Characterization of argon dielectric barrier discharges applied to ethyl lactate plasma polymerization
Bibliographic record
Abstract
Abstract The influence of the input voltage frequency (35 and 150 kHz), interelectrode gap (1 and 2 mm) and precursor concentration (250, 350, and 450 ppm) on the electron temperature ( T e ), number density of metastable Ar atoms ( n (Ar m )), and discharge current density (proportional to the electron density n e ) is studied in an argon-ethyl lactate dielectric barrier discharge (DBD). An argon-ammonia Penning mixture is also considered as reference. These results are correlated to the chemistry (XPS, IR) and topography (AFM) of the ethyl-lactate-based plasma polymer coatings. Low T e values from 0.3 to 0.5 eV were obtained for all discharges. This observation, in addition to resemblances with the Ar–NH 3 mixture, suggested that the ionization kinetics of ethyl lactate-based discharges is driven by Penning reactions. Among the investigated parameters, the dissipated power obtained through changes of the excitation frequency had the largest impact on both the coatings properties and the discharge behavior.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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) | 0.001 | 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".