Treatment of refractory powders by a novel, high enthalpy dc plasma
Bibliographic record
Abstract
Thermophysical properties of CO2–CH4 mixtures at high temperatures are very attractive for materials processing. In comparison with argon, at the same temperature, such a mixture possesses much higher enthalpy and higher thermal conductivity. At high temperatures, CO2–CH4 mixture has a complex composition with strong presence of CO which, in the case of powder treatment, could reduce oxidation. In this work, a dc plasma torch with graphite cathode was used to study the effect of plasma gas composition on spheroidization of tungsten carbide and alumina powders. Two different gas compositions were used to generate the plasma while the torch current was kept at 300 A. Various techniques were employed to assess the average concentration of carbides and oxides and the final shape of the treated powders. Process parameters such as input power and plasma gas composition allow controlling the degree of powder oxidation and spheroidization of high melting point ceramic powders.
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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) | 0.001 | 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".