Polyethylene Terephthalate Surface Modification by Filamentary and Homogeneous Dielectric Barrier Discharges in Air
Bibliographic record
Abstract
In this paper, polyethylene terephthalate (PET) films are modified using nonequilibrium plasma generated by homogeneous dielectric barrier discharges (DBDs) in air at medium pressure, and the results are compared to those treated by using filamentary DBDs in air at atmospheric pressure. The characteristics of homogeneous DBDs are studied and compared with those of filamentary DBDs by measuring their electrical discharge parameters and observing their light-emission phenomena, and the surface properties of PET films before and after the treatments are studied using contact-angle and surface-energy measurements, X-ray photoelectron spectroscopy, and scanning electron microscopy. It is found that the homogeneous DBD is quite homogeneous and stable in the whole gas gap, which differs from the filamentary DBD, and the plasma treatments modify the PET surface in both morphology and composition. The PET films modified in both treatments show a remarkable decrease in water contact and a remarkable increase in surface energy due to both the introduction of oxygen-containing polar groups onto the surface and the improvement in surface roughness. It is found that the homogeneous DBD is more effective in PET surface modification than the filamentary DBD as it can make the contact angle decline to a lower level by introducing more oxygen-containing groups, and the possible reason for this effect is discussed.
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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".