Probing Alkaline-Earth-Doped Garnet-Type Li<sub>7</sub>La<sub>2.75</sub>A<sub>0.25</sub>Zr<sub>1.75</sub>M<sub>0.25</sub>O<sub>12</sub> (A = Ca, Sr, Ba; M = Nb, Ta) Electrolytes for All-Solid-State Li Metal Batteries
Bibliographic record
Abstract
Solid (ceramic) electrolytes have demonstrated great potential for all-solid-state lithium metal batteries (ASSLMBs), providing better safety and stability over organic liquid electrolyte-based Li-ion batteries. A proper selection of solid electrolytes and an analysis of their compatibility with Li metal are critical for improving battery performance. Here, we present an extensive experimental study realizing the effect of substituting alkaline-earth-metal-doped Li 7 La 2.75 A 0.25 Zr 1.75 M 0.25 O 12 (A = Ca, Sr, Ba; M = Nb, Ta) garnet-type electrolytes on the ionic and electronic conductivity, Li-ion migration pathways, microstructures, and electrochemical stability properties. We examined the relationship between the bulk and surface properties of garnet solid electrolytes with Li using X-ray photoelectron spectroscopy and electrochemical impedance spectroscopy. Among all of the garnets studied, Ba and Ta codoped Li 7 La 2.75 Ba 0.25 Zr 1.75 Ta 0.25 O 12 showed better chemical stability against Li with an area specific resistance (ASR) of ∼33 Ω cm 2 and a critical current density of 0.5 mA cm –2 at 25 °C without any surface coating. At −30 and 50 °C, the cell can cycle up to 50 times with almost negligible voltage fluctuations. This work illustrates that doping could trigger ion-/electron-transport properties and improve the chemical stability of the garnet structure for ASSLMBs.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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; both teacher heads agree on what is shown here.
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".