Hydrogen storage is a key enabling technology required for attaining a hydrogen-based economy. Fundamental research can reveal the underlying principles controlling hydrogen uptake and release by storage materials, and also aid in characterizing and designing novel storage materials. New ideas for hydrogen storage materials come from exploiting the properties of hydrophobic hydration, which refers to water s ability to stabilize, by its mode of association, specific structures under specific conditions. Although hydrogen was always considered too small to support the formation of solid clathrate hydrate structures, exciting new experiments show that water traps hydrogen molecules at conditions of low temperatures and moderate pressures. Hydrogen release is accomplished by simple warming. While these experiments lend credibility to the idea that water could form an environmentally attractive alternative storage compound for hydrogen fuel, which would advance our nation s goals of attaining a hydrogen-based economy, much work is yet required to understand and realize the full potential of clathrate hydrates for hydrogen storage. Here we undertake theoretical studies of hydrogen in water to establish a firm foundation for predictive work on clathrate hydrate H{sub 2} storage capabilities. Using molecular simulation and statistical mechanical theories based in part on quantum mechanical descriptions of molecular interactions, we characterize the interactions between hydrogen and liquid water in terms of structural and thermodynamic properties. In the process we validate classical force field models of hydrogen in water and discover new features of hydrophobic hydration that impact problems in both energy technology and biology. Finally, we predict hydrogen occupancy in the small and large cages of hydrogen clathrate hydrates, a property unresolved by previous experimental and theoretical work.
A new formulation of configurational-bias Monte Carlo that uses arbitrary distributions to generate trial bond lengths, angles and dihedrals is described and shown to provide similar acceptance rates with substantially less computational effort. Several different trial distributions are studied and a linear combination of the ideal distribution plus Gaussian distributions automatically fit to the energetic and ideal terms is found to give the best results. The use of these arbitrary trial distributions enables a new formulation of coupled-decoupled configurational bias Monte Carlo that has significantly higher acceptance rates for cyclic molecules. The chemical potential measured via a modified Widom insertion is found to be ill-defined in the case of a molecule that has flexible bond lengths due to the unbounded probability distribution that describes the distance between any two atoms. We propose a simple standard state that allows the computation of consistent chemical potentials for molecules with flexible bonds. We show that the chemical potential via Widom insertion is not computed properly for molecules with Coulombic interactions when the number of trials for any of the nonbonded selection steps is greater than one. Finally, we demonstrate the power of the new algorithms by sampling the side-chain conformations of a polypeptide.
Germanium telluride undergoes rapid transition between polycrystalline and amorphous states under either optical or electrical excitation. While the crystalline phases are predicted to be semiconductors, polycrystalline germanium telluride always exhibits p -type metallic conductivity. We present a study of the electronic structure and formation energies of the vacancy and antisite defects in both known crystalline phases. We show that these intrinsic defects determine the nature of free-carrier transport in crystalline germanium telluride. Germanium vacancies require roughly one-third the energy of the other three defects to form, making this by far the most favorable intrinsic defect. While the tellurium antisite and vacancy induce gap states, the germanium counterparts do not. A simple counting argument, reinforced by integration over the density of states, predicts that the germanium vacancy leads to empty states at the top of the valence band, thus giving a complete explanation of the observed p -type metallic conduction.
We report on our studies of the structural properties of a hydrogen molecule dissolved in liquid water. The radial distribution function, coordination number and coordination number distribution are calculated using different representations of the interatomic forces within molecular dynamics (MD), Monte Carlo (MC) and ab initio molecular dynamics (AIMD) simulation frameworks. Although structural details differ in the radial distribution functions generated from the different force fields, all approaches agree that the average and most probable number of water molecules occupying the inner hydration sphere around hydrogen is 16. Furthermore, all results exclude the possibility of clathrate-like organization of water molecules around the hydrophobic molecular hydrogen solute.
Carbon nanotubes (CNT) are unique nanoscale building blocks for a variety of materials and applications, from nanocomposites, sensors and molecular electronics to drug and vaccine delivery. An important step towards realizing these applications is the ability to controllably self-assemble the nanotubes into larger structures. Recently, amphiphilic peptide helices have been shown to bind to carbon nanotubes and thus solubilize them in water. Furthermore, the peptides then facilitate the assembly of the peptide-wrapped nanotubes into supramolecular, well-aligned fibers. We investigate the role that molecular modeling can play in elucidating the interactions between the peptides and the carbon nanotubes in aqueous solution. Using ab initio methods, we have studied the interactions between water and CNTs. Classical simulations can be used on larger length scales. However, it is difficult to sample in atomistic detail large biomolecules such as the amphiphilic peptide of interest here. Thus, we have explored both new sampling methods using configurational-bias Monte Carlo simulations, and also coarse-grained models for peptides described in the literature. An improved capability to model these inorganichiopolymer interfaces could be used to generate improved understanding of peptide-nanotube self-assembly, eventually leading to the engineering of new peptides for specific self-assembly goals.
