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Record W2041756116 · doi:10.1002/app.12032

Effect of solvent on properties of solution‐cast dense SPPO films

2003· article· en· W2041756116 on OpenAlexaff
Boguslaw Kruczek, Takeshi Matsuura

Bibliographic record

VenueJournal of Applied Polymer Science · 2003
Typearticle
Languageen
FieldEngineering
TopicMembrane Separation and Gas Transport
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsSolventCastingAqueous solutionPolymerMaterials scienceChemical engineeringPolymer chemistrySolvent effectsChemistryComposite materialOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract The effect of solvent on properties of solution‐cast dense films was investigated using high molecular weight sulfonated poly(2,6‐dimethyl‐1,4‐phenylene oxide) (SPPO) and five different solvents having relatively similar molar volumes. The study revealed that polymer–solvent interactions existing in casting solution primarily determine the concentration of residual solvent and surface morphology of the films. On the other hand, the O 2 and CO 2 permeabilities, which for most permeable films were more than three times greater than for the least permeable ones, appear to be governed by the volatility of solvent in casting solution. At the same time, the more permeable films showed lower O 2 /N 2 and CO 2 /CH 4 permeability ratios than the less permeable ones. In addition to physical factors such as polymer–solvent interactions and volatility of solvent in casting solution, the differences in gas transport properties of SPPO films could arise from the formation of quaternary salts—in particular, in the case of films prepared from the pyridine solution. The analysis of casting solution properties, surface images by atomic force microscopy, and gas transport properties allowed us to associate defective structures of some SPPO films with a specific surface morphology and a particular combination of solvent properties. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 88: 1100–1110, 2003

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)0.001
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 score0.009
Threshold uncertainty score0.268

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.010
GPT teacher head0.221
Teacher spread0.210 · 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

Citations13
Published2003
Admission routes1
Has abstractyes

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