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The multiparticle collision dynamics (MPCD) simulation method is an attractive technique for studying the effects of hydrodynamic interactions in colloidal suspensions because of its flexibility, computational efficiency, and ease of implementation. Here, we analyze an extension of the basic MPCD method in which colloidal particles are discretized with a surface mesh of sensor nodes/particles that interact with solvent particles (MPCD + Discrete Particle or MPCD + DP). We use several situations that have been described analytically to probe the impact of colloidal particle mesh resolution on the ability of the MPCD + DP method to resolve short-ranged hydrodynamic interactions, which are important in crowded suspensions and especially in self-assembling systems that create high volume fraction phases. Specifically, we consider (A) hard-sphere diffusion near a wall, (B) two-particle diffusion, (C) hard-sphere diffusion in crowded suspensions, and (D) the dynamics of aggregation in an attractive colloidal suspension. We show that in each case, the density of sensor nodes plays a significant role in the accuracy of the simulation and that a surprisingly high number of surface nodes are needed to fully capture hydrodynamic interactions. [ABSTRACT FROM AUTHOR]

The equilibrium segregation of impurities at the melt–solid interface during silicon crystallization is a key factor in determining the impurity concentration and distribution in the crystal. Unfortunately, this property is difficult to measure experimentally due to the presence of complex transport physics in the melt. Here, using the Tersoff family of empirical potential models, we describe a thermodynamic integration framework for computing the interstitial oxygen and substitutional carbon segregation coefficients in silicon. Thermodynamic integration using an ideal gas reference state for the impurity atoms is shown to be an efficient and convenient pathway for evaluating impurity chemical potentials in both solid and liquid phases. We find that the segregation coefficient is captured well for substitutional carbon impurity while it is significantly underestimated for interstitial oxygen. The latter discrepancy is partially attributed to the qualitatively incorrect silicon solid-to-liquid density ratio predicted by the empirical interatomic potential. [ABSTRACT FROM AUTHOR]

A quantitative continuum model for oxide precipitation in silicon is presented that accounts for vacancy absorption and shape change as mechanisms of precipitate stress relief. All model parameters except one, the Si/SiO2 interface free energy, are fixed at values established in prior studies of microdefect formation. The interface free energy is described by an 8-parameter function, whose functional form and dependencies were based on an analysis of electronic structure calculations of small oxide cluster thermodynamics. The interface energy function parameters are regressed, using global optimization, to an experimental benchmark consisting of 13 wafer thermal anneals, with different temperature-time histories and resulting in widely varying measured final oxide precipitate densities. We demonstrate that the model is able to capture the benchmark features well with multiple parameter combinations and that additional constraints are required to fully specify a unique solution. We also show that a simple, single-parameter, constant interface free energy model cannot fully capture the diverse experimental benchmark, highlighting the complexity of oxide precipitation. The precipitation model is used to analyze the mechanisms responsible for several features of oxide nucleation and growth during wafer annealing. [ABSTRACT FROM AUTHOR]

The nucleation and growth of SiC precipitates in liquid silicon is important in the crystallization of silicon used for the photovoltaic industry. These processes depend strongly on the carbon concentration as well as the equilibrium solubility relative to the precipitate phase. Here, using a suite of statistical thermodynamic techniques, we calculate the solubility of carbon atoms in liquid silicon relative to the β-SiC phase. We employ several available empirical potentials to assess whether these potentials may reasonably be used to computationally analyze SiC precipitation. We find that some of the Tersoff-type potentials provide an excellent picture for carbon solubility in liquid silicon but, because of their severe silicon melting point overestimation, are limited to high temperatures where the carbon solubility is several percent, a value that is irrelevant for typical solidification conditions. Based on chemical potential calculations for pure silicon, we suggest that this well-known issue is confined to the description of the liquid phase and demonstrate that some recent potential models for silicon might address this weakness while preserving the excellent description of the carbon-silicon interaction found in the existing models. [ABSTRACT FROM AUTHOR]

Analysis of interdigitated transducers often relies on phenomenological models to approximate device electrical performance. While these approaches prove essential for signal processing applications, phenomenological models provide limited information on the device's mechanical response and physical characteristics of the generated acoustic field. Finite element method modeling, in comparison, offers a robust platform to study the effects of the full device geometry on critical performance parameters of interdigitated transducer devices. In this study, we fabricate a surface acoustic wave resonator on semi-insulating GaAs (100) , which consists of an interdigitated transducer and acoustic mirror assembly. The device is subsequently modeled using fem software. A vector network analyzer is used to measure the experimental device scattering response, which compares well with the simulated results. The wave characteristics of the experimental device are measured by contact-mode atomic force microscopy, which validates the simulation's mechanical response predictions. We further show that a computational parametric analysis can be used to optimize device designs for series resonance frequency, effective coupling coefficient, quality factor, and maximum acoustic surface displacement. [ABSTRACT FROM AUTHOR]

