Mixing, Domains, and Fast Li-Ion Dynamics in Ternary Li–Sb–Bi Battery Anode Alloys
Bibliographic record
Abstract
Both antimony and bismuth can alloy with up to three molar equivalents of lithium and are therefore attractive candidates for replacing graphite in Li-ion battery anodes. Li 3 Sb and Li 3 Bi have the same cubic structure ( Fm 3̅ m ), but the ternary Li–Sb–Bi system has not been studied. We synthesized Li 3 (Sb x Bi 1– x ) with different Sb mole fractions at room temperature by ball milling. These ternary alloys all have cubic crystal structures, as determined by X-ray diffraction (XRD), but show a tendency toward phase segregation for x = 0.25 and 0.50. For x = 0.25, the lattice parameter presents a clear positive deviation from Vegard’s law in XRD, while for x = 0.50, XRD reveals two phases after milling, with the Bi-rich minority phase diminishing after thermal annealing. Solid-state nuclear magnetic resonance spectroscopy provides evidence for a Sb-enriched environment around the Li atoms for Li 3 Sb 0.25 Bi 0.75, and nuclear spin–lattice relaxation measurements of the binary and ternary alloy phases point to low activation energies and rapid Li-ion diffusion in Li 3 Bi.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".