Atomic‐Scale Manipulation and In Situ Characterization with Scanning Tunneling Microscopy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Scanning tunneling microscope (STM) has presented a revolutionary methodology to nanoscience and nanotechnology. It enables imaging of the topography of surfaces, mapping the distribution of electronic density of states, and manipulating individual atoms and molecules, all at atomic resolutions. In particular, atom manipulation capability has evolved from fabricating individual nanostructures toward the scalable production of the atomic‐sized devices bottom‐up. The combination of precision synthesis and in situ characterization has enabled direct visualization of many quantum phenomena and fast proof‐of‐principle testing of quantum device functions with immediate feedback to guide improved synthesis. Several representative examples are reviewed to demonstrate the recent development of atomic‐scale manipulation, focusing on progress that addresses quantum properties by design in several technologically relevant materials systems. Integration of several atomically precisely controlled probes in a multiprobe STM system vastly extends the capability of in situ characterization to a new dimension where the charge and spin transport behaviors can be examined from mesoscopic to atomic length scale. The automation of atomic‐scale manipulation and the integration with well‐established lithographic processes further push this bottom‐up approach to a new level that combines reproducible fabrication, extraordinary programmability, and the ability to produce large‐scale arrays of quantum structures.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it