Enthalpies of Combustion and Formation of Severely Crowded Methyl-Substituted 1,3-dioxanes. The Magnitudes of 2,4- and 4,6-diaxial Me,Me-Interactions and the Chair-2,5-twist Energy Difference.

Enthalpies of combustion of 2,2-trans-4,6- (1) and 4,4,6,6-tetramethyl- (2) and 2,4,4,6,6- (3) and 2,2,4,4,6-pentamethyl-1,3-dioxanes (4) were determined to estimate their enthalpies of formation in the gas phase. By comparing the latter with the corresponding enthalpies estimated based on the various bond-bond interactions allowed to determine the chair-2,5-twist energy difference (ΔHCT = 29.8 kJ mol-1) for 1 since C-13 shift correlations indicate that it escapes to the 2,5-twist form where the 2-methyl groups are isoclinal and 4- and 6-methyl groups pseudoequatorial to avoid syn-axial interactions. Compounds 2 and 3 in turn give the values 21.0 and 21.6 kJ mol-1 for the 4,6-diaxial Me,Me-interaction. Finally compound 4, which retains the chair conformation to avoid pseudoaxial interactions in the twist forms gives the value 19.5 kJ mol-1 for the 2,4-diaxial Me,Me-interaction indicating that its chair form appears to be somewhat deformed.

Vapor-liquid equilibrium of ethanol by molecular dynamics simulation and Voronoi tessellation.

Explicit atom simulations of ethanol were performed by molecular dynamics using the OPLS-AA potential. The phase densities were determined self-consistently by comparing the distribution of Voronoi volumes from two-phase and single-phase simulations. This is the first demonstration of the use of Voronoi tessellation in two-phase molecular dynamics simulation of polyatomic fluids. This technique removes all arbitrary determination of the phase diagram by using single-phase simulations to self-consistently validate the probability distribution of Voronoi volumes of the liquid and vapor phases extracted from the two-phase molecular dynamics simulations. Properties from the two phase simulations include critical temperature, critical density, critical pressure, phase diagram, surface tension, and molecule orientation at the interface. The simulations were performed from 375 to 472 K. Also investigated were the vapor pressure and hydrogen bonding along the two phase envelope. The phase envelope agrees extremely well with literature values from GEMC at lower temperatures. The combined use of two-phase molecular dynamics simulation and Voronoi tessellation allows us to extend the phase diagram toward the critical point.

Measuring coexisting densities from a two-phase molecular dynamics simulation by voronoi tessellations.

A new algorithm is presented that allows for the determination of bulk liquid and vapor densities from a two-phase Molecular Dynamics (2phiMD) simulation. This new method does not use any arbitrary cutoffs for phase definitions; rather it uses single-phase simulations as a self-consistency check. The method does not use any spatial bins for generating histograms of local properties, thereby avoiding the statistical issues associated with bins. Finally, it allows one to approach very close to the critical point. The new method utilizes Voronoi tessellations to determine the molecular volume of every point at every instance in a molecular dynamics simulation. Since the molecular volume is calculated throughout the simulation, statistical parameters such as the average molecular volume and average molecular variance are easy to obtain. To define the phases, the normalized variance of the molecular volume from 1phiMD and 2phiMD is used as a self-consistency check. The new method gives new insight into the nature of the near-subcritical fluid. The critical properties from this analysis are T(c) = 1.293 and rho(c) = 0.313. Direct simulation of the two-phase system was performed up to a temperature of 1.292. The results show excellent agreement to experimental results and Gibbs Ensemble Monte Carlo for coexisting densities. We see that well below the critical temperature, some particles are neither liquid nor vapor. These interfacial particles are primarily, but not exclusively, concentrated at the bulk interface. However, as we approach the critical point, some particles are considered both liquid and vapor. These interfacial particles are distributed through the system.

A molecular dynamics study of a nafion polyelectrolyte membrane and the aqueous phase structure for proton transport.

A molecular dynamics simulation study of hydrated Nafion at water contents ranging from 5 to 20 wt % was performed to examine the structure and dynamics of the hydrated polyelectrolyte system. The simulations show that the system forms segregated hydrophobic regions consisting primarily of the polymer backbone and hydrophilic regions with an inhomogeneous water distribution. We find that the water clustering strongly depends on the water content. At low water content, only isolated small water clusters are formed. As the water content increases, it becomes increasingly possible that a predominant majority of water molecules form a single cluster, suggesting that the hydrophilic regions become connected. We characterize the atomic structures formed within the system by various atomic pair correlation functions. The water structure factor shows a peak at q values corresponding to an intercluster distance about 2.5 nm and greater. With increasing water content, the distance moves to larger values, consistent with findings from scattering experiments. We find that the degree of solvation of hydronium ions by water molecules is a strong function of water content. At 5 wt %, a majority of the hydronium ions are hydrated by no more than two water molecules, prohibiting structural diffusion. As water content increases, the hydronium ions continue to become increasingly hydrated, resulting in structures capable of forming eigen ions, a necessary step in structural diffusion. Addressing the experimentally observed fact that conductivity in these membranes abruptly drops near 5 wt %, we find that both the local structure of the poorly hydrated hydronium ions and the disconnected nature of the global morphology of the water nanonetwork at low water content should contribute to poor conductivity.