Hydrothermal aging of <scp>fire‐protective</scp> fabrics
Bibliographic record
Abstract
Abstract Fire‐protective fabrics made from high‐performance fibers are available to provide protection from various hazardous conditions such as extreme heat and flame. However, these fabrics are often exposed to other deteriorating conditions, including moisture. It is a concern for user's safety as some high‐performance fibers are sensitive to hydrolysis. This study exposed eight fire‐protective fabrics corresponding to typical blends used in firefighter protective suit outer shells to accelerated hydrothermal aging. They were immersed in water at different temperatures between 60 and 95°C for up to 1200 h. After exposure to hydrothermal aging, some fabrics exhibited a significant loss in tensile strength without any morphological changes. Based on results from energy‐dispersive X‐ray spectroscopy and pH measurements of the aging water, the larger loss in strength experienced by the para‐aramid/PBI fiber‐based fabrics can be related to the high amount of sulfur measured in the PBI fibers, contributing to an acceleration of the para‐aramid fiber's hydrolysis in acidic conditions. Hydrothermal aging also appears to affect the water‐repellent finish of some fabrics. The study provides an insight into the effect of a generally ignored hazard, that is, moisture, on the long‐term performance of fire‐protective fabrics.
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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) | 0.001 | 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".