Selective Synthesis of Large-Area Monolayer Tin Sulfide from Simple Substances
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Both tin monosulfide (SnS) and tin disulfide (SnS 2 ) are thermodynamically stable layered materials with the potential for spin-valleytronic devices and photodetectors. Notably, SnS, owing to its low symmetry, exhibits interesting properties such as ferroelectricity, shift-current, and a persistent spin helix state in the monolayer limit. Unlike SnS 2, however, creating large-area atomic-thickness crystals of SnS is challenging, owing to the enhanced interlayer interactions caused by lone pair electrons. Here, we demonstrate that p-type SnS can be selectively grown by varying the sulfur vapor concentration relative to tin using high-purity elemental precursors in a chemical vapor deposition setup. Based on that, we further show that monolayer SnS crystals, up to several tens of micrometers in lateral scale, can be obtained by controlled sublimation of bulk SnS crystals. These findings pave the way for device applications based on high-quality tin sulfide.
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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) | 0.001 | 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 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".