Role of Strong Electronic Correlations in the Metal-To-Insulator Transition in Disordered<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:msub><mml:mi>LiAl</mml:mi><mml:mi>y</mml:mi></mml:msub><mml:msub><mml:mi>Ti</mml:mi><mml:mrow><mml:mn>2</mml:mn><mml:mo>−</mml:mo><mml:mi>y</mml:mi></mml:mrow></mml:msub><mml:msub><mml:mi mathvariant="normal">O</mml:mi><mml:mn>4</mml:mn></mml:msub></mml:math>
Bibliographic record
Abstract
The compound LiAlyTi2-yO4 undergoes a metal-to-insulator transition for yc approximately 0.33. It is known that disorder alone is insufficient to explain this transition; e.g., a quantum site percolation model predicts yc approximately 0.8. We have included (Hubbard) electronic interactions into a model of this compound, using a real-space Hartree-Fock approach that achieves self-consistency at every site, and have found that for a Hubbard energy equal to 1.5 times the non-interacting bandwidth one obtains yc approximately 0.3. Further, with increasing Hubbard energy we find an Altshuler-Aronov suppression of the density of states, deltaN(epsilon) approximately square root /epsilon-epsilonF/, that reduces the density of states at the Fermi energy to zero at the critical Hubbard interaction. Using this ratio of correlation to hopping energy one is led to a prediction of the near-neighbor superexchange (J/t approximately 1/3) which is similar to that for the cuprate superconductors.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.005 |
| Meta-epidemiology (broad) | 0.001 | 0.005 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.322 | 0.004 |
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; both teacher heads agree on what is shown here.
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".