Density Functional Theory Calculations Revealing Metal‐like Band Structures for Ultrathin Germanium (111) and (211) Surface Layers
Bibliographic record
Abstract
To find out if germanium possesses facet-dependent electrical-conductivity properties, surface-state density functional theory (DFT) calculations were performed on one to six layers of germanium (100), (110), (111), and (211) planes. Tunable Ge(100) and Ge(110) planes always present the same semiconducting band structure with a band gap of 0.67 eV expected of bulk germanium. In contrast, one, two, four, and five layers of Ge(111) and Ge(211) plane models show metal-like band structures with continuous density of states (DOS) throughout the entire band. For three and six layers of Ge(111) and Ge(211) plane models, the normal semiconducting band structure was obtained. The plane layers with metal-like band structures also show Ge-Ge bond-length deviations and bond distortions, as well as significantly different 4s and 4p frontier-orbital electron counts and relative percentages integrated over the valence and conduction bands from those of the semiconducting state. These differences should contribute to strikingly dissimilar band structures. The calculation results suggest the observation of facet-dependent electrical-conductivity properties of germanium materials; when making transistors from germanium, the facet effects with shrinking dimensions approaching 3 nm may also need to be considered.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.004 | 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".