A new Monte Carlo simulation approach for the prediction of sorption equilibria of oligomers in polymer melts: Solubility of long alkanes in linear polyethylene

Equilibration of linear polyethylene melts with pre-defined molecular weight distributions employing united atom Monte Carlo simulations

Possessing control over the molecular size (molecular weight/chain length/degree of polymerization) distribution of a polymeric material is extremely important in applications. This is manifested de facto by the extensive contemporary scientific literature on processes for controlling this distribution experimentally. Yet, the literature on computational techniques for achieving prescribed molecular size distributions in simulations and exploring their impact on properties is much less abundant than its experimental/technical counterpart. Here, we develop-on the basis of united atom melt simulations employing connectivity-altering Monte Carlo moves-a new Metropolis selection criterion that drives the multichain system to a prescribed but otherwise arbitrary distribution of molecular sizes. The new formulation is a generalization of that originally proposed [P. V. K. Pant and D. N. Theodorou, Macromolecules 28, 7224 (1995)], but simpler and more computationally efficient. It requires knowledge solely of the target distribution, which need not be normalized. We have implemented the new formulation on long-chain linear polyethylene melts, obtaining excellent results. The target molecular size distribution can be provided in tabulated form, allowing absolute freedom as to the types of chain size profiles that can be simulated. Distributions for which equilibration has been achieved here for linear polyethylene include a truncated most probable, a truncated Schulz-Zimm, an arbitrary one defined in tabulated form, a broad truncated Gaussian, and a bimodal Gaussian. The last two are comparable to those encountered in industrial applications. The impact of the molecular size distribution on the properties of the simulated melts, such as density, chain dimensions, and mixing thermodynamics, is explored.

Modelling Sorption and Transport of Gases in Polymeric Membranes across Different Scales: A Review

Professor Giulio C. Sarti has provided outstanding contributions to the modelling of fluid sorption and transport in polymeric materials, with a special eye on industrial applications such as membrane separation, due to his Chemical Engineering background. He was the co-creator of innovative theories such as the Non-Equilibrium Theory for Glassy Polymers (NET-GP), a flexible tool to estimate the solubility of pure and mixed fluids in a wide range of polymers, and of the Standard Transport Model (STM) for estimating membrane permeability and selectivity. In this review, inspired by his rigorous and original approach to representing membrane fundamentals, we provide an overview of the most significant and up-to-date modeling tools available to estimate the main properties governing polymeric membranes in fluid separation, namely solubility and diffusivity. The paper is not meant to be comprehensive, but it focuses on those contributions that are most relevant or that show the potential to be relevant in the future. We do not restrict our view to the field of macroscopic modelling, which was the main playground of professor Sarti, but also devote our attention to Molecular and Multiscale Hierarchical Modeling. This work proposes a critical evaluation of the different approaches considered, along with their limitations and potentiality.

Molecular Modeling Investigations of Sorption and Diffusion of Small Molecules in Glassy Polymers

With a wide range of applications, from energy and environmental engineering, such as in gas separations and water purification, to biomedical engineering and packaging, glassy polymeric materials remain in the core of novel membrane and state-of the art barrier technologies. This review focuses on molecular simulation methodologies implemented for the study of sorption and diffusion of small molecules in dense glassy polymeric systems. Basic concepts are introduced and systematic methods for the generation of realistic polymer configurations are briefly presented. Challenges related to the long length and time scale phenomena that govern the permeation process in the glassy polymer matrix are described and molecular simulation approaches developed to address the multiscale problem at hand are discussed.

Continuous Fractional Component Monte Carlo: An Adaptive Biasing Method for Open System Atomistic Simulations

A new open system Monte Carlo procedure designed to overcome difficulties with insertion and deletion of molecules is introduced. The method utilizes gradual insertions and deletions of molecules through the use of a continuous coupling parameter and an adaptive bias potential. The method draws upon concepts from previous open system molecular dynamics and expanded ensemble Monte Carlo techniques and is applied to both the grand canonical and osmotic ensembles. It is shown to yield correct results for the volumetric properties of the Lennard-Jones fluid and water as well as the phase behavior of the CO2-ethanol binary system.

