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Record W3091885685 · doi:10.1021/acsanm.0c02501

Amorphous Ni-Based Nanoparticles for Alkaline Oxygen Evolution

2020· article· en· W3091885685 on OpenAlexafffund
Kevin M. Cole, Sagar Prabhudev, Gianluigi A. Botton, Donald W. Kirk, Steven J. Thorpe

Bibliographic record

VenueACS Applied Nano Materials · 2020
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsMcMaster UniversityUniversity of Toronto
FundersCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada
KeywordsAmorphous solidOxygen evolutionOverpotentialX-ray photoelectron spectroscopyCatalysisMaterials scienceChemical engineeringCyclic voltammetryNanoparticleLeaching (pedology)Amorphous metalTransmission electron microscopyElectrochemistryMetallurgyInorganic chemistryElectrodeNanotechnologyChemistryCrystallographyPhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Amorphous Ni79.2–xCoxNb12.5Y8.3 (x = 0 and 5 at %) nanoparticles were produced through a two-stage ball milling process for use as electrocatalysts in the alkaline oxygen evolution reaction (OER). Cyclic voltammetry demonstrated that these amorphous alloys have excellent long-term cyclic durability when compared to crystalline Ni and Ni95Co5. Potentiostatic polarization measurements showed that the catalytic performance of amorphous Ni74.2Co5Nb12.5Y8.3 was maintained by displaying a low overpotential of 346 mV at 10 mA cm–2 even after 10,000 cycles, while deactivation could be observed for the other catalysts. XPS analysis revealed that the retention of catalytic activity was attributed to the stabilization of β-NiOOH. Through transmission electron microscopy analysis, it was found that the surface of amorphous Ni74.2Co5Nb12.5Y8.3 remained amorphous, although definitive signs of electrochemically induced Nb leaching could be observed. The leaching of Nb aided the overall performance since Nb is not electrochemically active toward the OER and was solely added to facilitate the formation of an amorphous structure. These findings not only support the excellent long-term stability and activity of amorphous Ni74.2Co5Nb12.5Y8.3 nanoparticles toward the alkaline OER but also demonstrate how anodic cycling can be used to condition the surface of the catalyst.

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 score0.026
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)0.0000.001

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 head0.014
GPT teacher head0.213
Teacher spread0.199 · 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

Citations18
Published2020
Admission routes2
Has abstractyes

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