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Record W2560300165 · doi:10.1149/2.0181702jes

Charge/Discharge Asymmetry in Blended Lithium-Ion Electrodes

2016· article· en· W2560300165 on OpenAlexafffund
Zhiyu Mao, M. Farkhondeh, Mark Pritzker, Michael Fowler, Zhongwei Chen

Bibliographic record

VenueJournal of The Electrochemical Society · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Technologies Research
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsElectrodeCathodeLithium (medication)AsymmetryIonMaterials scienceDiffusionAnalytical Chemistry (journal)Charge (physics)Particle (ecology)ChemistryThermodynamicsPhysicsPhysical chemistry

Abstract

fetched live from OpenAlex

A multi-particle model for blended electrodes has been used to investigate the charge/discharge asymmetry in the response of a LiNi1/3Mn1/3Co1/3O2−LiMn2O4 (NMC-LMO) blended cathode at various applied currents. The analysis suggests that the contribution of LMO to the end-capacity of the electrode increases as discharge at higher C-rates progresses but decreases during charge at the same rates. Dynamic analysis of the blended cathode shows that this asymmetric charge/discharge behavior of the blended electrode can be attributed to the difference in the equilibrium potentials of the two components depending on Li concentration and electrode composition and to the differences in the rate of solid-state diffusion of Li and kinetics limitations in LMO and NMC.

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: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.428

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 communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.008
GPT teacher head0.243
Teacher spread0.235 · 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

Citations20
Published2016
Admission routes2
Has abstractyes

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