Bibliographic record
Abstract
The quantitative interatomic force measurements open a new pathway to materials characterization, surface science, and chemistry by elucidating the tip-sample interaction forces. Atomic force microscopy is the ideal platform to gauge interatomic forces between the tip and the sample. For such quantitative measurements, either the oscillation frequency or the oscillation amplitude and the phase of a vibrating cantilever are recorded as a function of the tip-sample separation. These experimental quantities are subsequently converted into the tip-sample interaction force, which can be compared with interatomic force laws to reveal the governing physical phenomena. Recently, it has been shown that the most commonly applied mathematical conversion techniques may suffer a significant deviation from the actual tip-sample interaction forces. To avoid the assessment of unphysical interatomic forces, the use of either very small (i.e., a few picometers) or very large oscillation amplitudes (i.e., a few nanometers) has been proposed. However, the use of marginal oscillation amplitudes gives rise to another problem as it lacks the feasibility due to the adverse signal-to-noise ratios. Here, we show a new mathematical conversion principle that confronts interatomic force measurements while preserving the oscillation amplitude within the experimentally achievable and favorable limits, i.e., tens of picometers. Our theoretical calculations and complementary experimental results demonstrate that the proposed technique has three major advantages over existing methodologies: (I) eliminating mathematical instabilities of the reconstruction of tip-sample interaction force, (II) enabling accurate conversion deep into the repulsive regime of tip-sample interaction force, and (III) being robust to the uncertainty of the oscillation amplitude and the measurement noise. Due to these advantages, we anticipate that our methodology will be the nucleus of a reliable evaluation of material properties with a more accurate measurement of tip-sample interaction forces.
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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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".