A new Monte Carlo algorithm for the simulation of atomistically detailed polymer melts is presented. The method introduces connectivity relationships as variables in the description of the polymer. The connectivity of the polymer is altered in Monte Carlo moves that satisfy the detailed constraints of molecular geometry. Connectivity-altering moves are seen to induce large jumps in the configuration space of the bulk polymer, thereby greatly enhancing the efficiency with which molecular configurations are sampled. Simulations are carried out in a semigrand ensemble in which the chain length distribution is controlled by a spectrum of chemical potentials. Limiting chain length distributions are derived and compared with simulation results. Volumetric and structural predictions of the method are found to be in agreement with previous work.
We use suspended graphene electromechanical resonators to study the variation of resonant frequency as a function of temperature. Measuring the change in frequency resulting from a change in tension, from 300 to 30 K, allows us to extract information about the thermal expansion of monolayer graphene as a function of temperature, which is critical for strain engineering applications. We find that thermal expansion of graphene is negative for all temperatures between 300 and 30 K. We also study the dispersion, the variation of resonant frequency with DC gate voltage, of the electromechanical modes and find considerable tunability of resonant frequency, desirable for applications like mass sensing and RF signal processing at room temperature. With a lowering of temperature, we find that the positively dispersing electromechanical modes evolve into negatively dispersing ones. We quantitatively explain this crossover and discuss optimal electromechanical properties that are desirable for temperature-compensated sensors.
Molecular dynamics simulations of diffusion of a small-molecule penetrant in an amorphous polymer matrix have been carried out for the examples of methane in polyethylene (PE) and methane in polyisobutylene (PIB). Particular attention waa paid to ensuring that the nonbonded potentiale representing the polymerpolymer bead interactions in the matrix were adequately calibrated. Accurate representation of equation of state (P-V-2') behavior for the polymers was used aa the criterion for this. The simulatione were carried out over a wide range of temperatures. The results are in accord with available experimental data. The temperature variation of the diffusion coefficients for PE was non-Arrhenius in character and of the WLF type. Analysis of the diffusion trajectories in PE indicates that the diffusion mechanism changes significantly over the temperature range studied. At lower temperatures, the diffusant motion is characterized by relatively long periods of quiescence interspersed with fairly large jumps. However, at higher temperatures, a broad spectrum of frequent jumps obtains. The diffusion rates are obviously very sensitive to the free volume and hence to the molecular packing. However, the polymer chain mobility is found to play a role aa well. The diffusion activation energy at higher temperature ia similar to that for the decay of the torsional angle autocorrelation function for the polymer. It ie also found that increaaing the torsional barrier reduces the diffusion rate. In PIB where the free volume ie significantly lees than that in PE, the diffusion rates are much lower than those in the latter. The mechanism over the range studied resembles that of the lower temperature regime in PE.
Polyisobutylene (PIB) is an elastomer that is notable for low rates of diffusion of small molecules. This has been suggested to be due to efficient intermolecular packing as evidenced by relatively low specific volume. In the present work these questions were studied via simulations. Polyethylene (PE), which is chemically isomeric with PIB, was studied as a comparison material. Monte Carlo simulations of bulk PIB were carried out at constant temperature and pressure, and molecular dynamics simulations of methane diffusion in both polymers were made. The MC simulations result in lower specific volumes for PIB compared to PE, as observed experimentally. The more efficient packing in PIB is attributed to the unoccupied volume in the systems being largely at the intermolecular interfaces and thus a molecular surface phenomenon. The thicker cross-sectioned PIB molecules have less surface area per carbon atom. The MD simulations show a slower diffusion rate in PIB. Further simulations at different densities show the diffusion to be very sensitive to small volume changes. For example, diffusion in PIB at the experimental density of polyethylene is calculated to be faster than for PE at this density.
An accurate equation of state (EOS) for polyethylene is required in order to model high energy density experiments for CH 2 densities above 1 g/cc, temperatures above 1 eV, and pressures above 1 Mbar. Density Functional Theory (DFT) based molecular dynamics has been established as a method capable of yielding high fidelity results for many materials at a wide range of pressures and temperatures and has recently been applied to complex polymers such as polyethylene [1]. Using high density polyethylene as the reference state, we compute the principal Hugoniot to 350 GPa, compression isentrope, and several release isentropes from states on the principal Hugoniot. We also calculate the specific heat and the dissociation along the Hugoniot. Our simulation results are validated by comparing to experimental data [2, 3] and then used to construct a wide range EOS.
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.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.