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Local structure and dynamics of dense colloidal systems : from patchy particles to hard spheres

Abstract : The role played by the structure in determining the dynamics of glassy colloidal systems is still a subject of debate. However, there is compelling evidence of a direct link between changes in the local structure and the dynamical slowdown in glassy systems. Here, we explore the interplay between local structure and dynamics by using patchy particles as glass formers. This is done by making use of molecular dynamics simulations. We show that reinforcing icosahedral geometry causes, the system to exhibit an extreme slowdown in its dynamics. With these results, we provide a route for controlling glassy dynamics through the use of patchy particles. Additionally, an interesting point is whether we can extract information about dynamics from only structural information. In order to explore this point, we simulate a wide variety of hard-sphere mixtures. We show that global dynamics of these systems can be precisely predicted by quantifying the tetrahedrality of the local structure: an order parameter that consists of counting the number of tetrahedra each particle participates in. The predictions of this order parameter maintain their accuracy over a wide variety of densities proving its universality in this family of glass formers. Moreover, it is also capable of capturing the changes in the local dynamics, as regions with high tetrahedrality are strongly correlated with regions with slow dynamics. Finally, we demonstrate that unsupervised machine learning techniques can be used to classify particles with different structural environments, which are strongly correlated to local dynamics.
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Submitted on : Friday, January 29, 2021 - 2:08:09 PM
Last modification on : Thursday, July 1, 2021 - 4:48:42 PM
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  • HAL Id : tel-03125448, version 1


Susana Marín Aguilar. Local structure and dynamics of dense colloidal systems : from patchy particles to hard spheres. Soft Condensed Matter [cond-mat.soft]. Université Paris-Saclay, 2020. English. ⟨NNT : 2020UPASP052⟩. ⟨tel-03125448⟩



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