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Record W2999055884 · doi:10.6000/1929-5995.2019.08.10

Thermal Resistance Properties of Polyurethanes and its Composites: A Short Review

2019· review· en· W2999055884 on OpenAlexvenueno aff
Javier Carlos Quagliano Amado

Bibliographic record

VenueJournal of Research Updates in Polymer Science · 2019
Typereview
Languageen
FieldMaterials Science
TopicPolymer composites and self-healing
Canadian institutionsnot available
Fundersnot available
KeywordsMaterials sciencePolyurethanePetrochemicalIsocyanateComposite materialThermal resistancePolyolMicrostructureChemical resistanceExtenderThermalOrganic chemistry

Abstract

fetched live from OpenAlex

The nature of starting materials and the conditions of polyurethane (PU) preparation are regarded as the main general parameters that determine PU thermal resistance. The effect of structure and presence of additives were identified as the major general factors on this regard. Structural factors include phase microstructure, i.e. chemical structure, proportion and segregation of soft and hard segments); polyol type (petrochemical or natural oil-based); isocyanate and chain extender type and thermoplasticity of PU. Respect to the effect of additives, the incorporation of fillers is the most direct strategy to increase PU heat resistance. With respect to fiber additives, in general a positive effect is found on improving thermal resistance, although this generalization could not apply, considering the large number of different PU and environmental conditions of usage.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.146
GPT teacher head0.418
Teacher spread0.273 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations16
Published2019
Admission routes1
Has abstractyes

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