Toward Understanding the Reactivity of Garnet-Type Solid Electrolytes with H<sub>2</sub>O/CO<sub>2</sub> in a Glovebox Using X-ray Photoelectron Spectroscopy and Electrochemical Methods
Bibliographic record
Abstract
Chemical stability of garnet-type lithium ion conductors is one of the critical issues in their application in all-solid-state batteries. Here, we conducted quantitative analysis of impurity layers on the garnet-type solid electrolytes, Li6.5La3–xAExZr1.5–xTa0.5+xO12 (x = 0 and 0.1; AE = Ca, Sr, and Ba), by means of X-ray photoelectron spectroscopy (XPS) and electrochemical methods. Two complimentary XPS techniques were employed: (i) background analyses by Tougaard’s method and (ii) relative intensity analyses of La 3d/La 4d spectra to determine the surface chemical composition. XPS revealed that even after cleaning by annealing and polishing, the surface is covered by LiOH- and Li2CO3-based compounds with a thickness of 4–6 nm within 30 min as a result of the reaction with traces of H2O (<0.5 ppm) and CO2 (<5 ppm) in an Ar-filled glovebox. The sensitivity to H2O and CO2 depends on the basicity of dopants. Ba-doped solid electrolytes exhibited the thickest impurity layers compared to Sr- and Ca-doped compounds. A surface cleaning process, consisting of annealing and polishing, effectively reduces the charge-transfer resistance to 10–15 Ω cm2 because of negligible impurity layers. Highest short-circuit tolerance is obtained for a 700 °C annealed specimen (critical current density: 0.5 mA cm–2), which is possibly due to the strengthened grain boundaries by Li2CO3 among grains around its melting point.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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".