Fabrication of spatially-variable heterostructured CoCrFeMnNi high entropy alloy by laser processing
Bibliographic record
Abstract
This study investigates the fabrication of spatially-variable heterostructured CoCrFeMnNi high entropy alloy (HEA) using pulsed laser processing. Two distinct fabrication approaches, involving single-(SP) and double-sided (DP) laser passes, were employed. Microstructural characterization through electron backscatter diffraction revealed significant differences. SP-HEA exhibited a spatially heterogeneous microstructure with coarse columnar grains, while DP-HEA displayed a sandwich-like structure with fine equiaxed recrystallized grains. Microhardness mapping demonstrated a gradient trend in SP-HEA, with the fusion zone exhibiting the lowest hardness and the base material the highest. In contrast, DP-HEA displayed an overall soft-hard-soft structure. Tensile testing revealed distinct mechanical responses, with DP-HEA exhibiting higher strength and ductility compared to SP-HEA. The improved performance of DP-HEA was attributed to a more uniform distribution of heterogeneity, minimizing mechanical interactions between soft and hard domains. Moreover, corrosion resistance was assessed, showing that DP-HEA outperformed SP-HEA and non-processed material, suggesting superior stability in corrosive environments. These findings highlight the profound influence of fabrication parameters on the microstructure and mechanical properties of spatially-variable heterostructured HEAs. The study contributes valuable insights for material design and applications based on CoCrFeMnNi high entropy alloys.
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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".