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Record W3088719303 · doi:10.1149/09809.0585ecst

(Invited) Electrochemical Energy Storage and Conversion Devices Incorporating C2-Protected Polybenzimidazoliums and Polyimidazoliums

2020· article· en· W3088719303 on OpenAlexaff
Qiliang Wei, Binyu Chen, Simon Cassegrain, Steven Holdcroft

Bibliographic record

VenueECS Transactions · 2020
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsHydroxideElectrochemistryCatalysisMembraneCathodeMaterials sciencePolymerIon exchangeChemical engineeringEnergy storageLayer (electronics)IonInorganic chemistryNanotechnologyChemistryElectrodeOrganic chemistryComposite materialEngineering

Abstract

fetched live from OpenAlex

Alkaline anion exchange membranes (AAEMs) which are capable of conducting hydroxide ions have been investigated in various alkaline based electrochemical energy storage and conversion technologies. Electrochemical systems relying on alkaline-based active components possess unique advantages over their acidic counterparts but at the same time are associated with significant challenges. In our research, we have been investigating C2-protected polybenzimidazolium and polyimidazolium polymers as hydroxide ion conducting polymers, for membranes and ionomer in catalyst layers, because of their stability in caustic conditions, scalability in synthesis, and mechanical strength. As an example of this work, we report on the performance of C2-protected hexamethylterphenyl-polybenzimidazole-based fuel cells in which the content and surface of the carbon support in the cathode catalyst layer is functionalized. We demonstrate that the composition of the cathode catalyst layer plays a large role in determining the performance of these particular anion exchange polymers.

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 score0.198
Threshold uncertainty score0.725

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 head0.006
GPT teacher head0.169
Teacher spread0.162 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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