Our research can be summarized in two words: Matter and Machine. On the Matter side, Z lab studies far-from-equilibrium physics. They synergistically combine and push the boundaries of statistical and stochastic thermodynamic theories, accelerated molecular simulations, understandable AI/ML/DS methods, and neutron scattering experiments, with the goal of significantly extending our understanding of a wide range of long timescale phenomena and rare events. Particular emphasis is given to the physics and chemistry of liquids and complex fluids, especially at interfaces, driven away from equilibrium, or under extreme conditions. On the Machine side, leveraging their expertise in materials and modeling, his group advances the development of soft robots and human-compatible machines, swarm robots and collective intelligence, and robots in extreme environments, which can lead to immediate societal impact.
Large-scale computational methods to study the structural, electronic, and optical properties of materials and nanostructures.
Emmanouil (Manos) Kioupakis, Materials Science and Engineering
First-principles auger calculations in nitride LEDs
Emmanouil Kioupakis, Materials Science and Engineering
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.
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.
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 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.
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 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.
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.