Enhanced performance in contact mode atomic force microscopy
Bibliographic record
Abstract
Atomic force microscopy (AFM) had and continues to have a substantial impact on nanosciences and technologies. However, the low scanning speed continues to be one of the obstacles that impede the widespread adoption of AFM. This paper presents a solution to control system design issues for constant force contact AFM operation to enhance the performance of AFM systems with respect to scanning speed and image resolution. The purpose of the controller is to maintain a constant slope at the free end of the AFM cantilever through suitable displacement of the base end of the cantilever. Given that the sample surface profile is not known a priori, the difficulty in the controller design lies in attempting to track an unknown and time-varying reference signal, representing the unknown surface profile. To overcome this problem, it is proposed in this paper to use an adaptive regulator design approach. The regulator design approach is based on two steps. The first step involves using the Q-parameterization of stabilizing controllers to construct a set of parameterized stabilizing controllers for the system under consideration. The second step involves tuning the Q parameter in the expression of stabilizing controller so that the controller converges to the desired controllers needed to achieve regulation. The proposed control strategy makes it possible to use small contact forces and high scanning speeds, hence improving the performance of contact mode AFM systems.
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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".