Nanoparticles can influence the properties of polymer materials by a variety of mechanisms. With fullerene, carbon nanotube, and clay or graphene sheet nanocomposites in mind, we investigate how particle shape influences the melt shear viscosity η and the tensile strength τ , which we determine via molecular dynamics simulations. Our simulations of compact (icosahedral), tube or rod-like, and sheet-like model nanoparticles, all at a volume fraction φ ≈ 0.05, indicate an order of magnitude increase in the viscosity η relative to the pure melt. This finding evidently can not be explained by continuum hydrodynamics and we provide evidence that the η increase in our model nanocomposites has its origin in chain bridging between the nanoparticles. We find that this increase is the largest for the rod-like nanoparticles and least for the sheet-like nanoparticles. Curiously, the enhancements of η and τ exhibit opposite trends with increasing chain length N and with particle shape anisotropy. Evidently, the concept of bridging chains alone cannot account for the increase in τ and we suggest that the deformability or flexibility of the sheet nanoparticles contributes to nanocomposite strength and toughness by reducing the relative value of the Poisson ratio of the composite. The molecular dynamics simulations in the present work focus on the reference case where the modification of the melt structure associated with glass-formation and entanglement interactions should not be an issue. Since many applications require good particle dispersion, we also focus on the case where the polymer-particle interactions favor nanoparticle dispersion. Our simulations point to a substantial contribution of nanoparticle shape to both mechanical and processing properties of polymer nanocomposites.
Whereas there has been extensive theoretical and experimental investigation of the properties of linear polymer chains in solution, there has been far less work on sheet-like polymers having 2D connectivity and 3D crumpled or collapsed shapes caused by thermal fluctuations, attractive self-interactions, or both. Sheet-like polymers arise in a variety of contexts ranging from self-assembled biological membranes (e.g., the spectrin network of red blood cells, microtubules, etc.) to nanocomposite additives to polymers (carbon nanotubes, graphene, and clay sheets) and polymerized monolayers. We investigate the equilibrium properties of this broad class of polymers using a simple model of a sheet polymer with a locally square symmetry of the connecting beads. We quantify the sheet morphology and the dilute-limit hydrodynamic solution properties as a function of molecular mass and sheet stiffness. First, we reproduce the qualitative findings of previous work indicating that variable sheet stiffness results in a wide variety of morphologies, including flat, crumpled or collapsed spherical, cylindrical or tubular, and folded sheets that serve to characterize our particular 2D polymer model. Transport properties are of significant interest in characterizing polymeric materials, and we provide the first numerical computations of these properties for sheet polymers. Specifically, we calculate the intrinsic viscosity and hydrodynamic radius of these sheet morphologies using a novel path-integration technique and find good agreement of our numerical results with previous theoretical scaling predictions.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.