MétaCan
Menu
Back to cohort
Record W1996713432 · doi:10.1002/macp.200500574

Syntheses, Structures and Proton Conductivities of Polyphthalazinone Ionomers Derived from a Direct NC Coupling Reaction

2006· article· en· W1996713432 on OpenAlexaff
Yulin Chen, Yuezhong Meng, Shuanjin Wang, Shuanghong Tian, Allan S. Hay

Bibliographic record

VenueMacromolecular Chemistry and Physics · 2006
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsMcGill University
Fundersnot available
KeywordsMembraneNafionIonomerProton exchange membrane fuel cellPolymerThermal stabilityPolymer chemistryElectrolyteMonomerConductivityMaterials scienceChemical engineeringHydrolysisProtonChemistryCopolymerOrganic chemistryComposite materialElectrochemistryPhysical chemistryElectrode

Abstract

fetched live from OpenAlex

Abstract Summary: Nafion perfluorinated resins that contain perfluorosulfonic acid groups have outstanding properties as membranes in polymer electrolyte membrane (PEM) fuel cells when used only at temperatures lower than 80 °C. At higher temperatures, dehydration of the membrane occurs with a concomitant loss of conductivity. In this paper, we report a new approach to synthesize polyphthalazinone ionomers via an NC coupling reaction. The sulfonated polymers produced showed excellent thermal and oxidative stability because of their specially designed structure. Membranes cast from solution possessed good water affinity and high proton conductivity. Different bisphthalazinone monomers resulted in varying properties of the corresponding polymers. The membranes exhibited excellent resistance both to hydrolysis and oxidation, demonstrating their promising application as proton exchange membranes in PEM fuel cells. The relationship between the structure and properties for the synthesized polymeric ionomers was discussed. Polyphthalazinone ionomers. magnified image Polyphthalazinone ionomers.

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 score0.006
Threshold uncertainty score0.536

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 head0.005
GPT teacher head0.177
Teacher spread0.171 · 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

Citations4
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueMacromolecular Chemistry and PhysicsSame topicFuel Cells and Related MaterialsFrench-language works237,207