摘要
一直以来膜污染都是膜过滤技术中亟待解决的问题,新型的膜污染表征定量技术的开发有助于对膜污染过程的深入了解,并为膜污染控制提供参考.本研究开发了采用前表面荧光法对有机膜污染物质进行直接测量的表征方法.以牛血清蛋白(BSA)为标准污染物进行聚偏二氟乙烯膜(PVDF)的超滤实验,结合使用平行因子分析法,对超滤过程中膜表面累积的污染物进行定量,并评估其准确性.实验证实前表面三维荧光法能够准确地定量黏附在膜表面的BSA污染物,表征结果表明,在膜污染初期BSA的黏附相对较慢,随着过滤进行,膜表面形成滤饼层,黏附作用逐渐加快,造成膜阻力的增大也越来越快.用前表面三维荧光法定量有机膜污染物质,操作简便且准确直观,有望为膜污染的深入研究及膜污染的在线检测提供技术支撑.
Membrane fouling has always been an urgent issue to be tackled in membrane filtration field.The development of new characterization technology of membrane fouling is beneficial for understanding its process and provides reference for its control.This research tried to characterize organic membrane foulants directly through the front-face fluorescence excitation-emission matrix(FF-EEM).Bovine Serum Albumin(BSA),as the standard foulant,was used with Polyvinylidene fluoride(PVDF)membrane for this ultrafiltration experiment.The FF-EEM coupled with parallel factor analysis(PARAFAC)quantified the foulants accumulated on the surface of the membrane during the experiment.The research confirmed the validity of the application of FF-EEM on membrane foulants characterization.The result showed that the BSA deposition rate was relatively slow at the initial stage of the experiment,while as the filtration went on,a filter cake layer was formed on the surface of the membrane and the BSA deposition rate got faster,which led to more filtration resistance.It proved that FF-EEM is accurate and convenient in the characterization of the membrane foulants,and is expected to provide technical support for further research studies and online detection of organic membrane fouling.
作者
吴梓坚
余华荣
梁恒
WU Zijian;YU Huarong;LIANG Heng(State Key Laboratory of Urban Water Resource and Environment (Harbin Institute of Technology), Harbin 150090, China)
出处
《哈尔滨工业大学学报》
EI
CAS
CSCD
北大核心
2019年第2期22-26,共5页
Journal of Harbin Institute of Technology
基金
国家自然科学基金面上项目(51778170)
国家重点研发计划课题(2016YFC0305404)
关键词
超滤
有机膜污染
表征
前表面三维荧光
平行因子分析
ultrafiltration
organic membrane fouling
characterization
front-face fluorescence excitation-emission matrix(FF-EEM)
parallel factor analysis(PARAFAC)