Measuring Oxygen Solubility in Amorphous and Semicrystalline Polyolefins Using Test Particle Insertion: A Comparative Study of Polyethylene and Isotactic Polypropylene.

The test particle insertion method is used to study the solubility of oxygen in two commonly used polymers: polyethylene (PE) and isotactic polypropylene (iPP). Amorphous samples for both polymers were prepared by means of Monte Carlo and molecular dynamics simulations, and the oxygen solubility was measured across different temperatures. The solubility-temperature dependence for iPP proved to be nonmonotonic due to the interplay between binding and reorganizational enthalpy, while for PE, it appeared to be monotonic based on the available data in the studied temperature range.

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.

A coarse-grained model for capturing the helical behavior of isotactic polypropylene.

Understanding the process-property relations of helical polymers using molecular simulations has been an attractive research field over the years. Specifically, isotactic polypropylene still remains a challenge for current computational experimentation, as it exhibits phenomena such as crystallization that emerge on large spatial and temporal scales. Coarse-graining is an efficient technique for approaching such phenomena, although previous coarse-grained models lack in preserving important atomistic and structural details.

Promising Route for the Development of a Computational Framework for Self-Assembly and Phase Behavior Prediction of Ionic Surfactants Using MARTINI.

Surfactants are amphiphilic molecules with multiple uses and industrial applications as detergents, wetting agents, emulsifiers, and so forth. They can be divided into three main categories: nonionic, ionic, and zwitterionic. The development of a universal computational framework able to predict key properties such as their critical micelle concentration (cmc) and the size of the micelles they form and to ultimately extract phase diagrams for their aqueous solutions, possibly in the presence of salts and oils, using their chemical constitution as input, would provide valuable information for the design and the production of these materials.

Thermodynamic Analysis of n-Hexane-Ethanol Binary Mixtures Using the Kirkwood-Buff Theory.

A complete thermodynamic analysis of mixtures consisting of molecules with complex chemical constitution can be rather demanding. The Kirkwood-Buff theory of solutions allows the estimation of thermodynamic properties, which cannot be directly extracted from atomistic simulations, such as the Gibbs energy of mixing (Δ G). In this work, we perform molecular dynamics simulations of n-hexane-ethanol binary mixtures in the liquid state under two temperature-pressure conditions and at various mole fractions.