(Invited) Dry Process for the Preparation of Porous Composite Electrodes for Battery Application
Bibliographic record
Abstract
The development of advanced Li-ion battery would require innovative approaches to improve the present performances, while lowering the environmental footprint and price of their fabrication. In this scope, we are currently carrying out different projects to consider the electrode materials as well the process to make the batteries. This presentation will focus on the second aspects, which concerns the development of a solvent-free process to make composite electrodes using an owned patented process by Hutchinson [1]. Currently, most of the electrode fabrication involves the use of organic solvent (typically N-methyl-2-pyrrolidone, NMP, which is toxic). Life cycle analysis studies of the LiB manufacturing process showed that this type of electrode preparation accounts for a significant portion of their overall environmental imprint [2]. While the use of water, instead of NMP, would be preferable to minimize this impact [3], a solvent-free electrode manufacturing consumes less energy in comparison to solvent-based methods [4]. Different electrode formulations were prepared by the dry process. The mechanical, electrical and electrochemical properties in half cells were assessed and compared to composite electrodes obtained by doctor blade coating using the classical PVdF binder. The different steps of the dry process (mixing, lamination and adhesion to current collectors) were studied and optimized separately to reach the maximum loading, while ensuring good power performances. The Ragone plots for each electrode, tested in half cells, were evaluated and the best formulation was retained for the full cell manufacture. The performances of LiFePO4/Li4Ti5O12 batteries are comparable to our best electrodes made with PVdF. The different aspects of the process will be discussed in this presentation. References [1] Ph. Sonntag, D. Aymé-Perrot, B. Dufour, Arnaud Prébé, N. Garois, Patent WO2015124835A1 [2] G. Majeau-Bettez, T.R. Hawkins, A.H. Stromman, Environmental Science & Technology, 2011, 45, 4548. [3] M. Zackrisson, L. Avellan, J. Orlenius, Journal of Cleaner Production, 2010, 18, 1519. [4] Environmental Protection Agency “Lithium-ion batteries and nanotechnology for electric vehicles: A life cycle assessment,” EPA 744-R-12-001, 2012.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.016 |
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".