Interplay between lattice distortion and spin-orbit coupling in double perovskites
Bibliographic record
Abstract
We develop anisotropic pseudo-spin antiferromagnetic Heisenberg models for monoclinically distorted double perovskites. We focus on these A${}_{2}$BB${}^{\ensuremath{'}}$O${}_{6}$ materials that have magnetic moments on the $4d$ or $5d$ transition metal B${}^{\ensuremath{'}}$ ions, which form a face-centered cubic lattice. In these models, we consider local $z$-axis distortion of B${}^{\ensuremath{'}}$-O octahedra, affecting relative occupancy of ${t}_{2g}$ orbitals, along with geometric effects of the monoclinic distortion and spin-orbit coupling. The resulting pseudo-spin-$1/2$ models are solved in the saddle-point limit of the Sp($N$) generalization of the Heisenberg model. The spin $S$ in the SU(2) case generalizes as a parameter $\ensuremath{\kappa}$ controlling quantum fluctuation in the Sp($N$) case. We consider two different models that may be appropriate for these systems. In particular, using Heisenberg exchange parameters for La${}_{2}$LiMoO${}_{6}$ from a spin-dimer calculation, we conclude that this pseudo-spin-$1/2$ system may order, but will be very close to a disordered spin liquid state.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".