Angela Violi

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Angela Violi is a Professor in the Department of Mechanical Engineering, and adjunct faculty in Chemical Engineering, Biophysics, Macromolecular Science and Engineering, and Applied Physics. The research in the group of Violi is focused on the application of statistical mechanics and computational methods to chemically and physically oriented problems in nanomaterials and biology. The group investigates the formation mechanisms of nanomaterials for various applications, including energy and biomedical systems, and the dynamics of biological systems and their interactions with nanomaterials.

violinanoparticlegenesis

Don Siegel

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Don Siegel is an Associate Professor affiliated with the Mechanical Engineering Department and the Department of Material Science and Engineering. His research targets the discovery, characterization, and understanding of novel materials for energy-related applications. These efforts primarily employ atomic scale modeling to predict thermodynamic properties and kinetics. These data provide the necessary ingredients for identifying performance limiting mechanisms and for the “virtual screening” of candidate compounds having desired properties. Prof. Siegel is currently exploring several varieties of energy storage materials, lightweight structural alloys, and materials suitable for use in carbon capture applications.

Atomic scale model of a liquid electrolyte/solid Li2O2 interface in a Li-air battery cathode.

Atomic scale model of a liquid electrolyte/solid Li2O2 interface in a Li-air battery cathode.

Jeff Fessler

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Jeff Fessler is a Professor in the Department of Electrical Engineering and Computer Science – Electrical and Computer Engineering Division. His research interests include numerical optimization, inverse problems, image reconstruction, computational imaging, tomography, magnetic resonance imaging.  Most of these applications involve large problem sizes and parallel computing methods (cluster, cloud, GPU, SIMD, etc.) are needed.

Katsuyo Thornton

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Thornton’s research focuses on computational and theoretical investigations of the evolution of microstructures and nanostructures during processing and operation of materials. These investigations facilitate the understanding of the underlying physics of materials and their performance, which will aid us in designing advanced materials with desirable properties and in developing manufacturing processes that would enable their fabrication. The topics include growth and coarsening of precipitates, evolution of morphologically and topologically complex systems, microstructure-based simulations of electrochemical systems such as batteries, and self-assembly of quantum dots and other nanoscale phenomena during heteroepitaxy of semiconductors.  These projects involve advanced computational methods and large-scale simulations performed on high-performance computational platforms, and insights provide a means for material design and optimization.

A snapshot from a simulation of charge-discharge process in a lithium-ion battery, based on an experimentally obtained microstructure.

A snapshot from a simulation of charge-discharge process in a lithium-ion battery, based on an experimentally obtained microstructure.

Eric Johnsen

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His research interests lie in the development of numerical methods and models for massively parallel computations of fluid mechanics problems on modern computing architectures, including GPUs. He specifically focuses on high-order accurate finite difference/volume/element and spectral methods desgined for robust, accurate and efficient simulations. With his codes, he investigates the basic physics of multiphase flows, high-speed flows and shock waves, turbulence and mixing, interfacial instabilities, complex fluids and plasmas. Target applications include biomedical engineering, energy, aeronautics and naval engineering.

Time sequence showing turbulent mixing between two fluids of different densities. Vortical structures colored by density highlight how the mixing region grows while the turbulence decays. The results are obtained using direct numerical simulation (DNS), in which all dynamical scales are resolved.

Time sequence showing turbulent mixing between two fluids of different densities. Vortical structures colored by density highlight how the mixing region grows while the turbulence decays. The results are obtained using direct numerical simulation (DNS), in which all dynamical scales are resolved.

Emmanouil (Manos) Kioupakis

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His group uses first-principles computational methods and high-performance computing resources to predictively model the structural, electronic, and optical properties of bulk materials and nanostructures. The goal is to understand, predict, and optimize the properties of novel electronic, optoelectronic, photovoltaic, and thermoelectric materials.

The Kioupakis group uses high-performance computing to predictively model the electronic and optical properties of semiconductor nanostructures such as nanoporous silicon, nitride nanowires, and novel 2D materials.

The Kioupakis group uses high-performance computing to predictively model the electronic and optical properties of semiconductor nanostructures such as nanoporous silicon, nitride nanowires, and novel 2D materials.

Charles Brooks

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Charles L. Brooks III is the Warner-Lambert/Parke-Davis Professor of Chemistry and a Professor of Biophysics. He is affiliated with the department of Chemistry, Biophysics Program, program in Applied Physics, Molecular Biophysics Training Program (Director), program in Chemical Biology, Bioinformatics Graduate Program, Center for Computational Medicine and Bioinformatics and the Medicinal Chemistry Interdepartmental Graduate Program. The research in the group of Charles L. Brooks III is focused on the application of statistical mechanics, quantum chemistry and computational methods to chemically and physically oriented problems in biology. The group develops and applies computational models to studies of the dynamics of proteins, nucleic acids and their complexes, including virus structure and assembly. They specifically develop novel computational methods for the inclusion of pH effects in modeling biological systems. Significant focus is in the development of a large, world-wide distributed software package for molecular simulations, CHARMM. Efforts are ongoing to explore new means of parallel and accelerated computation utilizing scalable parallel algorithms for molecular dynamics and integrated CPU/GPU computational models.

R. Paul Drake

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Prof. Drake has played a leading role in the development of two related fields of inquiry — High-Energy-Density Physics (HEDP) and High-Energy-Density Laboratory Astrophysics (HEDLA). This has grown from his scientific work, encompassing experiment, theory, and simulation in several topical areas. His work at Michigan, since 1996, has emphasized hydrodynamics and radiation hydrodynamics with an emphasis on connections to supernovae and other applications to astrophysics.

Vikram Gavini

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His research group aims to develop computational and mathematical techniques to address various aspects of materials behavior, which exhibit complexity and structure on varying length and time scales. The work draws ideas from quantum mechanics, statistical mechanics and homogenization theories to create multi-scale models from fundamental principles, which provide insight into the complex behavior of materials. Topics of research include developing multi-scale methods for density-functional theory (electronic structure) calculations at continuum scales, electronic structure studies on defects in materials, quasi-continuum method, analysis of approximation theories, numerical analysis, and quantum transport in materials.

Hierarchy of triangulations that form the basis of a coarse-graining methods (quasi-continuum reduction) for conducting electronic structure calculations at macroscopic scales.

Hierarchy of triangulations that form the basis of a coarse-graining methods (quasi-continuum reduction) for conducting electronic structure calculations at macroscopic scales.