Design of multifunctional interfaces on ceramic solid electrolytes for high-performance lithium-air batteries
Bibliographic record
Abstract
High-energy-density lithium (Li)–air cells have been considered a promising energy-storage system, but the liquid electrolyte-related safety and side-reaction problems seriously hinder their development. To address these above issues, solid-state Li–air batteries have been widely developed. However, many commonly-used solid electrolytes generally face huge interface impedance in Li–air cells and also show poor stability towards ambient air/Li electrodes. Herein, we fabricate a differentiating surface-regulated ceramic-based composite electrolyte (DSCCE) by constructing disparately LiI-containing polymethyl methacrylate (PMMA) coating and Poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP) layer on both sides of Li1.5Al0.5Ge1.5(PO4)3 (LAGP). The cathode-friendly LiI/PMMA layer displays excellent stability towards O2- and also greatly reduces the decomposition voltage of discharge products in Li–air system. Additionally, the anode-friendly PVDF-HFP coating shows low-resistance properties towards anodes. Moreover, Li dendrite/passivation derived from liquid electrolyte-induced side reactions and air/I-attacking can be obviously suppressed by the uniform and compact composite framework. As a result, the DSCCE-based Li–air batteries possess high capacity/low voltage polarization (11836 mA h g-1/1.45 V under 500 mA g-1), good rate performance (capacity ratio under 1000 mA g-1/250 mA g-1 is 68.2 %) and long-term stable cell operation (300 cycles at 750 mA g-1 with 750 mAh g-1) in ambient air.
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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) | 0.001 | 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".