Description of noble gas diffusion in a polymer matrix by a hopping model

Hop, Skip, and Jump: Hydrogen Molecular Transport through Amorphous Polyethylene Matrices Studied via Molecular Dynamics Simulations

In the pursuit of advancing and diversifying energy technologies for a more sustainable future, the possibilities of hydrogen (H2) usage will broaden, as will our understanding of its containment materials. Polyethylene (PE) has a vast assortment of uses and applications, which are growing with demands for alternative energy possibilities. One use of PE liner is as a prime candidate for nonmetallic piping and pressurized type IV storage devices. Such applications require PE to effectively prevent H2 transport through containment systems. To study the molecular transport mechanism of hydrogen through polymeric barriers, a system containing hydrogen molecules absorbed within amorphous PE is modeled here using molecular dynamics simulations. The simulations are conducted within a range of temperatures that span the glass transition temperature of amorphous PE. The simulated PE displays bulk density, radius of gyration, and self-diffusion coefficient that are consistent with experimental data. The simulated trajectories are interrogated to study the movement of the guest gas molecules. The results show that the diffusion coefficients increase with temperature, as expected. However, the mobility of the PE chains is found to affect the mobility of absorbed H2 molecules to a much lower extent than it affects that of CH4 molecules because of the much smaller size of the former than of the latter guest. From a molecular perspective, a "hopping" mechanism is observed, according to which H2 molecules hop between one vacant free volume space to another within the polymer matrix, in combination with longer, straight, undisturbed "jumps" or "skips" along directions aligned with regions of ordered PE chains. This suggests that the orientation of the crystallites within the semicrystalline PE matrix affects the H2 containment. Implications of these findings toward PE usage as containment material are discussed.

Variational kinetic clustering of complex networks

Efficiently identifying the most important communities and key transition nodes in weighted and unweighted networks is a prevalent problem in a wide range of disciplines. Here, we focus on the optimal clustering using variational kinetic parameters, linked to Markov processes defined on the underlying networks, namely, the slowest relaxation time and the Kemeny constant. We derive novel relations in terms of mean first passage times for optimizing clustering via the Kemeny constant and show that the optimal clustering boundaries have equal round-trip times to the clusters they separate. We also propose an efficient method that first projects the network nodes onto a 1D reaction coordinate and subsequently performs a variational boundary search using a parallel tempering algorithm, where the variational kinetic parameters act as an energy function to be extremized. We find that maximization of the Kemeny constant is effective in detecting communities, while the slowest relaxation time allows for detection of transition nodes. We demonstrate the validity of our method on several test systems, including synthetic networks generated from the stochastic block model and real world networks (Santa Fe Institute collaboration network, a network of co-purchased political books, and a street network of multiple cities in Luxembourg). Our approach is compared with existing clustering algorithms based on modularity and the robust Perron cluster analysis, and the identified transition nodes are compared with different notions of node centrality.

Nanoparticle diffusion in polymer melts in the presence of weak nanoparticle-monomer attractive interactions: A mode-coupling theory study

Mode-coupling theory is developed and employed to compute the nanoparticle diffusion coefficient in polymer solutions. Theoretical results are compared with molecular dynamics simulation data for a similar model. The theory properly reproduces the simulated effects of the nanoparticle size, mass, and concentration on the nanoparticle diffusion coefficient. Within the mode-coupling theory framework, a microscopic interpretation of the nonmonotonic dependence of the diffusion coefficient on the nanoparticle concentration is given in terms of structural and dynamic effects. Both the size dependence and mass dependence of the diffusion coefficient indicate a pronounced breakdown of the Stokes-Einstein relation for the present model.

Nanoparticle diffusion in polymer melts: Molecular dynamics simulations and mode-coupling theory

Nanoparticle diffusion in polymer melts is studied by the combination of Molecular Dynamics (MD) simulations and Mode-Coupling Theory (MCT). In accord with earlier experimental, simulation, and theoretical studies, we find that the Stokes-Einstein (SE) hydrodynamic relation D_n ∼ 1/R_n holds when the nanoparticle radius R_n is greater than the polymer gyration radius R_g, while in the opposite regime, the measured nanoparticle diffusion coefficient D_n exceeds the SE value by as much as an order of magnitude. The MCT values of D_n are found to be consistently higher than the MD simulation values. The observed discrepancy is attributed to the approximations involved in constructing the microscopic friction as well as to the approximate forms for dynamic structure factors used in MCT. In a thorough test of underlying MCT assumptions and approximations, various structural and dynamical quantities required as input for MCT are obtained directly from MD simulations. We present the improved MCT approach, which involves splitting of the microscopic time-dependent friction into two terms: binary (originating from short-time dynamics) and collective (due to long-time dynamics). Using MD data as input in MCT, we demonstrate that the total friction is largely dominated by its binary short-time term, which, if neglected, leads to severe overestimation of D_n. As a result, the revised version of MCT, in agreement with the present MD data, predicts 1/R_n ² scaling of the probe diffusion coefficient in a non-hydrodynamic regime when R_n < R_g. If the total friction is dominated by the collective long-time component, one would observe 1/R_n ³ scaling of D_n in accordance with previous studies.

Single particle jumps in a binary Lennard-Jones system below the glass transition

We study a binary Lennard-Jones system below the glass transition with molecular dynamics simulations. To investigate the dynamics we focus on events (jumps) where a particle escapes the cage formed by its neighbors. Using single particle trajectories we define a jump by comparing for each particle its fluctuations with its changes in average position. We find two kinds of jumps: "reversible jumps," where a particle jumps back and forth between two or more average positions, and "irreversible jumps," where a particle does not return to any of its former average positions, i.e., successfully escapes its cage. For all investigated temperatures both kinds of particles jump and both irreversible and reversible jumps occur. With increasing temperature, relaxation is enhanced by an increasing number of jumps and growing jump lengths in position and potential energy. However, the waiting time between two successive jumps is independent of temperature. This temperature independence might be due to aging, which is present in our system. We therefore also present a comparison of simulation data with three different histories. The ratio of irreversible to reversible jumps is also increasing with increasing temperature, which we interpret as a consequence of the increased likelihood of changes in the cages, i.e., a blocking of the "entrance" back into the previous cage. In accordance with this interpretation, the fluctuations both in position and energy are increasing with increasing temperature. A comparison of the fluctuations of jumping particles and nonjumping particles indicates that jumping particles are more mobile even when not jumping. The jumps in energy normalized by their fluctuations are decreasing with increasing temperature, which is consistent with relaxation being increasingly driven by thermal fluctuations. In accordance with subdiffusive behavior are the distributions of waiting times and jump lengths in position.