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Record W2137265160 · doi:10.1149/2.021207jes

Measurement of Parasitic Reactions in Li Ion Cells by Electrochemical Calorimetry

2012· article· en· W2137265160 on OpenAlexafffund
L. J. Krause, L. D. Jensen, J. R. Dahn

Bibliographic record

VenueJournal of The Electrochemical Society · 2012
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsCalorimetryCalorimeter (particle physics)ElectrolyteElectrochemistryLithium (medication)ElectrodeElectrochemical cellFaraday efficiencyElectrochemical energy conversionAnalytical Chemistry (journal)GraphiteSpecific energyIsothermal titration calorimetryChemistryIonMaterials scienceThermodynamicsPhysical chemistryOrganic chemistryElectrical engineeringPhysics

Abstract

fetched live from OpenAlex

A method for measuring the energy produced from parasitic cell reactions in lithium ion cells by electrochemical calorimetry is described. Negative electrode symmetric cells were charged and discharged by high precision current sources in an isothermal heat flow calorimeter while the cell voltage was accurately measured. Two sources of graphite of different BET surface areas were investigated. Symmetric cells of Li 4 Ti 5 O 12 and lithium/graphite half cells were also measured by this method. The measured parasitic energy was well correlated to the loss of active Li, or coulombic efficiency, confirming the source of the parasitic energy as the heat of reaction occurring between the lithiated electrodes and the electrolyte. The effect of electrode formulation was also explored. Electrochemical calorimetry of symmetric cells is an excellent method to study new material sets to determine which will lead to extended cell lifetime.

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)0.001
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
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 head0.010
GPT teacher head0.235
Teacher spread0.225 · 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

Citations94
Published2012
Admission routes2
Has abstractyes

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