Induction Plasma Deposition of Refractory Metal: Processing Parameters Optimization
Bibliographic record
Abstract
Abstract To prepare a dense, defect-free deposit of refractory metals relies not only on the droplets’ state, their temperature and velocity prior to impact on the surface of substrate and/or the precedent deposited layer, but also on the surface temperature of the substrate, whereupon the droplets impact. This paper presents a comprehensive investigation, in which the particles temperature, velocity, and the substrate temperature are studied all-in-one step to understand their influence on the deposit quality. The experimental results make our knowledge of the induction plasma spray of refractory metals process more integrated. Based on our estimation on the effect of all of the three factors, a set of optimized process parameters was established and proved by applying it in producing stationary deposits and coating layers. The results obtained distinguish the induction plasma spray a unique technique, which is ideal to be utilized in refractory metals deposit.
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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".