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Record W3108363628 · doi:10.3390/batteries6040059

Evaluation of the Stability of Carbon Conductor in the Cathode of Aqueous Rechargeable Lithium Batteries against Overcharging

2020· article· en· W3108363628 on OpenAlexafffund
The Nam Long Doan, Tuan K.A. Hoang, Sameh M.I. Saad, P. Chen

Bibliographic record

VenueBatteries · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsUniversity of Waterloo
FundersMitacs
KeywordsCarbon blackCathodeMaterials scienceCarbon fibersBattery (electricity)Lithium (medication)ElectrochemistryChemical engineeringGraphitePolyvinylidene fluorideAqueous solutionLithium iron phosphateComposite materialPolymerComposite numberChemistryElectrodeOrganic chemistry

Abstract

fetched live from OpenAlex

Three major components in a cathode of aqueous rechargeable lithium batteries are the active material, the polymer binder, and the carbon conductive additive. The stability of each component in the battery is the key to long service life. To evaluate the stability of the carbon component, we introduce here a quick and direct testing method. LiMn2O4 is chosen as a typical active material for the preparation of the cathode, with polyvinylidene fluoride (PVdF), and a commercial carbon, which is chosen among Acetylene black, superP, superP-Li, Ketjen black 1, Ketjen black 2, Graphite, KS-6, splintered glassy carbon, and splintered spherical carbon. This method reveals the correlation between the electrochemical stability of a carbon and its physical and structural properties. This helps researchers choose the right carbon component for a Li-ion cathode if they want the battery to be robust, especially at near full state of charge.

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)0.001
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 score0.014
Threshold uncertainty score0.433

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.000
Research integrity0.0000.000
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 head0.075
GPT teacher head0.277
Teacher spread0.201 · 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

Citations1
Published2020
Admission routes2
Has abstractyes

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