Improved Single Molecule Force Spectroscopy Using Micromachined Cantilevers
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Bibliographic record
Abstract
Enhancing the short-term force precision of atomic force microscopy (AFM) while maintaining excellent long-term force stability would result in improved performance across multiple AFM modalities, including single molecule force spectroscopy (SMFS). SMFS is a powerful method to probe the nanometer-scale dynamics and energetics of biomolecules (DNA, RNA, and proteins). The folding and unfolding rates of such macromolecules are sensitive to sub-pN changes in force. Recently, we demonstrated sub-pN stability over a broad bandwidth (Δf = 0.01-16 Hz) by removing the gold coating from a 100 μm long cantilever. However, this stability came at the cost of increased short-term force noise, decreased temporal response, and poor sensitivity. Here, we avoided these compromises while retaining excellent force stability by modifying a short (L = 40 μm) cantilever with a focused ion beam. Our process led to a ∼10-fold reduction in both a cantilever's stiffness and its hydrodynamic drag near a surface. We also preserved the benefits of a highly reflective cantilever while mitigating gold-coating induced long-term drift. As a result, we extended AFM's sub-pN bandwidth by a factor of ∼50 to span five decades of bandwidth (Δf ≈ 0.01-1000 Hz). Measurements of mechanically stretching individual proteins showed improved force precision coupled with state-of-the-art force stability and no significant loss in temporal resolution compared to the stiffer, unmodified cantilever. Finally, these cantilevers were robust and were reused for SFMS over multiple days. Hence, we expect these responsive, yet stable, cantilevers to broadly benefit diverse AFM-based studies.
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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