Liang Qi

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Professor Qi’s research fields are investigations of the mechanical and chemical properties of materials by applying theoretical and computational tools, including first-principles calculations, atomistic simulations and multiscale modeling. His major research interests are quantitative understanding of the intrinsic electronic/atomistic mechanisms for the mechanical deformation, phase transformation and chemical degradation (corrosion/oxidation) of advanced alloys and other structural/functional materials. Currently he is focusing on the studies of deformation defects and interfaces in materials under extreme conditions, such as high stress and/or chemically active environment, where the materials behaviors and properties can be dramatically different than those predicted by classical theories and models. He is also developing the numerical methods to integrate these electronic/atomistic results with large-scale simulations and experimental characterizations in order to design materials with improved mechanical performances and chemical stabilities.

A Jahn-Teller distortion signifies the onset of the shear instability for a body-centered-cubic crystal placed under tension. The symmetry breaking correlates with the intrinsic ductility of the material, and the strain at which it appears can be controlled by alloying.

A Jahn-Teller distortion signifies the onset of the shear instability for a body-centered-cubic crystal placed under tension. The symmetry breaking correlates with the intrinsic ductility of the material, and the strain at which it appears can be controlled by alloying.

Don Siegel

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Don Siegel is a Professor in the Department of Mechanical Engineering 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.

Kai Sun

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His  research focuses on understanding the role of strong correction effects in many-body quantum systems. The objective is to discover novel quantum states/materials and to understand their exotic properties using theoretical/numerical methods (with emphasis on topological properties). In his research, numerical techniques are applied to resolve the fate of a quantum material (or a theoretical model) in the presence of multiple competing ground states and to provide quantitative guidance for further (experimental/theoretical) investigations.

TI Animation

Interaction induced topological insulator with spontaneously-generated orbital rotations. This figure demonstrate how to use strong interactions to generate a topological state of matter in a many-body quantum system.

Veera Sundararaghavan

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Prof. Sundararaghavan develops multi-scale computational methods for polycrystalline alloys, polymer composites, and ultra-high temperature ceramic composites to model the effect of microstructure on the overall deformation, fatigue, failure, thermal transport and oxidation response. Recent packages developed include a fully parallel multiscale approach for optimization of polycrystalline alloys during forming processes and a multiscale approach for modeling oxidative degradation in high temperature fiber reinforced ceramic matrix composites. He has made seminal contributions towards the use of multiscale models for accelerated “microstructure-sensitive design” including development of data mining methods for microstructures and reduced order techniques for graphical visualization of microstructure-process-property relationships.

Results from a parallel crystal plasticity code showing the stress distribution in Aluminum alloy microstructure during compression testing.

Results from a parallel crystal plasticity code showing the stress distribution in Aluminum alloy microstructure during compression testing.

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.

Anthony Waas

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Anthony M. Waas is the Richard A. Auhll Department Chair of Aerospace Engineering at the University of Michigan, Ann Arbor where he holds the Felix Pawlowski Collegiate Chair since September 1, 2018. Prior to that, he was the Boeing Egtvedt Endowed Chair Professor and Department Chair in the William E. Boeing Department of Aeronautics and Astronautics at the University of Washington, Seattle.

The development of validated analytical and computational methods to understand how a structure (such as an air-vehicle wing, a fuselage, the load bearing structure of a land-vehicle, the wing of an insect, a wind turbine blade) made of multi-materials responds to external environments is the overarching goal of Wass’ research group. Naturally, this involves multi-physics and mechanics based models at different spatial and temporal scales. To achieve this goal, the group performs a combination of experiments, computational modeling and analysis, and theoretical developments when necessary. This work has led to novel algorithms and multi-scale methods that provide a balance between high fidelity and computational efficiency, with particular emphasis on capturing damage and failure mechanics, including interaction between these in a mesh (discretization) objective manner.

Professor Waas is a Fellow of the American Institute of Aeronautics and Astronautics (AIAA), the American Society of Mechanical Engineering (ASME), and the American Academy of Mechanics (AAM). He is a recipient of several best paper awards, the 2016 AIAA/ASME SDM award, the AAM Jr. Research Award, the ASC Outstanding Researcher Award, and several distinguished awards from the University of Michigan. He received the AIAA-ASC James H. Starnes, Jr. Award, 2017, for seminal contributions to composite structures and materials and for mentoring students and other young professionals. In 2017, Professor Waas was elected to the Washington State Academy of Sciences, and in 2018 to the European Academy of Sciences and Arts.

