Dynamically lithium‐compensated polymer artificial SEI to assist highly stable lithium‐rich manganese‐based anode‐free lithium metal batteries
Bibliographic record
Abstract
Abstract Owing to the unique structure, anode‐free lithium metal batteries (AFLMBs) have higher energy density and lower production cost than traditional lithium metal batteries (LMBs) or lithium‐ion batteries (LIBs). However, AFLMBs suffer from an inherently finite Li reservoir and exhibit poor cycle stability, low Coulombic efficiency (CE) and severe dendrite growth. In this work, polydiallyl lithium disulfide (PDS‐Li) was successfully synthesized and coated on Cu current collector by electrochemical polymerization. The PDS‐Li acts as an additional lithium resource to compensate for the irreversible loss of lithium during cycling. In addition, the special structure and lithiophilicity of PDS‐Li contribute to lower nucleation overpotential and uniform lithium deposition. When coupled with Li‐rich manganese‐based (LRM) cathode of Li 1.2 Mn 0.54 Ni 0.13 Co 0.13 O 2 , the anode‐free full cell exhibits significantly improved cycle stability over 100 cycles and capacity retention of 63.3% and 57% after 80 and 100 cycles, respectively. We believe that PDS‐Li can be used to ensure stable cycling performance and high‐energy–density in AFLMBs.
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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".