文献类型：期刊文献

英文题名：Preparation and crystallization kinetics of micron-sized Mg(OH)2 in a mixed suspension mixed product removal crystallizer

作者：Song, Xingfu[1];Tong, Kefeng[1];Sun, Shuying[1];Sun, Ze[1];Vu, Jianguo[1]

机构：[1]E China Univ Sci & Technol, Natl Engn Res Ctr Integrated Utilizat Salt Lake R, Shanghai 200237, Peoples R China

年份：2013

卷号：7

期号：2

起止页码：130

外文期刊名：FRONTIERS OF CHEMICAL SCIENCE AND ENGINEERING

收录：;WOS:【SCI-EXPANDED(收录号:WOS:000209385700002)】；

基金：This work was supported by the Shanghai Natural Science Foundation (09ZR147900) and the Program for New Century Excellent Talents in University (NCET-08-0776).

语种：英文

外文关键词：magnesium hydroxide; precipitation; micronsized; crystallization kinetics

摘要：Magnesium hydroxide is an important chemical, and is usually obtained from seawater or brine via precipitation process. The particle size distribution of magnesium hydroxide has great effects on the subsequent filtration and drying processes. In this paper, micron-sized magnesium hydroxide with high purity, large particle size and low water content in filter cake was synthesized via simple wet precipitation in a mixed suspension mixed product removal (MSMPR) crystallizer. The effects of reactant concentration, residence time and impurities on the properties of magnesium hydroxide were investigated by X-Ray diffraction (XRD), Scanning Electron Microscopy (SEM) and Malvern laser particle size analyzer. The results show that NaOH concentration and residence time have great effects on the water content and particle size of Mg(OH)(2). The spherical Mg(OH)(2) with uniform diameter of about 30 mu m was obtained with purity higher than 99% and water content less than 31%. Furthermore, the crystallization kinetics based on the population balance theory was studied to provide the theoretical data for industrial enlargement, and the simulation coefficients (R-2) based on ASL model and C-R model are 0.9962 and 0.9972, respectively, indicating that the crystal growth rate of magnesium hydroxide can be well simulated by the sizedependent growth models.