Thermally trainable dual network hydrogels

Shanming Hu, Yuhuang Fang, Chen Liang, Matti Turunen, Olli Ikkala*, Hang Zhang*

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

17 Citations (Scopus)
42 Downloads (Pure)

Abstract

Inspired by biological systems, trainable responsive materials have received burgeoning research interests for future adaptive and intelligent material systems. However, the trainable materials to date typically cannot perform active work, and the training allows only one direction of functionality change. Here, we demonstrate thermally trainable hydrogel systems consisting of two thermoresponsive polymers, where the volumetric response of the system upon phase transitions enhances or decreases through a training process above certain threshold temperature. Positive or negative training of the thermally induced deformations can be achieved, depending on the network design. Importantly, softening, stiffening, or toughening of the hydrogel can be achieved by the training process. We demonstrate trainable hydrogel actuators capable of performing increased active work or implementing an initially impossible task. The reported dual network hydrogels provide a new training strategy that can be leveraged for bio-inspired soft systems such as adaptive artificial muscles or soft robotics.

Original languageEnglish
Article number3717
Pages (from-to)1-10
Number of pages10
JournalNature Communications
Volume14
Issue number1
DOIs
Publication statusPublished - Dec 2023
MoE publication typeA1 Journal article-refereed

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