Towards Safer Li-Ion Battery Cathodes and Electrolytes
Bibliographic record
Abstract
Lithium-ion batteries (LIBs) have revolutionized society by extending the portability of personal electronic devices. They have high energy density and good cycle life compared to other energy storage systems. The properties of the first generation of LIBs aroused the interest of scientists to improve upon them while expanding their applications. As a result, there have been a variety of chemistries in development for LIB.1 Due to this multitude of chemistries, LIBs can be tuned to suit a wide number of applications. Currently, they are not only limited to small portable electronic devices but include large-scale applications as well. Smart grids, electric vehicles can be powered by LIB packs.2 To make electric vehicles as popular as cellular phones amongst consumers, their LIBs must provide high energy without compromising the users’ safety. This energy can be increased by either raising the operating potential or the specific capacity. For safety, two levels should be considered; the single LIB cell and the pack design. The former implies the intrinsic thermal stability of the active material itself and its interaction with the other cell components, whereas the latter is associated to issues originating from differences in the state of charge (SOC) in each cell within the pack as well as the pack design itself. A difference in the SOC of individual cells may lead to an overcharge abuse condition causing local chemical and electrochemical reactions that might be extended to the whole pack. As a result, gas release or temperature increase can generate an out-of-control accelerated reaction. The consequences of such situations are more complicated in systems that dissipate heat inefficiently like LIB packs. To protect LIBs against overcharge, the use of safety mechanisms like redox-shuttles has been proposed.3 Redox-shuttles act electrochemically by carrying the excess current between the two electrodes in a cell during overcharge. Several redox-shuttles used as additives in common LIBs’ electrolytes have been reported.3 Moreover, when the benefit of redox shuttle protection can be incorporated into ionic liquids by functionalizing the ions with an electroactive moiety, the LIB’s safety is expected to be improved.4 The fundamental parameters identified above can be evaluated by Accelerating Rate Calorimetry (ARC). It consists of simulating the same conditions of heat dissipation in an actual LIB pack where the heat generated from an eventual exothermic reaction is not very well dissipated from the initiation point, resulting in heat build-up in a small area. This can generate an out of control reaction. The ARC allows the investigation of these reactions under adiabatic conditions in order to understand and improve the thermal properties of the studied samples. In this presentation, a study of the thermal stability of different cathode materials will be reported. The investigated materials represent different chemistries, (LiCoO2, LiFePO4 and LiMn2-x NixO4), in order to understand the relationship between the structure and the thermal behaviour of cathode materials. Additionally, two imidazolium (EMIm)-based ionic liquids incorporating 2,5-di-tert-butyl-1,4-dimethoxybenzene were studied and will be presented; (DDB-EMIm-TFSI) and (DDB-EMIm-PF6). Their electrochemical behaviour in Lithium-ion cells and their thermal properties were investigated . References: 1. J. B. Goodenough and Y. Kim, Chemistry of Materials, 2009, 22, 587-603. 2. V. Etacheri, R. Marom, R. Elazari, G. Salitra and D. Aurbach, Energy & Environmental Science, 2011, 4, 3243-3262. 3. Z. H. Chen, Y. Qin and K. Amine, Electrochimica Acta, 2009, 54, 5605-5613. 4. J. C. Forgie, S. El Khakani, D. D. MacNeil and D. Rochefort, Physical Chemistry Chemical Physics, 2013, 15, 7713-7721.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.009 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 0.008 |
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".