Abstract
Traditionally, slide-ring gels are stretchable but soft as a result of an elasticity-stretchability trade-off. Herein, we introduce a new approach to breaking this trade-off and creating reinforced slide-ring networks with mobile crosslinkers. Our approach involves the construction of a polyethylene glycol double-threaded γ-cyclodextrin-based pro-slide-ring crosslinker that serves as a modular component for 3D printing and copolymerization. The resulting crystalline-domain-reinforced slide-ring hydrogels, or CrysDoS-gels, exhibit both high elasticity and high stretchability. The modular synthesis allows for high-throughput synthesis of CrysDoS-gels, generating a large amount of data for structure-property analysis. By employing data science techniques, such as machine learning and linear regression, not only were we able to identify which chemical components influence the mechanical properties of CrysDoS-gels, but this analysis also aided in the discovery of better-performing CrysDoS-gels. Finally, we demonstrate the potential application of the newly discovered CrysDoS-gels as sensing devices by 3D printing them as stress sensors with high sensitivity and a broad detection range.
| Original language | English |
|---|---|
| Pages (from-to) | 3515-3531 |
| Number of pages | 17 |
| Journal | Chem |
| Volume | 9 |
| Issue number | 12 |
| DOIs | |
| State | Published - Dec 14 2023 |
Keywords
- 3D printing
- SDG12: Responsible consumption and production
- SDG3: Good health and well-being
- cyclodextrin
- double-threaded network
- high-throughput synthesis
- hydrogel
- machine learning
- polyrotaxane
- slide ring
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