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Record W2009319848 · doi:10.5539/mas.v2n2p131

Effect of Blending Temperature on the Characteristics of Modified Polyacrylonitrie Homopolymer

2008· article· en· W2009319848 on OpenAlexvenueno aff
Ahmad Fauzi Ismaila, Azeman Mustafa, Muhammad Syukri Abd Rahaman

Bibliographic record

VenueModern Applied Science · 2008
Typearticle
Languageen
FieldEngineering
TopicFiber-reinforced polymer composites
Canadian institutionsnot available
FundersKementerian Sains, Teknologi dan InovasiNational Science Foundation
KeywordsPolyacrylonitrileComonomerItaconic acidMaterials scienceSpinningFiberPolymer chemistrySynthetic fiberDimethylformamideFourier transform infrared spectroscopyAcrylonitrileChemical engineeringComposite materialPolymerPolymerizationOrganic chemistryChemistryCopolymerSolvent

Abstract

fetched live from OpenAlex

This paper examines the modification of polyacrylonitrile (PAN) homopolymer by a blending technique. The discussion on this modified PAN fiber involves the comparison a new concept of comonomer attachment compared to the conventional method. The PAN homopolymer and comonomers (i.e. itaconic acid (IA) and methylacrylate (MA)) were dissolved in dimethylformamide (DMF) at two different temperatures; 70°C (Type 1) and ambient temperature (Type 2). These fibers were fabricated using a simple the dry/wet spinning process before subjected to a stabilization process. FTIR result shows that the peaks (around 1600cm-1) indicated that the comonomers in Type 1 fiber were attached to the PAN homopolymer backbone during the dope preparation step. However for Type 2 fibers, the comonomers were only attached to the PAN homopolymer backbone during the stabilization process. Type 1 fibers also have higher weight loss and faster stabilization compared to Type 2 fibers. Therefore, the blending process at heat temperature of 70ºC is claimed as the technique that can modify the PAN homopolymer and make the stabilization process of PAN fibers faster.

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)0.001
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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.007
GPT teacher head0.200
Teacher spread0.192 · 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

Citations1
Published2008
Admission routes1
Has abstractyes

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