自愈水凝胶
生物相容性
纳米技术
计算机科学
表征(材料科学)
人工智能
材料科学
系统工程
深度学习
工程类
制造工程
3D打印
3d打印
人工智能应用
数据科学
生化工程
组织工程
作者
Siling Zhang,Hao Wang,Feifan Liu,Yujing Su,Kang Han,Yongli Liu,Fangxia Guan,Hongtao Liu,Shanshan Ma
摘要
Due to the excellent biocompatibility and adjustability, hydrogels have broadened their application in different fields, such as 3D printing, tissue engineering, drug delivery, and biosensing. However, traditional hydrogel research is confronted with low screening efficiency and insufficient design and characterization methods. In recent years, artificial intelligence (AI) has become a revolutionary tool for hydrogel research. AI technologies such as machine learning and deep learning have driven hydrogels towards intelligence and functionality. This article reviews the innovations of AI in the design and performance optimization of hydrogels, as well as their multi-scenario applications, such as 3D printing, environmental detection, and wound healing. Finally, the limitations, challenges and strategies for AI-driven hydrogel research are discussed. In conclusion, the cross-integration of AI and hydrogels has become an important trend of scientific research, providing new tools for the research of new hydrogel materials.
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