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Bifunctional Phenol-Enabled Sequential Polymerization Strategy for Printable Tough Hydrogels.

Jiayi Wei¹, Bo Zhang², Ping Zhang¹

¹Key Laboratory of Synthetic and Natural Functional Molecule Chemistry of the Ministry of Education, College of Chemistry and Materials Science, Northwest University, Xi'an, 710069, China.

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|June 24, 2022

Summary

This summary is machine-generated.

Researchers developed high-performance multinetwork hydrogels using a novel bifunctional phenol-enabled sequential polymerization (BPSP) strategy. This method enhances mechanical properties and printability for applications in soft robotics and sensors.

Keywords:

3D printing orthogonal photochemistry sequential polymerization stretchable electronics tough hydrogels

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Area of Science:

Materials Science
Polymer Chemistry
Soft Robotics

Background:

Hydrogels are essential for soft robotics, sensors, and regenerative medicine.
Developing multinetwork hydrogels with superior mechanical properties and printability remains a challenge.

Purpose of the Study:

To introduce a bifunctional phenol-enabled sequential polymerization (BPSP) strategy for fabricating high-performance multinetwork hydrogels.
To enhance the mechanical strength, toughness, and printability of hydrogels.

Main Methods:

Utilized orthogonal catalysis via ruthenium photochemistry for sequential polymerization.
Employed bifunctional phenols to polymerize with monomers and themselves, forming phenol-containing polymers (Ph-Ps).
Fabricated Ph-Ps-based multinetwork tough hydrogels.

Main Results:

Achieved maximum stress of 0.75 MPa and toughness of 2.2 MJ m⁻³ at 800% strain.
Demonstrated property improvements up to 16 times greater than control hydrogels.
Shortened gelation times to approximately 4 seconds, enabling rapid 3D printing.
Successfully created a 3D scaffold for sensitive mechanical sensors detecting human motion.

Conclusions:

The BPSP strategy effectively produces high-performance, tough, and printable multinetwork hydrogels.
The developed hydrogels show significant potential in advanced applications like mechanical sensors and soft robotics.
This approach offers a versatile platform for designing next-generation functional polymer materials.