First‐principles prediction of fast migration channels of potassium ions in KAlSi<sub>3</sub>O<sub>8</sub> hollandite: Implications for high conductivity anomalies in subduction zones
Bibliographic record
Abstract
Abstract Materials sharing the hollandite structure were widely reported as fast ionic conductors. However, the ionic conductivity of KAlSi 3 O 8 hollandite (K‐hollandite), which can be formed during the subduction process, has not been investigated so far. Here first‐principles calculations are used to investigate the potassium ion (K + ) transport properties in K‐hollandite. The calculated K + migration barrier energy is 0.44 eV at a pressure of 10 GPa, an energy quite small to block the K + migration in K‐hollandite channels. The calculated ionic conductivity of K‐hollandite is highly anisotropic and depends on its concentration of K + vacancies. About 6% K + vacancies in K‐hollandite can lead to a higher conductivity compared to the conductivity of hydrated wadsleyite and ringwoodite in the mantle. K + vacancies being commonly found in many K‐hollandite samples with maximum vacancies over 30%, the formation of K‐hollandite during subduction of continental or alkali‐rich oceanic crust can contribute to the high conductivity anomalies observed in subduction zones.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".