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Record W2605497120 · doi:10.1002/ente.201700108

Self‐Supported Cobalt Nickel Nitride Nanowires Electrode for Overall Electrochemical Water Splitting

2017· article· en· W2605497120 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.

Bibliographic record

VenueEnergy Technology · 2017
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsOxygen evolutionOverpotentialWater splittingTafel equationMaterials scienceNanowireElectrochemistryChemical engineeringCobaltElectrodeNickelCatalysisBifunctionalInorganic chemistryNanotechnologyChemistryMetallurgyPhysical chemistry

Abstract

fetched live from OpenAlex

Abstract The design and synthesis of electrocatalysts possessing both hydrogen and oxygen evolution activity is of critical importance to simplify the water splitting system. In this work, we reported the preparation of porous Ni–Co nitride nanowires (NiCoN NWs) supported on carbon cloth, and used as bifunctional electrocatalysts to achieve overall water splitting. Benefiting from the 1D porous nanowire structure, the close contact between catalysts and support, and the increased conductivity, the resultant NiCoN NWs exhibited high activities in both the hydrogen and oxygen evolution reactions (HER and OER) with low overpotential at a current density of 10 mA cm −2 (≈145 mV for HER and 360 mV for OER), low Tafel slope (105.2 mV dec −1 for HER and 46.9 mV dec −1 for OER), and good electrochemical stability. Good stability was also obtained upon using the material as HER and OER catalysts in a two‐electrode system to split water.

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)0.000
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 score0.244
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0010.000
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 head0.006
GPT teacher head0.228
Teacher spread0.221 · 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