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Record W2507610770 · doi:10.1149/2.0991610jes

Honeycomb Compound Na<sub>3</sub>Ni<sub>2</sub>BiO<sub>6</sub>as Positive Electrode Material in Na Cells

2016· article· en· W2507610770 on OpenAlexafffund
Lituo Zheng, M. N. Obrovac

Bibliographic record

VenueJournal of The Electrochemical Society · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsElectrodeHoneycombKineticsMaterials sciencePhase (matter)DiffractionHoneycomb structureKinetic energyAnalytical Chemistry (journal)SodiumPhase transitionChemical engineeringChemistryCrystallographyThermodynamicsPhysical chemistryMetallurgyComposite material

Abstract

fetched live from OpenAlex

Honeycomb compound Na 3 Ni 2 BiO 6 was synthesized and studied as positive electrode material in sodium cells for the first time. This material exhibits a reversible capacity of ∼80 mAh/g and an average voltage of ∼3.1 V, corresponding to the reversible removal of half of the sodium from the structure. The sodiation/desodiation mechanism was studied by in situ X-ray diffraction and involves multiple phase transitions. It was observed that the phase transitions are different for the first charge/discharge processes, possibly due to kinetic hindrance. The multiple phase transitions may lead to sluggish kinetics that are responsible for the poor rate capability.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.004
GPT teacher head0.203
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 source (direct Gemma or distilled Codex), 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

Citations26
Published2016
Admission routes2
Has abstractyes

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