(Invited) Dry Adhesives for MEMS Assembly, Manipulation and Integration: Progress and Challenges
Bibliographic record
Abstract
Bioinspired synthetic dry adhesives offer unique potential in the field of micro assembly and manipulation. These adhesives, which take their basic operating principle from animals like geckos, use van der Waals adhesion forces and mechanical fiber optimization to produce significant forces. For several years, these materials have been of interest for climbing robots and adhesive surfaces due to potential characteristics like self-cleaning or anti-fouling behavior, anisotropic adhesion strengths and non-transferring materials. These same strengths would make these materials an ideal mechanism for handling delicate parts or manipulating structures in the field of micro-electro-mechanical systems (MEMS) packaging. In this paper, I review the specific fabrication processes developed by our group and examine some of the challenges in their integration with MEMS assembly and packaging processes. Improving normal adhesion strength and directionality of adhesives has been completed and work is beginning to focus on reducing polymer transfer and improving the anti-static compatibility of the structural materials used in the adhesives.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.013 |
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".