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Molecular-level modeling dynamics

Essential progress has been made recently in the area of molecular level modeling of capillary condensation. The methods of grand canonical Monte Carlo (GCMC) simulations [4], molecular dynamics (MD) [5], and density functional theory (DFT) [6] are capable of generating hysteresis loops for sorption of simple fluids in model pores. In our previous publications (see [7] and references therein), we have shown that the non-local density functional theory (NLDFT) with properly chosen parameters of fluid-fluid and fluid-solid intermolecular interactions quantitatively predicts desorption branches of hysteretic isotherms of nitrogen and argon on reference MCM-41 samples with pore channels narrower than 5 nm. [Pg.51]

Although the term mechanism of action itself implies a classification according to the dynamics of drug substance effects at the molecular level, the dynamics of these interactions are only speculative models at present, and so mechanism of action can currently only be used to describe static targets, as discussed above. [Pg.68]

Both aerosol modeling and more fundamental atomistic and molecular level models have been applied to this problem. Aerosol dynamics modeling has lead to a better understanding of the individual steps that comprise the formation of particles, all the way from nucleation to subsequent growth. Both molecualar orbital and reaction rate theory was used as sources of fundamental data for input to the aerosol dynamics model. A simplistic molecular dynamics computation has been used to explain the particle morphology observed. [Pg.63]

Molecular level computer simulations based on molecular dynamics and Monte Carlo methods have become widely used techniques in the study and modeling of aqueous systems. These simulations of water involve a few hundred to a few thousand water molecules at liquid density. Because one can form statistical mechanical averages with arbitrary precision from the generated coordinates, it is possible to calculate an exact answer. The value of a given simulation depends on the potential functions contained in the Hamiltonian for the model. The potential describing the interaction between water molecules is thus an essential component of all molecular level models of aqueous systems. [Pg.183]

In 1978, Doi and Edwards adopted this view and developed the tube theory for polymer melts. The main objective of this work was to derive the constitutive equations for polymer melts from a molecular level model. It was in this work that the tube concept and reptational motion were combined for a concise mathematical description of polymer melt dynamics. [Pg.420]

While thin polymer films may be very smooth and homogeneous, the chain conformation may be largely distorted due to the influence of the interfaces. Since the size of the polymer molecules is comparable to the film thickness those effects may play a significant role with ultra-thin polymer films. Several recent theoretical treatments are available [136-144,127,128] based on Monte Carlo [137-141,127, 128], molecular dynamics [142], variable density [143], cooperative motion [144], and bond fluctuation [136] model calculations. The distortion of the chain conformation near the interface, the segment orientation distribution, end distribution etc. are calculated as a function of film thickness and distance from the surface. In the limit of two-dimensional systems chains segregate and specific power laws are predicted [136, 137]. In 2D-blends of polymers a particular microdomain morphology may be expected [139]. Experiments on polymers in this area are presently, however, not available on a molecular level. Indications of order on an... [Pg.385]

Continuum models remove the difficulties associated with the statistical sampling of phase space, but they do so at the cost of losing molecular-level detail. In most continuum models, dynamical properties associated with the solvent and with solute-solvent interactions are replaced by equilibrium averages. Furthermore, the choice of where the primary subsystem ends and the dielectric continuum begins , i.e., the boundary and the shape of the cavity containing the primary subsystem, is ambiguous (since such a boundary is intrinsically nonphysical). Typically this boundary is placed on some sort of van der Waals envelope of either the solute or the solute plus a few key solvent molecules. [Pg.3]

Most of the new molecular-level results concern the structure and dynamics of water at interfaces. We begin this review with a brief summary of this area. Several recent review articles and books can be consulted for additional information. " We then examine in some detail the new insight gained from molecular dynamic simulations of the structure of the electric double layer and the general behavior of ions at the water/metal interface. We conclude by examining recent developments in the modeling of electron transfer reactions. [Pg.116]

Inner slip, between the solid wall and an adsorbed film, will also influence the surface-liquid boundary conditions and have important effects on stress propagation from the liquid to the solid substrate. Linked to this concept, especially on a biomolecular level, is the concept of stochastic coupling. At the molecular level, small fluctuations about the ensemble average could affect the interfacial dynamics and lead to large shifts in the detectable boundary condition. One of our main interests in this area is to study the relaxation time of interfacial bonds using slip models. Stochastic boundary conditions could also prove to be all but necessary in modeling the behavior and interactions of biomolecules at surfaces, especially with the proliferation of microfluidic chemical devices and the importance of studying small scales. [Pg.82]

The complications for fhe fheoretical description of proton fransporf in the interfacial region befween polymer and water are caused by the flexibility of fhe side chains, fheir random distributions at polymeric aggregates, and their partial penetration into the bulk of water-filled pores. The importance of an appropriate flexibilify of hydrated side chains has been explored recently in extensive molecular modeling studies. Continuum dielectric approaches and molecular dynamics simulations have been utilized to explore the effects of sfafic inferfacial charge distributions on proton mobility in single-pore environments of Molecular level simulations were employed... [Pg.383]

Biochemistry and chemistry takes place mostly in solution or in the presence of large quantities of solvent, as in enzymes. As the necessary super-computing becomes available, molecular dynamics must surely be the method of choice for modeling structure and for interpreting biological interactions. Several attempts have been made to test the capability of molecular dynamics to predict the known water structure in crystalline hydrates. In one of these, three amino acid hydrates were used serine monohydrate, arginine dihydrate and homoproline monohydrate. The first two analyses were by neutron diffraction, and in the latter X-ray analysis was chosen because there were four molecules and four waters in the asymmetric unit. The results were partially successful, but the final comments of the authors were "this may imply that methods used currently to extract potential function parameters are insufficient to allow us to handle the molecular-level subtleties that are found in aqueous solutions" (39). [Pg.25]

MD simulations of model membrane systems have provided a unique view of lipid interactions at a molecular level of resolution [21], Due to the inherent fluidity and heterogeneity in lipid membranes, computer simulation is an attractive tool. MD simulations allow us to obtain structural, dynamic, and energetic information about model lipid membranes. Comparing calculated structural properties from our simulations to experimental values, such as areas and volumes per lipid, and electron density profiles, allows validation of our models. With molecular resolution, we are able to probe lipid-lipid interactions at a level difficult to achieve experimentally. [Pg.7]


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See also in sourсe #XX -- [ Pg.485 ]




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