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Record W6901729172 · doi:10.60692/scws2-1am28

Sulfide interlayered cobalt-based oxynitrides for efficient oxygen evolution reaction in neutral pH water and seawater

2023· article· en· W6901729172 on OpenAlexaff

Bibliographic record

VenueGreater South Information System · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGeomagnetism and Paleomagnetism Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsOxygen evolutionSeawaterCatalysisSulfideOxygenChronoamperometryNickelFaraday efficiency

Abstract

fetched live from OpenAlex

Sluggish kinetics of the anodic oxygen evolution reaction (OER) and minor upstream upsets in feed water quality remain bottlenecks for efficient water electrolysis, which is exacerbated under near-neutral pH environments due to H2O dissociation. In this work, we report the introduction of a NiSx interlayer in a Co-(NiFe) oxide/nitride catalyst on nickel foam substrate. Postmortem OER characterization in neutral pH synthetic seawater (SSW) shows that stable cationic [Co-(NiFe)]δ+ and anionic [O-N]δ– surface species coupled with the NiSx interlayer accelerate H2O dissociation, thereby enhancing activity and kinetics. The electrocatalysts exhibit stable performance at 100 mA cm−2 for 50 h in alkaline and neutral pH SSW with 350 and 425 mV of overpotential, respectively. The faradaic efficiency of the NiSx interlayer catalysts is enhanced by 10.3% and 8.5% achieving 94.5% and 87.4% under alkaline and neutral pH SSW, respectively, during chronoamperometry tests at a high applied voltage of 1.75 V (vs. RHE).

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 score0.002

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 integrity0.0000.000
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 head0.017
GPT teacher head0.209
Teacher spread0.192 · 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
Published2023
Admission routes1
Has abstractyes

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