Ionogels have shown tremendous potential in flexible electronics applications, such as electronic skin, human-machine interfaces, and soft robotics. Here, the multifunctional polythioctic acid (PTA)-ionic liquid supramolecular ionogels are constructed by combining hydroxypropyl celluloses with hierarchical dynamic disulfide, Zn2+ coordination, and hydrogen bonds. As a result, the ionogels exhibit exceptional mechanical performance, with the tensile strains exceeding 15 000% and toughness up to 20.3 MJ m−3, as well as superior damping properties with energy dissipation efficiency above 80% and high loss factors of 1.67. These excellent characteristics arise from a multi-gradient energy dissipation mechanism, in which the progressive rupture of aggregated ionic clusters is combined with the sequential dissociation of hierarchical dynamic bonds. More importantly, based on the reliable conductivity, a respiratory monitoring system for patients with respiratory diseases is constructed by integrating the ionogel with deep learning techniques, which enables real-time detection and rapid response to breathing patterns to ensure patient safety. Furthermore, the ionogels demonstrate high self-healing efficiency (95.7%) and green recyclability as well.

Ultrastretchable and Recyclable Ionogels with Hierarchical Dynamic Bonds for Respiratory Monitoring

Puglia, Debora;Yang, Weijun;
2025

Abstract

Ionogels have shown tremendous potential in flexible electronics applications, such as electronic skin, human-machine interfaces, and soft robotics. Here, the multifunctional polythioctic acid (PTA)-ionic liquid supramolecular ionogels are constructed by combining hydroxypropyl celluloses with hierarchical dynamic disulfide, Zn2+ coordination, and hydrogen bonds. As a result, the ionogels exhibit exceptional mechanical performance, with the tensile strains exceeding 15 000% and toughness up to 20.3 MJ m−3, as well as superior damping properties with energy dissipation efficiency above 80% and high loss factors of 1.67. These excellent characteristics arise from a multi-gradient energy dissipation mechanism, in which the progressive rupture of aggregated ionic clusters is combined with the sequential dissociation of hierarchical dynamic bonds. More importantly, based on the reliable conductivity, a respiratory monitoring system for patients with respiratory diseases is constructed by integrating the ionogel with deep learning techniques, which enables real-time detection and rapid response to breathing patterns to ensure patient safety. Furthermore, the ionogels demonstrate high self-healing efficiency (95.7%) and green recyclability as well.
2025
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11391/1609819
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