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Record W2335583725 · doi:10.1021/je100488v

Determination of Solubilities of CO<sub>2</sub> in Linear and Branched Polypropylene Using a Magnetic Suspension Balance and a <i>PVT</i> Apparatus

2010· article· en· W2335583725 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Chemical & Engineering Data · 2010
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Foaming and Composites
Canadian institutionsUniversity of TorontoUniversity of Waterloo
Fundersnot available
KeywordsPolypropyleneSuspension (topology)Electromagnetic suspensionBalance (ability)Materials scienceAnalytical Chemistry (journal)Aqueous suspensionChemical engineeringChemistryChromatographyComposite materialEngineeringMechanical engineeringPhysical chemistryMathematicsMagnetAqueous solution

Abstract

fetched live from OpenAlex

Using a PVT apparatus for high pressure and temperature combined with a magnetic suspension balance, the solubility of carbon dioxide in linear and branched polypropylene (PP) was measured at temperatures from (453 to 493) K and at pressures of up to 31 MPa. The solubility of CO 2 in both molten polymers increased linearly with pressure and decreased with temperature. However, above 20 MPa, the solubility−pressure relationship was no longer linear. This might be due to a significant hydrostatic effect on the swelling of the polymer that results from gas absorption above 20 MPa, so that swelling is no longer linearly related to pressure. At a high pressure, swelling significantly affects solubility, which is then no longer linearly related to pressure. It was noted that linear PP absorbs more gas than branched PP, due to the branched PP’s chain entanglement. The solubility of CO 2 in the PP melts was compared with semiempirical data (determined by empirically measuring gas uptake and theoretically predicting swelling) and theoretical values calculated from the Simha−Somcynsky (SS) and Sanchez−Lacombe (SL) equations of state (EOSs). The Simha−Somcynsky equation of state (SS-EOS) was observed to have a better prediction capacity of the swelling effect and to thus provide better solubility predictions for both semiempirical and theoretical cases than the Sanchez−Lacombe equation of state (SL-EOS).

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.

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 score0.047
Threshold uncertainty score0.311

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 head0.012
GPT teacher head0.240
Teacher spread0.228 · 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