Pressure-Induced Stabilization of 3D Hyperhoneycomb Li <sub>2</sub> (Sn <sub> 1– <i>x</i> </sub> Ru <sub> <i>x</i> </sub> )O <sub>3</sub>
Bibliographic record
Abstract
Metal-ordered rock-salt oxides (e.g., AMO 2, A 2 MO 3, A 3 MO 4 ) exhibit diverse functionalities arising from cation ordering, yet their structural evolution is difficult to predict due to the lack of systematic design principles. For A 2 MO 3 compounds, although two-dimensional (2D) honeycomb structures have been widely explored, the three-dimensional (3D) hyperhoneycomb phase is still rare, despite its appeal as a battery cathode and as a Kitaev spin-liquid candidate. Here, we report pressure-induced phase transitions of Li 2 SnO 3, from the ambient-pressure honeycomb phase to a hyperhoneycomb phase at 3 GPa, and subsequently to a Li 2 PbO 3 -type phase at 8 GPa. By integrating analyses of octahedral connectivity and Madelung energy, together with machine-learning-assisted molecular dynamics simulations, we established the thermodynamic landscape governing these transitions. Specifically, the hyperhoneycomb structure becomes competitive with the honeycomb structure under pressure and is stabilized by elevated temperatures, whereas the Li 2 PbO 3 -type structure stabilizes only at high pressures. This framework rationalizes the entire sequence of observed pressure-induced phase transitions. Furthermore, the hyperhoneycomb phase is accessible across the entire solid solution of Li 2 (Sn 1– x Ru x )O 3, although Ru-rich compositions require higher pressure. Remarkably, the phase-pure hyperhoneycomb x = 0.75 exhibits complete electrochemical lithium deintercalation. Given the prevalence of 2D oxides under ambient conditions, designing hyperhoneycomb phases via pressure highlights a hidden yet attractive chemical space of 3D polymorphs, offering new chemical landscapes and exotic functionalities.
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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) | 0.002 | 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".