Effect of thermal aging on the mechanical and barrier properties of an e‐PTFE/Nomex® moisture membrane used in firefighters' protective suits
Bibliographic record
Abstract
Abstract Moisture membranes play a key role in high performance protective clothing by preventing outside water to get in while allowing the human body to perspire properly. However, these membranes are confronted to high environmental constraints, in particular within firefighters' protective clothing. The resulting aging effect may lead to modifications of their performances, for example their mechanical or barrier properties. In this study, the thermal aging of an e‐PTFE/Nomex® moisture membrane was carried out at five temperatures between 190 and 320°C. The effect of aging on the mechanical performance was assessed by tensile tests and trapezoid tear strength measurements. Variation in the moisture membrane water vapor permeability due to aging was also studied. Large modifications in the membrane mechanical properties as a result of thermal aging were recorded. It was associated in part with a degradation of the Nomex® fibers. The membrane water vapor permeability was observed to decrease with aging time below 220°C while values larger than those corresponding to the unaged material were measured above that temperature. This was possibly related to the occurrence of two competing phenomena relative to water vapor permeability: closure of pores in the e‐PTFE laminate and creation of cracks and holes. These results show that the aging of the moisture membrane must be considered carefully while estimating the service life of protective clothing. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2011
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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) | 0.001 | 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".