Toward Dendrite-Free Metallic Lithium Anodes: From Structural Design to Optimal Electrochemical Diffusion Kinetics
Bibliographic record
Abstract
Lithium metal anodes are ideal for realizing high-energy-density batteries owing to their advantages, namely high capacity and low reduction potentials. However, the utilization of lithium anodes is restricted by the detrimental lithium dendrite formation, repeated formation and fracturing of the solid electrolyte interphase (SEI), and large volume expansion, resulting in severe "dead lithium" and subsequent short circuiting. Currently, the researches are principally focused on inhibition of dendrite formation toward extending and maintaining battery lifespans. Herein, we summarize the strategies employed in interfacial engineering and current-collector host designs as well as the emerging electrochemical catalytic methods for evolving-accelerating-ameliorating lithium ion/atom diffusion processes. First, strategies based on the fabrication of robust SEIs are reviewed from the aspects of compositional constituents including inorganic, organic, and hybrid SEI layers derived from electrolyte additives or artificial pretreatments. Second, the summary and discussion are presented for metallic and carbon-based three-dimensional current collectors serving as lithium hosts, including their functionality in decreasing local deposition current density and the effect of introducing lithiophilic sites. Third, we assess the recent advances in exploring alloy compounds and atomic metal catalysts to accelerate the lateral lithium ion/atom diffusion kinetics to average the spatial lithium distribution for smooth plating. Finally, the opportunities and challenges of metallic lithium anodes are presented, providing insights into the modulation of diffusion kinetics toward achieving dendrite-free lithium metal batteries.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".