MétaCan
Menu
Back to cohort
Record W2076422268 · doi:10.1149/1.3515072

A Guide to Li-Ion Coin-Cell Electrode Making for Academic Researchers

2010· article· en· W2076422268 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of The Electrochemical Society · 2010
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsDalhousie University
Fundersnot available
KeywordsElectrodeLithium (medication)FOIL methodBattery (electricity)ElectrochemistryMaterials scienceNanotechnologyIonCarbon blackLithium-ion batteryParticle (ecology)Current densityEngineering physicsComposite materialChemistryEngineeringPhysics

Abstract

fetched live from OpenAlex

To remain as relevant as possible, academic researchers need to be able to produce electrodes for lithium ion batteries that are comparable to those used in industry. This requires both a high percentage of active material and a high electrode density. Furthermore, the electrodes also need to adhere well enough to the current collecting foil to prevent particle detachment during cycling. While much of the knowledge needed to produce such electrodes is widely known in the industrial sphere, it is not readily available in the academic literature. Now that Li-ion battery technology has matured, reports of materials and cells tested using impractical electrodes are of limited value. This report outlines an effective method for producing high density, high capacity electrodes that have low amounts of binder and carbon black while still possessing excellent adhesion and electrochemical performance.

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.

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 score0.036
Threshold uncertainty score0.551

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 science0.0010.000
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 head0.019
GPT teacher head0.324
Teacher spread0.305 · 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