Highly efficient semiconductor modules making controllable parallel microchannels for non-compressible hemorrhages
Bibliographic record
Abstract
Nature makes the most beautiful solution to involuted problems. Among them, the parallel tubular structures are capable of transporting fluid quickly in plant trunks and leaf stems, which demonstrate an ingenious evolutionary design. This study develops a mini-thermoelectric semiconductor P-N module to create gradient and parallel channeled hydrogels. The modules decrease quickly the temperature of polymer solution from 20 °C to -20 °C within 5 min. In addition to the exceptional liquid absorption rate, the foams exhibited shape memory mechanics. Our mini device universally makes the inspired structure in such as chitosan, gelatin, alginate and polyvinyl alcohol. Non-compressible hemorrhages are the primary cause of death in emergency. The rapid liquid absorption leads to fast activation of coagulation, which provides an efficient strategy for hemostasis management. We demonstrated this by using our semiconductor modules on collagen-kaolin parallel channel foams with their high porosity (96.43%) and rapid expansion rate (2934%). They absorb liquid with 37.25 times of the own weight, show 46.5-fold liquid absorption speed and 24-fold of blood compared with random porous foams. These superior properties lead to strong hemostatic performance in vitro and in vivo.
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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".