Ultrafast One‐Step Synthesis of Garnet‐Type Solid Electrolytes With Modified Surface and Microstructure for Solid‐State Lithium‐Metal Batteries
Bibliographic record
Abstract
Abstract Garnet‐type Li 6.5 La 3 Zr 1.5 Ta 0.5 O 12 (LLZTO) solid electrolytes provide the necessary electrochemical stability and ionic conductivity for solid‐state lithium‐metal batteries (SSLMBs). However, their wider application is hindered by their high interfacial resistance with electrodes and a lengthy synthesis process. This study presents the synthesis of densified LLZTO electrolytes using unconventional Li 2 O and Li 2 ZrO 3 precursors through an ultrafast (≈60 s) Joule heat‐assisted synthesis approach in a single‐step process. The lower sintering temperature of Li 2 ZrO 3 compared to traditional ZrO 2 precursor yields LLZTO with larger grains, resulting in enhanced Li + conductivity (7.0 × 10 −4 S cm −1 at 25 °C), reduced electronic conductivity (1.7 × 10 −10 S cm −1 ), and higher density (94.2%). Applying a 52–80 nm Sn:SnF 2 coating on the LLZTO surface using a melt‐quenching approach produces a uniform interlayer that chemically converts to Li‐Sn alloy and LiF upon contact with lithium, resulting in a near‐zero interfacial resistance and a critical current density of 4.2 mA cm −2 at 25 °C. The SSLMBs, incorporating Sn:SnF 2 ‐coated LLZTO electrolyte with NMC811 cathode, demonstrate remarkable initial capacity (181.1 mAh g −1 ) and cycle performance (88.63% capacity retention at 3000th cycle). The results indicate that this approach has the potential to advance the commercial fabrication technology for high‐performance solid electrolytes for SSLMBs.
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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) | 0.001 | 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) | 0.000 | 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".