Melt-Process for the Preparation of Porous Composite Electrodes for Battery Application
Bibliographic record
Abstract
Lithium-ion batteries have become the dominant technology for electrochemical energy storage. They have been used in electronic portable devices for decades and now taking the lead in the transportation sector in electrical vehicles. As it has long been known, the release of CO2 from combustion engine-powered constituted a significant proportion of our global emission of greenhouse gases. In order to reduce this proportion, efforts are being deployed to increase the market penetration of electric vehicles which puts a growing pressure on the production of lithium-ion batteries. As a result, this production is predicted to rapidly and sharply grow in the next few years. This fast development raises novel issues regarding the electrode production process and its impact on the environment. Currently, most of the electrode fabrication processes require organic solvent such as N-methyl-2-pyrrolidone (NMP), which is toxic and costly. It is therefore essential to find an alternative which is more sustainable that the solvent process yet that meets requirements of scalability, cost and productivity. In this context, we propose a new approach to electrodes fabrication process developed by our industrial partner Hutchinson (Patent US20130244098A1). It consists of a melt process which is well-known in the polymer industry to make composites. As such, our process does not require any solvent. In our study, we optimised the electrode formulation for power applications. In this presentation, we will report the different steps of the new melt process. The active materials and the conductive carbons used are the same as in the conventional wet process, but the binder needs to be chosen with care. Indeed, due to constraints in terms of temperature, shear forces and of the mixing process itself, the binder must be a heat-tolerant elastomer, to allow good mixing properties to the blend and flexibility to the resulting electrode. As an alternative to the most commonly-used binder, PVdF, a lower-cost commercial elastomer, Hydrogenated Nitrile Butadiene Rubber (HNBR), was used as the binder. To evaluate its compatibility and performance in lithium-ion battery composite electrodes, it was first compared to PVdF with the common wet process to make electrodes. After the validation of HNBR as a binder, it was used with the melt-process. Power testing and cycling performances of electrodes made with different active materials will be presented, showing the feasibility of electrodes and the versatility of the melt-process.
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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) | 0.000 | 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".