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Record W2346848854 · doi:10.1149/ma2016-03/2/1014

A Simple Maturation Process to Increase the Performance of Si-Based Anodes for Li-Ion Batteries

2016· article· en· W2346848854 on OpenAlexaff
Cuauhtémoc Reale Hernandez, Zouina Karkar, Dominique Guyomard, Bernard Lestriez, Lionel Roué

Bibliographic record

VenueECS Meeting Abstracts · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsMaterials scienceElectrodeElectrolyteElectrochemistryChemical engineeringNanocrystalline materialGravimetric analysisFOIL methodSiliconGraphiteAnodeNanotechnologyComposite materialMetallurgyChemistry

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 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 More recently, we have shown that the storage conditions of the Si-based film before assembling in the electrochemical cell has also a major impact on the electrode performance.2 In this context, we have elaborated a film maturation process which simply consists of storing the electrode in humid air (85% RH) at room temperature for at least two days. This process has a significant positive impact on the electrode performance as is illustrated in Fig. 1a which compares the cycling performance of ball-milled Si-based electrodes cast on a copper foil with and without a film maturation step. Different mechanisms are proposed to explain why humid storage has such a beneficial impact on the electrode performance. Firstly, humid air may increase the film adherence on the copper current collector by increasing the amount of CuOH groups which can create bonds with the CMC binder. This tends to be supported by the fact that the film maturation step has no significant impact when a carbon layer is deposited on the copper current collector prior to the maturation step as shown on Fig. 1b. Secondly, water molecules from air can 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. 2a, a significant increase of the intensity 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 intensity of the peak centered at 1750 cm-1 assigned to ester bond between Si and CMC is decreased. This suggests that during the maturation step, some of the ester bonds between Si particles and CMC binder are converted into less rigid hydrogen bonds as schematized in Fig.2b. This may increase the deformability of the electrode, which can better accommodate volume variations with cycling. Thirdly, the humid air could modify the surface chemistry of silicon particles by increasing the amount of silicon oxide and/or silanols (SiOH). This would increase the amount of bonds between silicon particles and binder, and/or help to stabilise the SEI layer. Various experiments for supporting these different hypotheses will be presented. References 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. C. Real Hernandez, Z. Karkar, D. Guyomard, B. Lestriez, L. Roué. A film maturation process for improving the cycle life of Si-based anodes for Li-ion batteries. Electrochem. Comm. 61 (2015) 102-105. Figure 1

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 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)0.000
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
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.012
GPT teacher head0.251
Teacher spread0.239 · 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
Published2016
Admission routes1
Has abstractyes

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