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Polymer damage mitigation---predictive lifetime models of polymer insulation degradation and biorenewable thermosets through cationic polymerization for self-healing applications.

机译:减轻聚合物损伤-聚合物绝缘降解和可阳离子固化的生物可再生热固性塑料的寿命预测模型,可用于自修复。

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摘要

Over the past 50 years, the industrial development and applications for polymers and polymer composites has become expansive. However, as with any young technology, the techniques for predicting material damage and resolving material failure are in need of continued development and refinement. This thesis work takes two approaches to polymer damage mitigation—material lifetime prediction and spontaneous damage repair through self-healing while incorporating bio-renewable feedstock. First, material lifetime prediction offers the benefit of identifying and isolating material failures before the effects of damage results in catastrophic failure. Second, self-healing provides a systematic approach to repairing damaged polymer composites, specifically in applications where a hands-on approach or removing the part from service are not feasible.;With regard to lifetime prediction, we investigated three specific polymeric materials—polytetrafluoroethylene (PTFE), poly(ethylene-alt-tetrafluoroethylene) (ETFE), and Kapton. All three have been utilized extensively in the aerospace field as a wire insulation coating. Because of the vast amount of electrical wiring used in aerospace constructions and the potential for electrical and thermal failure, this work develops mathematical models for both the thermal degradation kinetics as well as a lifetime prediction model for electrothermal breakdown. Isoconversional kinetic methods, which plot activation energy as a function of the extent of degradation, present insight into the development each kinetic model. The models for PTFE, ETFE, and Kapton are one step, consecutive three-step, and competitive and consecutive five-step respectively. Statistical analysis shows that an nth order autocatalytic reaction best defined the reaction kinetics for each polymer's degradation.;Self-healing polymers arrest crack propagation through the use of an imbedded adhesive that reacts when cracks form. This form of damage mitigation focuses on repairing damage before the damage causes a failure in the polymer's function. In this work, the healing agent (adhesive) is developed using bio-renewable oils instead of solely relying on petroleum based feedstocks. Several bio-renewable thermosetting polymers were successfully prepared from tung oil through cationic polymerization for the use as the healing agent in self-healing microencapsulated applications. Modifications to both the monomers in the resin and the catalyst for polymerization were made and the subsequent changes to mechanical, thermal, and structural properties were identified. Furthermore, compressive lap shear testing was used to confirm that the adhesive properties would be beneficial for self-healing applications. Finally, scanning electron microscopy of the crack plane was used to study the fracture mechanism of the crack.
机译:在过去的50年中,聚合物和聚合物复合材料的工业发展和应用已经变得广阔。但是,与任何年轻技术一样,预测材料损坏和解决材料故障的技术也需要不断发展和完善。这项工作采用两种方法来减轻聚合物的损害:材料寿命的预测和在结合生物可再生原料的同时通过自我修复的自然修复作用。首先,材料寿命预测的好处是可以在损坏的影响导致灾难性故障之前识别和隔离材料故障。其次,自修复技术提供了一种修复受损聚合物复合材料的系统方法,特别是在无法动手操作或将零件从服务中移除的应用中。;关于寿命预测,我们研究了三种特殊的聚合物材料-聚四氟乙烯( PTFE),聚(乙烯-alt-四氟乙烯)(ETFE)和Kapton。这三种材料在航空航天领域已被广泛用作电线绝缘涂层。由于用于航空航天构造的大量电线以及潜在的电气和热故障,这项工作为热降解动力学以及电热击穿寿命预测模型开发了数学模型。等转化动力学方法绘制活化能与降解程度的函数关系图,从而为开发每种动力学模型提供了见识。 PTFE,ETFE和Kapton的模型分别为一步,连续三步,竞争和连续五步。统计分析表明,n级自催化反应最能确定每种聚合物降解的反应动力学。自愈聚合物通过使用嵌入的粘合剂阻止裂纹扩展,该粘合剂在形成裂纹时会发生反应。减轻损害的这种形式集中于在损害引起聚合物功能失效之前修复损害。在这项工作中,使用生物可再生油开发了治愈剂(胶粘剂),而不是仅仅依靠石油基原料。从桐油通过阳离子聚合成功地制备了几种生物可更新的热固性聚合物,用作自修复微囊化应用中的治愈剂。对树脂中的单体和用于聚合的催化剂都进行了改性,并确定了机械,热和结构性能的后续变化。此外,使用压缩搭接剪切测试来确认粘合性能对于自修复应用将是有益的。最后,利用裂纹面的扫描电子显微镜研究了裂纹的断裂机理。

著录项

  • 作者

    Hondred, Peter Raymond.;

  • 作者单位

    Iowa State University.;

  • 授予单位 Iowa State University.;
  • 学科 Chemistry Polymer.;Engineering Materials Science.
  • 学位 Ph.D.
  • 年度 2013
  • 页码 200 p.
  • 总页数 200
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:40:45

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