Elucidating the Surface Properties of Sr<sub>3</sub>PbO Inverse‐Perovskite Topological Insulator: A First‐Principles Study
Bibliographic record
Abstract
The emergence of robust surface electronic states in topological insulators such as bulk Sr3PbO inverse‐perovskite makes them suitable candidates for spintronic devices and solid‐state quantum computers. Herein, the atomic structure, surface energetics, and electronic properties of Sr3PbO inverse‐perovskite Sr2O (SO)‐terminated and SrPb‐terminated (001) surfaces are examined using density functional theory. A comparison of the computed structural properties of SO‐termianted and SrPb‐terminated (001) surfaces reveals maximum surface rumpling and changes in interlayer distances for the SrPb‐terminated surface of Sr3PbO. However, the calculated surface energies indicate that both SO‐termianted and SrPb‐terminated (001) surfaces of Sr3PbO are energetically feasible, indicating that these surfaces can coexist in a polycrystalline sample of this material. Due to the presence of Pb in Sr3PbO, a comprehensive examination of the electronic structure of bulk and supercell slab structures of Sr3PbO by taking spin–orbit coupling effects into consideration is conducted. Noninsulating nature of electronic structure for the two possible (001) terminations of Sr3PbO is found. The domination of Pb‐6p states at the Fermi energy and the hole screening observed at the SrPb‐terminated surface of Sr3PbO support the p‐type nature observed in the experiment.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".