A recently demonstrated approach for creating structured compositional gradients in the near-surface region of SiGe substrates is studied parametrically using a multiresolution coarse-grained lattice kinetic Monte Carlo simulation method. In the "stress patterning" process, a patterned elastic stress field is generated in the SiGe substrate by pressing an array of micro-indenters into it. The stressed substrate is then thermally annealed to drive the atomic diffusion in which the larger Ge atoms are pushed away from the areas of compressive stress. By varying a subset of the parameters that characterize the high-dimensional input space of the process (e.g., indenter spacing, indenter tip shape, and indenter array symmetry) we show that technologically interesting compositional configurations may be readily generated. In particular, we show that it is theoretically possible to generate arrays of well-delineated nanoscale regions of high Ge content surrounded by essentially pure Si. Such configurations may be useful as Ge "quantum dots" that exhibit three-dimensional quantum confinement, which have otherwise been very challenging to create with high degrees of size and spatial uniformity. These simulation results will be instrumental in guiding future experimental demonstrations of stress patterning. [ABSTRACT FROM AUTHOR]

Direct molecular dynamics simulation of atomic deposition under realistic conditions is notoriously challenging because of the wide range of time scales that must be captured. Numerous simulation approaches have been proposed to address the problem, often requiring a compromise between model fidelity, algorithmic complexity, and computational efficiency. Coarse projective integration, an example application of the "equation-free" framework, offers an attractive balance between these constraints. Here, periodically applied, short atomistic simulations are employed to compute time derivatives of slowly evolving coarse variables that are then used to numerically integrate differential equations over relatively large time intervals. A key obstacle to the application of this technique in realistic settings is the "lifting" operation in which a valid atomistic configuration is recreated from knowledge of the coarse variables. Using Ge deposition on amorphous SiO2 substrates as an example application, we present a scheme for lifting realistic atomistic configurations comprised of collections of Ge islands on amorphous SiO2 using only a few measures of the island size distribution. The approach is shown to provide accurate initial configurations to restart molecular dynamics simulations at arbitrary points in time, enabling the application of coarse projective integration for this morphologically complex system. [ABSTRACT FROM AUTHOR]

The segregation behavior of carbon and oxygen atoms at various silicon grain boundaries was studied using a combination of atomistic simulation and analytical modeling. First, quasi-lattice Grand Canonical Monte Carlo simulations were used to compute segregation isotherms as a function of grain boundary type, impurity atom loading level, and temperature. Next, the atomistic results were employed to regress different analytical segregation models and extract thermodynamic and structural properties. The multilayer Brunauer--Emmett-Teller (BET) isotherm was found to quantitatively capture all the simulation conditions probed in this work, while simpler, single layer models such as the Langmuir-McLean model did not. Some of the BET parameters, namely, the binding free energy of the first adsorption layer and the impurity holding capacity of each layer, were tested for correlation with various measures of grain boundary structure and/or mechanical properties. It was found that certain measures of the atomistic stress distribution correlate strongly with the first-layer binding free energy for substitutional carbon atoms, while common grain boundary identifiers such as sigma value and energy density are not useful in this regard. Preliminary analysis of the more complex case of interstitial oxygen segregation showed that similar measures based on atomistic stress also may be useful here, but more systematic correlative studies are needed to develop a comprehensive picture. [ABSTRACT FROM AUTHOR]

We study computationally the formation of thermodynamics and morphology of silicon selfinterstitial clusters using a suite of methods driven by a recent parameterization of the Tersoff empirical potential. Formation free energies and cluster capture zones are computed across a wide range of cluster sizes (2i<150) and temperatures (0.65m<1). Self-interstitial clusters above a critical size (Ni∼25) are found to exhibit complex morphological behavior in which clusters can assume either a variety of disordered, three-dimensional configurations, or one of two macroscopically distinct planar configurations. The latter correspond to the well-known Frank and perfect dislocation loops observed experimentally in ion-implanted silicon. The relative importance of the different cluster morphologies is a function of cluster size and temperature and is dictated by a balance between energetic and entropic forces. The competition between these thermodynamic forces produces a sharp transition between the three-dimensional and planar configurations, and represents a type of order-disorder transition. By contrast, the smaller state space available to smaller clusters restricts the diversity of possible structures and inhibits this morphological transition. [ABSTRACT FROM AUTHOR]