Physical mechanisms of thermal-diffusivity depth-profile generation in a hardened low-alloy Mn, Si, Cr, Mo steel reconstructed by photothermal radiometry
Bibliographic record
Abstract
It is well established that in hardened steels thermal-diffusivity broadly anticorrelates with microhardness, allowing thermal-wave depth profilometry to be used as a tool to measure microhardness profiles. Nevertheless, the physical mechanisms for this anticorrelation have not been well understood. In this work, the thermal-diffusivity profiles of rough, hardened industrial steels were reconstructed after the elimination of roughness effects from the experimental data. Carburizing and quenching are widely used for the heat treatment of steel components, and it is important to understand their effects on thermal-diffusivity profiles. A thorough examination of the actual mechanism by which thermal-diffusivity depth profiles are affected by first carburizing and then quenching AISI-8620 steels was performed. It was concluded that the variation of thermal diffusivity with depth is dominated by the carbon concentration profile, whereas the absolute value of the thermal diffusivity is a function of microstructure.
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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".