超疏水多孔有机聚合物的制备及油-水分离性能
Preparation and Oil-water Separation Performance of Superhydrophobic Porous Organic Polymers
高昌源 1向婷婷 1陈士欣 1孙琪琪 1王佳乐 1郑桂月 2赵子谊 1刘子煜 1崔博 2闫卓君 2布乃顺 1武悦3
作者信息
- 1. 辽宁大学环境学院,沈阳 110036
- 2. 辽宁大学化学院,沈阳 110036
- 3. 辽宁省地质勘探矿业集团有限责任公司,沈阳 110032
- 折叠
摘要
以四(三苯基膦)钯为催化剂,N,N-二甲基甲酰胺为溶剂,通过三(4-硼酸频呢醇酯苯基)胺与3,6-二溴咔唑的Suzuki偶联反应合成了一种超疏水多孔有机聚合物LNU-40.该聚合物的比表面积为32 m2/g,具有良好的热稳定性且在常见有机溶剂中不溶解或分解.LNU-40具有较低的表面能和152.4°的水接触角,表现出较好的酸碱环境抵御能力,能够制备具有优异自清洁性能的超疏水表面.使用LNU-40制成的超疏水柔性织物对有机溶剂的分离效率可达90%以上,对油的吸附能力可达其自身质量的3～8倍,吸附分离性能优越,可用于石油化工、食品及制药等行业含油等有机溶剂废水的油-水分离处理.
Abstract
A superhydrophobic porous organic polymer denominated as LNU-40 was synthesized via a Suzuki coupling reaction of 4-(4,4,5,5-tetramethyl-1,3,2-dioxaborolan-2-yl)-N,N-bis[4-(4,4,5,5-tetramethyl-1,3,2-dioxaborolan-2-yl)phenyl]aniline,3,6-dibromocarbazole,tetrakis(triphenylphosphine)-palladium,and N,N-dimethyl-2-(piperazin-1-yl)benzamide oxalate.LNU-40 possesses a specific surface area of 32 m2/g and manifests thermal stability.Dissolution or decomposition does not occur when it is dispersed in commonly encountered organic solvents.LNU-40 is characterized by a low surface energy and a water contact angle of 152.4°,demonstrating excellent resistance to acidic and alkaline environments.This property enables the fabrication of a superhydrophobic surface with outstanding self-cleaning capabilities.The superhydrophobic flexible fabric prepared with LNU-40 achieves a separation efficiency of over 90%for organic solvents and exhibits an oil adsorption capacity ranging from 3 to 8 times of its own mass.The superior adsorption and separation performance make it suitable for the treatment of oily wastewater containing organic solvents in industries such as petrochemicals,food,and pharmaceuticals.
关键词
超疏水多孔有机聚合物/共轭结构/油-水分离性能Key words
Superhydrophobic porous organic polymer/Conjugated structure/Oil-water separation引用本文复制引用
基金项目
国家自然科学基金(31972522)
辽宁省自然科学基金(2021-MS-149)
"兴辽英才计划"青年拔尖人才项目(XLYC2007032)
辽宁润中供水有限责任公司课题()
黑龙江省寒区湿地生态与环境研究重点实验室开放基金()
辽宁大学大学生创新创业训练计划()
出版年
2024
国家科技期刊平台
NSTL
万方数据