A seeded growth method for the fabrication of high-permeance, high-separation-factor zeolite (siliceous ZSM-5, [Si96O192]-MFI) membranes is reported. The method consists of growing the crystals of an oriented seed layer to a well-intergrown film by avoiding events that lead to a loss of preferred orientation, such as twin overgrowths and random nucleation. Organic polycations are used as zeolite crystal shape modifiers to enhance relative growth rates along the desirable out-of-plane direction. The polycrystalline films are thin (approximately 1 micrometer) with single grains extending along the film thickness and with large in-plane grain size (approximately 1 micrometer). The preferred orientation is such that straight channels with an open diameter of approximately 5.5 angstroms run down the membrane thickness. Comparison with previously reported membranes shows that these microstructurally optimized films have superior performance for the separation of organic mixtures with components that have small differences in size and shape, such as xylene isomers.

Allosteric regulation is an essential function of many proteins that control a variety of different processes such as catalysis, signal transduction, and gene regulation. Structural rearrangements have historically been considered the main means of communication between different parts of a protein. Recent studies have highlighted the importance, however, of changes in protein flexibility as an effective way to mediate allosteric communication across a protein. Scapharca dimeric hemoglobin (HbI) is the simplest possible allosteric system, with cooperative ligand binding between two identical subunits. Thermodynamic equilibrium studies of the binding of oxygen to HbI have shown that cooperativity is an entropically driven effect. The change in entropy of the system observed upon ligand binding may arise from changes in the protein, the ligand, or the water of the system. The goal of this study is to determine the contribution of the change in entropy of the protein backbone to HbI cooperative binding. Molecular dynamics simulations and nuclear magnetic resonance relaxation techniques have revealed that the fast internal motions of HbI contribute to the cooperative binding to carbon monoxide in two ways: (1) by contributing favorably to the free energy of the system and (2) by participating in the cooperative mechanism at the HbI subunit interface. The internal dynamics of the weakly cooperative HbI mutant, F97Y, were also investigated with the same methods. The changes in backbone NH dynamics observed for F97Y HbI upon ligand binding are not as large as for the wild type, in agreement with the reduced cooperativity observed for this mutant. The results of this study indicate that interface flexibility and backbone conformational entropy of HbI participate in and are important for the cooperative mechanism of carbon monoxide binding.

Using the helix-coil transitions of alanine pentapeptide as an illustrative example, we demonstrate the use of diffusion maps in the analysis of molecular dynamics simulation trajectories. Diffusion maps and other nonlinear data-mining techniques provide powerful tools to visualize the distribution of structures in conformation space. The resulting low-dimensional representations help in partitioning conformation space, and in constructing Markov state models that capture the conformational dynamics. In an initial step, we use diffusion maps to reduce the dimensionality of the conformational dynamics of Ala5. The resulting pretreated data are then used in a clustering step. The identified clusters show excellent overlap with clusters obtained previously by using the backbone dihedral angles as input, with small-but nontrivial-differences reflecting torsional degrees of freedom ignored in the earlier approach. We then construct a Markov state model describing the conformational dynamics in terms of a discrete-time random walk between the clusters. We show that by combining fuzzy C-means clustering with a transition-based assignment of states, we can construct robust Markov state models. This state-assignment procedure suppresses short-time memory effects that result from the non-Markovianity of the dynamics projected onto the space of clusters. In a comparison with previous work, we demonstrate how manifold learning techniques may complement and enhance informed intuition commonly used to construct reduced descriptions of the dynamics in molecular conformation space.

A molecular-dynamics study is presented to assess the performance of a united-atom model in the prediction of liquid-vapor interfacial properties for short-chain perfluoroalkanes and their alkane counterparts. In particular, the ability of this model to discriminate between the surface-energy values of these two types of compounds was investigated over a wide temperature range corresponding to the liquid-vapor region.Comparisons with available experimental data and surface-tension predictions given by other force-field parameterizations, including those based on the more computationally demanding all-atom method, were performed to gauge the viability of this model. It was found that the model used in this study captures qualitatively the expected behavior of surface energy between alkanes and perfluoroalkanes and yields values that are in excellent agreement with experimental data, especially in the high-temperature limit as the critical temperature is approached. 2

