Synergy of laser powder bed fusion (LPBF) and heat treatment for CuNi2SiCr alloy enhancement
Bibliographic record
Abstract
This research explores the thermal and mechanical properties of a CuNi 2 SiCr alloy made by laser powder bed fusion (LPBF) for potential use in the neck insert of extrusion blow molds. Process parameter optimization, aging heat treatment design, thermal and mechanical property characterizations, microstructural analysis, and an exploration of the factors affecting thermal conductivity are presented. Results showed that the aging thermal cycle significantly enhanced the thermal conductivity of the as-build sample from ∼ 70 W/mK) to ∼ 180 W/mK. Numerical analysis of the involvement of various scattering phenomena in the overall mean free path of conducting electrons revealed that such a significant increase in thermal conductivity originated from the emergence of nanoscale Ni, Cr, and Si containing precipitates from the supersaturated matrix which depleted the matrix of extrinsic scattering sites accounting for ∼ 80 % of electron scattering in the as-built specimen. The sample subjected to heat treatment showed a 95 % increase in nanohardness and significantly higher yield strength (575 MPa) and ultimate tensile strength (687 MPa) compared to the as-built specimen (236 MPa and 291 MPa, respectively). The improvements obtained in this study in both thermal and mechanical properties showcase the potential of LPBF and subsequent heat treatment in enhancing Cu alloy materials for various industrial applications.
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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) | 0.000 | 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) | 0.000 | 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".