Effects of pulsed laser surface treatments on microstructural characteristics and hardness of CrCoNi medium-entropy alloy
Bibliographic record
Abstract
A hot-swaged/annealed CrCoNi medium-entropy alloy (MEA) was surface-treated by pulsed laser at two different powers (400 and 200 W). Microstructural characteristics of the laser-modified zones were characterised and analysed by energy dispersive spectroscopy, electron backscatter diffraction and electron channelling contrast imaging techniques. Results show that melting and rapid solidification occur on the surfaces of both laser-treated specimens, and profuse annealing twins existing in the initial microstructures are essentially eliminated in the melting zone (MZ) with plentiful low-angle boundaries appearing. Meanwhile, the initial equiaxed grains are replaced by new grains in the MZ with either granular or columnar appearance (in the 2D cross-sectional views). These grains are comprised of fine cellular structures with relatively uniform sizes (∼1–2 μm in width/diameter), the formation of which is related to the segregation of Cr during solidification. With the laser power decreasing from 400 to 200 W, the volume of the MZ and grain sizes in its interior are reduced. This is due to less heat supply and faster cooling caused by reducing the laser power. Hardness tests reveal that the surfaces of both the laser-treated specimens are slightly softened (by 10–20%), and quantitative analyses suggest that this is mainly related to grain coarsening and the disappearance of annealing twins in the MZ.
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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) | 0.002 | 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 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".