低共熔腈基树脂形成机理及其应用研究

The new generation of advanced composite materials for high-speed aircraft, with low cost and high performance, put forward a special requirement to the matrix resin, which need to have the three excellent performances simultaneously- high temperature resistance, excellent mechanical properties and suitable to liquid composite molding at low temperature. However, a large number of studies show that the three performances have mutual checks and balances among each other. In other words, no resin can have the three excellent performances at the same time. However, the author's previous research showed that the novel phthalonitrile(PN), with a lower eutectic point, can possess the three excellent performances simultaneously. Therefore, it is need to study the formation mechanism of the novel eutectic PN, which maybe originate from the intermolecular forces other than hydrogen bond. Based on the understanding of the formation mechanism, a deep-synergy among the three performances may be achieved. Taking the key molecular structure parameters as input variables, obtained from the formation mechanism study of the eutectic PN, the neural network model for predicting melting point and viscosity of eutectic PN can be established. Then, an optimization model of new eutectic PN can be established through genetic algorithm and neural network. Based on the optimization model, a new eutectic PN with more excellent three performances can be designed. The mechanism and model disclosed in this study can not only relieve the conflict among the three properties, but also can be applied to develop other high performance resins. Therefore, new advanced composite materials for high-speed aircraft can be developed based on the new high performance eutectic resins.

高性能、低成本树脂基复合材料是新一代高速飞行器的关键材料，其树脂基体须同时具备耐高温、力学性能优良、低温液相成型特性，但这三方面的性能互相存在制衡关系，难以兼备。申请人前期工作已初步证实了利用低共熔技术解决高性能腈基树脂三性能间矛盾的可行性。本项目以前期获得的低共熔腈基树脂为对象，从分子层面深入研究这种非氢键主导作用下低共熔树脂的形成机理及影响机制，期望实现高性能树脂耐热性、力学性能及液相成型之间的深入协同；以获得的分子关键结构参数为变量，建立低共熔树脂熔点和粘度预测的神经网络模型，在此基础上，借助遗传算法建立新型低共熔树脂的优化设计模型；基于优化模型设计高性能低共熔腈基树脂体系。本项目揭示的低共熔机理及所建模型不仅可深入调和低共熔腈基树脂的三性能间矛盾，还有望推广应用至其他高性能树脂体系，支撑新一代高速飞行器用先进树脂基复合材料的研制。

耐高温、力学性能优良、可低温液相成型的高性能树脂体系是先进树脂基复合材料研制的关键。但这三方面的性能互相存在制衡关系，难以兼备。本项目从分子层面深入研究非氢键主导作用下低共熔树脂的形成机理，获得对低共熔树脂定性和定量的深入认识，并利用该认识指导了新型高性能NPN树脂的设计与合成。.首先，从分子结构的角度，本项目获取了自制9种腈基树脂单体的6种分子结构参数，并对其进行二元体系的数学处理。用SPSS中的因子分析模块对其进行主成分分析，结果显示降维后的前2个主成分能够代表之前6个分子结构参数90%的信息；用Isight中的DOE模块对其与低共熔度进行灵敏度分析，结果表明与低共熔度关联性最大的分子结构参数为LUMO能、HOMO能以及LUMO、HOMO能差值。.然后以关键分子结构参数为输入，低共熔度为输出，建立GA-BP神经网络获得二者间的量化关系模型。模型结果显示，选用减法处理后的主成分作为输入参数，最佳模型R2取值为0.990，且低共熔度预测相对误差在5%以内。同时给出最高86.7℃的优化低共熔度，相比于实验所得最大值48.5℃提升近40℃。当第一主成分取值为0.23~0.38和第二主成分取值为0.25~0.97之间时，二元低共熔物的优化低共熔度可达85.2~86.7℃之间。.接着，从分子间相互作用力的角度，用Gaussian计算出二元低共熔物之间的相互作用能。建立相互作用能与低共熔度间的GA-BP神经网络，模型结果显示，最佳模型R2取值为0.990，且低共熔度预测相对误差在5%以内。同时给出最高76.9℃的优化低共熔度，相比于实验所得最大值48.5℃提升近30℃。当相互作用能取值在−5.84~−5.01kcal/mol之间时，低共熔度可达75.5~76.9℃之间。.基于低共熔形成机理的深入认识结果，本项目设计将邻苯二甲腈与酚羟基融合在一个分子结构内——预聚物NPN，并实验合成。工艺性、耐热性测试结果显示，NPN既有很好的工艺性，又有很好的耐温性，这说明本项目认识的低共熔机理确实可以有效指导新型高性能树脂的设计与合成，同时也说明这一理论认识也可以不局限于腈基树脂，对于腈基/氰酸酯基杂化树脂也有很好的指导意义。