Nguyen Tung Huy, Nguyen Nhung Thi, Nguyen Thao Thi Phuong, Doan Ngoc Thi, Tran Lam Anh Thi, Nguyen Linh Pham Duy, Bui Thanh Tien
Center for Polymer Composite and Paper, School of Chemical Engineering, Hanoi University of Science and Technology, Hai Ba Trung District, Hanoi 11600, Vietnam.
Polymers (Basel). 2022 Jul 14;14(14):2866. doi: 10.3390/polym14142866.
Cationic polyacrylamide (CPAM) emulsifier is widely applied in the wastewater treatment industry, mining industry, paper industry, cosmetic chemistry, etc. However, optimization of input parameters in the synthesis of CPAM by using the traditional approach (i.e., changing one factor while leaving the others fixed at a particular set of conditions) would require a long time and a high cost of input materials. Onsite mass production of CPAM requires fast optimization of input parameters (i.e., stirring speed, reaction temperature and time, the amount of initiator, etc.) to minimize the production cost of specific-molecular-weight CPAM. Therefore, in this study, we synthesized CPAM using reverse emulsion copolymerization, and proposed response surface models for predicting the average molecular weight and reaction yield based on those input parameters. This study offers a time-saving tool for onsite mass production of specific-molecular-weight CPAM. Based on our response surface models, we obtained the optimal conditions for the synthesis of CPAM emulsions, which yielded medium-molecular-weight polymers and high conversion, with a reaction temperature of 60-62 °C, stirring speed of 2500-2600 rpm, and reaction time of 7 h. Quadratic models showed a good fit for predicting molecular weight (Adj.R = 0.9888, coefficient of variation = 2.08%) and reaction yield (Adj.R = 0.9982, coefficient of variation = 0.50%). The models suggested by our study would benefit the cost-minimization of CPAM mass production, where one could find optimal conditions for synthesizing different molecular weights of CPAM more quickly than via the traditional approach.
阳离子聚丙烯酰胺(CPAM)乳化剂广泛应用于废水处理行业、采矿业、造纸工业、化妆品化学等领域。然而,采用传统方法合成CPAM时(即在特定条件下固定其他因素,仅改变一个因素),优化输入参数需要很长时间且原料成本高昂。CPAM的现场大规模生产需要快速优化输入参数(即搅拌速度、反应温度和时间、引发剂用量等),以将特定分子量CPAM的生产成本降至最低。因此,在本研究中,我们采用反相乳液共聚法合成了CPAM,并基于这些输入参数提出了用于预测平均分子量和反应产率的响应面模型。本研究为现场大规模生产特定分子量的CPAM提供了一种节省时间的工具。基于我们的响应面模型,我们获得了合成CPAM乳液的最佳条件,该条件下可得到中分子量聚合物且转化率高,反应温度为60 - 62°C,搅拌速度为2500 - 2600 rpm,反应时间为7 h。二次模型对预测分子量(调整后R = 0.9888,变异系数 = 2.08%)和反应产率(调整后R = 0.9982,变异系数 = 0.50%)显示出良好的拟合效果。我们研究提出的模型将有助于CPAM大规模生产的成本最小化,在此过程中,人们可以比通过传统方法更快地找到合成不同分子量CPAM的最佳条件。