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Record W2291192452 · doi:10.1149/ma2015-02/7/520

Impact of the Film Storage Conditions on the Performance of Si-Based Anodes for Li-Ion Batteries

2015· article· en· W2291192452 on OpenAlexaff
Cuauhtémoc Reale Hernandez, Zouina Karkar, Dominique Guyomard, Bernard Lestriez, Lionel Roué

Bibliographic record

VenueECS Meeting Abstracts · 2015
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsMaterials scienceElectrolyteElectrodeRelative humidityGravimetric analysisChemical engineeringElectrochemistryNanocrystalline materialGraphiteSiliconComposite materialNanotechnologyMetallurgyChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

For several years, great attention has been paid to silicon as negative electrode material for Li-ion batteries, due to its very high gravimetric capacity (3579 mAh g-1) in comparison to that of graphite (372 mAh g-1). However, Si electrodes suffer from poor cyclability due to the large volumetric expansion (up to 300%) of Si upon its lithiation, resulting in the electrode architecture disintegration, and in the instability of the solid electrolyte interphase (SEI). We have recently shown that low-cost and high-performance Si-based electrodes can be obtained by combining (i) the use of ball-milled (nanocrystalline) Si powder resulting in a smoother phase transition; (ii) the processing of the electrode at pH 3 with carboxymethylcellulose (CMC) binder favoring the covalent grafting of the CMC to the Si particles; (iii) the use of fluoroethylene and vinylene carbonates (FEC/VC) electrolyte additives resulting in a more stable SEI.1 In the present study, it is shown for the first time that the storage conditions of the Si-based film before assembling in the electrochemical cell has also a major impact on the electrode performance. This is illustrated in Fig. 1 which compares the evolution of the discharge capacities with cycling* of ball-milled Si-based electrodes prepared after storage at room temperature of the composite film** (a) for 1 day and 55 days in air and (b) for 6 days in air (10-15% relative humidity) and in humid air (70% relative humidity). It clearly appears that the film storage in air has a very positive impact on the electrode cycle life, which is accentuated under humid atmosphere. A possible explanation is that during the film storage, water molecules from air react with the film and modify the chemical links between the Si particles and the CMC binder. This tends to be confirmed by attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) analysis of the composite electrodes***. Indeed, as shown in Fig. 2, a significant increase of the peak centered at 1630 cm− 1 assigned to the stretching band of the carboxyl group of CMC is observed for the film stored in humid air, while the peak centered at 1750 cm-1assigned to a covalent bond between Si and CMC is decreased. This suggests an increase of the hydrogen bonds between the Si particles and CMC binder (Fig. 3), which could increase the deformability of the electrode, favorable to its mechanical stability with cycling. We believe that an optimum covalent / hydrogen bond ratio is required to obtain a film sufficiently rigid to maintain electronic connections but flexible enough to vary in volume without breaking/peeling off during cycling. * Electrodes were cycled in Swagelok-type cells with Li as counter/ref. electrode at full capacity between 1 and 0.005 V at a current density of 480 mA g-1 of Si. The electrolyte was LP30 + 10wt%FEC. ** (Si + CB + CMC+ pH3 buffer salts) in a weight ratio of 73.1/11.0/7.3/8.6. The Si loading was 1 mg/cm2. *** Electrodes were dried at 100°C under vacuum prior to ATR-FTIR analysis (same procedure as prior electrode cycling). Reference 1. M. Gauthier, D. Mazouzi, D. Reyter, B. Lestriez, P. Moreau, B. Lestriez, D. Guyomard, L. Roué. A low-cost and high-performance Si-based electrode for Li-ion batteries. Energy Environ. Sci. 6 (2013) 2145–2155. Figure 1

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.027
GPT teacher head0.272
Teacher spread0.245 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2015
Admission routes1
Has abstractyes

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