Surface Area of Lithium-Metal Electrodes Measured by Argon Adsorption
Bibliographic record
Abstract
Rechargeable cells that rely on the stripping and plating of lithium during discharge and charge, respectively, must maintain smooth and flat lithium morphology to attain long cycle life. Higher surface area lithium metal, associated with dendrites or porous deposits, will increase the rate of reaction with liquid electrolyte, accelerate capacity loss, and decrease safety. Here we use argon BET to measure the specific surface area of lithium-metal electrodes as a function of cycle number. For "anode-free" cells with 1M LiPF 6 in FEC:DEC electrolyte, the specific surface area of the lithium electrode increases by more than three times after 20 charge-discharge cycles. This measurement provides an assessment of degradation that can be linked to capacity loss and safety, which averages over the entire electrode and is therefore an excellent quantitative complement to SEM images used to look at lithium-morphology.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".