Evolution of mechanical properties of ferrite and pearlite phases during spheroidization process and their relationship to the overall properties of low alloy steel
Bibliographic record
Abstract
Mechanical properties of ferrite-pearlite low alloy steel are strictly determined by the properties of ferrite and pearlite phases. In this present paper, the evolution of mechanical properties of ferrite and pearlite phases during spheroidization process is investigated by using nanoindentation tests. Meanwhile, the overall mechanical properties of the material were measured using uniaxial tensile tests. Test results indicate that with the intensification of spheroidization of layered cementite in pearlite, the hardness and yield strength of pearlite phase decrease from 2.72 GPa to 1.73 GPa and 411.5 GPa–256.1 GPa, respectively. However, the mechanical properties of ferrite phase exhibit an opposite trend, with hardness and yield strength increasing from 1.6 GPa to 1.67 GPa and 188.1 GPa–208.4 GPa, respectively. Uniaxial tensile tests results indicate that overall yield strength of steel decreases significantly as the degree of spheroidization increases, from the original 276 MPa–229 MPa. Although the strength of pearlite decreased by 38%, the overall strength of alloy steel decreased by only 15% due to an 11% increase in ferrite strength. During spheroidization process, the relationship between pearlite hardness, yield strength, and interlayer spacing of cementite in pearlite can be expressed in Hall-Petch type relationships as: H=0.482×S−12+1.34 and σy=91.44×S−12+149; and the relationship between the strengths of ferrite-pearlite aggregate and ferrite and pearlite phases is σy=Vf1.95σf+(1−Vf1.95)σp.
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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".