High-temperature Fe oxidation coupled with redistribution of framework cations in lobanovite, K<sub>2</sub>Na(Fe<sup>2+</sup><sub>4</sub>Mg<sub>2</sub>Na)Ti<sub>2</sub>(Si<sub>4</sub>O<sub>12</sub>)<sub>2</sub>O<sub>2</sub>(OH)<sub>4</sub>– the first titanosilicate case
Bibliographic record
Abstract
The high-temperature (HT) behaviour of lobanovite, K2Na(Fe2+4Mg2Na)Ti2(Si4O12)2O2(OH)4, was studied usingin situpowder X-ray diffraction in the temperature range 25–1000°C andex situsingle-crystal X-ray diffraction of 17 crystals quenched from different temperatures. HT iron oxidation associated with dehydroxylation starts at 450°C, similar to other ferrous-hydroxy-rich heterophyllosilicates such as astrophyllite and bafertisite. A prominent feature of lobanovite HT crystal chemistry is the redistribution of Fe and Mg+Mn cations over theM(2),M(3),M(4) sites of the octahedral (O) layer that accompanies iron oxidation and dehydroxylation. This HT redistribution of cations has not been observed in titanosilicates until now, and seems to be triggered by the need to maintain bond strengths at the apical oxygen atom of the TiO5pyramid in the heteropolyhedral (H) layer during oxidation–dehydroxylation. Comparison of the HT behaviour of lobanovite with five-coordinated Ti and astrophyllite with six-coordinated Ti shows that the geometry of the Ti polyhedron plays a key role in the HT behaviour of heterophyllosilicates. The thermal expansion, geometrical changes and redistribution of site occupancies which occur in lobanovite under increasing temperature are reported. A brief discussion is given of minerals in which the cation ordering (usually for Fe and Mg) occurs together with iron oxidation–dehydroxylation at elevated temperatures: micas, amphiboles and tourmalines. Now this list is expanded by the inclusion of titanosilicate minerals.
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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) | 0.001 | 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".