Surface pattern transfer in<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:mi mathvariant="normal">GaAs</mml:mi></mml:mrow></mml:math>with molecular beams of<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:msub><mml:mrow><mml:mi mathvariant="normal">Cl</mml:mi></mml:mrow><mml:mn>2</mml:mn></mml:msub></mml:mrow></mml:math>
Bibliographic record
Abstract
The time evolution of surface gratings on $\mathrm{GaAs}(001)$ during maskless thermal ${\mathrm{Cl}}_{2}$ etching is investigated using atomic force microscopy and real-time measurements of diffracted light intensity. The decay of the grating depends strongly on its orientation with respect to the crystal axes. The pattern transfer can be altered significantly by using a directional molecular beam of ${\mathrm{Cl}}_{2}$ instead of exposure to a nondirectional low-pressure gas phase. In particular, if the molecular beam is incident on the sample from an off-normal direction, the grating shape develops a strong asymmetry. A numerical model consisting of two coupled partial differential equations for the surface height and the concentration of chlorine on the surface is in good quantitative agreement with the observed shape evolution. The model includes the effects of the crystal anisotropy of the etch rate, spatial inhomogeneity of the ${\mathrm{Cl}}_{2}$ flux to the surface, and surface diffusion of the chlorine. Fits of the model to the surface shapes allow us to determine the diffusion length of chlorine on $\mathrm{GaAs}(001)$ to be on the order of $50\phantom{\rule{0.3em}{0ex}}\mathrm{nm}$ at 200 \ifmmode^\circ\else\textdegree\fi{}C.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".