Bibliographic record
Abstract
Quantum spin liquids have been drawing much attention in recent years as a platform to develop future quantum technologies, such as topological quantum computing. In particular, Kitaev’s honeycomb model has provided a blueprint to realize a quantum spin liquid that has Majorana fermions as its elementary excitation. While numerous theoretical studies have shown intriguing properties of quantum spin liquids, an experimental realization remains elusive. The recent observation of the quantized thermal Hall effect in α-RuCl3 has brought us tantalizingly close to an experimental realization of Kitaev quantum spin liquids. However, various groups report conflicting results, indicating that the Kitaev quantum spin liquid phase might be very fragile and its properties strongly depend on the sample. Here, we present a short overview of the rise of α-RuCl3 as a prime candidate material for realizing Kitaev quantum spin liquids. There are already many excellent review papers on this topic, so the emphasis will be on the materials aspect, comparing different crystal growth methods and crystal morphologies. We also discuss current research attempts to find other candidate materials to realize Kitaev quantum spin liquids, mostly focused on 3d transition-metal compounds, such as transition-metal halides and layered cobalt compounds.
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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) | 0.002 | 0.001 |
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".