Capillary performance of strut-based lattice wicks fabricated using laser powder bed fusion
Bibliographic record
Abstract
Laser powder bed fusion (LPBF) can be used to fabricate porous wicks with customized geometries for two-phase heat transport devices such as heat pipes; LPBF enables integration of these wicks into any two-phase transport device form factor in a single manufacturing step. Strut-based wicks with four different unit-cell geometries (simple cubic, body-centered cubic, face-centered cubic, and fluorite) with different porosities were designed and fabricated using LPBF. The capillary performance of the wicks was characterized using the mass rate-of-rise (m-t) method and quantified in terms of the ratio of permeability to effective pore radius ( K/r eff ). Both unit-cell geometry and porosity significantly affect the capillarity of these strut-based wicks, with K/r eff ranging from 0.05 to 1.43 μm, which is commensurate with conventional sintered metal wicks. This is due to a relatively high permeability, ranging from 39 μm 2 to 788 μm 2 , and an effective pore radius ranging from 233 μm to 1022 μm. The simple cubic 52 % and 65.1 % porous wicks exhibited the highest capillary performance with a K/r eff of 1.43 μm and 1.31 μm, respectively. These results suggest that modifying the LPBF process for finer feature resolution could result in higher capillarity.
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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 | 0.001 |
| 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 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".