Feasibility Study: Statistical Modelling of Microstructural Variables in Particulate Filled Composite Materials

随着纳米技术的发展，颗粒增强聚合物正成为一类越来越重要的材料。现代材料可以是多种尺度的复合材料，既包含纤维又包含颗粒。颗粒相的微观结构可以非常不同。这些变化包括改变颗粒大小和分布。本可行性研究的总体目标是探索统计建模在确定颗粒复合材料力学性能的微观结构依赖性方面的作用。本可行性研究中包括的微观结构参数为粒度和粒度分布。这项建议是受到目前正在进行的工作的启发。为了从颗粒改性的聚合物获得最佳性能，认为颗粒应该良好分散，并且每个颗粒应该被聚合物润湿。如果不是这种情况，则附聚物将作为缺陷，导致性能降低而不是任何增强。受差分散影响的材料特性包括弹性特性（例如刚度）、强度、断裂行为、渗透性和传导性。在制备制剂时，实现良好的分散是一个主要挑战。由于高表面积和与基质聚合物的不相容性，通常颗粒，尤其是纳米颗粒的分散是困难的，并且通常需要表面处理或相容剂。然而，即使使用超声处理或高剪切混合，这也不能保证获得良好的稳定分散体。一旦发生团聚，团聚体就很难破碎。评估分散程度是非常主观的，分散程度可能会因长度尺度而异。例如，样品可能在宏观尺度上看起来均匀，但电子显微镜可能表明颗粒在微米或纳米尺度上聚集。消除这种主观性所需要的是量化分散程度的参数的数值。然而，据调查人员所知，没有定量方法来评估颗粒的分散。目前使用的定性方法通常依赖于操作员的意见，因此一个人的“好”分散是“差”的其他人。提供数值来描述分散程度的能力将允许更快地筛选颗粒表面处理并改进工艺控制。它将使学术界和工业界有能力评估和跟踪集聚的演变，而不带有目前方法的主观性。

Particulate reinforced polymers are becoming an increasingly important class of materials particularly with the development of nanotechnology. Modern materials may be composites on many scales containing both fibres and particles. The microstructure of the particulate phase can be very varied. These variations include both changing particle size and distribution. The overall aim of this feasibility study is to explore the role of statistical modelling in defining the microstructural dependence of the mechanical properties of particulate composite materials. The microstructural parameters which will be included in this feasibility study will be particle size and particle distribution. This proposal has been inspired by work currently being undertaken. To obtain the best properties from a particle-modified polymer, it is considered that the particles should be well-dispersed, and each particle should be wetted by the polymer. If this is not the case, then the agglomerates will act as defects resulting in a reduction in performance rather than any enhancement. The material properties affected by poor dispersion include elastic properties (such as stiffness); strength; fracture behaviour, permeability and conductivity. Achieving a good dispersion is a major challenge when preparing formulations. The dispersion of particles in general, and especially nanoparticles, is difficult due to the high surface area and incompatability with the matrix polymer, and generally a surface treatment or compatabiliser is required. However, this does not guarantee that a good stable dispersion will be achieved even when ultrasonication or high-shear mixing is used. Once agglomeration occurs it is very difficult to break up the agglomerates.Assessing the degree of dispersion is very subjective, and the dispersion may vary across the length scales. For example a sample may look homogeneous at the macroscale, but electron microscopy may indicate that the particles are agglomerated at the micro- or nanoscale. What is required to remove this subjectivity is a numerical value of a parameter that quantifies the degree of dispersion. However, to the investigators' knowledge, there are no quantitative methods to assess the dispersion of particles. The qualitative methods currently used generally rely on an operator's opinion, and hence one person's 'good' dispersion is 'poor' to someone else. The ability to provide a numerical value to describe the degree of dispersion will allow faster screening of surface treatments for particles and improved process control. It will provide both academia and industry with the ability to assess and follow the evolution of agglomeration, without the subjectivity attached to current methods.