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list_of_the_dpd_club_meeting_topics [2017/03/03 04:16] xl24 [02/23/17] |
list_of_the_dpd_club_meeting_topics [2017/05/24 20:05] xl24 [05/25/17] |
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===== List of Past DPD Club Meeting Topics ===== | ===== List of Past DPD Club Meeting Topics ===== | ||
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+ | ===== 05/25/17 ===== | ||
+ | Speaker: Drs. [[https://www.brown.edu/research/projects/capture-and-conversion-of-co2/yin-jia-zhang|Yin-Jia Zhang]] (Department of Chemistry, Brown University) & [[http://www.dam.brown.edu/people/ytang/|Yu-Hang Tang]] (Division of Applied Mathematics, Brown University)\\ Title: Accelerating DFT-based atomistic geometry calculations using Artificial Neural Networks and the AMP package. \\ Reference: \\ | ||
+ | 1. A. Khorshidi and A. Peterson (2016). [[http://www.sciencedirect.com/science/article/pii/S0010465516301266|AMP: A modular approach to machine learning in atomistic simulations.]] Comput Phys Commun, 207: 310-324. | ||
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+ | ===== 04/27/17 ===== | ||
+ | Speaker: Dr. [[Alireza Yazdani]] \\ Title: Multiscale Modeling of Blood Clotting in Flow using DPD. | ||
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+ | ===== 04/06/17 ===== | ||
+ | * Speaker: Dr. [[https://nnf.mit.edu/people/safa-jamali|Safa Jamali ]](Department of Mechanical Engineering, MIT) \\ Title: Connecting Microstructure to Macroscopic Properties in Complex Fluids: Towards Design of Soft Materials with Tunable Properties \\ Abstract: The field of complex fluids encompasses a wide class of materials, which exhibit unusual mechanical responses to an applied stress or strain. In virtually all complex fluids, this rich and unusual mechanical response originates from a microstructure that responds to different applied stress or strain in specific and varied ways. Thus understanding the microstructure – macroscopic behavior relationship is a crucial step for systematically designing complex fluid materials for novel applications. The complex fluid landscape can be subdivided based on the particle-level interactions that govern their underlying microstructure and the resulting macro rheology. For example, viscosity of a dense suspension of repulsive or neutral colloidal particles progressively increases with increasing the rate of deformation. This behavior is called Shear-Thickening behavior, and is best exemplified by someone’s ability to run on a pool of cornstarch and water, and sinking in while standing still. On the other hand, a distinct hallmark of attractive Brownian particles, even at small and intermediate concentrations, is their ability to self-assemble into percolated networks that span over the sample size. These structures show a rich time and rate dependent response to applied deformation/forces such as yielding, shear banding, microphase separation and flow heterogeneities, etc. I will present a computational framework to bridge the gap between microstructure to macroscopic properties of complex fluids, using hydrodynamics and statistical mechanics: First I will discuss the role of hydrodynamics, friction and particle geometry/deformability in shear-thickening fluids, and secondly, the role of microstructural evolutions of attractive systems in defining their mechanical response. | ||
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+ | ===== 03/09/17 ===== | ||
+ | * Speaker: Kang-Sahn Kim (Department of Chemistry, KAIST-Korea Advanced Institute of Science and Technology) \\ Title: Estimation of shear viscosity for simple and complex fluids using equilibrium MD simulations: statistical errors and system size effects. | ||
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===== 02/23/17 ===== | ===== 02/23/17 ===== |