Alkali-Induced Phase Transition to β-Spodumene along the LiAlSi2O6-LiAlSi4O10 Join
Bibliographic record
Abstract
Due to the refractory nature of α-spodumene (LiAlSi2O6) and petalite (LiAlSi4O10), two major lithium minerals, conventional lithium recovery processes involve a high-temperature pre-treatment (>1000 °C) to induce a phase transition to tetragonal β-spodumene, an open structure allowing easier access to lithium through ion exchange. Considering that these high temperatures are not dictated by thermodynamics but rather sluggish kinetics, the study investigates the mechanisms enhancing the rate of transformation to β-spodumene at lower temperatures while minimizing the growth of metastable hexagonal β-quartz typically observed at the onset of the conversion. The heat treatment of natural α-spodumene revealed that rapid growth of β-spodumene veinlets is achieved at ≤600 °C by activation of alkali-rich fluid inclusions, through a dissolution–recrystallization process. For petalite, the mechanism of the phase transition, initiated at ≈750 °C is a solid-state transformation keeping crystallographic coincidence with the mineral host. Synthetic growth experiments along the LiAlSi2O6-LiAlSi4O10 join indicate a compositional dependence on the resulting β-phase structure, where minor sodium doping strongly favors β-spodumene, as the tetrahedral framework of β-quartz does not allow the extent of deformation to accommodate the larger alkali. These findings open opportunities for energy-efficient lithium recovery pathways where the phase transition and ion exchange can be achieved simultaneously without a high-temperature pre-treatment.
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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".