Disassembling Glancing Angle Deposited Films for High-Throughput, Single-Post Growth Scaling Measurements
Bibliographic record
Abstract
With growing interest in nanostructured thin films produced by glancing angle deposition (GLAD), it becomes increasingly important to understand their overall growth mechanics and nanocolumn structure. We present a new method of isolating the individual nanocolumns of GLAD films, facilitating automated measurement of their broadening profiles. Data collected for α = 81° TiO2 vertical nanocolumns deposited across a range of substrate rotation rates demonstrates that these rates influence growth scaling parameters. Further, individual posts were found in each case that violate predicted Kardar-Parisi-Zhang growth scaling limits. The technique's current iteration is comparable to existing techniques in speed: though data were studied from 10,756 individual objects, the majority could not be confidently used in subsequent analysis. Further refinement may allow high-throughput automated film characterization and permit close examination of subtle growth trends, potentially enhancing control over GLAD film broadening and morphology.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".