Process Measurements in Avacuum Microplasma Spray System
Bibliographic record
Abstract
Summary form only given. A system has been developed and refined for small-scale vacuum plasma spraying of metals. This system operates at arc power 1-3 kW and deposition rates below 0.1 g min-1. The plasma is an argon-hydrogen mixture expanded through a Laval nozzle into chamber pressures in the range 5.3-13 kPa (40-100 torr). The vacuum spray environment, which distinguishes this work from other published plasma spray work at similar power levels, helps to enable the deposition of titanium or tungsten. These materials and others may also be deposited simultaneously with vapor-deposited material in order to synthesize composite materials. This hybrid processing is made possible by the reduction of spray deposition rate to be comparable to vapor deposition rates. Other potential applications include small-scale, reduced-cost versions of conventional plasma spray, such as barrier coatings and biomedical coatings. Sprayed materials and system behavior are discussed in terms of system measurements for tuning of particle trajectory, particle impact state, and coating microstructure. Planar laser Mie scattering was used to visualize particle trajectory fields in order to align them with the plasma jet's core. In stainless steel coatings, spray deposition efficiency (DE) is seen to correlate well with such trajectory alignment.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".