Modulating physicochemical interfaces enables li-rich oxides based ceramic solid-state li batteries under ambient conditions
Bibliographic record
Abstract
Li-rich layered oxides exhibit promising potential applications in high-energy-density solid-state lithium metal batteries. Nevertheless, the strong oxidative oxygen species generate at high voltage, which poses great challenges to positive electrode-side interface stability. Herein, a robust in-situ polymerization gel polymer electrolyte with bifunctional additives is designed for interface modification. These additives, include lithium difluoro(oxalate) borate and LiPO2F2, regulate the Li+ chemical environment in gel polymer electrolyte to enhance crosslink density without residual oligomer, which reduce gas generation and suppress contact loss, thus avoiding interfacial impedance divergence. Concurrently, the designed gel polymer electrolyte enables a wide electrochemical stability window (up to 4.7 V) and a high Li+ transference number (0.82). Additionally, the additives induced F- and B-rich inorganic cathode-electrolyte interphase inhibits side reactions and oxygen/transition metal loss effectively, stabilizing the chemical interface. The as-constructed Li-rich layered oxides-based ceramic solid-state lithium metal batteries with gel polymer electrolyte interface modification exert a high discharge capacity of 276.5 mAh g-1 at 30 °C without external pressure, delivering a retention of 81.7% after 100 cycles at 25 mA g-1 during 2.0-4.7 V. This work provides a guideline for developing high-voltage solid-state lithium metal batteries via interfacial design. Strong oxidative oxygen species generated at high voltage pose great challenges to positive electrode-side interface stability in lithium-based batteries. Herein, authors propose a robust gel polymer electrolyte with bifunctional additives for interface modification, achieving high-voltage ceramic solid-state lithium 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 | 0.000 |
| 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".