Monitoring and Mapping Imperfections in Silane-Based Self-Assembled Monolayers by Chemical Amplification
Bibliographic record
Abstract
This paper describes an innovative and simple technique for analyzing defects in silane-based self-assembled monolayers. The assembly of monolayers is a simple method for chemically modifying surfaces, which can be important for resisting chemical attack or adhesion of biomolecules. Measuring the molecular scale properties of monolayers and the reproducibility of their ability to uniformly modify a surface requires tools that provide limits of detection at the level of at least a few atoms per million with specificity to the top couple nanometers of the surface. To achieve this level of sensitivity a new technique is developed that combines spectroscopy and microscopy techniques (particularly atomic force microscopy) with chemical amplification of exposed silicon in self-assembled monolayers of silane molecules. This development is an important achievement for monitoring the quality of monolayers as a function of modifications to the method(s) used to deposit the silane molecules. Techniques presented here could be easily extended to assessing the molecular scale quality of other surface modifications.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".