SCANNING TUNNELING MICROSCOPY MANIPULATION OF COMPLEX ORGANIC MOLECULES ON SOLID SURFACES
Bibliographic record
Abstract
Organic molecules adsorbed on solid surfaces display a fascinating variety of new physical and chemical phenomena ranging from self-assembly and molecular recognition to nonlinear optical properties and current rectification. Both the fundamental interest in these systems and the promise of technological applications have motivated a strong research effort in understanding and controlling these properties. Scanning tunneling microscopy (STM) and, in particular, its ability to manipulate individual adsorbed molecules, has become a powerful tool for studying the adsorption geometry and the conformation and dynamics of single molecules and molecular aggregates. Here we review selected case studies demonstrating the enormous capabilities of STM manipulations to explore basic physiochemical properties of adsorbed molecules. In particular, we emphasize the role of STM manipulations in studying the coupling between the multiple degrees of freedom of adsorbed molecules, the phenomenon of molecular molding, and the possibility of creating and breaking individual chemical bonds in a controlled manner, i.e., the concept of single-molecule chemistry.
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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".