Our research interests are in the area of multi-scale modeling of complex systems
with special emphasis on theoretical & computational materials science &
engineering. Our research program aims at simulation of processing and function and
prediction of structure, properties, and reliability of electronic and structural
materials. In addition to obtaining a fundamental understanding of the behavior of
complex material systems, we are especially interested in modeling processing and
function of semiconductor and metallic thin films used in the fabrication of electronic,
optoelectronic, and photovoltaic devices. All of these material systems are characterized
by structural inhomogeneities, such as crystalline lattice imperfections, surfaces,
interfaces, and a variety of nanostructural features. Understanding the formation and
evolution of such nano/micro-structure during physical or chemical processing and during
device function is particularly important in developing processes that yield optimal
material properties and guarantee device performance and reliability. Our research
efforts focus on the development and implementation of computational quantum,
statistical, and continuum mechanical methods for the study of structure and dynamics and
for predictions of bulk and interfacial properties of heterogeneous materials. Special
emphasis is placed on establishing rigorous links between atomistic and macroscopic
(continuum) length scales and between fast and slow time scales: this enables us to
develop coarse descriptions of multi-scale, multi-physics phenomena in complex materials
starting from an atomistic, first-principles-based description of bonding and dynamics.
Consequently, our research employs computational methods that span the spectrum from
electronic structure calculation techniques to continuum numerical modeling, including:
ab initio calculations of atomic structure, total energy, and atomic-scale dynamics based
on density functional theory; structural relaxation, lattice-dynamics, Monte Carlo, and
molecular-dynamics simulation methods based on empirical and semi-empirical descriptions
of interatomic interactions; kinetic Monte Carlo and mean-field rate equation models; and
continuum modeling techniques based on domain discretization such as finite-element,
finite-difference, and boundary-element methods. In addition, analytical and numerical
stability & bifurcation theory are implemented for understanding materials’
structural and morphological response upon variation of processing and operating
parameters. Currently, we are especially interested in developing methods for overcoming
time-scale limitations of atomistic dynamical simulators and enabling such simulators to
perform numerical bifurcation & stability analysis. 

No subject area

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Mechanical Behavior of Ultra-low-dielectric-constant Mesoporous Amorphous Silica (with M. R. Gungor and J. J. Watkins), Applied Physics Letters (2011)

We report results for the dependence of the mechanical properties of ordered mesoporous silica structures...

 

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Electromechanically Driven Chaotic Dynamics of Voids in Metallic Thin Films (with M. R. Gungor and V. Tomar), Physical Review B (2010)

We report a systematic investigation of complex asymptotic states reached in the electromigration-driven morphological evolution...

 

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Analysis of Diamond Nanocrystal Formation from Multiwalled Carbon Nanotubes (with E. S. Aydil, T. Singh, and A. R. Muniz), Physical Review B (2009)

A systematic analysis is presented of the nanocrystalline structures generated due to the intershell C-C...

 

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Comparative Study of the Mechanical Behavior Under Biaxial Strain of Prestrained Face-centered Cubic Metallic Ultrathin Films (with M. R. Gungor and K. Kolluri), Applied Physics Letters (2009)

We report a molecular-dynamics study of the mechanical response to dynamic biaxial tensile straining of...

 

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Kinetic Monte Carlo simulations of surface growth during plasma deposition of silicon thin films (with T. Singh and S. Pandey), Journal of Chemical Physics (2009)

Based on an atomically detailed surface growth model, we have performed kinetic Monte Carlo (KMC)...