Deposition of anti‐fog coatings on glass substrates using the jet of an open‐to‐air microwave argon plasma at atmospheric pressure
Bibliographic record
Abstract
Abstract This study reports a one‐step process for the formation of anti‐fog coatings on commercial glass substrates using the jet of an open‐to‐air microwave argon plasma at atmospheric pressure with hexamethyldisiloxane (HMDSO) as the precursor for plasma‐enhanced chemical vapor deposition. Optical microscopy and broadband light transmittance measurements revealed significant precursor fragmentation and gas phase association reactions when HMDSO was injected close to the tube outlet, resulting in powder‐like, hydrophobic, and semiopaque glass surfaces. On the contrary, injection of HMDSO close to the substrate led to smoother, homogeneous, hydrophilic, and transparent glass surfaces. In addition, transmittance measurements at 590 nm in humid air according to American Society for Testing and Materials standard tests revealed superior anti‐fogging properties to plasma‐treated glass substrates. On the basis of the optical emission and absorption spectroscopy measurements, electrons, metastable argon atoms, and hot neutral argon atoms were mostly responsible for the significant precursor fragmentation close to the tube outlet, whereas the contribution of hot neutrals and ultraviolet photons became important close to the substrate.
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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 | 0.000 |
| 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".