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Record W2268507863 · doi:10.1039/c8sm00424b

Crystallization of low molecular weight atactic polystyrene

2018· article· en· W2268507863 on OpenAlexafffund
Yu Chai, James A. Forrest

Bibliographic record

VenueSoft Matter · 2018
Typearticle
Languageen
FieldMaterials Science
TopicPolymer crystallization and properties
Canadian institutionsRegional Municipality of WaterlooPerimeter InstituteUniversity of Waterloo
FundersÉcole Supérieure de Physique et de Chimie Industrielles de la Ville de ParisNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsPolystyreneCrystallizationMaterials sciencePolymer sciencePolymer chemistryChemical engineeringComposite materialPolymerEngineering

Abstract

fetched live from OpenAlex

polystyrene exhibits observable crystals on the surface. The crystals appear to be a few nm thick and nm to microns wide. These crystals grow at all temperatures less than ∼290 K. Melting of crystals was probed over an extended temperature range, and some fraction of the crystals start to melt at 302 K, but some fraction persist to higher temperatures and do not exhibit complete melting until 343 K. The tacticity of the molecules is tested with NMR spectroscopy and found to be atactic. We suggest that the crystals form due simply to the distribution of isomerism along the molecule which necessarily leaves some fraction of the molecules with uniform stereoregularity. This natural crystallinity may be related to previously observed and not definitively explained gel formation in atactic PS (a-PS), as well as cluster formation. The measurements are compared with the theory by Semenov (Macromolecules, 2009, 42, 6761) and together suggest that such crystallinity is possible over a wide range of polymerization index (N), and is limited only by the vanishingly small volume fractions and sluggish growth.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.082
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
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)0.0110.001

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 head0.221
Teacher spread0.213 · 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; both teacher heads agree on what is shown here.

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
Published2018
Admission routes2
Has abstractyes

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