Scalable Approach to Molecular Motor‐Polymer Conjugates for Light‐Driven Artificial Muscles

材料科学 人工肌肉 结合 聚合物 可扩展性 分子马达 纳米技术 计算机科学 人工智能 复合材料 执行机构 数据库 数学分析 数学
作者
Xuyang Yao,Jude Ann Vishnu,Claudius Lupfer,Daniel Hoenders,Oliver Skarsetz,Weixiang Chen,Damien Dattler,Alexis Perrot,Wenzhi Wang,Chuan Gao,Nicolas Giuseppone,Friederike Schmid,Andreas Walther
出处
期刊:Advanced Materials [Wiley]
卷期号:36 (28) 被引量:2
标识
DOI:10.1002/adma.202403514
摘要

The integration of molecular machines and motors into materials represents a promising avenue for creating dynamic and functional molecular systems, with potential applications in soft robotics or reconfigurable biomaterials. However, the development of truly scalable and controllable approaches for incorporating molecular motors into polymeric matrices has remained a challenge. Here, it is shown that light-driven molecular motors with sensitive photo-isomerizable double bonds can be converted into initiators for Cu-mediated controlled/living radical polymerization enabling the synthesis of star-shaped motor-polymer conjugates. This approach enables scalability, precise control over the molecular structure, block copolymer structures, and high-end group fidelity. Moreover, it is demonstrated that these materials can be crosslinked to form gels with quasi-ideal network topology, exhibiting light-triggered contraction. The influence of arm length and polymer structure is investigated, and the first molecular dynamics simulation framework to gain deeper insights into the contraction processes is developed. Leveraging this scalable methodology, the creation of bilayer soft robotic devices and cargo-lifting artificial muscles is showcased, highlighting the versatility and potential applications of this advanced polymer chemistry approach. It is anticipated that the integrated experimental and simulation framework will accelerate scalable approaches for active polymer materials based on molecular machines, opening up new horizons in materials science and bioscience.

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