A superelastic alloy microgripper with embedded electromagnetic actuators and piezoelectric force sensors: a numerical and experimental study
Bibliographic record
Abstract
This paper presents the analysis, design, and characterization of a superelastic alloy (NiTi) microgripper with integrated electromagnetic actuators and piezoelectric force sensors. The microgripper, fabricated by electro-discharge machining, features force sensing capability, large force output, and large displacements to accommodate objects of various sizes. The design parameters for the embedded electromagnetic actuators were selected on the basis of finite element sensitivity analysis. In order to make the microgripper capable of resolving gripping forces, piezoelectric force sensors were fabricated and integrated into the microgripper. The performance of the microgripper, the integrated force sensors, and the electromagnetic actuators was experimentally evaluated. A satisfactory match between experimental results and finite element simulations was obtained. Furthermore, comparison studies demonstrated that the superelastic alloy (NiTi) microgripper was capable of producing larger displacement than a stainless steel microgripper. Finally, experimental results of optical fiber alignment and the manipulation of tiny biological tissues with the superelastic microgripper were presented.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".