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Record W2996676511 · doi:10.1021/acsaem.9b01695

Effective Mass Transport Properties in Lithium Battery Electrodes

2019· article· en· W2996676511 on OpenAlex
Md. Sazzad Hossain, Lisa I. Stephens, Mojgan Hatami, Mohammadreza Zamanzad Ghavidel, Danny Chhin, Jeremy I. G. Dawkins, Laurence Savignac, Janine Mauzeroll, Steen B. Schougaard

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueACS Applied Energy Materials · 2019
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsMcGill UniversityUniversité du Québec à Montréal
FundersNatural Sciences and Engineering Research Council of CanadaUniversité du Québec à MontréalGeneral Motors Corporation
KeywordsThermal diffusivityScanning electrochemical microscopyElectrolyteMaterials scienceElectrodeLithium (medication)DiffusionPorosityBattery (electricity)Ionic conductivityLithium-ion batteryElectrochemistryNanotechnologyChemistryComposite materialPower (physics)ThermodynamicsPhysics

Abstract

fetched live from OpenAlex

Lithium ion battery performance becomes increasingly limited by ionic transport as the current demand increases. Especially detrimental is the transport within the liquid electrolyte that fills the porous electrode, yet reliable measurement of practical lithium diffusivity within this complex structure has been a longstanding challenge. In this work, we have developed a “single sided” analytical technique to determine the diffusivity in porous networks using scanning electrochemical microscopy (SECM) and a molecular redox marker. SECM surface mapping of porous films shows measurement consistency, and diffusion limited currents through a test structure with well-defined geometry matches the results of numerical modeling within 10%. Diffusivity measurement shows significant deviation from the Bruggeman model for porosities below 60%. The developed technique is applicable to all porous structures independent of their electronic conductivity. Importantly, for lithium-ion batteries the technique does not require free-standing electrodes and therefore is applicable to industrially relevant high power electrodes as a tool for optimization as well as for quality control.

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)0.000
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 score0.012
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)0.0010.000

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 head0.005
GPT teacher head0.180
Teacher spread0.175 · 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