Robust Metallic Lithium Anode Protection by the Molecular‐Layer‐Deposition Technique
Bibliographic record
Abstract
Abstract The Li metal anode is considered as a promising alternative candidate for next‐generation Li metal batteries with high specific capacity, low potential, and light weight. However, the crucial problem for the Li metal anode is one of the biggest challenges. Mossy or dendritic growth of Li occurs in the repetitive Li stripping/plating process with an unstable solid electrolyte interphase (SEI) layer of nonuniform ionic flux, which can not only lead to low Coulombic efficiency, but can also create the risk of a short‐circuit, resulting in possible burning or explosion. Here, an advanced molecular‐layer‐deposition (MLD) Alucone protective layer is first demonstrated for Li metal anodes. By protecting Li foil with a controllable Alucone layer, the dendrites and mossy Li formation are effectively suppressed and the lifetime is significantly improved in different electrolytes (carbonate‐based and ether‐based). Furthermore, the detailed surface changes are studied by the advanced characterization technique of Rutherford backscattering spectrometry. The novel design of the MLD‐protected Li metal anode may bring in new opportunities to the realization of the next‐generation high‐energy‐density Li 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 | 0.000 |
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".