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基于径向基函数神经网络优化制备复合改性钠基蒙脱土/橡胶复合材料及其补强-阻燃性能 被引量:1

Optimizing preparation of compound modified Na-montmorillonite/rubber composites based on radial basis function neural network and its reinforcement-flame retardant properties
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摘要 以钠基蒙脱土作为研究对象,以十六烷基三甲基溴化铵与去离子水的混合液、硅烷偶联剂KH550与无水乙醇的混合液作为改性剂,制备复合改性钠基蒙脱土,并将复合改性钠基蒙脱土代替部分炭黑,与促进剂、硫磺、ZnO、硬脂酸、橡胶进行复合,制备复合改性钠基蒙脱土/橡胶复合材料。利用径向基函数(RBF)神经网络模型优化复合改性钠基蒙脱土/橡胶复合材料的制备工艺参数,并且对复合改性钠基蒙脱土和复合改性钠基蒙脱土/橡胶复合材料进行表征与测试。结果表明,当扩展系数为0.50~0.65时,所建立复合改性钠基蒙脱土/橡胶复合材料力学性能和阻燃性能的RBF神经网络模型具有最佳的逼近效果。当去离子水用量为1074g、十六烷基三甲基溴化铵用量为13.7g、无水乙醇用量为14.8g、硅烷偶联剂KH550用量为0.32g、搅拌速度为2890r/min时,复合改性钠基蒙脱土/橡胶复合材料具有良好的力学性能和补强性能,即拉伸强度19.1MPa、撕裂强度43.5kN/m和极限氧指数32.83%。 With Na-montmorillonite as the research object,mixture of cetyl trimethyl ammonium bromide and absolute ethyl alcohol,mixture of silane coupling agent KH550and absolute ethyl alcohol as modifier to prepare compound modified Na-montmorillonite,compound modified Na-montmorillonite/rubber composites were prepared by accelerant,sulfur,zinc oxide,stearic acid,rubber and carbon black partially substituted by compound modified Namontmorillonite.The preparation process parameters of compound modified Na-montmorillonite/rubber composites were optimized by radial basis function(RBF)neural network,compound modified Na-montmorillonite and compound modified Na-montmorillonite/rubber composites were tested and characterized.The results show that RBF neural network of reinforcement properties and the flame retardant property of compound modified Na-montmorillonite/rubber composites have the best approximation effect when“spread coeficient”is 0.50-0.65.Compound modified Na-montmorillonite/rubber composites show good reinforcement properties and flame retardant property(tensile strength of 19.1MPa,tear strength of 43.5kN/m and limit oxygen index of 32.83%)when the amount of deionized water is 1074g,amount of cetyl trimethyl ammonium bromide is 13.7g,amount of absolute ethyl alcohol is 14.8g,amount of silane coupling agent KH550is 0.32g and stirring rate is 2890r/min.
作者 张浩 范威威 徐远迪 ZHANG Hao;FAN Weiwei;XU Yuandi(School of Civil Engineering and Architecture,Anhui University of Technology,Ma’anshan 243032,China;Key Laboratory of Metallurgical Emission Reduction&Resources Recycling,Anhui University of Technology,Ma’anshan 243002,China)
出处 《复合材料学报》 EI CAS CSCD 北大核心 2019年第10期2389-2397,共9页 Acta Materiae Compositae Sinica
基金 中国博士后科学基金(2017M612051) 国家自然科学基金(51206002) 安徽省博士后研究人员科研活动经费(2017B168) 冶金减排与资源综合利用教育部重点实验室(安徽工业大学)项目(KF17-08)
关键词 钠基蒙脱土 RBF神经网络 复合改性 优化制备 补强性能 阻燃性能 Na-montmorillonite RBF neural network compound modified optimizing preparation reinforcement properties flame retardant property
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