合理设计
计算机科学
材料科学
碳纤维
共价键
密度泛函理论
多孔性
纳米技术
环境科学
金属有机骨架
表面改性
钥匙(锁)
聚合物
水分
蒙特卡罗方法
热的
设计要素和原则
组分(热力学)
生化工程
多孔介质
材料设计
系统工程
碳捕获和储存(时间表)
吸附
工艺工程
作者
Wei Wei,Ziyang Wang,Chao Xu,Zhiyi Li,Hongliang Bai,Zhijun Liu
标识
DOI:10.1021/acs.iecr.5c03598
摘要
The increasing concentration of atmospheric carbon dioxide (CO2) poses a severe threat to global climate security, prompting an urgent demand for efficient carbon removal technologies. Among various carbon capture strategies, direct air capture (DAC) stands out due to its ability to extract CO2 directly from ambient air, making it a critical component of negative emissions approaches. Covalent organic frameworks (COFs), as a class of crystalline and porous organic polymers with tunable structures and high thermal and chemical stability, have emerged as promising candidates for DAC applications. Their well-defined architectures enable precise control over pore size, topology, surface area, and functional group incorporation, all of which are key to achieving selective and efficient CO2 adsorption under low-concentration conditions. This review systematically summarizes recent advances in the structural design and functional regulation of COFs for DAC. We first introduce the evolution of COF structural dimensionality─from 2D to 3D frameworks─and their impact on porosity and mass transfer. Subsequently, we discuss various strategies for functionalizing COFs with active sites, such as amines, ionic groups, and metal centers, to enhance the CO2-binding affinity and moisture resistance. Computational approaches, including grand canonical Monte Carlo (GCMC) simulations, density functional theory (DFT), and machine learning (ML), are also reviewed as powerful tools to guide the rational design of COF-based DAC materials. Finally, we evaluate the performance of representative COFs in DAC applications and outline the current challenges and future directions toward scalable, energy-efficient, and cost-effective COF-DAC systems. This review aims to provide a comprehensive reference for advancing COF-based materials toward practical deployment in carbon capture technologies.
科研通智能强力驱动
Strongly Powered by AbleSci AI