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Record W4401928264 · doi:10.1016/j.decarb.2024.100073

Investigating mass transport in Li-ion battery electrodes using SECM and SICM

2024· article· en· W4401928264 on OpenAlexafffund
Anjana Raj Raju, Andrew S. Danis, Steen B. Schougaard

Bibliographic record

VenueDeCarbon · 2024
Typearticle
Languageen
FieldChemistry
TopicElectrochemical Analysis and Applications
Canadian institutionsUniversité du Québec à Montréal
FundersNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsElectrodeIonBattery (electricity)Mass transportOptoelectronicsChemistryMaterials scienceEngineering physicsPhysicsPower (physics)

Abstract

fetched live from OpenAlex

Lithium-ion batteries (LIBs) are indispensable as global energy production transitions to sustainable production. Nevertheless, the use of LIBs in renewable energy storage applications is challenging due to their limited power densities. To comprehend the origin of this limitation, it is crucial to investigate the effect of electrode architecture on the Li + ion transport within their pores (solution-phase). In this work, the solution phase transport in various porous Li 4 Ti 5 O 12 (LTO) films was investigated using scanning ion conductance microscopy (SICM) and scanning electrochemical microscopy (SECM). When the porosity of LTO film increases, SECM and SICM approach curves show an increase in current. This is attributed to the ion transport through the film pores. The 2D topographical mapping using both techniques shows their ability to detect the LTO film's heterogeneity. Most importantly, this work gives insight into the complementary nature of the two scanning probe techniques as demonstrated by the comparable MacMullin numbers.

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 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 score0.057
Threshold uncertainty score0.396

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.013
GPT teacher head0.248
Teacher spread0.235 · 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

Citations8
Published2024
Admission routes2
Has abstractyes

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