Imaging the microstructure of lithium and sodium metal in anode-free solid-state batteries using electron backscatter diffraction
Bibliographic record
Abstract
Abstract ‘Anode-free’ or, more fittingly, metal reservoir-free cells could drastically improve current solid-state battery technology by achieving higher energy density, improving safety and simplifying manufacturing. Various strategies have been reported so far to control the morphology of electrodeposited alkali metal films to be homogeneous and dense, but until now, the microstructure of electrodeposited alkali metal is unknown, and a suitable characterization route is yet to be identified. Here we establish a reproducible protocol for characterizing the size and orientation of metal grains in differently processed lithium and sodium samples by a combination of focused ion beam and electron backscatter diffraction. Electrodeposited films at Cu|Li 6.5 Ta 0.5 La 3 Zr 1.5 O 12 , steel|Li 6 PS 5 Cl and Al|Na 3.4 Zr 2 Si 2.4 P 0.6 O 12 interfaces were characterized. The analyses show large grain sizes (>100 µm) within these films and a preferential orientation of grain boundaries. Furthermore, metal growth and dissolution were investigated using in situ electron backscatter diffraction, showing a dynamic grain coarsening during electrodeposition and pore formation within grains during dissolution. Our methodology and results deepen the research field for the improvement of solid-state battery performance through a characterization of the alkali metal microstructure.
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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) | 0.000 | 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) | 0.000 | 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".