Publications

Abstract not provided.

Thermal boundary resistance (inverse of conductance) between different material layers can dominate the overall thermal resistance in nanostructures and therefore impact the performance of the thermal property limiting nano devices. Because relationships between material properties and thermal boundary conductance have not been fully understood, optimum devices cannot be developed through a rational selection of materials. Here we develop generic interatomic potentials to enable material properties to be continuously varied in extremely large molecular dynamics simulations to explore the dependence of thermal boundary conductance on the characteristic properties of materials such as atomic mass, stiffness, and interfacial crystallography. To ensure that our study is not biased to a particular model, we employ different types of interatomic potentials. In particular, both a Stillinger-Weber potential and a hybrid embedded-atom-method + Stillinger-Weber potential are used to study metal-on-semiconductor compound interfaces, and the results are analyzed considering previous work based upon a Lennard-Jones (LJ) potential. These studies, therefore, reliably provide new understanding of interfacial transport phenomena particularly in terms of effects of material properties on thermal boundary conductance. Our most important finding is that thermal boundary conductance increases with the overlap of the vibrational spectra between metal modes and the acoustic modes of the semiconductor compound, and increasing the metal stiffness causes a continuous shift of the metal modes. As a result, the maximum thermal boundary conductance occurs at an intermediate metal stiffness (best matched to the semiconductor stiffness) that maximizes the overlap of the vibrational modes. © 2013 the Owner Societies.

Abstract not provided.

Abstract not provided.

Abstract not provided.

In this work we apply a Lagrangian kernel-based estimator of continuum fields to atomic data to estimate the J-integral for the emission dislocations from a crack tip. Face-centered cubic (fcc) gold and body-centered cubic (bcc) iron modeled with embedded atom method (EAM) potentials are used as example systems. The results of a single crack with a K-loading compare well to an analytical solution from anisotropic linear elastic fracture mechanics. We also discovered that in the post-emission of dislocations from the crack tip there is a loop size-dependent contribution to the J-integral. For a system with a finite width crack loaded in simple tension, the finite size effects for the systems that were feasible to compute prevented precise agreement with theory. However, our results indicate that there is a trend towards convergence. © 2013 IOP Publishing Ltd.

Abstract not provided.

Abstract not provided.

Abstract not provided.

We present a methodology to assess the predictive fidelity of multiscale simulations by incorporating uncertainty in the information exchanged between the atomistic and continuum simulation components. Focusing on uncertainty due to finite sampling in molecular dynamics (MD) simulations, we present an iterative stochastic coupling algorithm that relies on Bayesian inference to build polynomial chaos expansions for the variables exchanged across the atomistic-continuum interface. We consider a simple Couette flow model where velocities are exchanged between the atomistic and continuum components. To alleviate the burden of running expensive MD simulations at every iteration, a surrogate model is constructed from which samples can be efficiently drawn as data for the Bayesian inference. Results show convergence of the coupling algorithm at a reasonable number of iterations. The uncertainty associated with the exchanged variables significantly depends on the amount of data sampled from the MD simulations and on the width of the time averaging window used in the MD simulations. Sequential Bayesian updating is also implemented in order to enhance the accuracy of the stochastic algorithm predictions. © 2012 Society for Industrial and Applied Mathematics.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.