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Record W2168979871 · doi:10.1149/2.010310eel

The Impact of Electrolyte Additives Determined Using Isothermal Microcalorimetry

2013· article· en· W2168979871 on OpenAlexafffund
Laura E. Downie, K. J. Nelson, R. Petibon, Vincent Chevrier, J. R. Dahn

Bibliographic record

VenueECS Electrochemistry Letters · 2013
Typearticle
Languageen
FieldChemistry
Topicthermodynamics and calorimetric analyses
Canadian institutionsDalhousie University
FundersDalhousie University
KeywordsIsothermal microcalorimetryIsothermal processElectrolyteMaterials scienceThermodynamicsDistilled waterAnalytical Chemistry (journal)ChemistryChemical engineeringOrganic chemistryChromatographyPhysical chemistryElectrodePhysics

Abstract

fetched live from OpenAlex

Isothermal microcalorimetry is a quick and simple method of determining the effect an additive or additive combination has on the parasitic reactions occurring as a function of state of charge. It can easily discriminate exactly where in the voltage range the additive is providing a benefit with just a single cycle. As a demonstrative example, the effect of varying concentrations of vinylene carbonate (VC) on a LiCoO 2 /graphite cell is examined. Machine-made pouch cells were used such that the cells were nominally identical except for the concentration of VC. The measured heat flow for the different cells is then identical except for the heat flow that results from parasitic reactions. It is shown that the presence of VC reduces parasitic reactions above 3.9 V, and continues to reduce these reactions with increasing state of charge. The heat flow during open circuit conditions at the top of charge also shows that the presence of VC dramatically reduces the heat due to parasitic reactions.

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)0.003
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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.006
GPT teacher head0.237
Teacher spread0.231 · 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

Citations39
Published2013
Admission routes2
Has abstractyes

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