Superior Stable and Long Life Sodium Metal Anodes Achieved by Atomic Layer Deposition
Bibliographic record
Abstract
Na‐metal batteries are considered as the promising alternative candidate for Li‐ion battery beneficial from the wide availability and low cost of sodium, high theoretical specific capacity, and high energy density based on the plating/stripping processes and lowest electrochemical potential. For Na‐metal batteries, the crucial problem on metallic Na is one of the biggest challenges. Mossy or dendritic growth of Na occurs in the repetitive Na stripping/plating process with an unstable solid electrolyte interphase layer of nonuniform ionic flux, which can not only lead to the low Coulombic efficiency, but also can create short circuit risks, resulting in possible burning or explosion. In this communication, the atomic layer deposition of Al 2 O 3 coating is first demonstrated for the protection of metallic Na anode for Na‐metal batteries. By protecting Na foil with ultrathin Al 2 O 3 layer, the dendrites and mossy Na formation have been effectively suppressed and lifetime has been significantly improved. Furthermore, the thickness of protective layer has been further optimized with 25 cycles of Al 2 O 3 layer presenting the best performance over 500 cycles. The novel design of atomic layer deposition protected metal Na anode may bring in new opportunities to the realization of the next‐generation high energy‐density Na metal batteries.
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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) | 0.001 | 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".