The Insights of Lithium Metal Plating/Stripping in Porous Hosts: Progress and Perspectives
Bibliographic record
Abstract
Lithium (Li) metal is strongly regarded as a promising anode for next‐generation secondary batteries. However, the nonuniform plating/stripping and volume fluctuation of the Li metal anode give rise to low Coulombic efficiency and short lifespan of Li metal batteries, which hinder practical applications of the Li metal anode. A composite Li metal anode that employs a stable porous host has been proposed as a promising strategy to regulate the behaviors of Li plating/stripping and relieve volume fluctuation. In a porous host, the basic building block is a pore. The pore structure affects the distribution of electric and Li‐ion concentration fields during Li plating/stripping, thus regulating Li plating/stripping and the lifespan of the composite Li metal anode. Therefore, herein, the recent progress in investigating the behavior of Li plating/stripping in a pore based on liquid electrolytes is summarized from the aspects of pore diameter, depth, and tortuosity. Furthermore, the perspectives of rational design of the pore structure for a composite Li metal anode are presented to promote the development of Li metal anodes.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".