“Order-Disorder-Property Relationships in Structural Materials: Guided by Randomness”
Presented by Professor Daniel S. Gianola
Materials Department, University of California Santa Barbara
Emerging classes of structural materials that have been developed to meet the demands of aggressive applications requiring structural integrity in extreme environments, such as those encountered in the aerospace and power generation sectors, all share a common theme: complexity across a large range of length scales. A common denominator is the intentional design of randomness – or disorder – in these new materials. In load-bearing materials, this disorder can manifest as topological disorder (uncertainty in atomic positions) as found in interface-dominated or glassy materials, or chemical disorder (uncertainty in elemental occupancy) as found in compositionally-concentrated alloys. This begs a question that underpins new materials-by-design strategies: should the conventional wisdom of searching for structure-property relationships give way to those that focus on disorder-property ones? This talk will show two examples that lend credence to the notion of embracing the role of disorder in materials.
The first will highlight the novel materials design paradigm of multi-principal element (MPE) alloying that has shown great success, yet opportunities to advance refractory-based high temperature body centered cubic (BCC) alloys for high temperature structural applications must confront fundamentally different avenues for the accommodation of plastic deformation. We show a unique combination of homogeneous plastic deformability and strength at low temperature in the BCC MPE alloy MoNbTi, enabled by the rugged atomic environment through which dislocations must navigate. In situ observations of dislocation motion and atomistic calculations unveil the unexpected dominance of non-screw character dislocations and numerous equiprobable slip planes for dislocation glide. This remarkable behavior reconciles theories explaining the exceptional high temperature strength of similar alloys. Our results, when paired with a material density lower than that of state-of-the-art superalloys, provide sharp focus to alloy design strategies for materials capable of performance across the temperature spectrum.
The second example will demonstrate novel synthesis and processing routes for controlling disorder in nanocrystalline materials – and as a consequence, the mechanical properties. We study relaxation processes at grain boundaries in nanocrystalline materials that facilitate atomic reconfigurations toward a lower energy state such as low temperature annealing, which enhance mechanical strength while promoting shear localization. A particular focus in this talk will be on strategies for rejuvenation at grain boundaries with the goal of suppressing shear localization and endowing damage tolerance. Parallels between our results and rejuvenation processes in glasses, as well as the interplay between grain boundary structure and chemistry through segregation engineering, will be discussed in the context of controlling metastable structural configurations.
Daniel S. Gianola is a Professor of Materials at the University of California Santa Barbara and can be reached at: firstname.lastname@example.org. He is currently the faculty director of the Microscopy and Microanalysis Facility at UCSB, which is a central shared facility with over 400 active users. Dr. Gianola joined the Materials Department at UCSB in early 2016 after holding the positions of Associate Professor and Skirkanich Assistant Professor, all in the Department of Materials Science and Engineering at the University of Pennsylvania. He received a BS degree from the University of Wisconsin-Madison and his PhD degree from Johns Hopkins University. Prior to joining the University of Pennsylvania, Gianola was an Alexander von Humboldt Postdoctoral Fellow at the Forschungszentrum Karlsruhe (now Karlsruhe Institute of Technology) in Germany. Dr. Gianola is the recipient of the National Science Foundation CAREER, Department of Energy Early Career, and TMS Early Career Faculty Fellow awards. His research group at UCSB specializes in research dealing with deformation at the micro- and nanoscale, particularly using in situ nanomechanical testing techniques.
4:10 pm Presentation
“Breakup of Bubbles Driven by Vortex Ring Collision”
Presented by YINGHE QI (Adviser: Prof. Ni)
We present an experimental investigation of bubble breakup at the moment when two vortex rings collide with each other head on at high Reynolds numbers. At this moment, as the vortex cores break into finer scales, bubbles will experience strong fluctuations of local shear and pressure at multiple length scales, reproducing a flow environment that bubbles tend to experience in fully-developed turbulence. In this study, we use the piston-cylinder arrangement to produce and control the vortex ring collision, and the timing of bubble injection is adjusted to vary the distance between bubbles and the location where two vortex cores touch each other. Four high-speed cameras are used to simultaneously measure both the bubble breakup process as well as the surrounding flow. This study will help us to explore the idea of bubble-eddy collision that has been widely used in describing bubble deformation and breakup in fully-developed turbulence.
4:35 pm Presentation
“Fractional Gradient Based Subgrid-Scale Models of Turbulence”
Presented by PATRICIO CLARK DI LEONI (Adviser: Prof. Meneveau)
In large eddy simulations, the effects of the unresolved scales are encapsulated in the turbulence subgrid-scale model. Whether the model can reproduce the correct two-point correlations in the filtered velocity field in LES is governed by its Karman-Howarth equation, and specifically whether the model correctly captures the two-point correlation functions between the stresses and the filtered strain-rates. Inspired by this statistical necessary condition, we develop a model that takes into account non-local effects by using fractional derivatives, and evaluate its performance using data from the Johns Hopkins Database (JHTDB). Starting from direct numerical simulation data of homogeneous isotropic turbulence and channel flows, we filter the data to separate the small and large scales, and calculate the two-point stress-strain rate correlations for the exact case and for models (a-priori) with different fractional orders. We observe that the Smagorinsky model based on standard gradients fails to produce the long-range correlations observed in the exact case, while the fractional-gradient models capture the longer tails of the true correlations. As one approaches the wall in channel flow, more complex, highly anisotropic behavior is found.
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.