On the Importance of Li Metal Morphology on the Cycling of Lithium Metal Polymer Cells
Bibliographic record
Abstract
Lithium metal anodes have recently earned greater attention in the context of the development of lithium batteries with high power and energy density for use in both the automotive industry and in portable electronic devices. Lithium metal is indeed an ideal anode for lithium batteries due to its high specific capacity (3860 mAh g −1 ). However, the growth of dendrites under high charge currents restricts the use of lithium anode in rechargeable batteries until solid electrolytes that can mechanically hamper dendrite growth can be developed. Efforts are currently dedicated to solving these problems by focusing on either improving the shear modulus of the electrolyte, or on the modification of the lithium-electrolyte interface. The electrochemical stability of novel solid electrolytes towards lithium is commonly determined by galvanostatic cycling of Li-Li symmetric cells. However, important characteristics of the lithium foil used in most studies are seldom provided, hence making comparisons between materials trivial. This paper demonstrates the importance of a thorough electrode characterization for the cycling of symmetric cells. In this study, two types of lithium foils are used with polyethylene oxide-based (PEO-based) electrolyte. A detailed characterization of the morphological and physico-chemical properties of the metallic electrodes is first performed by PeakForce Tunneling Atomic force microscopy (PeakForce-TUNA™), and X-ray photoelectron spectroscopy (XPS), followed by an evaluation of the interface with PEO-based electrolyte. It is demonstrated that lithium foil morphology is a key factor in the electrochemical performance of the cell and a novel electrochemical pre-treatment program is presented. This type of pre-treatment, still unreported in the existing literature, results in a longer life for lithium symmetrical cells.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".