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Record W2313940282 · doi:10.1021/am507376f

High Capacity and High Density Functional Conductive Polymer and SiO Anode for High-Energy Lithium-Ion Batteries

2014· article· en· W2313940282 on OpenAlexaff
Hui Zhao, Neslihan Yuca, Ziyan Zheng, Yanbao Fu, Vincent Battaglia, Abdelbast Guerfi, Karim Zaghib, Gao Liu

Bibliographic record

VenueACS Applied Materials & Interfaces · 2014
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsHydro-Québec
FundersVehicle Technologies ProgramTürkiye Bilimsel ve Teknolojik Araştırma Kurumu
KeywordsCalenderingMaterials scienceElectrodeComposite materialAnodeLithium (medication)Electrical conductorPorosityPolymerEnergy storage

Abstract

fetched live from OpenAlex

High capacity and high density functional conductive polymer binder/SiO electrodes are fabricated and calendered to various porosities. The effect of calendering is investigated in the reduction of thickness and porosity, as well as the increase of density. SiO particle size remains unchanged after calendering. When compressed to an appropriate density, an improved cycling performance and increased energy density are shown compared to the uncalendered electrode and overcalendered electrode. The calendered electrode has a high-density of ∼1.2 g/cm(3). A high loading electrode with an areal capacity of ∼3.5 mAh/cm(2) at a C/10 rate is achieved using functional conductive polymer binder and simple and effective calendering method.

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 categoriesMeta-epidemiology (narrow)
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 score0.011
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.013
GPT teacher head0.201
Teacher spread0.189 · 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.

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

Citations80
Published2014
Admission routes1
Has abstractyes

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