Control of power law scaling in the growth of silicon nanocolumn pseudo-regular arrays deposited by glancing angle deposition
Bibliographic record
Abstract
Nanocolumn pseudo-regular arrays of silicon with controlled aspect ratio and porosity are fabricated by electron-beam evaporation using the glancing angle deposition (GLAD) method with vapour impinging at oblique incidence onto rapidly rotating substrates. The width W at positions y along the height of one individual column scales with y following a power law dependence W approximately y(p). We demonstrate that the scaling exponent value, p, can be modified from 0.6 to 0.3 by varying the vapour incidence angle from 75 degrees to a glancing 89 degrees from the substrate normal. This exponent is an important morphological factor for thin films, as it determines the morphological correlation length, nanocolumn profile, size, and spacing. The nanocolumn mean diameter can be varied between 12 and 40 nm, while the intercolumnar spacing can be adjusted between 37 and 85 nm via changing the incidence angle. The growth mechanism and film morphology are explored in detail.
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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 | 0.001 |
| 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".