Professor Waas obtained his B.Sc in Aeronautics with First Class Honors from Imperial College, London, 1982, the ACGI in 1982, the MS and Ph.D in Aeronautics and Applied Mathematics (minor)  from Caltech, 1983 and 1988, respectively.

Crack growth prediction (code developed by Dr. Rudraa Raju)

Crack growth prediction (code developed by Dr. Rudraa Raju)

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.

Ronald Larson

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Ronald Larson is the A.H. White and G.G. Brown Professor of Chemical Engineering. He is affiliated with the departments of Chemical Engineering, Macromolecular Science, Biomedical Engineering, and Mechanical Engineering. He currently serves as interim Chair of Biomedical Engineering. Larson’s research interests include theory and simulations of the structure and flow properties of viscous or elastic fluids, sometimes called “complex fluids,” which include polymers, colloids, surfactant-containing fluids, liquid crystals, and biological macromolecules such as DNA, proteins, and lipid membranes. He also studies computational fluid mechanics, including microfluidics, and transport modeling, using mesoscopic and macroscopic simulation methods.  He has written numerous scientific papers and two books on these subjects, including a 1998 textbook, “The Structure and Rheology of Complex Fluids.”

Simulated three dimensional self assembly of spherical “Janus” particles with attractive faces (blue, on far left and red on far right) and non-attractive faces (white). The far left shows packing in the “rotator” phase, where the attractive faces have not ordered orientationally, which occurs at lower temperature. Other images show single sphere, or groups of spheres, indicating hexagonal ordering. Surrounding points show positions of surrounding spheres, at multiple time points, indicating motions about crystal lattice points.

Simulated three dimensional self assembly of spherical “Janus” particles with attractive faces (blue, on far left and red on far right) and non-attractive faces (white). The far left shows packing in the “rotator” phase, where the attractive faces have not ordered orientationally, which occurs at lower temperature. Other images show single sphere, or groups of spheres, indicating hexagonal ordering. Surrounding points show positions of surrounding spheres, at multiple time points, indicating motions about crystal lattice points.

Sherif El-Tawil

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Prof. El-Tawil’s general research interest lies in computational modeling, analysis, and testing of structural materials and systems. He is especially interested in how buildings and bridges behave under the extreme loading conditions generated by manmade and natural hazards such as seismic excitation, collision by heavy objects, and blast. The focus of his research effort is to investigate how to utilize new materials, concepts and technologies to create innovative structural systems that mitigate the potentially catastrophic effects of extreme loading.

Much of his research is directed towards the computational and theoretical aspects of structural engineering, with particular emphasis on computational simulation, constitutive modeling, multiscale techniques, macro-plasticity formulations, nonlinear solution strategies and visualization methods. Prof. El-Tawil also has a strong and long-sustained interest in multi-disciplinary research. He has conducted research in human decision making and social interactions during extreme events and the use of agent based models for egress simulations. He is also interested in visualization and has developed new techniques for applying virtual reality in the field of finite element simulations and the use of augmented reality for rapid assessment of infrastructure damage in the wake of disasters.
Modeling the collapse response of a 10-story building.

Modeling the collapse response of a 10-story building.

Krishna Garikipati

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His research is in computational physics, specifically biophysics (tumor growth and cell mechanics) and materials physics (battery materials, structural alloys and semiconductor materials). In these areas Garikipati’s group focuses on developing mathematical and numerical models of phenomena that can be described by continuum analyses that translate to PDEs. Usually, these are nonlinear, and feature coupled physics, for example chemo-thermo-mechanics. Our numerical techniques are mesh-based variational methods such as the finite element method and its many variants. In some problems we make connections with fine-grained models, in which case we work with kinetic Monte Carlo, molecular dynamics or electronic structure calculations in some form. In the realm of analysis, we often examine the asymptotic limits of our mathematical models, and the consistency, stability and convergence of our numerical methods.

Isogeometric analysis (weak form based-solution of PDEs with spline basis functions) of phase transformations in a battery material.

Isogeometric analysis (weak form based-solution of PDEs with spline basis functions) of phase transformations in a battery material.