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.
