Collaborative Research: Mechanics of Hybrid Random Fiber Networks

这笔赠款将支持关于聚合物细丝随机网络力学的研究和教育，这些网络由坚硬的颗粒增强。纤维网络是许多合成和天然材料的主要结构成分：聚合物或生物纤维和含有刚性夹杂物的纳米纤维广泛存在于生物组织、组织支架、生物医学植入物、静电纺丝空气过滤系统、纤维素产品等中。这些纤维体系大多形成了嵌入非纤维实体的复合材料。虽然连续介质基复合材料已经得到了广泛的研究，但具有离散矩阵的混合网络的力学至今还没有得到关注，尽管有太多的应用。这项研究的结果将影响纤维网络的广泛应用的设计，如非织造布、凝胶、橡胶、组织支架、纤维素产品等，以及我们对由异质随机网络组成的丰富的生物系统的力学行为的理解。在教育方面，一个面向高中生、本科生和研究生的计算活动和动手实验室实验的项目将包括以下几个方面的研究：(I)建立混杂纤维网络的结构-性质关系；(Ii)将具有连续矩阵的复合材料的理论扩展到其中的基质为离散纤维网络的复合材料；(Iii)建立实验研究纤维材料及其复合材料的新方法。连续体基复合材料的理论将扩展到混杂材料中，其中的基质是由不同于主网络(基质)的颗粒或纤维增强的纤维网络。因此，可以找到有效的方法来加固体积分数较小的网络，从而显著提高复合材料的刚度和强度。首先，实验和计算模型将评估孤立填充物对随机网络变形场的扰动，以建立网络的等价EShelby解。然后，探索填料浓度对小应变和大应变力学响应和网络强度的影响，以建立有效的混合网络均化方法。使用上述系统进行的受控实验的数据将用于验证数值模型，然后将用于广泛探索由网络和填充参数定义的设计空间。该奖项反映了NSF的法定使命，并已通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This grant will support research and education on the mechanics of random networks of polymeric filaments, which are reinforced with hard particles. Fiber networks are the main structural component of many synthetic and natural materials: polymeric or biological fibers and nanofibers with rigid inclusions are omnipresent in biological tissues, tissue scaffolds, biomedical implants, electrospun air filtration systems, cellulose products, etc. Most of these fibrous systems form composites with embedded non-fibrous entities. While continuum matrix composites have been studied extensively, the mechanics of hybrid networks with a discrete matrix has received no attention to date, despite the plethora of applications. The results of this research will influence the design of a wide range of applications of fibrous networks, such as non-wovens, gels, rubber, tissue scaffolds, cellulose products, etc. as well as our understanding of the mechanical behavior of a wealth of biological systems which are comprised of heterogeneous random networks. On the educational front, a program geared towards high school, undergraduate and graduate students with computational activities and hands on laboratory experiments will include several aspects of this research.This research will (i) establish structure-property relations of hybrid fiber networks, (ii) extend the theory of composites with continuum matrices to composites in which the matrix is a discrete fiber network, (iii) establish new methods to experimentally investigate fibrous materials and their composites. The theory of continuum matrix composites will be extended to hybrid materials in which the matrix is a fiber network reinforced with particles or fibers of different properties from those of the main network (matrix). Thereby, effective ways will be identified to reinforce networks with small volume fractions of fillers, and concomitantly improve dramatically on the composite stiffness and strength. First, experiments and computational modeling will evaluate the perturbation introduced by an isolated filler to the deformation fields of stochastic networks in order to establish an equivalent Eshelby solution for networks. Then, the effect of filler concentration on the small and large strain mechanical response and network strength will be explored to establish effective homogenization methods for hybrid networks. Data from controlled experiments performed with the aforementioned systems will be used to validate the numerical models, which will be then used to broadly explore the design space defined by the network and filler parameters.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.