Study the Interface of Cathode Material and Li-La-Zr-O Thin Film Prepared at Low Temperature for All Solid State Li Battery
Bibliographic record
Abstract
Switching from an organic polymer-based Li ion electrolyte to a ceramic Li ion electrolyte is expected to allow for the higher energy density, improve the safety and cycle lifetime. These, all solid state Li ion batteries can also be miniaturized, which will streamline the packing design. Among studied Li ion conductive solid electrolyte (1, 2) garnet family have recently gained lots of attention due to the high ionic conductivity and electrochemical stability at ambient temperature. Garnet-like structure, Li7La3Zr2O12 (LLZO) has shown comparable Li ion conductivity with the current Li ion electrolytes (3). However, the reported ionic conductivity of a thin film LLZO was three orders of magnitude lower compared to bulk phase (4). The main goal of the current research is to develop thin film solid electrolyte on the LiCoO2 electrode and investigate the interface. For this purpose, LLZO was fabricated using a liquid precursor technique. The Li-La-Zr nitrate solution was coated on the top surface of the LiCoO2 substrate for several times until the appropriate thickness (300 nm – 1 µm) is obtained. After each step of coating, the deposited precursor is dried and decomposed at 450 °C. Figure 1 shows cross section image of crack-free, flat, dense and homogenous solid electrolyte layer deposited on the surface of the LiCoO2. X-ray photoelectron spectroscopy (XPS) coupled with ion etching is used to understand the interface composition and thickness. Electrochemical impedance spectroscopy (EIS) was used to analyze and understand the electrolyte and interfacial resistance. References 1. S. Teng, J. Tan and A. Tiwari, Current Opinion in Solid State and Materials Science, 18, 29 (2014). 2. V. Thangadurai, D. Pinzaru, S. Narayanan and A. K. Baral, The Journal of Physical Chemistry Letters, 6, 292 (2015). 3. R. Murugan, V. Thangadurai and W. Weppner, Angewandte Chemie International Edition, 46, 7778 (2007). 4. K. Tadanaga, H. Egawa, A. Hayashi, M. Tatsumisago, J. Mosa, M. Aparicio and A. Duran, Journal of Power Sources, 273, 844 (2015). Figure 1
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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) | 0.000 | 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) | 0.001 | 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 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".