Ferroelectric Dipoles Tailoring Solid‐Electrolyte‐Interphase Chemistry to Enable Reversible Lithium Metal Batteries
Bibliographic record
Abstract
Abstract Solid‐electrolyte interphase (SEI) plays a decisive role in building reliable Li metal batteries. However, the scarcity of anions in Helmholtz layer (HL) caused by electrostatic repulsion usually leads to the inferior SEI derived from solvents, resulting in dendrites and ‘dead’ Li. Therefore, regulating the distribution of anions in electric double layer (EDL) and continuously introducing more anions into HL to tailor anions‐derived SEI is crucial for achieving stable Li plating/stripping. Herein, by jointly utilizing the controlled defects of reduced graphene oxide (rGO) and the oriented dipoles of ferroelectric BaTiO 3 (BTO), the rGO‐BTO composite layer sustainedly brings more TFSI − and NO 3 − into anion‐defecient HL, promoting favorable decomposition of anions and guiding the generation of robust and fast‐Li + ‐transport SEI containing more inorganics LiF and Li 3 N species. Thus, the resulting Li deposit shows smooth and dense morphologies without dendrites, leading to high average Coulombic efficiency. The Li//Cu@rGO‐BTO (10 mAh cm −2 plated Li) cell exhibits an enhanced Li plating/stripping stability (2700 h) and a higher rate capability. The LiFePO 4 full cell (N/P≈6.3) using rGO‐BTO displays an enhanced capacity retention (82.0 % @ 430 cycles). This work provides a new insight on the construction of robust SEI by regulating the distribution of anions within EDL.
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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) | 0.000 | 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 | 0.001 |
| 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 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".