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The structural evolution of surface gratings on a glassy material is investigated by means of molecular simulations. The gratings provide a means to probe surface diffusion in the vicinity of the glass transition temperature. A theory by Mullins [J. Appl. Phys. 30, 77 (1959)] is used to extract qu-antitative measures of surface diffusivity that rely on calculation of grating amplitude as a function of time. The simulations are implemented in the context of a model binary glass mixture [S. S. Ashwin and S. Sastry, J. Phys.: Condens. Matter 15, S1253 (2003)]. We find that surface diffusion is faster than bulk diffusion by several orders of magnitude, consistent with recent experimental data for an organic glass former. The diffusivities extracted by the grating-decay approach are consistent with those estimated on the basis of mean-squared particle displacements. The grating-decay approach, however, is more efficient than traditional techniques based on Einstein's diffusion equation. Grating decay is also more versatile and is shown to be applicable in a variety of sample geometries. [ABSTRACT FROM AUTHOR]

The free energy surfaces of a wide variety of systems encountered in physics, chemistry, and biology are characterized by the existence of deep minima separated by numerous barriers. One of the central aims of recent research in computational chemistry and physics has been to determine how transitions occur between deep local minima on rugged free energy landscapes, and transition path sampling (TPS) Monte-Carlo methods have emerged as an effective means for numerical investigation of such transitions. Many of the shortcomings of TPS-like approaches generally stem from their high computational demands. Two new algorithms are presented in this work that improve the efficiency of TPS simulations. The first algorithm uses biased shooting moves to render the sampling of reactive trajectories more efficient. The second algorithm is shown to substantially improve the accuracy of the transition state ensemble by introducing a subset of local transition path simulations in the transition state. The system considered in this work consists of a two-dimensional rough energy surface that is representative of numerous systems encountered in applications. When taken together, these algorithms provide gains in efficiency of over two orders of magnitude when compared to traditional TPS simulations. [ABSTRACT FROM AUTHOR]

We analyze the response of a nematic liquid-crystal film, confined between parallel walls, to the presence of nanoscopic particles adsorbed at the walls. This is done for a variety of patterns of adsorption (random and periodic) and operational conditions of the system that can be controlled in experimental liquid-crystal-based devices. We compute simulated optical textures and the total optical output of the sensor between crossed polars, as well as the correlation function for the liquid-crystal tensor order parameter; we use these observables to discuss the gradual destruction of the original uniform orientation. For large concentrations of particles adsorbed in random patterns, the liquid crystal at the center of the sensor adopts a multidomain state, characterized by a small correlation length of the tensor order parameter, and also by a loss of optical anisotropy under observation through crossed polars. In contrast, for particles adsorbed in periodic patterns, the nematic at the center of the cell can remain in a monodomain orientation state, provided the patterns in opposite walls are synchronized. [ABSTRACT FROM AUTHOR]