Synthesis and sintering of Fe-32Mn-6Si shape memory alloys prepared by mechanical alloying
Bibliographic record
Abstract
Fe-32Mn-6Si alloy was produced using the mechanical alloying (MA) process of high purity powders under an inert argon gas atmosphere. The aim of this investigation is the in-depth study of the microstructure and phase transformation during the milling-sintering process of Fe-32Mn-6Si shape memory alloys. During the milling process, a significant amount of amorphous phase was created as well the crystalline martensite and austenite phases. The amorphous phase was increased by milling time enhancement and then it was decreased due to the mechano-crystalization phenomenon. It was detected that the microhardness of the alloyed powder directly depends on the amount of the amorphous phase. Furthermore, the particle size of as-milled powder firstly decreased and then increased, when the amorphous phase cojoined gradually during the milling process the transformation of martensite into austenite. The lattice strain was increased considerably during the milling process which was a reason for martensite phase creation resulting in the high shape memory properties. The amount of pre-strain for Fe-32Mn-6Si alloy was calculated to be 3.3%. Furthermore, the optimum sintering temperature was approved to be 950 °C by reduction of the percentage of pores and suitable densification.
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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 | 0.000 | 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) | 0.001 | 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".