Fabrication and Testing of Bulk-Type Solid State Batteries Based on a Garnet Oxide Electrolyte
Bibliographic record
Abstract
Li-ion batteries have become the preferred energy storage technology for automotive traction applications. Li-ion batteries have several advantages over competing technologies, including higher energy and power density. However, Li-ion batteries do not have sufficient energy density to provide the long (~500 mile) range that customers are accustomed to in a reasonable packaging volume. In addition, the flammable liquid electrolyte in Li-ion batteries presents safety concerns that must be carefully managed. Potential high-energy replacements for current Li-ion batteries are Li-S, Li-air and solid state batteries (SSB). Among these technologies, SSBs are the one technology offering both higher energy density and a significant reduction in safety risks over Li-ion batteries. In this study, the performance of a bulk-type SSB was evaluated. This cell was fabricated using lithium metal as anode, lithium lanthanum zirconium oxide (LLZO) as a solid electrolyte and LiCoO2 as cathode. LLZO solid electrolyte was prepared using a solid state synthesis method. In this method, precursors were mixed well and calcined. Calcined LLZO was pressed into thick pellets, sintered and then sliced into thin (300 µm to 400 µm) sheets for cell testing. The measured ionic conductivity of these sheets was ~3 x10-4 S/cm. Composite cathode layers were fabricated by coating one side of several LLZO sheets with slurry containing LLZO and LiCoO2, which was dried and then sintered at various temperatures. After sintering, the other side of the LLZO sheet was attached to a lithium metal (anode) to form a solid state cell. The impedance contributions from the solid electrolyte, the anode/electrolyte interface and the cathode/electrolyte interface was determined for each cell using electrochemical impedance spectroscopy (EIS). EIS data showed that the main contribution to the cell impedances resulted from the cathode/electrolyte interfaces. Further performance and characterization studies are ongoing and its results will be presented at the meeting.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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; a candidate call from one source (direct Gemma or distilled Codex), 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".