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Record W2586245244 · doi:10.1021/acsami.6b14129

Hexagonal Arrays of Cylindrical Nickel Microstructures for Improved Oxygen Evolution Reaction

2017· article· en· W2586245244 on OpenAlexafffund
Michael T. Y. Paul, Brenden B. Yee, David Bruce, Byron D. Gates

Bibliographic record

VenueACS Applied Materials & Interfaces · 2017
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsZincNyx Energy Solutions (Canada)Simon Fraser University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCMC Microsystems
KeywordsMaterials scienceOxygen evolutionOverpotentialPassivationNickelElectrodeElectrochemistryAlkaline water electrolysisChemical engineeringElectrolysisPlanarWater splittingPower densityNanotechnologyMetallurgyCatalysisElectrolytePower (physics)

Abstract

fetched live from OpenAlex

Fuel-cell systems are of interest for a wide range of applications, in part for their utility in power generation from nonfossil-fuel sources. However, the generation of these alternative fuels, through electrochemical means, is a relatively inefficient process due to gas passivation of the electrode surfaces. Uniform microstructured nickel surfaces were prepared by photolithographic techniques as a systematic approach to correlating surface morphologies to their performance in the electrochemically driven oxygen evolution reaction (OER) in alkaline media. Hexagonal arrays of microstructured Ni cylinders were prepared with features of proportional dimensions to the oxygen bubbles generated during the OER process. Recessed and pillared features were investigated relative to planar Ni electrodes for their influence on OER performance and, potentially, bubble release. The arrays of cylindrical recesses were found to exhibit an enhanced OER efficiency relative to planar nickel electrodes. These microstructured electrodes had twice the current density of the planar electrodes at an overpotential of 100 mV. The results of these studies have important implications to guide the preparation of more-efficient fuel generation by water electrolysis and related processes.

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 score0.005
Threshold uncertainty score0.969

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 science0.0010.000
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 head0.011
GPT teacher head0.245
Teacher spread0.234 · 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

Citations28
Published2017
Admission routes2
Has abstractyes

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