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Anthony Waas

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Anthony Waas is the Felix Pawlowski Collegiate Professor Emeritus of Aerospace Engineering and Mechanical Engineering (courtesy). 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. Publications listed in ISI Web of Science, under the name “Waas, AM” will show the diversity of computational discovery and engineering related research that the group has done and is doing.

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.

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.

Eitan Geva

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Eitan Geva is a Professor of Chemistry. Modern computational chemistry strives to provide an atomistically detailed dynamical description of fundamental chemical processes. The strategy for reaching this goal generally follows a two-step program. In the first step, electronic structure calculations are used to obtain the force fields that the nuclei are subject to. In the second step, molecular dynamics simulations are used to describe the motion of the nuclei. The first step is always based on quantum mechanics, in the light of the pronounced quantum nature of the electrons. However, the second step is most often based on classical mechanics. Indeed, classical molecular dynamics simulations are rroutinely used nowadays for describing the dynamics of complex chemical systems that involve tens of thousands of atoms. However, there are many important situations where classical mechanics cannot be used for describing the dynamics. Our research targets the most chemically relevant examples of such processes.
  1. Vibrational end electronic relaxation. The pathways of intramolecular energy redistribution within molecules and intermolecular energy transfer between molecules, which dictate chemical reactivity, are governed by the rates of these processes. The pronounced quantum nature of these processes is attributed to the large gap between vibrational and electronic energy levels.
  2. Proton and electron transfer reactions. The elementary steps of many complex chemical processes are based on such reactions. Their pronounced quantum nature is attributed to the light mass of protons and electrons, which often give rise to quantum tunneling and zero-point energy effects.
  3. Nonadiabatic dynamics. Such dynamics underlie photochemistry and nonlinear spectroscopy is quantum in nature since it involves simultaneous motion on several potential surfaces that correspond to different electronic or vibrational states.

The challenge involved in simulating the quantum molecular dynamics of such systems has to do with the fact that the computational effort involved in solving the time-dependent Schrodinger equation is exponentially larger than that involved in Newton’s equations. As a result, a numerically exact solution of the Schrondinger equation is not feasible for a system that consists of more than a few atoms. The main research thrust of the Geva group is aimed at developing rigorous and accurate mixed quantum-classical, quasi-classical and semiclassical methods that would make it possible to simulate equilibrium and nonequilibrium quantum dynamics of systems that consist of hundreds of atoms and molecules. We put emphasis on applications to experimentally-relevant disordered complex condensed phase systems such as molecular liquids, which serve as hosts for many important chemical processes. We also specialize in modeling and analyzing different types of time resolved electronic and vibrational spectra that are used to probe molecular dynamics in those systems, often in collaboration with experimental groups.

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Sharon Glotzer

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Sharon Glotzer is a Professor of Chemical Engineering and of Material Science and Engineering. The Glotzer group uses computer simulations to discover the fundamental principles by which nanoscale systems of building blocks self-assemble into higher order, complex, and often hierarchical structures. Their goal is to learn how to manipulate matter at the molecular, nanoparticle, and colloidal scales to create “designer” structures through assembly engineering. Using molecular dynamics and Monte Carlo simulation codes developed in-house for graphics processors (GPUs) and scalable to large hybrid CPU/GPU clusters, they are the leading computational assembly group in the world, with the most powerful codes for studying assembly and packing. Among others, they are the lead developer of HOOMD-Blue, the fastest molecular dynamics code written solely for GPUs and distributed freely as open source software on codeblue.umich.edu.  Based on the fundament scientific principles of assembly gleaned from their studies, they carry out high throughout simulations for materials by design, contributing to the national Materials Genome Initiative.

Shapes can arrange themselves into crystal structures through entropy alone, new computational research from the University of Michigan shows.

Shapes can arrange themselves into crystal structures through entropy alone, new computational research from the University of Michigan shows.

Emanuel Gull

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Professor Gull works in the general area of computational condensed matter physics with a focus on the study of correlated electronic systems in and out of equilibrium. He is an expert on Monte Carlo methods for quantum systems and one of the developers of the diagrammatic ‘continuous-time’ quantum Monte Carlo methods. His recent work includes the study of the Hubbard model using large cluster dynamical mean field methods, the development of vertex function methods for optical (Raman and optical conductivity) probes, and the development of bold line diagrammatic algorithms for quantum impurities out of equilibrium. Professor Gull is involved in the development of open source computer programs for strongly correlated systems.

Cluster geometry of a 16-site cluster used to study the properties of high-temperature cuprate superconductors.

Cluster geometry of a 16-site cluster used to study the properties of high-temperature cuprate superconductors.