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Record W3044316268 · doi:10.1063/5.0007251

Dielectric properties of PVA cryogels prepared by freeze–thaw cycling

2020· article· en· W3044316268 on OpenAlexafffund
Nuwansiri Nirosh Getangama, John R. de Bruyn, Jeffrey L. Hutter

Bibliographic record

VenueThe Journal of Chemical Physics · 2020
Typearticle
Languageen
FieldMaterials Science
TopicMaterial Dynamics and Properties
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsDielectricPolyvinyl alcoholMaterials scienceRelaxation (psychology)Temperature cyclingActivation energyPolymerChemical engineeringPhase (matter)Composite materialPolymer chemistryThermodynamicsChemistryThermalPhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Solutions of polyvinyl alcohol (PVA) in water can form gels upon repeated freezing and thawing. These PVA cryogels have applications as biomaterials, including artificial tissue and drug delivery systems. We have studied the dielectric properties of PVA cryogels within the freeze-thaw cycles as a function of both frequency and temperature in order to understand the physical changes that take place during the thermal cycling process. Our results indicate that most of the changes in dielectric properties occur during the cooling phase of the first cycle and suggest that the solution must be cooled below a critical temperature of about 263 K for the formation of a gel that persists after thawing. The material's dielectric spectrum shows the presence of several relaxation processes. We identify one of these with the dielectric relaxation of ice and two others with motions of the PVA polymer chains. The temperature dependence of the polymeric relaxation times suggests that they are both thermally activated, with an activation energy of roughly 300 kJ/mol.

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 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 score0.002
Threshold uncertainty score0.258

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)0.0000.000

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 head0.023
GPT teacher head0.211
Teacher spread0.189 · 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

Citations10
Published2020
Admission routes2
Has abstractyes

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