3D Generation of Multipurpose Atomic Force Microscopy Tips
Bibliographic record
Abstract
In this work, 3D polymeric atomic force microscopy (AFM) tips, referred to as 3DTIPs, are manufactured with great flexibility in design and function using two-photon polymerization. With the technology holding a great potential in developing next-generation AFM tips, 3DTIPs prove effective in obtaining high-resolution and high-speed AFM images in air and liquid environments, using common AFM modes. In particular, it is shown that the 3DTIPs provide high-resolution imaging due to their extremely low Hamaker constant, high speed scanning rates due to their low quality factor, and high durability due to their soft nature and minimal isotropic tip wear; the three important features for advancing AFM studies. It is also shown that refining the tip end of the 3DTIPs by focused ion beam etching and by carbon nanotube inclusion substantially extends their functionality in high-resolution AFM imaging, reaching angstrom scales. Altogether, the multifunctional capabilities of 3DTIPs can bring next-generation AFM tips to routine and advanced AFM applications, and expand the fields of high speed AFM imaging and biological force measurements.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".