Constructing an anion-capturing interface to achieve Li+ cross-phase transport in composite solid electrolytes
Bibliographic record
Abstract
The ionic conductivity of solid electrolytes is still insufficient to approach performance promises of solid-state Li metal batteries, suffering from their charged interfaces among phase components and movable Li+ concentration. Herein, an anion-capturing interface based on FeF3 is established on Li6.5La3Zr1.5Ta0.5O12 surface through a sol-gel method. It promotes Li-salt dissociation and formation of anion aggregated layer before blending with polymer. Coulombic interaction of anion on grains boundary showcases multiple merits, including their weakened built-in electric field, restrained charge gradient layer, spontaneous Li+ cross-phase migration, and homogenized interfacial charge distribution. As such, the resulting composite solid electrolytes exhibits an ion conductivity of 1.1×10−4 S/cm2 and Li+ migration number of 0.75 at 25°C. Its resulting Li symmetrical batteries maintain Li plating/stripping behaviors for over 1300 h and low polarization at 0.1 mA/cm2 current density. When being assembled with LiFePO4 positive electrode in solid-state batteries, it performs a specific capacity of 152.8 mAh/g at 1.0 C (170 mA/g) with 96% retention after 600 cycles. This work prioritizes the promises of interface engineering for solid electrolytes in solid-state Li metal batteries. Composite solid electrolytes face sluggish inter-phase Li+ migration. Here, authors construct a FeF3-based anion-capturing layer onto Li6.5La3Zr1.5Ta0.5O12 nanofillers within PVdF solid electrolyte, where the charge gradient layer on the interface promotes Li+ cross-phase conductivity.
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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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".