Next Generation Fibre-Reinforced Composites: a Full Scale Redesign for Compression

高性能纤维增强聚合物复合材料是目前最先进的轻量化结构，其用途呈指数级增长，从航空航天到体育用品的广泛应用。它们具有出色的机械性能：高强度和刚度，低重量，低疲劳和腐蚀敏感性。使用纤维形式的高强度、高刚度材料可以减轻过早脆性破坏的趋势，使部件能够在低温或中等温度下形成，并使各向异性设计能够满足主要的承载要求。纤维在单轴拉伸时特别有效，但在压缩下，复合材料遭受一系列失效，通常与纤维微屈曲或扭结有关，与基体或界面问题有关；这些机制以复杂的方式在各种物理长度尺度上耦合。通常，这些类型的失效决定了复合材料的实际使用，并设定了设计限制，远远低于组成纤维的预期内在性能。另一方面，新的成分和工艺正在变得可用，使复合结构的定向组装成为可能，控制在比以前更大的长度范围内。因此，原则上，复合材料应该重新设计，以利用这些机会来抑制或重定向压缩中的破坏过程。天然材料，如木材和骨骼，是完全分层的，在每一个可能的放大倍数下都具有精确的结构特征。人造复合材料缺乏这种灵活性，但可以利用内在优越的成分。可视化、计算和控制结构的能力日益增强，包括定量精度，将使新一代复合材料得以开发。我们的目标是通过设计这样的分层压缩系统来实现纤维的全部内在潜力，从第一原理出发，利用材料、加工、表征和机械过程建模方面的最新发展。该方案侧重于提高复合材料在压缩中的绝对性能的挑战，既要解决当前材料的实际限制，并作为定量分层材料设计价值的示范。在本课程期间开发的工具和材料将在一系列其他情况下有用。这项工作将在每个长度尺度上开发和嵌入结构，从矩阵分子到最终组件的铺设，使用新的成分和新的架构，设计一个新的分析框架。该方案将受益于核心项目期间的高度创造性和跨学科方法，并得到主要国际顾问和合作者的贡献。一个广泛的工业伙伴团体将为该项目作出贡献，并在方案期间设计的概念示范的基础上帮助发展产出。科学和技术成果将在国内和国际上广泛传播，有助于确保英国在这一关键领域的领导地位。

High performance fibre-reinforced polymer composites are the current state-of-the-art for lightweight structures and their use is rising exponentially in a wide range of applications from aerospace to sporting goods. They offer outstanding mechanical properties: high strength and stiffness, low weight, and low susceptibility to fatigue and corrosion. The use of high strength, high stiffness materials in fibre form mitigates the tendency for premature brittle failure, enables components to be formed at low or moderate temperatures, and enables anisotropic designs to target the primary load-carrying demands. Fibres are particularly efficient in uniaxial tension but, under compression, composites suffer a range of failures typically associated with fibre micro-buckling or kinking, linked to matrix or interfacial issues; these mechanisms couple in a complicated way at a variety of physical lengthscales. Often, these types of failure determine the practical usage of composites and set design limits well below the expected intrinsic performance of the constituent fibres. On the other hand, new constituents and processes are becoming available that enable the directed assembly of composite structures, controlled across a much wider range of lengthscales than previously possible. In principle, then, composite materials should be redesigned to take advantage of these opportunities to supress or redirect the failure process in compression. Natural materials, such as wood and bone, are fully hierarchical, with precise structural features resolved at every possible magnification. Artificial composites lack this dexterity but can exploit intrinsically superior constituents. The increasing ability to visualise, calculate, and control structures, including with quantitative precision, will allow a new generation of composite materials to be developed. The ambition is to realise the full intrinsic potential of the fibres by designing such hierarchical systems for compression, from first principles, exploiting the latest developments in materials, processing, characterisation, and modelling of mechanistic processes.This programme focusses on the challenge of improving the absolute performance of composites in compression, both to address practical limitations of current materials, and as a demonstration of the value of quantitative hierarchical materials design. Tools and materials developed during this programme will be useful in a range of other contexts. The work will develop and embed structure at every lengthscale from the molecules of the matrix, to the lay-up of final components, using new constituents and new architectures, designed with a new analytical framework. The programme will benefit from a highly creative and interdisciplinary approach amongst the core project term, amplified by contributions from leading international advisors and collaborators. An extensive group of industrial partners will contribute to the project, and help to develop the outputs, building on concept demonstrators designed during the programme. The scientific and technical results will be widely disseminated nationally and internationally, helping to ensure UK leadership in this key field.