Rationalized approach to the determination of contact point in force–distance curves: Application to polymer brushes in salt solutions and in water
Bibliographic record
Abstract
In this work, we present two methods to determine the contact point in force-distance curves obtained with the atomic force microscope. These procedures are compared with the typical determination of contact point by a visual assessment of the data. One method, based on the assumption that the sample shows linear elastic behavior, provides results similar to those obtained by a visual assessment of the data, and will be suitable for determining the contact point in cases where ionic repulsion is not significant. The second method is based on a series of measurements in which the sample deformation is measured at increasing values of applied load; the contact point is determined by extrapolation to zero load. Because this method is based on extrapolation of measurements made in the contact regime, it is not subject to long-range repulsion. It is thus suitable for the analyses of the contact point even in cases where ionic repulsions will affect the point at which individual force curves deviate from the baseline or zero-force regime. The methods described here are demonstrated with a glycopolymer brush compressed with a colloidal silica particle on the tip of the AFM cantilever.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".