ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2026
Robust Stitching Interface and Deep Learning Empowered Hydrogel Human-Machine Interface.
Hao Dong, Yiming Luo, Chuanliu Liu, Mahamood Modupe Rasheedat, Wenjiayi Tan, Fangyu Zhao, Yixue Zhang, Chris Connor, Hua Hou, Hamdy Khamees Thabet and 2 more
Abstract read
In one paragraphArticle in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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12 authors.
Hao DongState Key Laboratory of Bio-based Fiber Materials, Tianjin Key Laboratory of Multivariate Identification for Port Hazardous Chemical Substances, Tianjin Key Laboratory of Brine Chemical Engineering and Resource Eco-Utilization, College of Chemical Engineering and Materials Science, Tianjin University of Science and Technology, Tianjin, China.
Yiming LuoState Key Laboratory of Bio-based Fiber Materials, Tianjin Key Laboratory of Multivariate Identification for Port Hazardous Chemical Substances, Tianjin Key Laboratory of Brine Chemical Engineering and Resource Eco-Utilization, College of Chemical Engineering and Materials Science, Tianjin University of Science and Technology, Tianjin, China.
Chuanliu LiuState Key Laboratory of Bio-based Fiber Materials, Tianjin Key Laboratory of Multivariate Identification for Port Hazardous Chemical Substances, Tianjin Key Laboratory of Brine Chemical Engineering and Resource Eco-Utilization, College of Chemical Engineering and Materials Science, Tianjin University of Science and Technology, Tianjin, China.ORCID https://orcid.org/0009-0007-1327-2936 Mahamood Modupe RasheedatSchool of Engineering, Physics and Mathematics, Northumbria University, Newcastle Upon Tyne, UK.
Wenjiayi TanCollege of Chemistry Fuzhou University, Fuzhou, China.
Fangyu ZhaoState Key Laboratory of Bio-based Fiber Materials, Tianjin Key Laboratory of Multivariate Identification for Port Hazardous Chemical Substances, Tianjin Key Laboratory of Brine Chemical Engineering and Resource Eco-Utilization, College of Chemical Engineering and Materials Science, Tianjin University of Science and Technology, Tianjin, China.
Yixue ZhangState Key Laboratory of Bio-based Fiber Materials, Tianjin Key Laboratory of Multivariate Identification for Port Hazardous Chemical Substances, Tianjin Key Laboratory of Brine Chemical Engineering and Resource Eco-Utilization, College of Chemical Engineering and Materials Science, Tianjin University of Science and Technology, Tianjin, China.
Hua HouSchool of Materials Science and Engineering, Taiyuan University of Science and Technology, Taiyuan, China.
Huige WeiState Key Laboratory of Bio-based Fiber Materials, Tianjin Key Laboratory of Multivariate Identification for Port Hazardous Chemical Substances, Tianjin Key Laboratory of Brine Chemical Engineering and Resource Eco-Utilization, College of Chemical Engineering and Materials Science, Tianjin University of Science and Technology, Tianjin, China.ORCID https://orcid.org/0000-0003-3977-1147 Funding
Engineering and Physical Sciences Research Council EU COST CA23155Engineering and Physical Sciences Research Council RIR18221018-1Young Elite Scientists Sponsorship Program by Tianjin NBU-FPEJ-2026-128-06Young Elite Scientists Sponsorship Program by Tianjin TJSQNTJ-2018-03
6 · The paper itselfAbstract
Mechanical mismatch and weak interfacial adhesion between hydrogels and encapsulation layers, particularly polyethylene terephthalate (PET), remain the primary cause of signal distortion in dynamic sensing applications. We address this through a molecular design strategy that exploits synergistic carboxylate anion-quaternary ammonium interactions to simultaneously strengthen the hydrogel-PET interface and the bulk hydrogel network. The strategy operates through two coupled mechanisms. Fe
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deep learninghuman‐computer interactioninformation transmissioninterface functionalization
Identifiers
PMID42559724
PMCPMC13445332
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