The structure of adsorbed cyclic chains

Abstract

In order to determine the structure of polymer films formed of cyclic chains (rings) we developed and studied a simple coarse-grained model. Our main goal was to check how the percolation and jamming thresholds in such a system were related to the thresholds obtained for linear flexible chains system, i.e., how the geometry of objects influenced both thresholds. All atomic details were suppressed and polymers were represented as a sequence of identical beads and the chains were embedded to a square lattice (a strictly 2D model). The system was athermal and the excluded volume was the only potential introduced. A random sequential adsorption algorithm was chosen to determine the properties of a polymer monolayer. It was shown that the percolation threshold of cyclic chains was considerably higher than those of linear flexible chains while the jamming thresholds for both chain architectures are very similar. The shape of adsorbed cyclic chains was found to be more prolate when compared to average single chain.

Inconsistency of Diffusion and Relaxation of Ring Polymers Adsorbed on Rough Surfaces

“…However, in the lateral direction, the closed architecture induces that the ring polymers cannot extend as well as linear polymers, resulting in the slightly smaller R g∥,r compared with R g∥,l . Moreover, the obstacles on the rough surface do not affect the adsorbed conformation of ring polymers and the radius of gyration of ring polymers ( R g,r ) scales with the chain length ( N ) as R g,r ∼ N 0.75 , which coincides well with other investigations. , …”

“…Moreover, the obstacles on the rough surface do not affect the adsorbed conformation of ring polymers and the radius of gyration of ring polymers (R g,r ) scales with the chain length (N) as R g,r ∼ N 0.75 , which coincides well with other investigations. 39,40 Subsequently, we explore the diffusion and the relaxation behaviors of ring polymers adsorbed on the rough surface with d = 4 and h = 1.2. The diffusion coefficient (D) is calculated by the Stocks−Einstein equation (MSD = 6Dt) through extracting a linear segment of MSD(t) curves to illustrate the diffusion behaviors, 41 where MSD is the mean-square displacement of center of mass of polymer chains.…”

Percolation in Polydisperse Polymer Systems: A Computer Simulation Study

“…One can observe that at low polymer concentrations in the cases of polydispersity under consideration the size of a chain scales as < R g 2 > ≈ N 2 ν for chains with N > 20 similarly to monodisperse systems. [ 49 ] Moreover, there are almost no differences in the scaling behavior of R g 2 for all polydispersities studied and therefore we present the results of the uniform distribution only. The scaling exponent was found to be 2 ν = 1.45 ± 0.01 for shorter chains at a low polymer concentration ( φ = 0.1).…”

Percolation in Two‐Dimensional Copolymer‐Solvent Systems

“…[ 28,42,47 ] The infl uence of the macromolecular architecture (linear chains, star-branched chains with a different number of branches and cyclic chains) on the percolation and jamming thresholds is found to be surprisingly weak. [ 28,48,49 ] It has also been shown that the percolation threshold is connected to the structure of chains and their fractal dimension. [ 47,48 ] The other simulation method is based on particle motion in a polymeric system represented by random walks.…”

“…When one looks at systems containing short flexible chains the percolation threshold decreases with the increase in the chain's length while for semiflexible chains it exhibits a minimum for considerably long polymers . The influence of the macromolecular architecture (linear chains, star‐branched chains with a different number of branches and cyclic chains) on the percolation and jamming thresholds is found to be surprisingly weak . It has also been shown that the percolation threshold is connected to the structure of chains and their fractal dimension .…”