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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 [2017/05/25 14:27] (current)
xl24 [04/27/17]
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 ===== List of Past DPD Club Meeting Topics ===== ===== List of Past DPD Club Meeting Topics =====
 +===== 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.
 +===== 04/27/17 =====
 +*Speaker: Dr. [[Alireza Yazdani]] \\ Title: Multiscale Modeling of Blood Clotting in Flow using DPD. \\
 +*Speaker: Dr. [[https://​scholar.google.com/​citations?​user=jlI9vl0AAAAJ&​hl=en|Hung-Yu Chang]] \\ Title: Gene Therapy in a Patient with Sickle Cell Disease \\ Reference: \\
 +1. J. Ribeil, et al. (2017). [[http://​www.nejm.org/​doi/​full/​10.1056/​NEJMoa1609677|Gene Therapy in a Patient with Sickle Cell Disease.]] N Engl J Med, 376: 848-855. \\
 +2. B. P. Frédéric, H. S. Martin, and D. C. Rees. (2017) [[http://​www.nejm.org/​doi/​full/​10.1056/​NEJMra1510865|Sickle Cell Disease]]. N Engl J Med, 376: 1561-1573.
 +===== 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.
 +===== 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.
 ===== 02/23/17 ===== ===== 02/23/17 =====

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