COMPUTATION ACCELERATED DESIGN OF MATERIALS AND INTERFACES FOR SOLID-STATE BATTERIES
Presented by Professor Yifei Mo
Department of Materials Science and Engineering,
University of Maryland, College Park
All-solid-state Li-ion battery based on solid electrolytes is a promising next-generation battery technology with high energy density, intrinsic safety, long cycle life, and wide operational temperatures. However, multiple challenges, such as low ionic conductivity of solid electrolytes and poor interfacial compatibility at the solid electrolyte-electrode interfaces, are impeding the development of this new battery technology. To resolve these materials challenges, we develop and leverage an array of computation techniques to provide unique materials insights into the fundamental materials limitations and to establish general design principles of materials and solid interfaces. Our first-principles atomistic modeling studies reveal the origin of ultra-fast Li+ diffusion in lithium super-ionic conductors. On the basis of the newly gained understanding, we establish design principles for fast ion-conductor materials and demonstrate these design principles for the computation discovery and design of new lithium super-ionic conductors. In addition, we developed thermodynamic calculations based on the materials-genome database for investigating the compatibility of heterogeneous interfaces between solid electrolytes and electrodes. Key factors affecting the compatibility of the solid electrolyte-electrode interfaces are identified, and interfacial design strategies are proposed from our thermodynamic computation. The demonstrated computation capabilities represent a transferable model in designing new materials and interfaces for emerging technologies.
Professor Yifei Mo is an Associate Professor of Materials Science and Engineering at the University of Maryland, College Park, USA. Dr. Mo’s research aims to advance the understanding, design, and discovery of engineering materials through cutting-edge computational techniques. His current research projects target critical materials problems in energy storage and conversion technologies, with current emphases on beyond Li-ion and all-solid-state batteries. Dr. Mo obtained his B.S. degree in Physics from Peking University and Ph.D. degree in Materials Science from the University of Wisconsin, Madison, USA (2005-2010). He performed his postdoctoral research at Massachusetts Institute of Technology (2010-2013). His research has been published in peer-reviewed journals including Nature, Nature Materials, Nature Communications, Journal of the American Chemical Society, Advanced Energy Materials, Joule, Angewandte Chemie, Nano Letter, Chemistry of Materials, and Physical Review B, etc.
4:10 pm Presentation
“Cavitation Inception and Associated Pressure Field in a Turbulent Shear Layer”
Presented by KARUNA AGARWAL (Adviser: Prof. Katz)
Cavitation inception in the near field of the shear layer occurs in the core of quasi-streamwise vortices that develop between the main spanwise vortices. These located between 45 to 75% of the reattachment length and form 1-2mm diameter and 5-7 mm long cavities that form and collapse in less than 200 µs. The frequency of events at the same cavitation index increases rapidly with velocity, suggesting yet-unknown scaling trends. Hence, it is essential to measure and characterize the instantaneous pressure fields generated in the core of the quasi-streamwise vortices. Tomographic imaging followed by 3D particle tracking using the Shake-the-Box method are used for calculating the instantaneous velocity and acceleration fields. The experimental results are interpolated using Constrained Cost Minimization to generate divergence-free velocity and curl-free material acceleration at a spatial resolution of 250 µm. The pressure is obtained by spatially integrating the material acceleration. The procedure is tested for synthetic data based on the Johns Hopkins Turbulence Database. The measurements are performed at Reynolds numbers based on separating boundary layer height of Re=7100 and 17700 to characterize the effect of Reynolds number on the frequency, time evolution, size, strength and the pressure in the quasi streamwise vortices. Ultra-high speed imaging is being used to characterize the explosive growth and collapse of the cavities and the effect of nuclei.
4:35 pm Presentation
“Simulation Prediction and Adjoint-Based Sensitivity of Laser-Based Ignition in High-Speed Flows”
Presented by DAVID BUCHTA (Adviser: Prof. Zaki)
Large-scale numerical simulations are starting to enable the prediction of multi-physics phenomena. Their interactions are usually so complex that theory and models alone have a limited predictive capacity. Thus, the Center for Exascale Simulation of Plasma-coupled Combustion (XPACC), a Multidisciplinary Simulation Center within the Predictive Science Academic Alliance Program II (PSAAP II), is developing high-fidelity numerical simulations in conjunction with Exascale-aimed computer science tools and uncertainty quantification (UQ) analyses, such as adjoint-based sensitivity, to provide a route to prediction. Specifically, our prediction is space-time transient ignition kernel (TIK) characteristics in plasma-coupled, high-speed flow turbulence applications, like those anticipated on scramjets. Ignition is seeded using the breakdown of a focused laser beam in fuel-oxidizer mixtures, which dissociates the local mixture into elemental species, generates vorticity, and heats the gas above 10000 Kelvin, activating combustion within 1 nanosecond. Depending on the flow, the kernel can develop into a sustained flame or extinguish completely. To help identify mechanisms of successful or failed ignition, the solution of the discrete-exact adjoint equations for the corresponding compressible reacting flow equations provides input-output sensitivity to our quantity of interest, like the TIK. This sensitivity guides optimization and reduces parameter space to support UQ.
Thao (Vicky) Nguyen will deliver a lecture titled “Biomechanics of the optic nerve head in glaucoma” as part of the Don P. Giddens Inaugural Professorial Lecture Series. Nguyen is a professor in the Department of Mechanical Engineering and the Marlin U. Zimmerman, Jr. Faculty Scholar.
