Micromechanical modelling of carbon nanotube reinforced composite materials with a functionally graded interphase

This paper introduces a new method of determining the mechanical properties of carbon nanotube-polymer composites using a multi-inclusion micromechanical model with functionally graded phases. The nanocomposite was divided into four regions of distinct mechanical properties; the carbon nanotube, the interface, the interphase and bulk polymer. The carbon nanotube and the interface were later combined into one effective fiber using a finite element model. The interphase was modelled in a functionally graded manner to reflect the true nature of the portion of the polymer surrounding the carbon nanotube. The three phases of effective fiber, interphase and bulk polymer were then used in the micromechanical model to arrive at the mechanical properties of the nanocomposite. An orientation averaging integration was then applied on the results to better reflect macroscopic response of nanocomposites with randomly oriented nanotubes. The results were compared to other numerical and experimental findings in the literature.

Relationship between Dynamic Instability of Individual Microtubules and Flux of Subunits into and out of Polymer

ABSTRACTBehaviors of dynamic polymers such as microtubules and actin are frequently assessed at one or both of two scales: (i) net assembly or disassembly of bulk polymer, (ii) growth and shortening of individual filaments. Previous work has derived various forms of an equation to relate the rate of change in bulk polymer mass (i.e., flux of subunits into and out of polymer, often abbreviated as “J”) to individual filament behaviors. However, these versions of this “J equation” differ in the variables used to quantify individual filament behavior, which correspond to different experimental approaches. For example, some variants of the J equation use dynamic instability parameters, obtained by following particular individuals for long periods of time. Another form of the equation uses measurements from many individuals followed over short time steps. We use a combination of derivations and computer simulations that mimic experiments to (i) relate the various forms of the J equation to each other; (ii) determine conditions under which these J equation forms are and are not equivalent; and (iii) identify aspects of the measurements that can affect the accuracy of each form of the J equation. Improved understanding of the J equation and its connections to experimentally measurable quantities will contribute to efforts to build a multi-scale understanding of steady-state polymer behavior.