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Record W4401395569 · doi:10.1002/app.56048

Moisture barriers used in firefighters' protective clothing: Effect of accelerated ultraviolet radiation aging on their mechanical and barrier performance

2024· article· en· W4401395569 on OpenAlexafffund
Laura Munevar‐Ortiz, John A. Nychka, Patricia I. Dolez

Bibliographic record

VenueJournal of Applied Polymer Science · 2024
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Performance
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for InnovationUniversity of Alberta
KeywordsMaterials scienceComposite materialMoistureUltraviolet radiationUltravioletClothingAccelerated agingRadiationChemistryOptoelectronicsOpticsPhysics

Abstract

fetched live from OpenAlex

Abstract Firefighters rely on their protective clothing as a second skin to perform their job. In the middle of this multilayered protective garment, the moisture barrier plays a vital role in preventing liquids to enter while allowing perspiration to escape. This research delves into the impact of accelerated ultraviolet (UV) aging on the performance of firefighter protective clothing moisture barriers, focusing on tear force retention, water vapor transmission rate (WVTR), and wetting via apparent contact angle. Changes in the tearing behavior and reductions in the tear force and tearing distance were observed after aging. Additionally, a reduction in WVTR was found for all the moisture barriers, due to pore closure in the ePTFE/FR PU membrane. In terms of water repellency, the base fabric side of one moisture barrier experienced a transition from hydrophobic to superhydrophilic potentially due to the degradation of the water‐repellent finish. The investigation also revealed that, due to the screening effect by the outer shell fabric, only a low percentage of UV radiation received by the turnout gear, less than 2% in the UVA range, may reach the moisture barrier. These results indicate the need to consider realistic exposure scenarios when assessing moisture barrier service life.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.242
Threshold uncertainty score0.452

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.020
GPT teacher head0.363
Teacher spread0.343 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2024
Admission routes2
Has abstractyes

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