Glancing angle deposition on a roll: Towards high-throughput nanostructured thin films
Bibliographic record
Abstract
Increasing the throughput of the powerful single-step glancing angle deposition (GLAD) method using a prototype simplified roll-to-roll (R2R) system has been explored. While the conventional GLAD technique is popular for fabricating nanostructured devices in a single deposition step, it is not a high-output process. To evaluate the feasibility of large area GLAD deposition, the authors examined the geometrical considerations required to eventually achieve GLAD in a roll-to-roll manufacturing system. Nominal deposition and rotation angles were mathematically translated to their effective R2R counterparts, allowing for deposition recipes of the archetype GLAD nanostructures (slanted posts, vertical posts, and square spirals) and the mechanics of the phi-sweep technique to be converted to this space. Representative structures were then deposited, and the phi-sweep technique successfully applied, in a prototype single barrel roller R2R experimental system. This prototype system provides a foundation for moving GLAD from the laboratory to mass production.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".