High-Fidelity 3D Printing of Programmable Magnetic Soft Robots
Bibliographic record
Abstract
Magnetic microrobots are an increasingly popular area of research with a wide range of potential applications including healthcare. These microrobots can be remotely controlled using an external magnetic field to perform various motions such as jumping, swimming, crawling, rolling, and grabbing. This allows for intricate tasks such as drug delivery, stent placements, and wound patching. However, fabricating microrobots is a challenging multi-step process that can take several hours or even days. Therefore, it is important to have an accurate, reproducible, and automated fabrication method. In this study, an existing fully automated stereolithography printer is tested to fabricate magnetic soft robots with voxel sizes smaller than a millimeter. The work focuses on updating the optics to create a smaller spot size ($803 \mu ~\mathrm{m}$) with more uniform curing distributions using a near ultraviolet beam shaper. The updated optics system in the printer is then used to print two microrobots: 'the beam' and 'the gripper' that are functionally tested using an externally applied magnetic field.
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.
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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".