The Development of High-Throughput Methods in the Study of Solid State Li-Electrolytes
Bibliographic record
Abstract
High-throughput experimentation is a fast and efficient methodology for materials discovery, screening, and optimization. It has, therefore, garnered a lot of attention from battery researchers as a potential way to accelerate the development of next-generation Li-ion batteries and battery systems beyond Li-ion. However, its successful use in battery materials discovery has been extremely limited due to a variety of challenges including: (i) difficulties in synthesizing mg-scale samples that are comparable to bulk samples made by industrial methods, (ii) limited high-throughput characterization acting like a bottleneck even after high throughput synthesis is developed, and (iii) high cost of commercially available high-throughput instrumentation. Here, we develop high throughput techniques for solid-state electrolytes. First, a novel synthesis approach is used to make 64 mg-scale solid electrolytes simultaneously. The powder samples are prepared by a citrate sol-gel method using an automated dispensing system. These powders were formulated into sixty-four pellets using a home-made high-throughput pellet press die. The samples are then sintered at high temperature to yield the solid electrolytes. The proof of concept here is performed on the Li-La-Ti-O pseudo-ternary system that includes the perovskites Li 3x La 2/3-x TiO 3 , considered candidates for solid-state electrolytes for high energy lithium-ion batteries. Given that vacancies and other defects play an essential role in ionic conductivity, the screening of complete phase diagrams has the potential to reveal phases with optimized defect contents and thus yield improved solid electrolytes. We have therefore developed a high-throughput characterization suite for solid electrolytes. First, we use a high throughput X-ray diffractometer capable of producing Rietveld quality patterns for mg-scale samples in 10 min such that 64 patterns can be obtained in under 12 h. This system is readily used to produce structural phase diagrams in ternary or even quaternary systems. Next, a high throughput electrochemical impedance spectrometer is used to map the ionic conductivities onto the phase diagrams. Finally, high throughput electrochemistry is used to determine the stability window of the electrolytes. All aspects of this workflow are demonstrated on the Li-La-Ti-O system. This now permits the synthesis and full characterization of approximately 192 compositions per week with one researcher only. This approach is well suited to determine the structure-property relations in complex composition spaces. The complete ternary Li-La-Ti phase diagram synthesized at 1150 °C with slow cooling was determined and will be presented in detail. The total (ionic + electronic) conductivity of the phase diagram was mapped by the electrochemical impedance spectroscopy. Quenching was performed to verify that transformations during slow cooling are moderate in this system. Consequences for the development of other solid electrolytes will also be discussed.
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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 | 0.010 | 0.003 |
| 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 | 0.001 | 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".