Glaucoma is a neurodegenerative disease characterized by damage to the optic nerve axons and remodeling of the connective tissues in the optic nerve head. High pressure in the the eye is a major risk factor for the disease, and lowering this pressure is currently the only effective way to slow the disease’s progression. Nguyen seeks to understand the fundamental biomechanical mechanisms through which changes in the intraocular pressure alter the physiological function of cells and remodel the collagen structures of the optic nerve head. In this presentation, she will describe ongoing work to measure the deformation response of the cellular and connective tissue structures of the optic nerve head to pressure, characterize alterations with age and glaucoma, model the effects of structural variations on the deformation and stress response, and investigate the mechanisms through which stress can direct connective tissue growth and remodeling.
The Don P. Giddens Inaugural Professorial Lecture Series began in 1993 as a way to honor newly promoted full professors. Professor Giddens, originator of the series, served as the fifth dean of Engineering at Johns Hopkins.
Safety-Critical Autonomous Systems: What is Possible? What is Required?
Presented by Professor Richard Murray
Thomas E. and Doris Everhart Professor of Control & Dynamical Systems and Bioengineering California Institute of Technology
The last 20 years have seen enormous progress in autonomous vehicles, from planetary rovers, to unmanned aerial vehicles, to the self-driving cars that we are starting to see on the roads around us. An open question is whether we can we make self-driving cars that are safer than human-driven cars, how much safer they need to be, and what advances will be required to bring them to fruition. In this talk, I will discuss some of the approaches used in the aerospace industry, where flight critical subsystems must achieve probability of failure rates of less than 1 failure in 10^9 flight hours (i.e. less than 1 failure per 100,000 years of operation). Systems that achieve this level of reliability are hard to design, hard to verify, and hard to validate, especially if software is involved. I will describe some of the challenges that the aerospace community faces in designing systems with this level of reliability, how they are designed and implemented done today, and what is being done for the next generation of (much more complex, software-driven) aerospace systems. I will also speculate about whether similar approaches are needed in self-driving cars, and whether these levels of safety are achievable.
Richard M. Murray received the B.S. degree in Electrical Engineering from California Institute of Technology in 1985 and the M.S. and Ph.D. degrees in Electrical Engineering and Computer Sciences from the University of California, Berkeley, in 1988 and 1991, respectively. He is currently the Thomas E. and Doris Everhart Professor of Control & Dynamical Systems and Bioengineering at Caltech. Murray’s research is in the application of feedback and control to networked systems, with applications in biology and autonomy. Current projects include analysis and design of biomolecular feedback circuits, synthesis of discrete decision-making protocols for reactive systems, and design of highly resilient architectures for autonomous systems.
Feedbacks between mechanics, geometry and polarity sorting ensures rapid and precise mitotic spindle assembly
Presented by Professor Alex Mogilner
Courant Institute and Department of Biology, New York University
One of the most fundamental cell biological events is assembly of the mitotic spindle – molecular machine that segregates sister chromatids into two daughter cells in the process of cell division. Two existent models of the mitotic spindle assembly are 1) search-and-capture (SAC) and 2) acentrosomal microtubule assembly (AMA). SAC model is pleasingly simple: microtubules (MTs), organized into two asters focused at two centrosomes, undergo dynamic instability: they grow and shrink randomly, rapidly and repeatedly. As soon as a growing MT end bumps into a kinetochore (KT) – molecular complex in the middle of a sister chromatid – the connection between the spindle pole (centrosome) and this chromatid is established. This model predicts that KTs are captured at random times and that slow spindle assembly is plagued by errors. For decades, the SAC model seemed to work. Our data ruins the SAC model and suggests that a hybrid between SAC and AMA models could work. I will explain how we used 3D tracking of centrosomes and KTs in animal cells to develop a computational agent-based model, which explains the remarkable speed and precision of the almost deterministic process of the spindle assembly emerging from random and imprecise molecular events.
Prof. Alex Mogilner received M.Eng. degree in Engineering Physics in 1985 from the Ural Polytechnic Institute. He received PhD degree in Physics from the USSR Academy of Sciences in 1990. He did research in Mathematical Physics until 1992, when he started studying Mathematical Biology at the University of British Columbia. After receiving PhD degree (adviser Leah Edelstein-Keshet) in Applied Mathematics from UBC in 1995, Alex worked at UC Berkeley with George Oster as a postdoctoral researcher, and in 1996 he came to the Math Department at the University of California at Davis as an Assistant Professor. He became an Associate professor in 1999, and in 2002 he became a Professor at the Department of Mathematics and Department of Neurobiology, Physiology and Behavior at UC Davis. Since 2014, Dr. Mogilner is a Professor of Mathematics and Biology at Courant Institute and Department of Biology at the New York University. Alex’s areas of expertise include Mathematical Biology, Cell Biology and Biophysics; he does research on mathematical and computational modeling of cell motility, cell division and galvanotaxis. Alex published about 130 papers in high impact journals including Nature, Science, PNAS. He developed models of keratocyte motility, polymerization ratchet, and search-and-capture mechanism of spindle assembly. His research is/was supported by NIH and NSF grants, Army Office of Research and by United States-Israel Binational Science Foundation. Alex served on editorial boards of many journals including Cell, Biophysical Journal, Current Biology, Journal of Cell Biology, Bulletin of Mathematical Biology, Molecular Biology of the Cell. He gave plenary talks and organized many international conferences on mathematical biology and cell biophysics, and taught at many summer schools. Dr. Mogilner was a panel chair at NIH. Multiple news and views were published about his scientific discoveries.