Are Large Particles of Iron Detrimental to Properties of Powder Metallurgy Steels?
Bibliographic record
Abstract
It is experimentally shown that a removal of particles exceeding 100 microns in size from iron powders typically used in the fabrication of medium density powder metallurgy steels has a weak effect on apparent density, flowability and compressibility of blends as well as on density and strength of green bodies. An elimination of such particles, i.e., cutting off a heavy tail of a size distribution histogram at the 100 μm threshold, improves a compositional uniformity of sintered materials, but has no noticeable beneficial effect upon the strength of a final product, which is likely be determined by a fraction of pores and their shapes. A presence of soft pearlitic inclusions hardly matters unless their number density becomes so large that a 3D continuity (integrity) of a hard martensitic matrix is lost. This finding suggests that such an expensive preparatory step as sieving away large particles from as-received mixtures would bear no technological advantages. It was experimentally found that an attempt to lower the threshold below 100 μm noticeably worsened apparent density, flowability and compressibility.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".