High-power laser powder bed fusion of Cu–Cr–Zr alloy: A comprehensive study on statistical process optimization, microstructure, and mechanical properties
Why this work is in the frame
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Bibliographic record
Abstract
This study explores high-power laser powder bed fusion (LPBF) of Cu–Cr–Zr alloy, focusing on optimizing process parameters to achieve high relative density ( RD ) and low surface roughness ( S a ). A Plackett-Burman design (PBD) identifies layer thickness, laser power, and scanning speed as the most significant parameters. A response surface method (RSM) with central composite design (CCD) further refines the process, yielding an optimized parameter set with an RD of 99.96 % and S a of 13.1 μm. After establishing the optimum process window, the process efficiency is examined by increasing layer thickness, demonstrating higher build rates while preserving high RD and acceptable S a . The samples are evaluated for mechanical properties and microstructural evolution . Microhardness mapping reveals a uniform hardness distribution , with values ranging from 90 to 94 HV. Microstructural analysis shows the grain morphology varies with process parameters; thinner layers tend to produce bimodal distributions, whereas thicker layers promote more uniform grain structures . Crystallographic analysis indicates a strong <001> texture in samples processed at high volumetric energy density ( VED ), while subgrain analysis highlights significant fractions of low-angle grain boundaries, reflecting residual stresses and high dislocation density .
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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 | 0.000 |
| 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) | 0.000 | 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 it