Ya-Wen Sheng

Ms. Ya-Wen Sheng


Research Focus & Metrics

Academic Career Length

2Years (2025-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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30 June 2025 in Fire
Verified
Journal Article
Open access
PDF file
WSWen-Wei Su
Wen-Wei Su
YLYang Li
Yang Li
PMPeng-Rui Man
Peng-Rui Man
YSYa-Wen Sheng
Ya-Wen Sheng
JWJian Wang
Jian Wang
The insulation layer of flame-retardant cables plays a critical role in mitigating fire hazards by influencing toxic gas emissions and the accuracy of fire modeling. This study systematically explores the pyrolysis kinetics and volatile gas evolution of flame-retardant polyvinyl chloride (PVC) and polyethylene (PE) insulation materials using advanced TG-FTIR-GC/MS techniques. Distinct pyrolysis stages were identified through thermogravimetric analysis (TGA) at heating rates of 10–40 K/min, while the KAS model-free method and Málek fitting function quantified activation energies and reaction mechanisms. Results revealed that flame-retardant PVC undergoes two major stages: (1) dehydrochlorination, characterized by the rapid release of HCl and low activation energy, and (2) main-chain scission, producing aromatic compounds that contribute to fire toxicity. In contrast, flame-retardant PE demonstrates a more stable pyrolysis process dominated by random chain scission and the formation of a dense char layer, significantly enhancing its flame-retardant performance. FTIR and GC/MS analyses further highlighted distinct gas evolution behaviors: PVC primarily generates HCl and aromatic hydrocarbons, whereas PE releases olefins and alkanes with significantly lower toxicity. Additionally, the application of a classification and regression tree (CART) model accurately predicted mass loss behavior under various heating rates, achieving exceptional fitting accuracy (R2 > 0.98). This study provides critical insights into the pyrolysis mechanisms of flame-retardant cable insulation and offers a robust data framework for optimizing fire modeling and improving material design.