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Record W2982135262 · doi:10.1002/aenm.201970157

Li–O<sub>2</sub> Batteries: Interfacial Super‐Assembled Porous CeO<sub>2</sub>/C Frameworks Featuring Efficient and Sensitive Decomposing Li<sub>2</sub>O<sub>2</sub> for Smart Li–O<sub>2</sub> Batteries (Adv. Energy Mater. 40/2019)

2019· article· en· W2982135262 on OpenAlexaff
Yue Hou, Jun Wang, Jiaqing Liu, Chuanxin Hou, Zhaohong Xiu, Yuqi Fan, Lanling Zhao, Yanjie Zhai, Hongyu Li, Jie Zeng, Xiang Gao, Shan Zhou, Dongwei Li, Yong Li, Feng Dang, Kang Liang, Pu Chen, Chang Ming Li, Dongyuan Zhao, Biao Kong

Bibliographic record

VenueAdvanced Energy Materials · 2019
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Materials and Technologies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsCathodeMaterials scienceNucleationPorosityChemical engineeringNanotechnologyOxygen evolutionCatalysisElectrodePhysical chemistryElectrochemistryComposite materialThermodynamicsChemistry

Abstract

fetched live from OpenAlex

In article number 1901751, Feng Dang, Biao Kong and co-workers propose the smart design of oxygen cathodes in Li–O2 batteries through employing super-assembled porous CeO2/C frameworks as cathode electrocatalysts, achieving long-term cyclability and high-rate capacity, and illustrate the surface-nucleation mechanism of Li2O2 generation. This technique is highly applicable to the future production of smart high-performance Li–O2 batteries with CeO2-based cathode catalysts.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesMeta-epidemiology (narrow)
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 score0.054
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0040.004
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0020.002
Research integrity0.0030.001
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 head0.004
GPT teacher head0.198
Teacher spread0.194 · 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; both teacher heads agree on what is shown here.

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

Citations5
Published2019
Admission routes1
Has abstractyes

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