Electrode Material Degradation Monitoring for Durable Dielectric Barrier Discharge Plasma Actuators Manufacturing
Bibliographic record
Abstract
This study aims to develop effcient, reproducible and durable plasma actuators. Thin metal deposition and high manufacturing reliability control were gained by adopting the photographic technique. As dielectric material degradation and electrodes corrosion are significant issues, emphasis was put in selecting materials that could withstand the plasma environment. Gold was selected as electrode material for all the geometric configurations. A Schott alkali-free borosilicate glass substrate was chosen as dielectric because of its resis- tance to material degradation in the plasma environment. Measurements of the actuator power consumption and capacitance were used to quantify the change in actuator performance over time. Moreover, scanning electron microscope images and energy dispersive X-ray spectroscopy analysis were utilised on the used devices to help explain the observed changes in actuator performance. After usage, unexpected degradation effects were ob- served on the gold electrodes, in both the front side and back side of each actuator. The electrode edges retracted and residual gold remained on the glass substrate. In particu- lar, the exposed electrode width reduced by up to approximately 50%, depending on the actuator working conditions. Moreover, the morphology of the electrode surfaces changed and melting/crystalline reorganization of the gold layer was observed at the borders of the shrunk electrodes. As a consequence, a decrease of the actuator cold capacitance with age was evident. Furthermore, a rise in the actuator power consumption and effective capac- itance was noted with increasing actuation time. At the same time, the actuator aging process produced an increase in its effective capacitance at a given dissipated powe
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".