Steering Micromotors via Reprogrammable Optoelectronic Paths
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Steering micromotors is important for using them in practical applications and as model systems for active matter. This functionality often requires magnetic materials in the micromotor, taxis behavior of the micromotor, or the use of specifically designed physical boundaries. Here, we develop an optoelectronic strategy that steers micromotors with programmable light patterns. In this strategy, light illumination turns hydrogenated amorphous silicon conductive, generating local electric field maxima at the edge of the light pattern that attracts micromotors via positive dielectrophoresis. As an example, metallo-dielectric Janus microspheres that self-propelled under alternating current electric fields were steered by static light patterns along customized paths and through complex microstructures. Their long-term directionality was also rectified by ratchet-shaped light patterns. Furthermore, dynamic light patterns that varied in space and time enabled more advanced motion controls such as multiple motion modes, parallel control of multiple micromotors, and the collection and transport of motor swarms. This optoelectronic steering strategy is highly versatile and compatible with a variety of micromotors, and thus it possesses the potential for their programmable control in complex environments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 it