Nano-porous Aerogel Granulometry for Enhancing Efficiency of Hemostatic Devices
Bibliographic record
Abstract
Hemorrhagic trauma is a leading cause of preventable mortality worldwide, particularly in regions with limited medical resources.This study explores the integration of silica-based aerogels into traditional medical gauze to enhance hemostatic efficacy.Aerogels, with their high porosity and exceptional absorption capacity, facilitate rapid clot formation and antimicrobial protection, which makes them ideal for emergency medical applications.Utilizing a controlled experimental design, aerogel-infused gauze was tested under simulated venous and arterial Hemorrhage conditions.The results demonstrated a significant reduction in fluid flow rates, with a nearcomplete cessation under gravitational flow and over 90% reduction under pressurized flow, validating the material's superior hemostatic properties (p < 0.005).Furthermore, variations in aerogel distribution patterns are presented to address diverse wound geometries, showcasing the adaptability to clinical needs.This innovation highlights the potential for lightweight, wound-healing inducing, highperformance haemostatic devices, offering promising use for trauma care in resource-constrained environments.Future directions include clinical trials, biocompatibility testing, and manufacturing optimization for scalable production.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".