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Record W2590262989 · doi:10.1149/ma2017-01/1/79

Impact of a Film Maturation Process on the Mechanical Stability of Silicon-Based Electrodes with High Areal Capacities

2017· article· en· W2590262989 on OpenAlexaff
Cuauhtémoc Reale Hernandez, Zouina Karkar, Alix Tranchot, Aurélien Etiemble, Éric Maire, Dominique Guyomard, Bernard Lestriez, Lionel Roué

Bibliographic record

VenueECS Meeting Abstracts · 2017
Typearticle
Languageen
FieldEngineering
TopicSemiconductor materials and devices
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsElectrodeMaterials scienceElectrolyteSiliconComposite materialNanotechnologyOptoelectronicsChemistry

Abstract

fetched live from OpenAlex

Over the last ten years, considerable efforts have been devoted to solve the problem of the low cycle life of Si-based electrodes for Li-ion batteries. This mainly originates from the huge volume variation (up to ~300%) of silicon during its lithiation/delithiation, which induces a rupture of the electrode conductive network and an instability of the solid electrolyte interphase (SEI). The use of nanosized Si materials (nanoparticles, nanowires, thin films…) able to better accommodate large strain without extensive electrode cracking has been successively developed for improving the Si electrode cycling stability. However, in most of these studies, the active mass loading is low, resulting in a low areal capacity, typically less than 1 mAh cm - ². This is much lower than that of commercial graphite-based negative electrodes, which can reach up to 5 mAh cm - ². Obtaining stable Si-based electrodes with high areal capacities is very challenging as the increase of the Si areal mass loading accentuates the mechanical strain generated by the Si volume change 1 . We have recently shown that the storing of a Si/C/CMC electrode in humid atmosphere for a few days before drying and cell assembling has a very positive impact on its cycling performance 2 . With such a ‘’maturated’’ electrode, an areal capacity higher than 4 mAh cm -2 can be achieved for more than 100 cycles compared to less than 3 cycles for a no matured electrode. The precise mechanism of this maturation process is still unclear Here, the impact of the maturation step on the mechanical properties of Si/C/CMC electrodes is investigated by means of indentation, peeling and scratch tests. They confirm the higher adhesion and cohesion strengths of the maturated electrode. Its more reversible expansion/contraction behavior upon cycling is also demonstrated from electrochemical dilatometry measurements and in-operando optical microscopy observations (Fig. 1). In addition, focused ion beam scanning electron microscopy (FIB-SEM) tomography shows a better preservation of the pore and Si particle connectivities with cycling for the matured electrode. Lastly, reflectance Fourier transform infrared spectroscopy ( ATR - FTIR) complemented by Nuclear Magnetic Resonance (NMR) analyses indicate that the nature and distribution of the Si-CMC bonds are modified by the maturation step. On the basis of these different analyses, a film maturation mechanism is proposed, which opens up new avenues for optimizing the manufacture process of high-performance Si-based electrodes. 1. Z. Karkar, D. Mazouzi, C. Reale Hernandez, D. Guyomard, L. Roué, B. Lestriez. Threshold-like dependence of silicon-based electrode performance on active mass loading and nature of carbon conductive additive . Electrochim. Acta 215 (2016) 276-288. 2. 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 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 score0.075
Threshold uncertainty score0.319

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 head0.020
GPT teacher head0.248
Teacher spread0.228 · 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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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