Ellen Arruda

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Mechanical behavior of materials including polymers, elastomers and soft tissue; tissue engineering of tendon and muscle constructs; constitutive modeling of growth, remodeling and functional adaptation in soft tissue; deformation mechanisms in polymers; crystal transformation mechanisms in semi-crystalline polymers; split Hopkinson pressure bar testing of polymers and elastomers for high strain rate applications including crashworthiness in automotive applications.

Jie Shen

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Dr. Shen is a professor in the department of computer & information science, the University of Michigan-Dearborn, USA. He is a fellow of ASME & IET, and the editor-in-chief of the International Journal of Modelling and Simulation (CiteScore 2018: 1.03), which is an EI-indexed, peer-reviewed research journal published through UK-based Taylor & Francis Group both in print and online. Professor Shen has published over 130 technical papers, 3 books, and organized many international conferences/workshops. His research areas include Modeling and Simulation, Machine Learning and Artificial Intelligence, Numerical Analysis and Optimization, Robotics, Data Science, Sensor Technology, Data Fusion, and Computational Materials Science. Dr. Shen is an innovator who is the creator of two software tools: (a) UM GeoModifier and (b) UM MatDiagnoser. He also contributed to the development of the well-known software OptiStruct.

Intelligent Multiscale Computational Diagnosis of Materials Performance and Life

Robert Deegan

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Professor Deegan’s research focuses on the dynamics of non-equilibrium systems. As a system, such as a fluid or a solid, is driven from equilibrium, it undergoes a series of transitions to progressively more organized dynamics. Everyday examples of this phenomenon are the bands of Jupiter, the Giant’s Causeway, and the crumpled edges of lettuce leaves.

Professor Deegan studies dynamical transitions though table-top experiments with the aim of understanding the origin of this behavior in each specific case and in general. His research covers a broad range of phenomena from drying drops to bursting balloons to vibrated slurries.

Bryan Goldsmith

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Bryan Goldsmith is an Assistant Professor in the Department of Chemical Engineering. His works focus on the development of novel catalysts and materials. The world is facing a growing population, mass consumerism, and rising greenhouse gas levels, all the while people strive to increase their standard of living. Computational modeling of catalysts and materials, and making use of its synergy with experiments, facilitates the process to design new systems since it provides a valuable way to test hypotheses and understand design criteria. His research team focuses on obtaining a deep understanding of catalytic systems and advanced materials for use in sustainable chemical production, pollution abatement, and energy generation. They use first-principles modeling (e.g., density-functional theory and wave function based methods), molecular simulation, and data analytics tools (e.g., statistical learning and data mining) to extract key insights of catalysts and materials under realistic conditions, and to help create a platform for their design.

A computational prediction for a group of gold nanoclusters (global model) could miss patterns unique to nonplaner clusters (subgroup 1) or planar clusters (subgroup 2)

A computational prediction for a group of gold nanoclusters (global model) could miss patterns unique to nonplaner clusters (subgroup 1) or planar clusters (subgroup 2)

Yue Fan

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Yue Fan is an Assistant Professor in the Department of Mechanical Engineering. The primary research interest in his group is to provide a substantive knowledge on the mechanics and micro-structural evolution in complex materials systems under extreme environments via predictive modeling. In particular, they focus on describing highly disordered systems (such as glasses, grain boundaries, etc) from the perspective of potential energy landscape (PEL), and correlating materials properties with their underlying PEL structures. The ultimate goal is to facilitate the development of new science-based high performance materials with novel functions and unprecedented strength, durability, and resistance to traditional degradation and failure.

Phani Motamarri

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Phani Motamarri is an Assistant Research Scientist in the department of Mechanical Engineering. His research interests lie in the broad scope of computational materials science with emphasis on computational nano-science leading to applications in the areas of mechanics of materials and energy. His research is strongly multidisciplinary, drawing ideas from applied mathematics, data science, quantum-mechanics, solid-mechanics, materials science and scientific computing.

The current research focus lies in developing systematically improvable real-space computational methodologies and associated mathematical techniques for conducting large-scale electronic-structure (ab-initio) calculations -via- density functional theory (DFT). Massively parallel and scalable numerical algorithms using finite-elements (DFT-FE) are developed as a part of this research effort, which enabled large-scale DFT calculations on tens of thousands of atoms for the first time using finite-element basis. These computational methods will aid fundamental studies on defects in materials, molecular and nanoscale systems which otherwise would have been difficult to study with the existing state of the art computational methods. Current areas of application include — (a) first-principles modelling of energetics of point defects and dislocations in Al, Mg and its alloys which are popular in light-weighting applications to provide useful inputs to meso-scale and continuum models, (b) providing all-electron DFT input to advanced electronic structure approaches like the GW method for accurate prediction of electronic properties in semiconductor-materials.

Electron-density contours of 3430 atom aluminum nanocluster using pseudopotential DFT-FE

Electron-density contours of 3430 atom aluminum nanocluster using pseudopotential DFT-FE

Electron density contours of 3920 electron silicon nanocluster using all-electron DFT-FE

Electron density contours of 3920 electron silicon nanocluster using all-electron DFT-FE

Computational time (CPU-Hrs) per SCF iteration for the reduced-scaling subspace projection method and conventional diagonalization approach(ChFSI-FE). Case study: Alkane chains upto 7000 atoms.

Computational time (CPU-Hrs) per SCF iteration for the reduced-scaling subspace projection method and conventional diagonalization approach(ChFSI-FE). Case study: Alkane chains upto 7000 atoms.

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

Dominika Zgid

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Dominika Zgid is an Assistant Professor in the Department of Chemistry. Her group bridges the fields of chemistry, physics and material sciences seeking to explain and predict the electronic movement in finite molecular systems and infinite crystalline materials. They develop new theoretical approaches that will advance current theoretical tools in chemistry that can be applied to a variety of industrial applications.

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 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.