A piezoelectric stick–slip drive nanopositioner with large velocity under high load
Bibliographic record
Abstract
Piezoelectric stick–slip drive nanopositioners are of central importance in in situ SEM nanorobotic systems due to their high precise positioning, large stroke, high speed, and compact structure. However, the output velocity under high load will be seriously influenced. In this paper, a new piezoelectric stick–slip drive nanopositioner with large velocity under high load by introducing the adjust bolts to decouple the driving unit and moving unit is presented. A MATLAB simulation model has been created to optimize the nanopositioner for a certain velocity, and a FEM is used to confirm that the leaf hinge has sufficient stiffness. The size of the prototype is 30 × 32 × 25 mm3. Testing results indicate that the nanopositioner achieves a maximum velocity of 3.467 mm/s and a minimum resolution of 6 nm. When the load increases from 0.4 kg to 2 kg, the maximum velocities only decrease from 3.457 mm/s to 3.143 mm/s. The proposed piezoelectric stick–slip nanopositioner shows large velocity under high load.
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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 | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".