Striped magnetic ground state on an ideal <i>S</i> = 2 Kagomé lattice
Bibliographic record
Abstract
We have used representational symmetry analysis of neutron powder diffraction data to determine the magnetic ground state of Fe4Si2Sn7O16. We recently reported a long-range antiferromagnetic (AFM) Nel ordering transition in this compound at TN = 3.0 K, based on magnetization measurements. [1] The only magnetic ions present are layers of highspin Fe2+ (d6, S = 2) arranged on a perfect kagom lattice (trigonal space group P-3m1). [2] Below TN = 3.0 K, the spins on 2/3 of these magnetic ions order into canted antiferromagnetic chains, separated by the remaining 1/3 which are geometrically frustrated and show no long-range ordered down to at least T = 0.1 K. Moessbauer spectroscopy shows that there is no static order on the latter 1/3 of the magnetic ions -i.e., they are in a liquid-like rather than a frozen statedown to at least 1.65 K. A heavily Mn-doped sample Fe1.45Mn2.55Si2Sn7O16 has the same ground state. Although the magnetic propagation vector k = (0, 1/2, 1/2) breaks hexagonal symmetry, we see no evidence for magnetostriction in the form of a lattice distortion within the resolution of our data. To the best of our knowledge, this type of magnetic order on a kagom lattice has no precedent experimentally and has not been explicitly predicted theoretically. We will discuss the relationship between our experimental result and a number of theoretical models that predict symmetry breaking ground states for perfect kagom lattices.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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 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".