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High-Fidelity 3D Printing of Programmable Magnetic Soft Robots

2025· article· en· W4412431526 on OpenAlexaff
Siwen Xie, Kaitlyn Clancy, Onaizah Onaizah

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Materials and Mechanics
Canadian institutionsMcMaster University
Fundersnot available
KeywordsRobot3D printingComputer scienceMaterials scienceArtificial intelligenceComposite material

Abstract

fetched live from OpenAlex

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 (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$803 \mu ~\mathrm{m}$</tex>) 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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.611
Threshold uncertainty score0.280

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.005
GPT teacher head0.210
Teacher spread0.205 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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