Butterfly Wing Microstructure Inspired Solid/Porous Alternating Layered Structures: In Situ Visualization of Confined Foaming
Bibliographic record
Abstract
This study explores confined foaming in micro-/nano-layered (MNL) solid/porous alternating structures inspired by the hierarchical architecture of Ulysses butterfly wings. Biomimetic MNL films composed of alternating polycarbonate (PC) and polymethyl methacrylate (PMMA) layers (17-513 layers) are fabricated via advanced coextrusion and foaming techniques. In situ visualization reveals confinement effects dependent on layer thickness; while nucleation primarily occurrs at PC/PMMA interfaces due to reduced energy barriers, a strong confinement zone within 10 µm of the interfaces significantly restricts cell growth, most notably in the 129-layer and 513-layer samples, where single-cell rows are observed. Thermal regulation tests show that the 513-layer bio-mimic structure reduces temperature rise by 80%, 65%, and 50% compared to polyethylene (PE) film, a three-layer sandwich structure, and butterfly wings, respectively. It also exhibits exceptional delay in heat accumulation under radiative conditions, with a time to reach half of the maximum temperature rise of 165 s, compared to 20 s (PE) and 40 s (both three-layer and butterfly wing). The bio-mimic architecture also exhibits strong anisotropic thermal conductivity, effectively suppressing through-thickness heat transfer while enhancing lateral dissipation. These results connect nature-inspired design and practical implementation, highlighting the potential of bio-mimic MNL structures for advanced thermal management applications.
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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 | 0.000 |
| 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 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".