Functionally Gradient H13 Tool Steel/Oxygen‐Free High Thermal Conductivity Cu Composites Manufactured by Laser‐Directed Energy Deposition
Bibliographic record
Abstract
H13 tool steel and copper (Cu) functionally gradient materials (FGMs) have been manufactured using laser‐directed energy deposition (L‐DED). Differential scanning calorimetry analysis of H13‐Cu blends shows clear separation of the Fe‐rich and Cu‐rich liquids due to the Fe–Cu miscibility gap. Also, in the analysis, it is determined that there is a large solidification range that will promote solidification cracking. A compositional gradient is produced by changing the powder feed rates in situ within the L‐DED system, to create six different compositions, beginning with 100% H13 at the substrate and ending at 100% Cu. Single‐track clads and three‐layer clad tracks of various H13‐Cu blends are successfully printed onto a wrought H13 substrate. The cross section of the clad samples containing Cu experiences vertical cracking, indicative of solidification cracking. Rectangular FGM samples of H13‐Cu are successfully printed onto a wrought H13 substrate using two different laser powers, namely 400 and 460 W; however, these samples experience major porosity and detrimental transverse cracking issues situated in the ≈25 and ≈45 wt% Cu sections. This is attributed to the Fe–Cu miscibility gap, difference in coefficient of thermal expansion, and Cu being known to promote cracking in steels. Some potential solutions to these issues are discussed.
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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) | 0.002 | 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 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".