We present a coarse molecular-dynamics (CMD) approach for the study of stress-induced structural transformations in crystals at finite temperatures. The method relies on proper choice of a coarse variable (order parameter, observable), which parameterizes the changes in effective free energy during the transformation. Results are reported for bcc-to-hcp lattice transitions under pressure. We explore coarse-variable space to reconstruct an effective free-energy landscape quantifying the relative stability of different metastable basins and locate the onset, at a critical pressure, of the bcc-to-hcp transformation.Being able to predict stable crystalline phases under applied mechanical loading is crucial in understanding polymorphic transitions in crystalline solids. While the molecular-dynamics (MD) method developed by Parrinello and Rahman 1 (PR-MD) has been a major contribution toward capturing solid-solid transformations under stress, it requires (if used on its own) tedious analysis of long transient trajectories near critical points for reasonably accurate predictions of polymorphic transition onsets. To address such challenges, novel developments, namely metadynamics 2-4 and coarse molecular dynamics (CMD) 5 have provided systematic alternatives to mere analysis of conventional MD trajectories.The purpose of this Letter is to demonstrate the capabilities of CMD as an efficient computational approach to (i) locate stable crystalline phases successfully and (ii) predict accurately the transformation onset in polymorphic transitions in crystals. Specifically, we focus on determining the loading condition, expressed by a critical pressure P = P c , at which the onset of a transition from a body-centered cubic (bcc) to a hexagonal closepacked (hcp) phase occurs in a crystal under hydrostatic loading. To validate our approach, we choose as a reference the work of Zhao et al. 6 that has outlined (based on PR-MD simulations and lattice-statics calculations) the stability limits of different Morse-model crystalline phases under hydrostatic loading at low temperature.In particular, we concentrate on the case of the Morse-Ni crystal, where a bcc phase is stabilized under compression. For comparison purposes, we mention that, in Ref. 6, the results are reported in terms of stretch factors, λ = (ρ 0 /ρ) 1/3 , where ρ 0 and ρ are the densities of the cubic crystal at zero pressure and at the pressure of interest, respectively.Our model consists of a cubic supercell with 1458 atoms arranged in a bcc lattice.The interatomic interactions are described by a Morse potential properly parameterized for Ni. 6 The equations of motion are obtained through the PR ansatz, where the supercell geometry is described by a matrix, h, whose columns correspond to the three vectors, a, b, and c, that define the edges of the supercell. Cell rotations are avoided by setting the subdiagonal elements of h to zero; this eliminates three out of the nine degrees of freedom while preserving the full geometrical flexibility of the cell. The equation...

Using a coarse molecular-dynamics (CMD) approach with an appropriate choice of coarse variable (order parameter), we map the underlying effective free-energy landscape for the melting of a crystalline solid. Implementation of this approach provides a means for constructing effective free-energy landscapes of structural transitions in condensed matter. The predictions of the approach for the thermodynamic melting point of a model silicon system are in excellent agreement with those of "traditional" techniques for melting-point calculations, as well as with literature values.PACS numbers: 64.70. Dv, 05.70.Fh Accurate determination of the onset of structural transitions in complex physical systems is of crucial importance in condensed matter and materials physics. As direct access to such physical responses is typically difficult to attain experimentally, computational techniques such as molecular dynamics (MD) have provided powerful tools for probing the underlying atomicscale dynamics and determining the transition onset. Though one of the most attractive features offered by MD lies in its ability to ultimately relate atomistic dynamics to macroscopically observable physical behavior, computing the evolution of all of the atomic coordinates over coarse (observable) time scales poses a severe limitation to the method. Recently, significant contributions have been made in addressing such time-scale limitations (see, e.g., [1][2][3]). Toward this goal, the so-called coarse molecular-dynamics (CMD) approach [4] was developed as an attempt to circumvent shortcomings for obtaining and analyzing the evolution of slow coarse-grained variables ("observables") of complex dynamical material systems. The projection operation formalism [5] relates, in principle, microscopic dynamics to such slow evolution; yet, exact formulas for the corresponding noise and memory terms are practically inaccessible. CMD circumvents the evaluation of such terms by estimating on the fly the thermodynamic driving forces for the slow evolution, as well as its local dynamics. This CMD approach has been used to study non-equilibrium phenomena. For example, the CMD method has been used to study the dynamics of biomolecules [4] and of water molecules filling or emptying carbon nanotubes [6]. Coarse-grained information, estimated on-the-fly from many short and properly initialized independent replica MD simulations, can be used to identify transition points in the physical behavior of the complex systems under consideration. CMD is a part of the so-called equation-free framework for complex/multiscale system modeling [7], which has also been used to study condensed-matter dynamical phenomena, such as line-defect motion in impure crystalline solids [8] and micelle formation [9] based on Monte Carlo (MC) simulations. This Letter aims at determining the onset of structural transitions in condensed-matter systems within the CMD framework. This is achieved by the first application of the method to predicting the melting transition of a crystalline solid...

The thermally induced order-to-disorder transition of a monolayer of krypton ͑Kr͒ atoms adsorbed on a graphite surface is studied based on a coarse molecular-dynamics ͑CMD͒ approach for the bracketing and location of the transition onset. A planar order parameter is identified as a coarse variable, , that can describe the macroscopic state of the system. Implementation of the CMD method enables the construction of the underlying effective free-energy landscapes from which the transition temperature, T t , is predicted. The CMD prediction of T t is validated by comparison with predictions based on conventional molecular-dynamics ͑MD͒ techniques. The conventional MD computations include the temperature dependence of the planar order parameter, the specific heat, the Kr-Kr pair correlation function, the mean square displacement and corresponding diffusion coefficient, as well as the equilibrium probability distribution function of Kr-atom coordinates. Our findings suggest that the thermally induced order-to-disorder transition at the conditions examined in this study appears to be continuous. The CMD implementation provides substantial computational gains over conventional MD.