麻纤维化学成分与结构形貌对纤维力学及复合材料界面性能的影响机制

Bast fiber composites have attracted wide attention due to their advantages of environmental protection, high mechanical properties, and low cost. The property difference between different batches of the bast fiber results in the instability of the mechanical properties of fibers and composites. It has become a consensus in the field of natural fiber composites to classify the bast fibers and implement relevant theories and basic research. However, due to the unique multi-scale structural characteristics of bast fiber, it is difficult to characterize the bast fiber structure fully and quantitatively. This project intends to use bast fiber and unsaturated polyester resin as the research object, taking the fiber chemical composition as the entry point, using near-infrared technology and partial least squares method to construct the content correction model of bast fiber, and explaining the effect mechanism of bsat fiber components on the internal and surface structure of fibers. The grey correlation analysis will be used to reveal the internal and surface structure changes during the bast fiber stretching process, and the influence mechanism of chemical composition and structure on bast fiber/resin interface will be studied. By using genetic algorithm to improve support vector machine nonlinear dynamic system, the response mechanism model of bast fiber mechanics and interfacial properties on fiber chemical composition and structure morphology will be constructed. It provides data and theoretical reference for bast fiber used in composites classification and grading, which has important environmental, economic and practical significance.

麻纤维复合材料因环保、力学性能高、价格低廉等优点而受到广泛关注。但麻纤维批次之间性能差异显著，导致纤维及其复合材料的力学性能稳定性差。对麻纤维进行分等、分级，并开展相关理论和基础研究，已成为天然纤维复合材料领域的共识。但因麻纤维自身独特的多尺度结构特点，对麻纤维结构形貌全面且量化的表征存在较大困难。本项目拟以麻纤维和不饱和聚酯树脂为研究对象，以纤维化学成分为切入点，采用近红外漫反射光谱技术结合偏最小二乘法构建麻纤维各成分含量校正模型，阐述麻纤维成分对纤维内部和表面结构形貌的影响机理，借助灰关联分析法揭示麻纤维拉伸过程中内部及表面结构的变化规律，研究化学成分及结构形貌对麻纤维/树脂界面作用的影响机制，采用遗传算法改进支持向量机非线性动力系统，构建麻纤维力学及复合材料界面性能对纤维化学成分及结构形貌的响应机制模型，为复合材料用麻纤维分等、分级提供数据和理论参考，具有重要的环保、经济和现实意义。

麻纤维复合材料因环保、力学性能高、价格低廉等优点而受到广泛关注。但麻纤维批次之间性能差异显著，导致纤维及其复合材料的力学性能稳定性差。对麻纤维进行分等分级，并开展相关理论和基础研究，已成为天然纤维复合材料领域的共识。但因麻纤维自身独特的多尺度结构特点，对麻纤维结构形貌全面且量化表征存在较大困难。.本项目从纤维化学成分角度入手，以湿化学分析法为基础，开展了麻纤维化学成分与结构形貌对纤维力学及复合材料界面性能的影响机制的研究，采用灰关联分析法揭示了麻纤维化学成分与微观结构以及宏观性能参数之间的关联机制，进一步明确了纤维素、半纤维素、木质素是决定纤维及纤维-树脂界面性能的关键因素。通过分级去除纤维中的化学成分，结合SEM、FTIR、TG及应力-应变曲线分析阐述了各主要化学成分对纤维性能的影响机制。以近红外光谱为化学成分特征值采集方式，构建了基于近红外光谱特征峰值的纤维素、半纤维素、木质素成分含量偏最小二乘校正模型，化学成分预测误差低于8.21%，为实现麻纤维化学成分的快速分析奠定了基础。.以麻纤维化学成分为自变量构建了麻纤维拉伸强度和界面结合强度支持向量机预测模型，预测绝对误差分别为7.18%和2.53%。本项目研究为实现麻纤维原料性能快速表征、快速分级及复合材料性能的预测奠定了基础，使其在高性能复合材料领域应用成为可能，具有重要的环保、经济和现实意义。.项目执行期间，累计获得国家科技进步二等奖1项，省部级科技奖励5项，获8项国家发明专利授权，出版专著1部，发表论文20余篇，其中SCI收录8篇，EI收录7篇，英文章节2个，培养毕业博士研究生1名，毕业硕士研究生9名。