Reliable lateral and vertical manipulations of a single Cu adatom on a Cu(111) surface with multi-atom apex tip: semiempirical and first-principles simulations
Bibliographic record
Abstract
We study the reliability of the lateral manipulation of a single Cu adatom on a Cu(111) surface with single-atom, dimer and trimer apex tips using both semiempirical and first-principles simulations. The dependence of the manipulation reliability on tip height is investigated. For the single-atom apex tip the manipulation reliability increases monotonically with decreasing tip height. For the dimer and trimer apex tips the manipulation reliability is greatly improved compared to that for the single-atom apex tip over a certain tip-height range. Two kinds of mechanism are found responsible for this improvement. One is the so-called enhanced interaction mechanism in which the lateral tip-adatom interaction in the manipulation direction is improved. The other is the suspended atom mechanism in which the relative lateral trapping ability of the tip is improved due to the strong vertical attraction of the tip on the adatom. Both mechanisms occur in the manipulations with the trimer apex tip, while in those with the dimer apex tip only the former is effective. Moreover, we present a method to realize reversible vertical manipulation of a single atom on a Cu(111) surface with the trimer apex tip, based on its strong vertical and lateral attraction on the adatom.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".