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Record W2017590852 · doi:10.1039/c4cp01968g

3D visualization of inhomogeneous multi-layered structure and Young's modulus of the solid electrolyte interphase (SEI) on silicon anodes for lithium ion batteries

2014· article· en· W2017590852 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

VenuePhysical Chemistry Chemical Physics · 2014
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsL'Alliance Boviteq
Fundersnot available
KeywordsInterphaseLithium (medication)ElectrolyteAnodeSiliconMaterials scienceModulusIonYoung's modulusLithium metalChemical engineeringComposite materialChemistryPhysical chemistryElectrodeOptoelectronicsOrganic chemistry

Abstract

fetched live from OpenAlex

The microstructure and mechanical properties of the solid electrolyte interphase (SEI) in non-aqueous lithium ion batteries are key issues for understanding and optimizing the electrochemical performance of lithium batteries. In this report, the three-dimensional (3D) multi-layered structures and the mechanical properties of the SEI formed on a silicon anode material for next generation lithium ion batteries have been visualized directly for the first time, through a scanning force spectroscopy method. The coverage of the SEI on silicon anodes is also obtained through 2D projection plots. The effects of temperature and the function of additives in the electrolyte on the SEI can be understood accordingly. A modified model about dynamic evolution of the SEI on the silicon anode material is also proposed, which aims to explain why the SEI is very thick and how the multi-layered structure is formed and decomposed dynamically.

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 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 score0.064
Threshold uncertainty score0.850

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 head0.008
GPT teacher head0.254
Teacher spread0.246 · 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