Phase Separation Kinetics and Cluster Dynamics in Two-Dimensional Active Dumbbell Systems
Molecular dynamics simulations were employed to investigate the phase separation process of a two-dimensional active Brownian dumbbell model. We evaluated the time dependence of the typical size of the dense component using the scaling properties of the structure factor, along with the averaged numb...
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description | Molecular dynamics simulations were employed to investigate the phase separation process of a two-dimensional active Brownian dumbbell model. We evaluated the time dependence of the typical size of the dense component using the scaling properties of the structure factor, along with the averaged number of clusters and their radii of gyration. The growth observed is faster than in active particle (disk) models, and this effect is further enhanced under stronger activity. Next, we focused on studying the hexatic order of the clusters. The length associated to the orientational order grows algebraically and faster than for active Brownian particles. Under weak active forces, most clusters exhibit a uniform internal orientational order. However, under strong forcing, large clusters consist of domains with different orientational orders. We demonstrated that the latter configurations are not stable, and given sufficient time to evolve, they eventually reach homogeneous configurations as well. No gas bubbles are formed within the clusters, even when there are patches of different hexatic order. Finally, attention was directed towards the geometry and motion of the clusters themselves. By employing a tracking algorithm, we showed that clusters smaller than the typical size at the observation time exhibit regular shapes, while larger ones display fractal characteristics. In between collisions or break-ups, the clusters behave as solid bodies. Their centers of mass undergo circular motion, with radii increasing with the cluster size. The center of mass angular velocity equals that of the constituents with respect to their center of mass. These observations were rationalised with a simple mechanical model. |
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We evaluated the time dependence of the typical size of the dense component using the scaling properties of the structure factor, along with the averaged number of clusters and their radii of gyration. The growth observed is faster than in active particle (disk) models, and this effect is further enhanced under stronger activity. Next, we focused on studying the hexatic order of the clusters. The length associated to the orientational order grows algebraically and faster than for active Brownian particles. Under weak active forces, most clusters exhibit a uniform internal orientational order. However, under strong forcing, large clusters consist of domains with different orientational orders. We demonstrated that the latter configurations are not stable, and given sufficient time to evolve, they eventually reach homogeneous configurations as well. No gas bubbles are formed within the clusters, even when there are patches of different hexatic order. Finally, attention was directed towards the geometry and motion of the clusters themselves. By employing a tracking algorithm, we showed that clusters smaller than the typical size at the observation time exhibit regular shapes, while larger ones display fractal characteristics. In between collisions or break-ups, the clusters behave as solid bodies. Their centers of mass undergo circular motion, with radii increasing with the cluster size. The center of mass angular velocity equals that of the constituents with respect to their center of mass. These observations were rationalised with a simple mechanical model.</description><identifier>EISSN: 2331-8422</identifier><language>eng</language><publisher>Ithaca: Cornell University Library, arXiv.org</publisher><subject>Algorithms ; Angular velocity ; Center of mass ; Clusters ; Configurations ; Molecular dynamics ; Phase separation ; Structure factor ; Time dependence</subject><ispartof>arXiv.org, 2024-02</ispartof><rights>2024. 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subjects | Algorithms Angular velocity Center of mass Clusters Configurations Molecular dynamics Phase separation Structure factor Time dependence |
title | Phase Separation Kinetics and Cluster Dynamics in Two-Dimensional Active Dumbbell Systems |
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