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Record W4400957483 · doi:10.1002/smtd.202400812

Hybrid Zwitterionic Hydrogels with Encoded Differential Swelling and Programmed Deformation for Small‐Scale Robotics

2024· article· en· W4400957483 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueSmall Methods · 2024
Typearticle
Languageen
FieldEngineering
TopicAdvanced Materials and Mechanics
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSelf-healing hydrogelsSoft roboticsMorphingSwellingMaterials scienceRobotSoft materialsComputer scienceNanotechnologyAcrylateBiomedical engineeringArtificial intelligenceComposite materialEngineeringPolymer chemistryPolymerCopolymer

Abstract

fetched live from OpenAlex

Stimuli-responsive shape-morphing hydrogels with self-healing and tunable physiochemical properties are excellent candidates for functional building blocks of untethered small-scale soft robots. With mechanical properties similar to soft organs and tissues, such robots enable minimally invasive medical procedures, such as cargo/cell transportation. In this work, responsive hydrogels based on zwitterionic/acrylate chemistry with self-healing and stimuli-responsiveness are synthesized. Such hydrogels are then judiciously cut and pasted to form hybrid constructs with predetermined swelling and elastic anisotropy. This method is used to program hydrogel constructs with predetermined 2D-to-3D deformation upon exposure to different environmental ionic strengths. Untethered soft robotic functionalities are demonstrated, such as actuation, magnetic locomotion, and targeted transport of soft and light cargo in flooded media. The proposed hydrogel expands the repertoire of functional materials for fabricating small-scale soft robots.

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 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: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.473
Threshold uncertainty score0.600

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 head0.023
GPT teacher head0.278
Teacher spread0.255 · 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