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Record W4292283980 · doi:10.1021/acsaem.2c01604

Role of Ionomers in Anion Exchange Membrane Water Electrolysis: Is Aemion the Answer for Nickel-Based Anodes?

2022· article· en· W4292283980 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueACS Applied Energy Materials · 2022
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNafionCatalysisIonomerMaterials scienceAnodeOverpotentialInorganic chemistryCyclic voltammetryElectrolysisHydroxideNickelMembrane electrode assemblyChemical engineeringOxygen evolutionIon exchangePotassium hydroxideElectrodeChemistryElectrochemistryElectrolyteIonMetallurgyComposite materialOrganic chemistryCopolymer

Abstract

fetched live from OpenAlex

The anode oxygen evolution reaction (OER) in anion exchange membrane water electrolysis (AEMWE) limits the process’ overall hydrogen production efficiency. Studies show that nickel-iron (NiFe)-based catalysts show excellent activity toward the OER. In anode catalyst layers, electrocatalysts must be paired with anion exchange ionomers (AEI) to bind the catalyst and conduct hydroxide ions. This work covers the first investigation of the commercial Aemion AEI with a non-noble-metal Ni90Fe10 nanoparticle anode catalyst for applications in AEMWE. The effects of Aemion are also studied for the first time in a three-electrode cell and compared to the commercial Fumion and Nafion ionomers. Cyclic voltammetry (CV) results show that Aemion distinctly interacts with NiFe to suppress the Ni(OH)2/NiOOH transition peak current by 39% (vs 11 and 17% for Nafion and Fumion, respectively), thus decreasing the OER activity of NiFe with a high overpotential of 369 mV at 10 mA cm–2 in 1 M potassium hydroxide (KOH). This effect was not alleviated by prolonged CV cycling, preconditioning the electrode in KOH, stabilizing the electrode deposition, or modifying the Aemion solvent. NiFe anode catalytic layers were also prepared for AEMWE testing with varying amounts of Aemion (7, 15, 25, and 35 wt %). Scanning electron microscopy (SEM) of the catalyst layers show catalyst-rich and ionomer-rich phases, each becoming more prominent with increasing ionomer. AEMWE testing shows that 7 wt % Aemion is the best ionomer loading, achieving a cell voltage of 1.941 V at 0.4 A cm–2 in 1 M KOH at 50 °C, 62 mV higher than our previously optimized 15 wt % Fumion anode. While less performing than Fumion, Ni90Fe10 with 7 wt % Aemion is more stable over time. Ex situ Raman spectroscopy of the spent 7 wt % Aemion electrode supports the CV results, where the electrode remains mostly in the Ni(OH)2 phase after polarization.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.059
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.006
GPT teacher head0.197
Teacher spread0.191 · 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