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Record W3217187826 · doi:10.1149/ma2019-04/2/112

Study of Sulfur-Based Electrodes By in Situ Characterization Techniques

2019· article· en· W3217187826 on OpenAlexaff
Quentin Lemarié, Hassane Idrissi, Fannie Alloin, Éric Maire, Pierre‐Xavier Thivel, Lionel Roué

Bibliographic record

VenueECS Meeting Abstracts · 2019
Typearticle
Languageen
FieldMaterials Science
TopicConducting polymers and applications
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsAcoustic emissionMaterials scienceCharacterization (materials science)CrackingElectrodeSynchrotronBattery (electricity)DiffractionDelamination (geology)Stress corrosion crackingComposite materialCorrosionNanotechnologyChemistryGeology

Abstract

fetched live from OpenAlex

The Lithium-Sulfur (Li/S) battery system is one of the most promising candidates to become the successor of the current Li-ion battery. However, in spite of its high theoretical specific capacity (1675 mAh.g -1 ) and energy density (up to 500 Wh kg -1 ), it still suffers from a shortened cycle life resulting from the numerous complex processes occurring upon cycling. Hence the constant need for understanding of those mechanisms drives the use of innovative in situ characterization techniques. In the present study, the acoustic emission technique (AE), in situ Synchrotron X-ray tomography and diffraction are used to help better understand the optimization of sulphur-based electrodes for Li/S batteries. The acoustic emission (AE) technique has been widely used since the 70’s for detecting anomalies such as leakages and cracks on large structure (e.g. bridges, pressure containers, and pipe lines). The analysis of the AE signals (transient elastic waves) can also be used to characterize the degradation mechanisms (crack growth, friction, delamination, matrix cracking, corrosion, etc) of various materials subjected to a stress by mechanical, pressure or thermal means. Recently, AE technique has also been used to evaluate the degradation of metal hydride electrodes for Ni-MH [1] and Si-based electrodes for Li-ion batteries [2,3]. Cracking of the active material and gas evolution are the main sources of AE signals identified in these studies. On the other hand, X-Ray computed tomography (XRCT) is certainly one of the most powerful analytical tools enabling non-destructive 3D imaging of objects with complex and porous morphologies. Using appropriate image processing, segmentation and analysis procedures, quantitative parameters can be extracted such as the volume fraction, the size distribution, the connectivity and the geometrical tortuosity of the constitutive phases of the Li/S electrodes. A spatial resolution of a few tens of nm can be reached with a synchrotron X-ray source compared to a few µm with a conventional laboratory X-ray source. This technique, coupled with in situ synchrotron X-ray Diffraction, enables to follow in great details the evolution of the different species inside the tested Li/S batteries and get invaluable information on their behavior and degradation mechanisms. Recently, in situ XRCT and XRD has been used to characterize Si-based anodes [4]. In the present study, the AE technique is used for studying upon cycling the mechanical degradation of S-based electrodes for Li/S batteries. The AE signals were recorded by a piezoelectric transducer fixed on the back of the working electrode. S-based electrodes made with two different binders (PVdF vs. CMC) and two different current collectors (standard Al foil vs. porous 3D carbon paper) were studied. In all cases, AE signals were mainly detected during the first plateau of the first discharge, suggesting that the electrode degradation mostly occurs during the initial dissolution of the S8 particles. AE signals were also detected during a few subsequent cycles when CMC binder is used. This is attributed to a better propagation of the AE signals through the electrode thanks to an improved adhesion of the electrode to the current collector in comparison to PVdF binder. This is confirmed by further mechanical resistance testing (peel and scratch tests). The use of a carbon paper as a current collector combined to CMC binder greatly improves the electrochemical performance of the S electrode by preventing the collapse of the electrode upon cycling. This electrode also presents an increased amount of AE signals, suggesting that the carbon fibres of the C paper act as an AE waveguide. This study demonstrated that AE could be used as an efficient tool to monitor the morphological degradation of S-based electrodes upon their cycling and offers relevant information for optimizing their formulation and architecture. Further electrode optimization was investigated with the use of a poly-electrolyte binder (PEB) enhancing the performances of S-based electrodes by creating a ionic layer at the surface of the electrode which confines the polysulfide chains and prevents sulfur loss over cycling. In situ synchrotron X-ray tomography and diffraction was used at ESRF in France to study the behavior of those electrodes in comparison to classic CMC-binder based electrodes. Coupled with in situ X-Ray diffraction, the aim of this study was to get a better global understanding at the reduced capacity loss of PEB-based electrodes, especially on Aluminum current collector. To do so, the morphology of the electrodes were compared, as well as the evolution of the different sulfur and lithiated species throughout the electrode and the electrolyte upon cycling. Batteries were studied again after 10 cycles to compare the evolution of their internal degradation. 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 score0.011
Threshold uncertainty score0.354

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 head0.015
GPT teacher head0.261
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

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
Published2019
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