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Record W2786661330 · doi:10.1149/ma2018-01/30/1801

In-Situ Electrochemical Characterization of Proton Exchange Membranes for Water Electrolysis

2018· article· en· W2786661330 on OpenAlexaff
Amelia Hohenadel, Hsu-Feng Lee, Thulile Khoza, Alejandro Oyarce Barnett, Steven Holdcroft

Bibliographic record

VenueECS Meeting Abstracts · 2018
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsProton exchange membrane fuel cellNafionMembraneElectrolysis of waterElectrolysisChemical engineeringConductivityAryleneElectrochemistryPolarization (electrochemistry)HydrogenSulfonic acidProton conductorMaterials scienceHigh-pressure electrolysisChemistryElectrodeOrganic chemistryEngineeringPhysical chemistryElectrolyte

Abstract

fetched live from OpenAlex

Proton exchange membrane water electrolysis (PEM-WE) is a clean method for hydrogen production and an important piece in the adoption of a hydrogen fuel economy. Proton exchange membranes require specific chemical and physical properties for efficient use in the PEM-WE system, and development of these membranes still presents a major challenge. Current industry standards such as Nafion®, developed by DuPont, are costly, show high gas permeability, and are limited to operation below 90 °C.1 Performance of a novel sulfonated poly(arylene ether) membrane, SA8, is investigated in this research. SA8 has shown a significantly higher glass transition temperature than Nafion, better mechanical properties, higher proton conductivity, and better chemical stability from various ex-situ tests and in-situ fuel testing. The multiphenylated backbone creates free volume around the sulfonic acid sites, which allows for greater water uptake with minimal swelling.2 The presence of water is not only necessary for proton conductivity but is of particular importance in the water electrolyzer where the cell is fed liquid water, rather than operated at various humidities as in a fuel cell. In this research SA8 is found to successfully operate in a water electrolysis system at a temperature of 90 °C for over 120 hours. Polarization curves taken at 60 °C show operation of a 25 μm membrane at 1.8 V reaching a current density of 4 A cm-2. Ito, H., Maeda, T., Nakano, A. & Takenaka, H. International Journal of Hydrogen Energy (2011) Lee, H. F., Huang, Y.C., Wang, P.H., Lee, C.C., Hung, Y.S., Gopal, R., Holdcroft, S., Huang, W.Y. Mater. Today Commun. 3, 114–121 (2015).

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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.205
Teacher spread0.199 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

Explore more

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