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扩链型低温固化双马来酰亚胺树脂配方的优化设计 被引量:1

On Improving Toughness of Low Temperature Curable Bismaleimide Resin with Chain-Extending Method
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摘要 引发剂可改进双马来酰亚胺树脂固化温度高的缺点,但树脂脆性仍大。作者试用二元胺对双马单体进行扩链改性,同时用引发剂降低固化温度,以期得到韧性较好的低温固化耐热双马树脂基体。本文运用计算机辅助二元二次回归正交设计的方法,优化扩链型低温固化双马树脂的配方。经9组实验和数据处理,得到树脂性能与组分配比的回归方程,并以此绘出性能──配比的立体曲面图。方差分析表明回归方程的显著性较好。优化配方的树脂浇铸体和复合材料具有较优异的性能。 Having succeeded in lowering cure temperature of bismaleimide resin with suitable initiator[3],we, after careful consideration, believe that its resulting but undesirable brittleness can be much reduced with chain-extending method. We do achieve significant reduction of brittleness. We apply well-known mathematical technique, orthogonal resresslon design,in conjunction with chain-extending method to achieve our objective. The four components selected are: 4, 4'- bismaleimidodiphenylmethane, diamine, 3,3'-diallylbisphenol A and low viscosity reactive additive. Regression eqs. (6), (7) and (8) with good reliabilities of 75%, 75%, and 99% respectively are obtained. Suitable component formulation can be selected with the help of Figs. 2, 3 and 4, corresponding to eqs. (6), (7) and (8) respectively.The surfaces in Figs. 2,3 and 4 show the effect of ratios of component quantities on flexural strength, impact strength and heat distortion temperature (HDT ) respectively. A further lowering of cure temperature from 160℃ to 150℃ is achieved. Table 3 compares the properties before and after the proper application of chain-extending method. Properties of both cact resin and glass fiber reinforced composites are given. LcXu 292 denotes properties for the low cure temperature of 160℃ attained previously by us, and BDDD denotes the properties for the low cure temperature of 150℃ now attained. With the exception of HDT decreasing from 300 ℃ to 272℃, the properties are much improved.
机构地区 西北工业大学
出处 《西北工业大学学报》 EI CAS CSCD 北大核心 1996年第3期329-334,共6页 Journal of Northwestern Polytechnical University
关键词 马来酰亚胺树脂 扩链 固化 配方 优化设计 bismaleimide resin, chain-extending method, low temperature cure, orthogonal regression design
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