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Record W2996194924 · doi:10.1021/acsaem.9b01829

High Performance Oxygen Reduction/Evolution Electrodes for Zinc–Air Batteries Prepared by Atomic Layer Deposition of MnO<sub><i>x</i></sub>

2019· article· en· W2996194924 on OpenAlexafffund
M.P. Clark, Ming Xiong, Ken Cadien, Douglas G. Ivey

Bibliographic record

VenueACS Applied Energy Materials · 2019
Typearticle
Languageen
FieldEngineering
TopicAdvanced battery technologies research
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAtomic layer depositionElectrodeElectrolyteDeposition (geology)Materials scienceZincPorosityOxygenLayer (electronics)Analytical Chemistry (journal)Chemical engineeringChemistryComposite materialMetallurgy

Abstract

fetched live from OpenAlex

Oxygen reduction electrodes for zinc–air batteries (ZAB) have been prepared by depositing conformal films of MnOx directly onto high surface area gas diffusion layers (GDL) via atomic layer deposition (ALD). MnOx films were prepared by means of two deposition conditions: one using a forming gas (95% N2, 5% H2) plasma (FG-MnOx) and one using an O2 plasma (O2-MnOx). A composite electrode of FG-MnOx + CoOx was also examined. The conformal nature of ALD films allowed for MnOx to be deposited within the porosity of the GDL, as confirmed by X-ray microanalysis. Full cell ZAB tests showed excellent performance for MnOx-coated electrodes, outperforming Pt/Ru–C at current densities larger than 100 mA cm–2. Annealed FG-MnOx and O2-MnOx electrodes had maximum power densities of 170 and 184 mW cm–2, respectively. With the catalyst distributed within the structure of the GDL, performance limitations associated with electrolyte flooding and air diffusion are reduced, improving discharge potential and cycling behavior. FG-MnOx + CoOx electrodes showed good cycling stability, both in a trielectrode configuration and bifunctionally. When cycled at 20 mA cm–2 for 100 h (200 cycles), FG-MnOx + CoOx had initial and final discharge potentials of 1.18 and 1.15 V, respectively.

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 categoriesMeta-epidemiology (narrow)
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 score0.015
Threshold uncertainty score1.000

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 head0.199
Teacher spread0.194 · 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.

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

Citations20
Published2019
Admission routes2
Has abstractyes

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