Skin-like hydrogel devices for wearable sensing, soft robotics and beyond
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Full frame distilled prediction
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.
- Candidate categories
- Meta-epidemiology (narrow)
- Consensus categories
- none
- Domain
- Candidate signal: noneConsensus signal: none
- Study design
- Candidate signal: Not applicableConsensus signal: none
- Genre
- Candidate signal: ReviewConsensus signal: Review
- Teacher disagreement score
- 0.991
- Threshold uncertainty score
- 1.000
- Validation status
machine_predicted_unvalidated·codex-gemma-dda1882f352a
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) | 0.001 | 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 | 0.000 |
Machine scores (provisional)
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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.
- Teacher spread
- 0.253 · how far apart the two teachers sit on this one work
- Validation status
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
Abstract
Skin-like electronics are developing rapidly to realize a variety of applications such as wearable sensing and soft robotics. Hydrogels, as soft biomaterials, have been studied intensively for skin-like electronic utilities due to their unique features such as softness, wetness, biocompatibility and ionic sensing capability. These features could potentially blur the gap between soft biological systems and hard artificial machines. However, the development of skin-like hydrogel devices is still in its infancy and faces challenges including limited functionality, low ambient stability, poor surface adhesion, and relatively high power consumption (as ionic sensors). This review aims to summarize current development of skin-inspired hydrogel devices to address these challenges. We first conduct an overview of hydrogels and existing strategies to increase their toughness and conductivity. Next, we describe current approaches to leverage hydrogel devices with advanced merits including anti-dehydration, anti-freezing, and adhesion. Thereafter, we highlight state-of-the-art skin-like hydrogel devices for applications including wearable electronics, soft robotics, and energy harvesting. Finally, we conclude and outline the future trends.
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.
The record
- Venue
- iScience
- Topic
- Advanced Sensor and Energy Harvesting Materials
- Field
- Engineering
- Canadian institutions
- McGill UniversityUniversity of Toronto
- Funders
- Natural Sciences and Engineering Research Council of CanadaUniversity of TorontoCanada Foundation for Innovation
- Keywords
- Soft roboticsSelf-healing hydrogelsElectronicsWearable computerWearable technologyNanotechnologyRoboticsComputer scienceElectronic skinSoft materialsMaterials scienceArtificial intelligenceRobotEmbedded systemEngineeringElectrical engineering
- Has abstract in OpenAlex
- yes