Study of Sulfur-Based Electrodes By Operando Acoustic Emission
Bibliographic record
Abstract
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. 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. A. Etiemble, H. Idrissi, P. Bernard, L. Roué. New insights into the pulverization of LaNi5-based alloys with different Co contents from electrochemical acoustic emission measurements. Electrochim. Acta 186 (2015) 112-116 A. Tranchot, A. Etiemble, P-X. Thivel, H. Idrissi., L. Roué. In-situ acoustic emission study of Si-based electrodes for Li-ion batteries, J. Power Sources 279 (2015) 259-266. A. Tranchot, P-X. Thivel, H. Idrissi, L. Roué. Influence of the Si particle size on the mechanical stability of Si-based electrodes evaluated by in-operando dilatometry and acoustic emission. J. Power Sources 330 (2016) 253-260. Figure 1
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".