期刊
MACROMOLECULES
卷 55, 期 16, 页码 7181-7192出版社
AMER CHEMICAL SOC
DOI: 10.1021/acs.macromol.2c00841
关键词
-
资金
- National Natural Science Foundation of China [2210011635]
- China Post-doctoral Science Foundation [2021M692348]
- Priority Academic Program Development (PAPD) of Jiangsu Higher Education Institutions
- Program of Innovative Research Team of Soochow University
In this study, a photoinduced free radical-promoted cationic reversible addition-fragmentation chain transfer (RAFT) polymerization method was developed for 3D printing. The polymerization mechanism and the effects of each component on the properties of the materials were investigated. Additionally, polymer welding of the printed objects was achieved, expanding the possibilities for postprinting and future applications.
Photopolymerization-based three-dimensional (3D) printing techniques have been widely utilized to fabricate polymeric materials with complex architectures. The application of reversible deactivation radical polymerization (RDRP) in 3D printing is emerging as a powerful tool to introduce various postprinting abilities but is still at an early stage. Here, a photoinduced free radical-promoted cationic reversible addition-fragmentation chain transfer (RAFT) polymerization method was developed, utilizing the direct photolysis of the RAFT agent as a radical source, which was further combined with photo-iniferter RAFT polymerization to prepare polymer networks. The polymerization mechanism was studied by model polymerization using monofunctional monomers. The effects of each component on the properties of the final materials and polymerization behavior of the cross-linking systems were studied in detail. This method was successfully applied in a digital light processing (DLP) technique-based commercial 3D printer. Finally, polymer welding of the printed objects through both cationic and radical RAFT chain extension was realized, expanding avenues of postprinting and future applications in various fields.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据