Engineering and modeling carbon nanofiller-based scaffolds for tissue regeneration
Date of Award
Ph.D. in Engineering
School of Engineering
Advisor: Khalid Lafdi
Conductive biopolymers are starting to emerge as potential scaffolds of the future. These scaffolds exhibit some unique properties such as inherent conductivity, mechanical and surface properties. Traditionally, a conjugated polymer is used to constitute a conductive network. An alternative method currently being used is nanofillers as additives in the polymer. In this dissertation, we fabricated an intelligent scaffold for use in tissue engineering applications. The main idea was to enhance the mechanical, electrical properties and cell growth of scaffolds by using distinct types of nanofillers such as graphene, carbon nanofiber and carbon black. We identified the optimal concentrations of nano-additive in both fibrous and film scaffolds to obtain the highest mechanical and electrical properties without neglecting any of them. Lastly, we investigated the performance of these scaffold with cell biology. To accomplish these tasks, we first studied the mechanical properties of the scaffold as a function of morphology, concentration and variety of carbon nanofillers. Results showed that there was a gradual increase of the modulus and the fracture strength while using carbon black, carbon nanofiber and graphene, due to the small and strong carbon-to-carbon bonds and the length of the interlayer spacing. Moreover, regardless of the fabrication method, there was an increase in mechanical properties as the concentration of nanofillers increased until a threshold of 7 wt% was reached for the nanofiller film scaffold and 1%wt for the fibrous scaffold. Experimental results of carbon black exhibited a good agreement when compared with data obtained using numerical approaches and analytical models, especially in the case of lower carbon black fractions. Second, we examined the influence of electrical properties of nanofillers based on the concentration and the geometry of carbon nanofillers in the polymer matrix using experimental and numerical simulation approaches. The experimental results showed an increase in conductivity as the amount of nanofiller concentration increased. And regardless of nanofiller type, the trend remained the same. The percolation threshold was around 4-5wt% of nano-additive with PCL and PAN matrices, respectively. However, at the same concentrations, conductivity was higher in graphene-based nanocomposites than for CNF and carbon black-based nanocomposites. The numerical modeling highlighted the effect of nanofillers as constructing a conductive network due to the aggregation phenomenon. The conductivity trend for carbon black and carbon nanofiber-based composites by the numerical simulation approach was similar to the experimental approach. Lastly, we studied the effect of these carbon nanocomposite-based scaffolds on the behavior of cell growth. The results showed that regardless of the scaffold shape (film or fiber) and the additive's type, when the concentration of nano-additives was increased, electrical conductivity and cell density increased also. For a given nano-additive concentration and type, cell density increased in the scaffolds with fiber shape vs. the film. Importantly, as the conductivity of the scaffolds increased, so did the cell density. Consequently, this study has highlighted the close relationship between electrical conductivity, cell density and scaffold orientation. An increase in conductivity can be achieved in two ways: by molecular orientation of the nanofillers or by the appropriate selection of nano-additives such as graphene and carbon nanofiber.
Tissue scaffolds, Carbon nanofibers Properties, Carbon-black Properties, Graphene Properties, Nanocomposites (Materials) Properties, Engineering, Materials Science, Biomedical Engineering, Conducive scaffold, Carbon nanofiller, Electrical properties, Mechanical properties, Cell density
Copyright 2017, author
Al Habis, Nuha Hamad, "Engineering and modeling carbon nanofiller-based scaffolds for tissue regeneration" (2017). Graduate Theses and Dissertations. 1270.