Study of the Lithium/Polymer Interface and Conductive Deposits on Lithium Metal Used for Lithium Metal Polymer Batteries.
Bibliographic record
Abstract
Lithium metal anode has recently regained tremendous attention in the frame of the development of higher power and energy density lithium batteries for automotive industry. Lithium metal is indeed an ideal anode for lithium batteries due to its high capacity (3860 mAh/g). However, upon high discharge currents, the growth of dendrites leads to cell short cuts and limited coulombic efficiency. This issue had first restrained its practical application in rechargeable batteries for high power applications until the use of solid polymer electrolytes that could mechanically prevent the dendrites from crossing the electrolyte. Among the different families of polymer electrolytes, polyethylene oxide-based (PEO-based) electrolytes have been established as the reference thanks to a reasonable conductivity above 60oC and its ability to form a stable solid electrolyte interphase (SEI) with lithium. Nevertheless, due to the low transference number of POE/LiTFSI electrolytes (t+≈0.15), dendrites or uneven lithium plating are still susceptible to form. Nowadays, many efforts are dedicated to solve these problems by focusing either on the improvement of the electrolyte or on the modification of the lithium-electrolyte interface. Gold layers have been proposed as an alternative to prevent dendrite formation; these gold coatings are used mainly together with ceramic electrolytes in order to improve the interface between Li metal anode and electrolyte. However, their use with polymer electrolytes where dendrite formation is favorable due to low transference number and mechanical strength have not being widely studied. In this presentation, three different coatings will be considered; aluminum (Al), gold (Au) and lithium fluoride (LiF). The choice of Al and Au is based on their ability to form Li-rich alloys while LiF is known to act as an artificial ion conducting SEI. The morphology and physico-chemical properties of the coatings are first characterized by Atomic Force Microscopy (AFM), X-Ray Diffraction (XRD) and X-ray photoelectron spectroscopy (XPS) before evaluation of the interface between POE-based electrolyte and coated Lithium. Eventually stability during long-term cycling in Lithium Metal Polymer batteries is performed and compared to that of cells made using bare Lithium.
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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 | 0.000 |
| 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".