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Record W4385421458 · doi:10.3390/cryst13081182

Alkali-Induced Phase Transition to β-Spodumene along the LiAlSi2O6-LiAlSi4O10 Join

2023· article· en· W4385421458 on OpenAlexafffund
Yves Thibault, Joanne Gamage McEvoy

Bibliographic record

VenueCrystals · 2023
Typearticle
Languageen
FieldEngineering
TopicExtraction and Separation Processes
Canadian institutionsNatural Resources Canada
FundersUniversity of British Columbia
KeywordsSpodumeneAlkali metalLithium (medication)Materials scienceMetastabilityDissolutionPhase (matter)Phase transitionCrystallographyChemistryMineralogyChemical engineeringThermodynamicsPhysical chemistryMetallurgyCeramic

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.036
GPT teacher head0.307
Teacher spread0.271 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2023
Admission routes2
Has abstractyes

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