Atomic Layer Deposited Lithium Silicates as Solid-State Electrolytes for All-Solid-State Batteries
Bibliographic record
Abstract
Development of solid-state electrolyte (SSE) thin films is a key toward the fabrication of all-solid-state batteries (ASSBs). However, it is challenging for conventional deposition techniques to deposit uniform and conformal SSE thin films in a well-controlled fashion. In this study, atomic layer deposition (ALD) was used to fabricate lithium silicate thin films as a potential SSE for ASSBs. Lithium silicates thin films were deposited by combining ALD Li 2 O and SiO 2 subcycles using lithium tert -butoxide, tetraethylorthosilane, and H 2 O as precursors. Uniform and self-limiting growth was achieved at temperatures between 225 and 300 °C. X-ray absorption spectroscopy analysis disclosed that the as-deposited lithium silicates were composed of SiO 4 tetrahedron structure and lithium oxide as the network modifier. X-ray photoelectron spectroscopy confirmed the chemical states of Li in the thin films were the same with that in standard lithium silicate. With one to one subcycle of Li 2 O and SiO 2 the thin films had a composition close to Li 4 SiO 4 whereas one more subcycle of Li 2 O delivered a higher lithium content. The lithium silicate thin film prepared at 250 °C exhibited an ionic conductivity of 1.45× 10 –6 S cm –1 at 373 K. The high ionic conductivity of lithium silicate was due to the higher lithium concentration and lower activation energy.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".