Identifying crystal structures and chemical reactions at the interface of stanene on Bi2Te3
Bibliographic record
Abstract
Synthesizing monolayers and heterostructures is an enabling approach to extract new physical phenomena from bulk materials. Among the structures amenable to this approach is stanene, which is a monolayer of tin, similar to graphene, and has been predicted to host one-dimensional topological states at its edges. Stanene can be tuned by decorating with different adatoms, which makes it a promising platform on which to engineer topological devices. Here, we deposit Sn on Bi2Te3 and characterize the growth using anomalous synchrotron x-ray scattering and x-ray photoelectron spectroscopy (XPS). X-ray diffraction data reveal the formation of epitaxial Sn-based structures, along with penetration of Sn into the Bi2Te3, with Sn intercalating between the upper 10 Bi2Te3 quintuple layers. Additionally, XPS data show deposited Sn reacting to form SnTe and Bi at the Bi2Te3 surface. The calculated heat of reaction for Sn and Bi2Te3 is consistent with an exothermic reaction to SnTe and Bi. Using thermodynamic calculations as a guide, we identify several candidate substrates that can stabilize the stanene phase.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".