THE INFLUENCES OF POWDER MIXING PROCESS ON THE QUALITY OF W-CU COMPOSITES
Bibliographic record
Abstract
The mixing homogeneity of powders has a significant influence on the quality of composites fabricated from a powder metallurgy process. The factors that influence the homogeneity include the powder mixer, the medium, and the ball-milling procedure. In this paper, the influences of powder mixers and mixing media on the quality of tungsten-particle reinforced copper matrix composites are studied. Apart from dry mixing, other media used in the wet mixing process include n-butyl alcohol, camphor oil, and paraffin oil. Comparisons on mixing feature are made to a TURBULA® mixer and a Random mixer. The TURBULA® mixer is commercially available, and the Random mixer is an in-house designed machine. Our results show that using paraffin oil as the mixing medium, one may obtain optimal homogeneity in the composites. The Random mixer is superior to the TUBULA® mixer due to the fact that the Random mixer offers an avalanching motion creating pure shear forces onto the powders.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".