Thermal aging of a blend of high‐performance fibers
Why this work is in the frame
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Bibliographic record
Abstract
Abstract The focus of this work is the study of the thermal aging of high‐performance fibers used in the making of fire protective garments. Accelerated thermal aging tests were carried out on fabric samples made up of a blend of Kevlar® (poly p ‐phenylene terephthalamide) and PBI (poly benzimidazole) staple fibers, as well as on yarns pulled from this fabric, by means of exposure to elevated temperatures, comprised between 190°C and 320°C. All samples underwent loss of breaking force retention. The material thermal life, defined as the time required for the fibers to attain a 50% reduction of the original breaking force, ranged between a dozen of days at the lowest exposure temperature, to less than an hour at the highest. Breaking force data were fitted using the Arrhenius model following two different approaches, namely the extrapolated thermal life value and the shift factors yielded by the time‐temperature superposition (TTS). The Arrhenius model seemed to describe appropriately the overall aging process, as inferred from the excellent fit obtained when using both approaches, although activation energies provided from both approaches are different. To follow the chemical evolution of the material with thermal aging, Fourier‐transform infrared (FTIR) analyses were conducted. The qualitative analysis of the FTIR spectra showed little evidence of chemical changes between the aged and the nonaged samples, indicating either that the aging process carries on without significant modification of the chemical structure of the fibers, or that FTIR is not an appropriate method to spot such a modification. © 2009 Wiley Periodicals, Inc. J Appl Polym Sci, 2010
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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 | 0.001 | 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 | 0.001 | 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 it