Crossing the Dimensional Divide with Optoelectronic Tweezers: Multicomponent Light‐Driven Micromachines with Motion Transfer in Three Dimensions
Bibliographic record
Abstract
Micromachines capable of performing diverse mechanical tasks in complex and constrained microenvironments are of great interest. Despite important milestones in this pursuit, until now, micromachines are confined to actuation within a single 2D plane due to the challenges of transferring motion across different planes in limited space. Here, a breakthrough method is presented to overcome this limitation: multi-component micromachines that facilitate 3D motion transfer across different planes. These light-driven 3D micromachines, fabricated using standard photolithography combined with direct laser writing, are assembled and actuated via programmable light patterns within an optoelectronic tweezers system. Utilizing charge-induced repulsion and dielectrophoretic levitation effects, the micromachines enable highly efficient mechanical rotation and effective inter-component motion transfer. Through this work, fascinating patterns of similarities are unveiled for the new microscale 3D systems when compared with the macro-scale world in which they live, paving the way for the development of micromechanical devices and microsystems with ever increasing functionality and versatility.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".