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Theoretical and experimental studies of electrified interfaces relevant to energy storage

Hayden, Carl C.; Templeton, Jeremy A.; Jones, Reese E.; Kliewer, Christopher J.; Sasaki, Darryl Y.; Reyes, Karla R.

Advances in technology for electrochemical energy storage require increased understanding of electrolyte/electrode interfaces, including the electric double layer structure, and processes involved in charging of the interface, and the incorporation of this understanding into quantitative models. Simplified models such as Helmholtz's electric double-layer (EDL) concept don't account for the molecular nature of ion distributions, solvents, and electrode surfaces and therefore cannot be used in predictive, high-fidelity simulations for device design. This report presents theoretical results from models that explicitly include the molecular nature of the electrical double layer and predict critical electrochemical quantities such as interfacial capacitance. It also describes development of experimental tools for probing molecular properties of electrochemical interfaces through optical spectroscopy. These optical experimental methods are designed to test our new theoretical models that provide descriptions of the electric double layer in unprecedented detail.

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Multiscale modeling for fluid transport in nanosystems

Jones, Reese E.; Lee, Jonathan L.; Zimmerman, Jonathan A.

Atomistic-scale behavior drives performance in many micro- and nano-fluidic systems, such as mircrofludic mixers and electrical energy storage devices. Bringing this information into the traditionally continuum models used for engineering analysis has proved challenging. This work describes one such approach to address this issue by developing atomistic-to-continuum multi scale and multi physics methods to enable molecular dynamics (MD) representations of atoms to incorporated into continuum simulations. Coupling is achieved by imposing constraints based on fluxes of conserved quantities between the two regions described by one of these models. The impact of electric fields and surface charges are also critical, hence, methodologies to extend finite-element (FE) MD electric field solvers have been derived to account for these effects. Finally, the continuum description can have inconsistencies with the coarse-grained MD dynamics, so FE equations based on MD statistics were derived to facilitate the multi scale coupling. Examples are shown relevant to nanofluidic systems, such as pore flow, Couette flow, and electric double layer.

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Molecular dynamics studies of material property effects on thermal boundary conductance

Physical Chemistry Chemical Physics

Zhou, X.W.; Jones, Reese E.; Duda, J.C.; Hopkins, P.E.

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.

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The application of an atomistic J-integral to a ductile crack

Journal of Physics Condensed Matter

Zimmerman, Jonathan A.; Jones, Reese E.

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.

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A stochastic multiscale coupling scheme to account for sampling noise in atomistic-to-continuum simulations

Multiscale Modeling and Simulation

Salloum, Maher S.; Sargsyan, Khachik S.; Jones, Reese E.; Debusschere, Bert D.; Najm, H.N.; Adalsteinsson, Helgi A.

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.

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Results 151–175 of 243
Results 151–175 of 243