Influence of Secondary Hydrogen on the Microstructure of Plasma-Sprayed Yttria-Stabilized Zirconia Coatings
Bibliographic record
Abstract
Abstract The influence of secondary hydrogen and current on the deposition efficiency (DE) and microstructure properties of yttria-stabilized zirconia (YSZ) coatings was evaluated. In order to better understand the influence of the spray process on coating consistency, an YSZ powder, -125+44 µm, was sprayed with nitrogen/hydrogen parameters and a 9MB gun. DE and coating porosity produced using two different spray gun conditions yielding the same input power were compared. Amperage was allowed to vary between 500 A and 560 A and hydrogen was adjusted in order to maintain constant power, while nitrogen flow was kept at a fixed level. Several power conditions, ranging from 32 to 39 kW, were tested. Different injection geometries, i.e., radial with and without a backward component, were also compared. The latter was found to produce higher in-flight temperatures due to a longer residence time of the powder particles in the hotter portion of the plasma. Porosity was based on cross-sectional photomicrographs. In-flight particle temperature and velocity measurements were also carried out with the DPV-2000 for each condition. Test results showed that DE and coating density could vary significantly when a different hydrogen flow rate was used in order to maintain constant input power. On the other hand, DE was found to correlate very well with the temperature of the in-flight particles. Therefore, to obtain more consistent and reproducible DE and microstructures, it is preferable to maintain constant the in-flight particle temperature instead of keeping the input power constant by adjusting the secondary hydrogen flow rate for obtaining more consistent and reproducible DE and microstructures.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".