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Updated: Jul 18, 2026

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进步金属有机框架选和修复条件优化,通过集成机器学习和理论计算洞察来消除持久有机污染物

Zhengwen Wei1, Sicheng Jing2, Xiang-Fei Lü2

  • 1Key Laboratory of Subsurface Hydrology and Ecological Effects in Arid Region of the Ministry of Education, Chang'an University, No. 126 Yanta Road, Xi'an 710054, Shaanxi, China; School of Water and Environment, Chang'an University, Xi'an 710054, China; Key Laboratory of Eco-hydrology and Water Security in Arid and Semi-arid Regions of Ministry of Water Resources, Chang'an University, China; College of Geological Engineering and Geomatics, Chang'an University, Xi'an, Shanxi 710054, China.

Journal of colloid and interface science
|March 5, 2026
PubMed
概括

本研究介绍了一种机器学习框架,以优化金属有机框架 (MOF) 复合材料,以消除持久有机污染物 (POP). 它将预测与微观相互作用联系起来,指导高效和可持续的POP修复.

关键词:
DFT计算的计算方法环境复合材料设计设计机器学习 机器学习持久性有机污染物 持久性有机污染物废水整治 废水整治 废水整治 废水整治

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