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纳米聚硅酸铝锌絮凝剂的制备及应用
引用本文:郭雅妮,王丽贤,黄沛,念宁.纳米聚硅酸铝锌絮凝剂的制备及应用[J].环境污染治理技术与设备,2013(11):4435-4439.
作者姓名:郭雅妮  王丽贤  黄沛  念宁
作者单位:[1]西安工程大学环境与化学工程学院,西安710048 [2]中石化西安分公司,西安710086
摘    要:将制备出的聚硅酸铝锌絮凝剂纳米化,在正交实验和单因素优化的基础上,研究了表面活性剂硬脂酸钠的加入量、超声频率、超声时间及投加量对絮凝剂絮凝效果的影响,并且考察了pH、投加量对印染废水的处理效果的影响。结果表明,超声时间对絮凝效果影响最大,超声频率次之,硬脂酸钠含量影响最小。纳米聚硅酸铝锌絮凝剂的最佳制备条件为:表面活性剂硬脂酸钠加入量为0.1%、超声频率为40Hz、超声时间为60min;考虑处理费用,处理印染废水时pH=6~9、投加量为5mL/250mL时效果较好,浊度去除率可达98.5%,色度去除率可达97.4%。

关 键 词:纳米聚硅酸铝锌絮凝剂(Nano—PSAZS)  制备  絮凝效果  优化

Preparation and application of nano-poly-silicate- aluminum-zinc flocculants
Guo YaniI Wang,LixianI Huang,Pei Nian Ning.Preparation and application of nano-poly-silicate- aluminum-zinc flocculants[J].Techniques and Equipment for Environmental Pollution Control,2013(11):4435-4439.
Authors:Guo YaniI Wang  LixianI Huang  Pei Nian Ning
Institution:2 School of Environment and Chemical Engineering, Xi' an Polytechnic University, Xi' an 710048, China 2. Xi' an Branch Company of China Petroleum & Chemical Corporation, Xi' an 710086, China)
Abstract:The poly-silicate-aluminum-zinc flocculants were prepared and nanorized. The effects of sodium stearate surface active agent containing, ultrasonic frequency and ultrasonic time were investigated on the basis of orthogonal experiments and single factor experiments. And the factors which could influence the removal efficien- cy of printing and dyeing wastewater such as pH and the optimum adding quantity were investigated. The results indicated that the effect of ultrasonic time was obvious and the ultrasonic frequency was the second factor. The effect of added surface active agent was little. And the optimum preparation conditions of nano-PSAZS were 0. 1% surface active agent sodium stearate containing, ultrasonic frequency of 40 Hz and ultrasonic time of 60 rain. The optimum adding quantity was 5 mL/250 mL for the economic benefits when it was used in printing and dyeing wastewater treatment ( pH =6 -9). The rernovnl rnto nf tl,~-k;rl;t O~ ~- --J J-__l
Keywords:nano-PSAZS  preparation  flocculation efficiency  optimization
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