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Record W4200336151 · doi:10.1088/1361-6528/ac4663

Coordinated Co-NC/CoFe dual active centre embedded three-dimensional ordered macroporous framework as bifunctional catalyst for efficient and stable zinc–air batteries

2021· article· en· W4200336151 on OpenAlexaff
Tongtao Wan, Chenhui Yang, Ximeng Zhao, Qinglin Han, Zisheng Zhang, Jingde Li, Xiaohang Du, Daolai Sun

Bibliographic record

VenueNanotechnology · 2021
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsUniversity of Ottawa
FundersNatural Science Foundation of Hebei ProvinceNational Natural Science Foundation of China
KeywordsBifunctionalMaterials scienceElectrocatalystCatalysisSpinelZincChemical engineeringNanoparticleBattery (electricity)AlloyBifunctional catalystOxygen evolutionOxygen reduction reactionCobaltOxygen reductionNanotechnologyMetallurgyElectrodeElectrochemistryPhysical chemistryOrganic chemistryChemistryPower (physics)

Abstract

fetched live from OpenAlex

Abstract Developing efficient and stable multifunctional electrocatalyst is very important for zinc–air batteries in practical. Herein, semiconductive spinel CuFe 2 O 4 supported Co–N co-doped carbon (Co-NC) and CoFe alloy nanoparticles were proposed. In this strategy, the three-dimensional ordered macroporous CuFe 2 O 4 support provides rich channels for mass transmission, revealling good corrosion-resistance and durability at the same time. ZIF-67 derived Co-NC decoration improves the conductivity of the catalyst. Further, the uniformly distributed Co-NC and CoFe nanoparticles (C/CF) dramatically promote the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) performance. Accordingly, C/CF@CuFe 2 O 4 catalyst shows remarkable bifunctional electrocatalytic activity, with an ORR half-wave potential of 0.86 V, and an OER over-potential of 0.46 V at 10 mA cm −2 . The zinc–air battery using this catalyst exhibits a power density of 95.5 mW cm −2 and a durable cyclability for over 170 h at a current density of 10 mA cm −2 , which implies a great potential in practical application.

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)0.001
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 score0.281
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.229
Teacher spread0.223 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

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