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Preparation and Characterization of Nitrile Butadiene Rubber (NBR)/Polyoxymethlene (POM) Blends Compatibilized by Maleic Anhydride Grafted POM (MAH-g-POM)

2013· article· en· W2106735665 on OpenAlexvenueno aff
Jiaqi Luo, Bin Yang, Guojun Cheng, Ru Xia, Li-Feng Su, Jibin Miao, Jiasheng Qian, Peng Chen

Bibliographic record

VenueJournal of Research Updates in Polymer Science · 2013
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Nanocomposites and Properties
Canadian institutionsnot available
FundersAnhui Provincial Department of EducationAnhui UniversityNational Natural Science Foundation of China
KeywordsMaterials scienceMaleic anhydrideCompatibilizationUltimate tensile strengthCopolymerNatural rubberComposite materialNitrile rubberScanning electron microscopeIzod impact strength testPolymer blendPolymer

Abstract

fetched live from OpenAlex

Maleic anhydride grafted POM (MAH-g-POM) was prepared and used as the compatibilizer for nitrile butadiene rubber (NBR) modified by acetal copolymer (POM) in different proportions. It was found that MAH-g-POM had good compatibilization effect for the blends. Both DSC and XRD results indicated that the process of blending POM with NBR considerably influenced the crystallization of POM. The scanning electron microscopy (SEM) study of tensile fracture surfaces of the blends clearly showed that the compatibility of NBR/POM blends was enhanced with increasing POM content. Mechanical properties indicated that NBR/MAH-g-POM had relatively higher elongation at break but lower tensile strength than NBR/POM blend. The present work will supply a good insight into the formula design and further optimization of polymer composites or blends.

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)0.004
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 score0.006
Threshold uncertainty score0.659

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.002
Scholarly communication0.0000.003
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 head0.020
GPT teacher head0.328
Teacher spread0.308 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

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