MétaCan
Menu
Back to cohort
Record W2007240311 · doi:10.1002/adem.200500116

Conditioning of Li(Ni,Co)O<sub>2</sub> Cathode Materials for Rechargeable Batteries During the First Charge‐Discharge Cycles

2005· article· en· W2007240311 on OpenAlexaff
Helmut Ehrenberg, Kristian Nikolowski, N. N. Bramnik, Carsten Baehtz, Thorsten Buhrmester, T. Gross

Bibliographic record

VenueAdvanced Engineering Materials · 2005
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMaterials scienceCathodeElectrochemistryLithium (medication)IonInsulator (electricity)MetalPhase (matter)Phase transitionTransition metalCharge orderingNickelChemical engineeringAnalytical Chemistry (journal)ElectrodeMetallurgyCharge (physics)Composite materialThermodynamicsPhysical chemistryChemistry

Abstract

fetched live from OpenAlex

Abstract As‐prepared Li(Ni,Co)O2 with good electrochemical performance is an insulator with low degree of cation disorder, i.e. Li and (Ni,Co) are distributed on different and alternating layers. Lithium extraction in the first cycle induces an irreversible first‐order phase transition into a metallic phase with a discontinuous change in the c/a ratio by 3.6% and an accompanied partial occupation of some of the vacant Li‐sites by Ni‐ions. The specific arrangement of those Ni‐ions on Li‐layers is proposed as a key feature for the good cycling behaviour of Li(Ni,Co)O2 based cathodes in rechargeable 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 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 score0.002
Threshold uncertainty score0.008

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)0.0020.000

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 head0.008
GPT teacher head0.225
Teacher spread0.217 · 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

Citations6
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueAdvanced Engineering MaterialsSame topicAdvancements in Battery MaterialsFrench-language works237,207