Application of molecular dynamics simulations in molecular property prediction II: diffusion coefficient

In this work, we have evaluated how well the general assisted model building with energy refinement (AMBER) force field performs in studying the dynamic properties of liquids. Diffusion coefficients (D) have been predicted for 17 solvents, five organic compounds in aqueous solutions, four proteins in aqueous solutions, and nine organic compounds in nonaqueous solutions. An efficient sampling strategy has been proposed and tested in the calculation of the diffusion coefficients of solutes in solutions. There are two major findings of this study. First of all, the diffusion coefficients of organic solutes in aqueous solution can be well predicted: the average unsigned errors and the root mean square errors are 0.137 and 0.171 × 10(-5) cm(-2) s(-1), respectively. Second, although the absolute values of D cannot be predicted, good correlations have been achieved for eight organic solvents with experimental data (R(2) = 0.784), four proteins in aqueous solutions (R(2) = 0.996), and nine organic compounds in nonaqueous solutions (R(2) = 0.834). The temperature dependent behaviors of three solvents, namely, TIP3P water, dimethyl sulfoxide, and cyclohexane have been studied. The major molecular dynamics (MD) settings, such as the sizes of simulation boxes and with/without wrapping the coordinates of MD snapshots into the primary simulation boxes have been explored. We have concluded that our sampling strategy that averaging the mean square displacement collected in multiple short-MD simulations is efficient in predicting diffusion coefficients of solutes at infinite dilution.

Monte Carlo simulations of equilibrium solubilities and structure of water in n-alkanes and polyethylene

Gibbs ensemble Monte Carlo methods based on a force field that combines the simple point charge [Berendsen et al., in Intermolecular Forces, edited by Pullman (Reidel, Dordrecht, 1981), p. 331] and transferable potentials for phase equilibria [Martin and Siepmann, J. Phys. Chem. B 102, 2659 (1998)] models were used to study the equilibrium properties of binary systems consisting of water and n-alkanes with chain lengths from hexane to hexadecane. In addition, systems where extended linear alkane chains (up to 300 carbon units long) were used to represent amorphous polyethylene were simulated in the presence of water using a connectivity altering osmotic Gibbs ensemble. In these simulations the equilibrium between a liquid water phase and a polymer phase into which water was inserted was studied. The predicted solubilities, which were determined between 350 and 550 K, are in good agreement with experiment, where experimental results are available, and the density of water molecules in the hydrocarbons is approximately 63% as high as in saturated water vapor under the same conditions. At the lower temperatures most of the water exists as monomers; increasing the temperature leads to an increase in the density of water in the alkane phase and hence in the fraction of molecules that participate in clusters. Dimers are the most prevalent clusters in all hydrocarbons and at all temperatures studied, and the fraction of clusters of given size decrease with increasing cluster size. A large fraction of trimers, tetramers, and pentamers, which are the cluster sizes for which topologies have been studied, are cyclic at low temperatures, but at higher temperatures linear structures predominate. The same properties are observed for pure water vapor clusters in equilibrium with the liquid phase, showing that the cluster topologies are not significantly affected by the surrounding hydrocarbon.

A generalized direct-particle-deletion scheme for the calculation of chemical potential and solubilities of small- and medium-sized molecules in amorphous polymers

The development, validation, and first applications of a generalized version of an inverse Widom method are described. It permits the calculation of solubility coefficients for molecules as large as, e.g., benzene in all polymers for which reasonable forcefield parameters exist. Predicting the solubility is a key to the knowledge-based design of materials utilized to solve permeability related problems. For long time, particle insertion methods, such as the Widom method, were the only way to predict solubilities from molecular models, but they, in most cases, only worked well for rather small penetrants (e.g., H2, O2, N2). Therefore, a few years ago, a new particle deletion algorithm "DPD" was introduced by Boulougouris, Economou, and Theodorou to overcome this problem in principle. The related computer code was, however, only applicable to special, relatively simple model systems. As application examples for the generalized version described here, solubility calculations for nitrogen, oxygen, and benzene in poly(dimethyl siloxane) are presented.

Glass transition of polymers: atomistic simulation versus experiments

With experimental investigations and current theories, molecular modeling became an inevitable technique to study the perplexing phenomenon of glass transition. Among polymers, small variations in atomic interactions yield different values of the glass transition temperature, T{g}. To reveal the influence of differences in the atomic functionality on the value of T{g}, and thus to probe the molecular mechanisms responsible for this transition, atomistic simulations have to be undertaken. However, such simulations are argued not to accurately represent physically the glass transition due to the long relaxation times involved. Here we show the universality of the well-known Williams-Landel-Ferry equation for the experimental thermal dependence of polymer viscosities as demonstrated with atomistic simulations. Consequently, atomic aspects could be explicitly revealed. The contribution of atomistic simulation to the study of glass transition is thus confirmed. However, it has to be used complementarily with experiments and coarse-grained simulation to reveal the atomic aspects of current theories.