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Ultrasensitive and Highly Stretchable Multiple‑Crosslinked Ionic hydrogel sensors with Long‑Term Stability

Nano-Micro Letters 2023年第4期15卷 85-96页

作者： Jin‑Young Yu Seung Eon Moon Jeong Hun Kim Seong Min Kang Department of Mechanical Engineering Chungnam National UniversityDaejeon 34134Korea Emerging Nano‑Materials Research Section Electronics and Telecommunications Research InstituteDaejeon 305‑700Republic of Korea

Flexible hydrogels are receiving significant attention for their application in wearable ***,most hydrogel materials exhibit weak and one-time adhesion,low sensitivity,ice crystallization,water evaporation,and poor self-recovery,thereby limiting their application as *** issues are only partly addressed in previous ***,a multiplecrosslinked poly(2-(methacryloyloxy)ethyl)dimethyl-(3-sulfopropyl)ammonium hydroxide-co-acrylamide)(P(SBMA-co-AAm))multifunctional hydrogel is prepared via a one-pot synthesis method to overcome the aforementioned ***,ions,glycerol,and 2-(methacryloyloxy)ethyl)dimethyl-(3-sulfopropyl)ammonium hydroxide are incorporated to reduce the freezing point and improve the moisture retention *** proposed hydrogel is superior to existing hydrogels because it exhibits good stretchability(a strain of 2900%),self-healing properties,and transparency through effective energy dissipation in its dynamic crosslinked ***,2-(methacryloyloxy)ethyl)dimethyl-(3-sulfopropyl)ammonium hydroxide as a zwitterion monomer results in an excellent gauge factor of 43.4 at strains of 1300-1600%by improving the ion transportability and achieving a strong adhesion of 20.9 kPa owing to the dipole-dipole *** proposed hydrogel is promising for next-generation biomedical applications,such as soft robots,and health monitoring.

关键词： hydrogel sensors Biocompatibility Multifunction High-sensitivity sensors Multiple-crosslink association

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hydrogel and Machine Learning for Soft Robots’ Sensing and Signal Processing: A Review

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Journal of Bionic Engineering 2023年第3期20卷 845-857页

作者： Shuyu Wang Zhaojia Sun Department of Control Engineering Northeastern UniversityQinhuangdao066001China Hebei Key Laboratory of Micro-Nano Precision Optical Sensing and Measurement Technology Qinhuangdao066004China

The soft robotics field is on the rise. The highly adaptive robots provide the opportunity to bridge the gap between machines and people. However, their elastomeric nature poses significant challenges to the perception, control, and signal processing. hydrogels and machine learning provide promising solutions to the problems above. This review aims to summarize this recent trend by first assessing the current hydrogel-based sensing and actuation methods applied to soft robots. We outlined the mechanisms of perception in response to various external stimuli. Next, recent achievements of machine learning for soft robots’ sensing data processing and optimization are evaluated. Here we list the strategies for implementing machine learning models from the perspective of applications. Last, we discuss the challenges and future opportunities in perception data processing and soft robots’ high level tasks.

关键词： Soft robots Bionic robots Machine learning hydrogel sensors Deep learning

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