Batch fabrication of ultra-sharp atomic force microscope probes with stair-shaped handles for high-precision imaging
Bibliographic record
Abstract
Atomic force microscope (AFM) systems rely on silicon (Si) probes for precise nanoscale characterization across diverse environments. However, fabricating high-aspect-ratio (HAR) and sharp Si tips and optimizing the handle geometries remain significant challenges. Conventional HAR probe fabrication methods lack scalability, precision, and cost efficiency, while cuboid-shaped handles risk obstructing laser detection and limiting compatibility. This study presents an innovative batch-fabrication strategy for high-performance Si AFM probes that integrate ultra-sharp HAR tips, rectangular cantilevers, and universally compatible stair-shaped handles. Notably, the tip fabrication process employs only low-cost microscale ultraviolet (UV) lithography, while still achieving nanoscale structural resolution. The fabricated probes exhibit a tip apex radius of 5 nm and a half-cone angle of 7.5°, enabling high-resolution and high-fidelity imaging. The novel stair-shaped handle geometry is introduced and fabricated via a single-step dry etching process, which provides unobstructed laser detection and ensures compatibility with a broad range of commercial AFM platforms. Durability testing demonstrates stable scanning performance for up to 8 hours within the 100 nm precision range, confirming the mechanical reliability of the design. This scalable, reproducible, and high-yield fabrication strategy represents a significant advancement in HAR AFM probe development, providing enhanced performance and extended applicability for diverse nanoscale imaging applications.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".