MétaCan
Menu
Back to cohort
Record W2119298575 · doi:10.1149/1.3543569

High-Precision Differential Capacity Analysis of LiMn<sub>2</sub>O<sub>4</sub>/graphite Cells

2011· article· en· W2119298575 on OpenAlexafffund
Aaron Smith, J. C. Burns, J. R. Dahn

Bibliographic record

VenueElectrochemical and Solid-State Letters · 2011
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Technologies Research
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of CanadaDalhousie University
KeywordsGraphiteMaterials scienceCoulometryDifferential (mechanical device)ElectrodeHeat capacityFadeSlippageCapacity lossAnalytical Chemistry (journal)ThermodynamicsComposite materialElectrochemistryChemistryComputer sciencePhysicsChromatographyPhysical chemistry

Abstract

fetched live from OpenAlex

The differential capacity and charge–discharge end points of a commercial LiMn2O4/graphite cell were examined using high precision constant-current chronopotentiometry and coulometry. The positive and negative electrodes from a fresh commercial cell were recovered and used to generate high precision "reference" potential-capacity data versus Li. The reference data were used to calculate differential capacity versus potential for "theoretical" LiMn2O4/graphite cells which could be perfectly matched to data from experiments on full cells. Matching was achieved primarily by relative "slippage" in capacity of the positive and negative potential-capacity curves. This allowed a detailed understanding of the aging processes and capacity fade of a full cell.

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)0.002
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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.010
GPT teacher head0.205
Teacher spread0.195 · 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

Citations92
Published2011
Admission routes2
Has abstractyes

Explore more

Same venueElectrochemical and Solid-State LettersSame topicAdvanced Battery Technologies ResearchFrench-language works237,207