High Throughput Studies of Li-La-Zr-O Garnet Solid Electrolytes
Bibliographic record
Abstract
Development of next-generation Li-ion batteries has increasingly focused on all-solid batteries employing either ceramic, polymer, or glass electrolytes in order to address shortcomings in currently commercialized liquid electrolyte Li-ion batteries including safety, limited lifetime, and lower energy densities resulting from instability with respect to Li metal anodes. [1] Lithium lanthanum zirconium oxide (LLZO) is a leading candidate for solid Li-batteries due to its high Li-ion conductivity, stability in air and against Li metal, and compatibility with high-voltage cathodes. [2] , [3] Despite significant progress being made, our understanding of LLZO is limited by the relatively small number of compositions which have been studied; especially considering the leading contender is a pseudo-quaternary oxide (Ga-doped LLZO) and many studies are now utilizing multiple dopants. [4] Herein, we have applied a high-throughput methodology for synthesizing, characterizing, and testing sets of 64 LLZO electrolytes at the mg-scale. We employ a citrate sol-gel synthesis method whereby reagent solutions are dispensed across a well-plate to give a composition gradient. After drying the samples and burning off the citrates, the resulting powders are pressed into pellets using a custom-made 64-pellet die and the pellets are sintered at the desired temperature. The high-throughput characterization techniques utilized include powder X-ray diffraction, electrochemical impedance spectrometry and electrochemical cycling in order to test electrolyte stability; with each method performed on up to 64 samples simultaneously. Using our methodology, we have studied over 700 samples to produce a full phase stability diagram for the Li-La-Zr-O pseudoternary system. We find that within the Li-La-Zr-O system, there is significant solubility of Li into the La2Zr2O7 pyrochlore structure commonly found as an impurity in LLZO synthesis due to lithium loss. We also find that LLZO appears as both tetragonal and cubic forms throughout the system, with the cubic LLZO appearing in an extremely restricted region that is difficult to access as pure phase due to lithium loss, while excess lithium leads to the tetragonal LLZO. Li conductivity measurements show that both cubic and tetragonal undoped LLZO have similar bulk conductivities, but there is only a limited region near the formal Li7La3Zr2O12 composition where grain boundary conductivity is high. Our methodology is also applied to a comprehensive doping study where over 40 different dopants are evaluated and promising dopants are tested in co-doped compositions. [1] D. Aurbach et al., Electrochimica Acta 2004, 50, 247-254. [2] Q. Liu, et al., J. Power Sources 2018, 389, 120-134. [3] T. Thompson, et al., ACS Energy Letters 2017, 2, 462-468. [4] F. Zheng, et al., J. Power Sources 2018, 389, 198-213.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".