First-Principles Study of Ethylene on Ge(001)—Electronic Structures and STM Images
Bibliographic record
Abstract
By using the first-principles density functional theory, we calculate the partial charge densities and STM images for the intradimer di-σ and interdimer end-bridge adsorption configurations of ethylene on Ge(001). Our simulated STM images show the effects of ethylene adsorption and clarify that, although STM images and surface structures evolve as the adsorption sites of ethylene on Ge(001), the molecular orbitals of the bare Ge atoms always remain the dominating electronic states near the Fermi level. For the di-σ model, the display of such dominance in STM images is, however, damped by the preferred tunneling paths between the tip and the electronic states of ethylene due to their short tunneling distances. In comparison, the distance between the tip and the end-bridge bound C 2 H 4 molecules is not so short relative to the distance between the tip and the up-Ge atoms of the bare Ge−Ge dimer; hence, the dominance of bare up-Ge atoms can still be found in the STM images at low bias voltages. Our simulated STM results confirm that the di-σ and paired-end-bridge configurations are observable adsorption structures for C 2 H 4 on Ge(001). The comparisons of the STM images between Ge(001) and Si(001) reveal the distinction of their highest occupied surface states, which explains the differences in geometry and reactivity of adsorbates, including C 2 H 4 and O 2, on Ge(001) versus Si(001).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".