High-performance PM steels utilizing extra-fine nickel
Bibliographic record
Abstract
Distribution of the alloying additives in powder metallurgy (PM) steels is a key element in achieving optimum sintered properties. Segregation must be avoided in order to ensure consistent part-to-part properties. Recent studies indicate that extra-fine nickel powders have a beneficial impact on the overall properties of nickel-copper-carbon PM steels. Therefore, the use of extra-fine nickel powder in segregation-free PM mixes could be an efficient way to optimize properties. To this end, the effect of the size and size distribution of two nickel powders on the physical and mechanical properties of two binder-treated steel powder premixes processed on a polit scale has been assessed. The properties of these two mixes are compared with those of a diffusion-alloyed mix of the same composition. Mechanical properties and dimensional change of the binder-treated mixes are shown to be superior to those of the diffusion-alloyed mix. The physical and sintered properties of the binder-treated mixes can be further improved by using extra-fine nickel powder (D₅₀ 1.5µm) instead of a standard size (D₅₀ 8µm) nickel powder.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".