Dipole Moment Influences the Reversibility and Corrosion of Lithium Metal Anodes
Bibliographic record
Abstract
Abstract Lithium metal batteries (LMBs) must have both long cycle life and calendar life to be commercially viable. However, “trial and error” methodologies remain prevalent in contemporary research endeavors to identify favorable electrolytes. Here, a guiding principle for the selection of solvents for LMBs is proposed, which aims to achieve high Coulombic efficiency while minimizing the corrosion. For the first time, this study reveals that the dipole moment and orientation of solvent molecules have significant impacts on lithium metal reversibility and corrosion. Solvents with high dipole moments are more likely to adsorb onto lithium metal surfaces, which also influence the solid electrolyte interphase. Using this principle, the use of LiNO3 is demonstrated as the sole salt in LiNi0.8Co0.1Mn0.1O2/Li cells can achieve excellent cycling stability. Overall, this work bridges the molecular structure of solvents to the reversibility and corrosion of lithium metal, and these concepts can be extended to other metal‐based 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 | 0.001 |
| 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".