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Electrical properties of sulfonated polyether ether ketone/polyetherimide blend membranes doped with inorganic acids

2000· article· en· W2101006171 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 Polymer Science Part B Polymer Physics · 2000
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsPolyetherimideMembraneMaterials scienceSwellingEtherDopingConductivityChemical engineeringPolymer chemistryKetoneAdsorptionAbsorption of waterAbsorption (acoustics)Composite materialPolymerOrganic chemistryChemistryPhysical chemistry

Abstract

fetched live from OpenAlex

The influence of blending with polyetherimide (PEI) and doping with HCl and H3PO4 on the properties of sulfonated polyether ether ketone (SPEEK) was studied. Blending with PEI first results in an increase and then in a decrease in membrane swelling at PEI concentrations greater than 5%. The electrical conductivity of blend membranes follows the same trend. Doping with the acids enhances the conductivity several times, and the effect of doping with HCl is more significant. PEI forms spherical particles dispersed in the SPEEK matrix and, at the same time, partially dissolves in SPEEK, which reduces the swelling of the matrix at higher PEI concentrations. The increase in the membrane capacity to absorb water at small PEI contents is due to the formation of new water adsorption sites along the interface between the particles and the matrix. A modified effective medium model yielded calculated results in good agreement with the measured conductivity values, when the experimental absorption data were used in the simulation. © 2000 John Wiley & Sons, Inc. J Polym Sci B: Polym Phys 38: 1386–1395, 2000

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 score0.034
Threshold uncertainty score0.921

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.198
Teacher spread0.188 · 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