Improved sinter-hardenability of prealloyed Fe-Cr-Mo steels by extra-fine nickel additions
Bibliographic record
Abstract
Extra-fine nickel (XFNi) powder was added to powder formulations based on prealloyed Fe-1.5Cr-0.2Mo, while XFNi and copper were admixed to a blend of Fe-1.5Cr-0.2Mo and Fe-0.5Mo in order to obtain a hybrid diluted PM steel (Fe-0.75Cr-0.35Mo) with admixed Ni and Cu. Parts with three different thicknesses were compacted from these blends at constant green denisty and then sinter-hardened at three different cooling rates. Extra-fine Ni additions were shown to clearly improve the sinter-hardenability of these PM steels. The density and mechanical properties increased significantly with admixed Ni content, while the properties of the hybrid diluted steel, which contained half the chromium, were either equal or superior to the base alloy. The properties generally increased with cooling rate irrespective of part thickness. The results of this investigation clearly show the potential of XFNi for improving the properties of PM Fe-Cr-Mo steels most effectively at lower cooling rates.
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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) | 0.000 | 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) | 0.002 | 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".