Vapor pressure and heats of vaporization are computed for the industrial fluid properties simulation challenge (IFPSC) data set using the Towhee Monte Carlo molecular simulation program. Results are presented for the CHARMM27 and OPLS-aa force fields. Once again, the average result using multiple force fields is a better predictor of the experimental value than either individual force field.
This LDRD project has involved the development and application of Sandia's massively parallel materials modeling software to several significant biophysical systems. They have been successful in applying the molecular dynamics code LAMMPS to modeling DNA, unstructured proteins, and lipid membranes. They have developed and applied a coupled transport-molecular theory code (Tramonto) to study ion channel proteins with gramicidin A as a prototype. they have used the Towhee configurational bias Monte-Carlo code to perform rigorous tests of biological force fields. they have also applied the MP-Sala reacting-diffusion code to model cellular systems. Electroporation of cell membranes has also been studied, and detailed quantum mechanical studies of ion solvation have been performed. In addition, new molecular theory algorithms have been developed (in FasTram) that may ultimately make protein solvation calculations feasible on workstations. Finally, they have begun implementation of a combined molecular theory and configurational bias Monte-Carlo code. They note that this LDRD has provided a basis for several new internal (e.g. several new LDRD) and external (e.g. 4 NIH proposals and a DOE/Genomes to Life) proposals.
Accurate predictions of retention times, retention indices, and partition constants are a long sought-after goal for theoretical studies in chromatography. Although advances in computational chemistry have improved our understanding of molecular interactions, little attention has been focused on chromatography, let alone calculations of retention properties. Configurational-bias Monte Carlo simulations in the isobaric-isothermal Gibbs ensemble were used to investigate the partitioning of benzene, toluene, and the three xylene isomers between a squalane liquid phase and a helium vapor phase. The united-atom representation of the TraPPE (transferable potentials for phase equilibria) force field was used for all solutes and squalane. The Gibbs free energies of transfer and Kovats retention indices of the solutes were calculated directly from the partition constants (which were averaged over several independent simulations). While the calculated Kovats indices of benzene and toluene at T = 403 K are significantly higher than their experimental counterparts, much better agreement is found for the xylene isomers at T = 365 K.
We present the results of Molecular Dynamics and Monte Carlo simulations of n-butane and isobutane in silicalite. We begin with a comparison of the bulk adsorption and diffusion properties for two different parameterizations of the interaction potential between the hydrocarbon species, both of which have been shown to reproduce experimental gas-liquid coexistence curves. We examine diffusion as a function of the loading of the zeolite, as well as the temperature dependence of the diffusion constant at loading and for infinite dilution. Both force fields give accurate descriptions of bulk properties. We continue with simulations in which interfaces are formed between single component gases and the zeolite. After reaching equilibrium, we examine the dynamics of exchange between the bulk gas and the zeolite. In particular, we examine the average time spent in the adsorption layer by molecules as they enter the zeolite from the gas in an attempt to probe the microscopic origins of the surface barrier. The microscopic barrier is found to be insignificant for experimental systems. Finally, we calculate the permeability of the zeolite for n-butane and isobutane as a function of pressure. Our results underestimate the experimental results by an order of magnitude, indicating a strong effect from the surface barrier in these simulations. Our simulations are performed for a number of different gas temperatures and pressures, covering a wide range of state points.
The Transferable Potentials for Phase Equilibria-United Atom (TraPPE-UA) force field for hydrocarbons is extended to alkenes and alkylbenzenes by introducing the following pseudo-atoms: CH{sub 2}(sp{sup 2}), CH(sp{sup 2}), CH(aro), R-C(aro) for the link to aliphatic side chains, and C(aro) for the link of two benzene rings. In this united-atom force field, the nonbonded interactions of the hydrocarbon pseudo-atoms are solely governed by Lennard-Jones 12-6 potentials, and the Lennard-Jones well depth and size parameters for the new pseudo-atoms were determined by fitting to the single-component vapor-liquid phase equilibria of a few selected model compounds. Configurational-bias Monte Carlo simulations in the NVT version of the Gibbs ensemble were carried out to calculate the single-component vapor-liquid coexistence curves for ethene, propene, 1-butene, trans- and cis-2-butene. 2-methylpropene, 1,5-hexadiene, 1-octene, benzene, toluene, ethylbenzene, propylbenzene, isopropylbenzene, o-, m-, and p-xylene, and naphthalene. The phase diagrams for the binary mixtures of (supercritical) ethene/n-heptane and benzene/n-pentane were determined from simulations in the NpT Gibbs ensemble. Although the TraPPE-UA force field is rather simple and makes use of relatively few different pseudo-atoms, its performance, as judged by comparisons to other popular force fields and available experimental data, is very satisfactory.