Effect of heat treatment on the dynamic impact response of Cu–Cr–Zr alloy manufactured by laser powder bed fusion
Bibliographic record
Abstract
This study investigates the effect of heat treatment on the dynamic impact behavior of a Cu–Cr–Zr alloy fabricated via high-power laser powder bed fusion (LPBF). Experiments utilized a split Hopkinson pressure bar (SHPB) setup with firing pressures of 100 kPa and 250 kPa, corresponding to maximum strain rates of 4400 s-1 and 11300 s-1 for as-built samples, and 1700 s-1 and 4700 s-1 for heat-treated samples. True stress-strain curves reveal a significant difference in strain accommodation mechanisms between as-built and heat-treated samples. Heat treatment markedly enhances the ultimate compressive strength (UCS) and work hardening rate under dynamic loading conditions, likely due to the Orowan strengthening mechanism by finely dispersed precipitates formed during heat treatment. The heat-treated samples exhibit continuous strength gains with increasing strain, reflecting pronounced strain hardening. In contrast, as-built samples show a plateau after reaching their UCS, where the activation of softening mechanisms, such as adiabatic shear band (ASB) formation, reduces the effectiveness of strain hardening. Despite the substantial changes in mechanical behavior, macro-texture analysis reveals minimal differences between as-built and heat-treated samples, suggesting that the performance disparities stem primarily from microstructural changes, such as precipitate formation and distribution in heat-treated samples, rather than shifts in crystallographic orientation.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".