Core Insights - The article discusses the development of a new AI-assisted bioinspired super adhesive hydrogel that can maintain strong adhesion in harsh underwater environments, showcasing its potential for various biomedical applications and marine uses [2][6][10]. Group 1: Material Design and AI Integration - Researchers from Hokkaido University, led by Professor Gong Jianping, have redefined material design by utilizing AI to analyze natural adhesive protein sequences and construct iterative optimization models [2][4]. - The complexity of designing soft materials like hydrogels is highlighted, as it requires selecting appropriate building blocks and determining their arrangement, which creates a vast design space [3][5]. - Data-driven strategies, including data mining and machine learning, are becoming increasingly important in material research to reduce experimental burdens and improve performance predictions [3][4]. Group 2: Hydrogel Development and Testing - The research team developed a method for designing super adhesive hydrogels inspired by natural adhesive proteins, integrating data mining, experimental synthesis, and machine learning [6][10]. - They analyzed amino acid sequences of adhesive proteins from aquatic organisms to identify functional characteristics, leading to the design of 180 different hydrogels [7][10]. - The hydrogels demonstrated excellent underwater adhesion strength and stability in various wet environments, maintaining strong adhesion for over a year [9][10]. Group 3: Applications and Future Potential - The super adhesive hydrogels have shown significant potential in various applications, including biomedical uses such as prosthetic coatings and wearable biosensors, as well as marine applications like underwater repairs [10][11]. - The data-driven design approach used in developing these hydrogels illustrates its advantages in creating high-performance materials and its potential for broader applications in functional soft material design [11][12].