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Record W2295073251 · doi:10.1002/anie.201600750

Pomegranate‐Inspired Design of Highly Active and Durable Bifunctional Electrocatalysts for Rechargeable Metal–Air Batteries

2016· article· en· W2295073251 on OpenAlexafffund
Ge Li, Xiaolei Wang, Jing Fu, Jingde Li, Moon Gyu Park, Yining Zhang, Gregory Lui, Zhongwei Chen

Bibliographic record

VenueAngewandte Chemie International Edition · 2016
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaCompute CanadaUniversity of WaterlooMcMaster University
KeywordsOverpotentialBifunctionalElectrocatalystOxygen evolutionMaterials scienceBattery (electricity)CatalysisComposite numberChemical engineeringTransition metalOxideNanotechnologyChemistryElectrodeComposite materialMetallurgyElectrochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Rational design of highly active and durable electrocatalysts for oxygen reactions is critical for rechargeable metal-air batteries. Herein, we report the design and development of composite electrocatalysts based on transition metal oxide nanocrystals embedded in a nitrogen-doped, partially graphitized carbon framework. Benefiting from the unique pomegranate-like architecture, the composite catalysts possess abundant active sites, strong synergetic coupling, enhanced electron transfer, and high efficiencies in the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER). The Co3O4-based composite electrocatalyst exhibited a high half-wave potential of 0.842 V for ORR, and a low overpotential of only 450 mV at the current density of 10 mA cm(-2) for OER. A single-cell zinc-air battery was also fabricated with superior durability, holding great promise in the practical implementation of rechargeable metal-air batteries.

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: none
Teacher disagreement score0.630
Threshold uncertainty score0.698

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 communication0.0000.001
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 head0.015
GPT teacher head0.228
Teacher spread0.212 · 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

Citations286
Published2016
Admission routes2
Has abstractyes

Explore more

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