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Record W2567962783 · doi:10.1002/app.44748

Comparative behavior of <i>in situ</i> silica generation in saturated rubbers: EPDM and hydrogenated natural rubber

2017· article· en· W2567962783 on OpenAlexaff
Kitti Ongwongsakul, Garry L. Rempel, Sirilux Poompradub, Napida Hinchiranan

Bibliographic record

VenueJournal of Applied Polymer Science · 2017
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Nanocomposites and Properties
Canadian institutionsUniversity of Waterloo
FundersThailand Research Fund
KeywordsNatural rubberMaterials scienceSwellingGlass transitionEthylene propylene rubberEPDM rubberVulcanizationPolymerComposite materialChemical engineeringPolymer chemistryCopolymer

Abstract

fetched live from OpenAlex

ABSTRACT Role of carbon‐carbon double (CC) bonds content and their position in ethylene‐propylene diene ter‐polymer (EPDM), hydrogenated natural rubber (HNR) and natural rubber (NR) on in situ silica formation using tetraethoxysilane (TEOS) as a silica precursor is comparatively investigated. Glass transition temperature ( T g ) reflecting rubber chain flexibility is found as an important factor for in situ silica generation via swelling method. Despite of similar solubility parameters, NR has higher TEOS‐swelling degree resulting in the higher in situ silica content (30.8 phr) than EPDM (3.50 phr) and HNR (10.4–17.6 phr) due to the higher T g of EPDM and HNR providing the less chain flexibility to be swollen in TEOS solution. The morphological analysis implies that CC bonds in saturated rubbers may be agglomeration sites for in situ silica particles. For practical applications, saturated rubbers containing in situ silica/NR vulcanizates showed the improvement of mechanical properties and resistance of thermal and ozone degradation. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017 , 134 , 44748.

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)0.001
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 score0.015
Threshold uncertainty score0.457

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.024
GPT teacher head0.281
Teacher spread0.256 · 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

Citations7
Published2017
Admission routes1
Has abstractyes

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