Transient adhesion and conductance phenomena in initial nanoscale mechanical contacts between dissimilar metals
Bibliographic record
Abstract
We report on transient adhesion and conductance phenomena associated with tip wetting in mechanical contacts produced by the indentation of a clean W(111) tip into a Au(111) surface. A combination of atomic force microscopy and scanning tunneling microscopy was used to carry out indentation and to image residual impressions in ultra-high vacuum. The ∼7 nm radii tips used in these experiments were prepared and characterized by field ion microscopy in the same instrument. The very first indentations of the tungsten tips show larger conductance and pull-off adhesive forces than subsequent indentations. After ∼30 indentations to a depth of ∼1.7 nm, the maximum conductance and adhesion forces reach steady state values approximately 12 × and 6 × smaller than their initial value. Indentation of W(111) tips into Cu(100) was also performed to investigate the universality of tip wetting phenomena with a different substrate. We propose a model from contact mechanics considerations which quantitatively reproduces the observed decay rate of the conductance and adhesion drops with a 1/e decay constant of 9-14 indentation cycles. The results show that the surface composition of an indenting tip plays an important role in defining the mechanical and electrical properties of indentation contacts.
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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) | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".