{"title":"基于高吸水性藻酸盐纤维的具有肌肉样结构的各向异性水凝胶传感器","authors":"Chen Hang, Zihan Guo, Kai Li, Jiuyong Yao, Hailing Shi, Ruihao Ge, Junxuan Liang, Fengyu Quan, Kewei Zhang, Xing Tian, Yanzhi Xia","doi":"10.1016/j.carbpol.2024.123015","DOIUrl":null,"url":null,"abstract":"<div><div>Hydrogel sensors have attracted much attention as they play a critical role in health monitoring, multifunctional electronic skin, and human-machine interfaces. However, the isotropic structure makes existing hydrogel sensors exhibit isotropic sensing performance. Therefore, it is a challenge to fabricate hydrogels with human tissue-like structures to achieve anisotropic sensing performance. Herein, we proposed a novel method to prepare anisotropic hydrogel sensors using high-absorbent alginate fibers. The anisotropic hydrogel, HAFG@CNTs, was prepared by adsorbing carbon nanotubes on high-absorbent alginate fibers and immobilized using polyacrylamide bonds. The hydrogel had anisotropic mechanical properties and anisotropic ionic conductivity. The modulus and toughness in the parallel fiber direction were 2.31 and 3.75 times higher than those in the perpendicular fiber direction, respectively, and the sensitivity of the parallel fiber direction was higher than that of the vertical direction when strain occurred. In addition, machine learning algorithms were used to predict and classify different action signals obtained from HAFG@CNTs with an accuracy of up to 98.18 %. These advantages offer great potential for applying HAFG@CNTs to wearable devices and medical monitoring.</div></div>","PeriodicalId":261,"journal":{"name":"Carbohydrate Polymers","volume":"349 ","pages":"Article 123015"},"PeriodicalIF":10.7000,"publicationDate":"2024-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Anisotropic hydrogel sensors with muscle-like structures based on high-absorbent alginate fibers\",\"authors\":\"Chen Hang, Zihan Guo, Kai Li, Jiuyong Yao, Hailing Shi, Ruihao Ge, Junxuan Liang, Fengyu Quan, Kewei Zhang, Xing Tian, Yanzhi Xia\",\"doi\":\"10.1016/j.carbpol.2024.123015\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Hydrogel sensors have attracted much attention as they play a critical role in health monitoring, multifunctional electronic skin, and human-machine interfaces. However, the isotropic structure makes existing hydrogel sensors exhibit isotropic sensing performance. Therefore, it is a challenge to fabricate hydrogels with human tissue-like structures to achieve anisotropic sensing performance. Herein, we proposed a novel method to prepare anisotropic hydrogel sensors using high-absorbent alginate fibers. The anisotropic hydrogel, HAFG@CNTs, was prepared by adsorbing carbon nanotubes on high-absorbent alginate fibers and immobilized using polyacrylamide bonds. The hydrogel had anisotropic mechanical properties and anisotropic ionic conductivity. The modulus and toughness in the parallel fiber direction were 2.31 and 3.75 times higher than those in the perpendicular fiber direction, respectively, and the sensitivity of the parallel fiber direction was higher than that of the vertical direction when strain occurred. In addition, machine learning algorithms were used to predict and classify different action signals obtained from HAFG@CNTs with an accuracy of up to 98.18 %. These advantages offer great potential for applying HAFG@CNTs to wearable devices and medical monitoring.</div></div>\",\"PeriodicalId\":261,\"journal\":{\"name\":\"Carbohydrate Polymers\",\"volume\":\"349 \",\"pages\":\"Article 123015\"},\"PeriodicalIF\":10.7000,\"publicationDate\":\"2024-11-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Carbohydrate Polymers\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0144861724012414\",\"RegionNum\":1,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, APPLIED\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Carbohydrate Polymers","FirstCategoryId":"92","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0144861724012414","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, APPLIED","Score":null,"Total":0}
Anisotropic hydrogel sensors with muscle-like structures based on high-absorbent alginate fibers
Hydrogel sensors have attracted much attention as they play a critical role in health monitoring, multifunctional electronic skin, and human-machine interfaces. However, the isotropic structure makes existing hydrogel sensors exhibit isotropic sensing performance. Therefore, it is a challenge to fabricate hydrogels with human tissue-like structures to achieve anisotropic sensing performance. Herein, we proposed a novel method to prepare anisotropic hydrogel sensors using high-absorbent alginate fibers. The anisotropic hydrogel, HAFG@CNTs, was prepared by adsorbing carbon nanotubes on high-absorbent alginate fibers and immobilized using polyacrylamide bonds. The hydrogel had anisotropic mechanical properties and anisotropic ionic conductivity. The modulus and toughness in the parallel fiber direction were 2.31 and 3.75 times higher than those in the perpendicular fiber direction, respectively, and the sensitivity of the parallel fiber direction was higher than that of the vertical direction when strain occurred. In addition, machine learning algorithms were used to predict and classify different action signals obtained from HAFG@CNTs with an accuracy of up to 98.18 %. These advantages offer great potential for applying HAFG@CNTs to wearable devices and medical monitoring.
期刊介绍:
Carbohydrate Polymers stands as a prominent journal in the glycoscience field, dedicated to exploring and harnessing the potential of polysaccharides with applications spanning bioenergy, bioplastics, biomaterials, biorefining, chemistry, drug delivery, food, health, nanotechnology, packaging, paper, pharmaceuticals, medicine, oil recovery, textiles, tissue engineering, wood, and various aspects of glycoscience.
The journal emphasizes the central role of well-characterized carbohydrate polymers, highlighting their significance as the primary focus rather than a peripheral topic. Each paper must prominently feature at least one named carbohydrate polymer, evident in both citation and title, with a commitment to innovative research that advances scientific knowledge.