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Record W3081143157 · doi:10.1021/acs.jpcc.0c04278

Water Content and Ionic Conductivity of Thin Films of Different Anionic Forms of Anion Conducting Ionomers

2020· article· en· W3081143157 on OpenAlexafffund
Udit N. Shrivastava, Avital Zhegur-Khais, Maria Bass, Sapir Willdorf‐Cohen, Viatcheslav Freger, Dario R. Dekel, Kunal Karan

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2020
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaIsrael National Research Center for Electrochemical PropulsionCanada First Research Excellence FundH2020 Industrial LeadershipCouncil for Higher EducationIsrael Science FoundationMinistry of National Infrastructure, Energy and Water ResourcesPlanning and Budgeting Committee of the Council for Higher Education of IsraelTechnion-Israel Institute of TechnologyUniversity of Calgary
KeywordsIonomerThin filmConductivityMaterials scienceIonic conductivityElectrolyteChemical engineeringIon exchangeElectrochemistryFluorideBromideInorganic chemistryPolymerIonChemistryComposite materialPhysical chemistryNanotechnologyOrganic chemistryElectrode

Abstract

fetched live from OpenAlex

Typically, in polymer electrolyte-based electrochemical devices such as electrolyzers and fuel cells, ionomers in the catalyst layers are present as ultrathin films coating the electrochemically active component. Acidic ionomer thin films have been extensively characterized over the past decade, yet there are few reports on the alkaline ionomer thin films. Here, we present a study on anion-exchange ionomers; specifically, we investigate the water content and conductivity of fluoride, bromide, and carbonate forms of 50 nm thick FAA3 and PPO ionomer thin films at 30 °C and 0–90% RH. A thermodynamic analysis was performed to compute the Gibbs free energy of anionic interaction with water to discuss the impact of anion type on the anionic mobility. Structural analysis using GISAXS was performed on the anion-exchange ionomer thin films. Furthermore, conductivity and water content relationships between FAA3 thin films and membranes and between FAA3 and PPO thin films were compared and discussed in terms of structure and ion clustering.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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

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 head0.031
GPT teacher head0.211
Teacher spread0.181 · 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 source (direct Gemma or distilled Codex), 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

Citations18
Published2020
Admission routes2
Has abstractyes

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Same venueThe Journal of Physical Chemistry CSame topicFuel Cells and Related MaterialsFrench-language works237,207