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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".