Scanning tunneling microscopy tip-assisted modification of Ti(IV) dithiothreitol self-assembled monolayers on Au(111): restructuring of the gold surface
Bibliographic record
Abstract
Au(111) surfaces modified by exposure to a dilute solution of a Ti(IV)/dithiothreitol ligand to metal charge transfer complex (Ti(DTT)2) show a remarkable response to continuous scanning by scanning tunneling microscopy (STM). Vacancy islands on the gold surface, which are formed during the self-assembly of the molecular overlayer, coarsen and even merge during STM scanning at negative sample bias. In certain instances, the vacancy islands even line up to form parallel nanostructures. We believe the effect is due to mechanical interactions between tip and sample, which is enhanced by electrostatic effects. The Ti(DTT)2 complex is anchored to the gold surface via Au−S bonds, but due to the fact that there are multiple thiol groups, there may be “uncoordinated” thiols left “dangling”. The tip-induced modification involves the interaction of the tip with these “dangling” sulfurs, which in turn causes movement of single complex molecules with the attached sulfur-bonded gold. Under negative sample bias, the electric field weakens the binding between the sulfur-bonded gold atoms and the surrounding gold atoms in the surface allowing for the observed tip-induced dynamics. In contrast with the Ti(DTT)2 complex, a similar Ti(IV)/3-mercapto-1,2-propanediol complex (Ti(MPD)2) does not exhibit any tip-induced effects. In this case, there are no dangling sulfurs to interact with the STM tip. In addition, similarly prepared dithiothreitol, dithiothreitol titanium isopropoxide, and 3-mercapto-1,2-propanediol self-assembled monolayers (without dangling sulfurs) do not exhibit the tip-induced effect.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".