetric, and extended along the chain direction. These atomically flat domains routinely span several germanium terraces and indicate that chain formation involves considerable mass transport of gold and germanium atoms.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".