共聚物
材料科学
纳米技术
化学工程
纳米结构
块(置换群论)
聚合物
几何学
数学
工程类
复合材料
作者
Yuanzhi Li,Abigail Plummer,Jörg G. Werner
出处
期刊:ACS Nano
[American Chemical Society]
日期:2024-07-13
卷期号:18 (29): 19150-19160
被引量:2
标识
DOI:10.1021/acsnano.4c04394
摘要
Soft gels with spatially defined mesoscale distributions of chemical activity that guide and accelerate reactions by chemical nanoconfinement are found ubiquitously in nature but are rare in artificial systems. In this study, we introduce chemically nanostructured bulk organogels with periodically ordered morphologies from self-assembled block copolymer monoliths with a single selectively cross-linked block (xBCP). Ordered bulk organogels are fabricated with various distinct morphologies including hexagonally packed cylinders and two gyroidal three-dimensionally periodic network structures that exhibit macroscopic and nanoscopic structural integrity upon swelling. Small-angle X-ray scattering and transmission electron microscopy confirm that the periodic arrangement of the chemically distinct blocks in the self-assembled xBCP is retained at polymer fractions as low as 15 vol %. Our results reveal that the swelling equilibrium is not exclusively determined by the cross-linked block despite its structural role but is strongly influenced by the weighted interactions between solvent and the individual nanophases, including the non-cross-linked blocks. Therefore, substantial swelling can be obtained even for solvents that the cross-linked block itself has unfavorable interactions with. Since these ordered organogels present a class of solvent-laden bulk materials that exhibit chemically distinct nanoenvironments on a periodic mesoscale lattice, we demonstrate their use for selective infusion templating (SIT) in a proof-of-concept nanoconfined synthesis of poly(acrylonitrile) from which a monolithic ordered gyroidal mesoporous carbon is obtained. Going forward, we envision using xBCP gels and SIT to enable the fabrication of traditionally hard-to-template materials as periodically nanostructured monoliths due to the extensive tunability in their physicochemical parameter space.
科研通智能强力驱动
Strongly Powered by AbleSci AI