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High Flame Retardant Performance of SiO2-TiO2 Sol Coated on Polyester/Cotton Fabrics

2021· article· en· W3150132103 on OpenAlexfundno aff
Phạm Thị Thu Trang, Giang H. Le, Nguyen Ba Manh, Trinh Duc Cong, Ngo Trinh Tung, Vu Tuan Anh

Bibliographic record

VenueVNU Journal of Science Natural Sciences and Technology · 2021
Typearticle
Languageen
FieldMaterials Science
TopicFlame retardant materials and properties
Canadian institutionsnot available
FundersPartenariat Canadien Contre Le CancerVietnam Academy of Science and Technology
KeywordsMaterials scienceFire retardantSodium silicatePolyesterCoatingComposite materialThermal stabilityFourier transform infrared spectroscopyTitaniumChemical engineeringMetallurgy

Abstract

fetched live from OpenAlex

SiO2 and TiO2 sols were successfully synthesized by using sodium silicate and titanium chloride as Si and Ti sources. SiO2-TiO2 sol coated polyester/cotton fabric was fabricated by deep-coating method and using SiO2, TiO2 sols as coating materials. SiO2-TiO2 coated fabric were characterized by XRD, FTIR, TGA, SEM and EDX. From SEM image, it showed the SiO2, TiO2 particles of 20-30 nm which well deposited on fabric surface. TGA result revealed the significant improvement of thermal resistance and stability of SiO2-TiO2 coated fabric as compared to those of uncoated fabric. Flame retardant performance of SiO2-TiO2 coated fabrics was much better than that of uncoated fabric. Thus, SiO2-TiO2 coated fabric SiO2-TiO2 content of 26wt% showed the UL-94 classification of V-0 and LOI value of 30.3 were obtained. Moreover, mechanical property (tear strength) of SiO2-TiO2 coated fabrics were also improved.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.230
Teacher spread0.219 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2021
Admission routes1
Has abstractyes

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Same venueVNU Journal of Science Natural Sciences and TechnologySame topicFlame retardant materials and propertiesFrench-language works237,207