The thickness dependence of dielectric properties in the plasma polymer thin films
Bibliographic record
Abstract
In this study, the results of dielectric spectroscopy of plasma polymerized poly(ethylene oxide) thin films are presented. The films were deposited by plasma-assisted physical vapour deposition at radio-frequency plasma discharge power of 5 W, and film thicknesses of 20, 100, and 250 nm. Dielectric measurements of the films were performed in the frequency range of 10−1–107 Hz and temperature was scanned between 173 and 353 K. The dielectric constant ([Formula: see text]) and dielectric loss ([Formula: see text]) of plasma polymerized poly(ethylene oxide) thin films were calculated by measuring capacitance (C) and dielectric loss factor (tanδ). It was observed that there were two relaxation mechanisms in the investigated frequency range. These were called α and β relaxations. These relaxations shift toward higher frequencies with increasing temperature. Moreover, α-relaxation starts to appear at different temperatures. This shows the difference between the polarizability abilities of samples at the same temperature and same frequencies. The reason for this behavior can be expressed by the dead layer concept, which is a result of good adhesion of the bottom layer of plasma polymer to the substrate. In light of these interpretations, with thinner samples it is possible to have structurally similar thin films like thin films deposited at high plasma power. A thinner film may support more transparency and these thinner films may be effective as coverage of optical devices, such as lenses, visors, etc.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".