论文标题
剪切诱导的与互动互动的系统中的订购：机器学习研究
Shear induced ordering in systems with competing interactions: A machine learning study
论文作者
论文摘要
当短距离景点与胶体颗粒系统中的远距离排斥相结合时，可以出现复杂的麦克相。在这里，我们研究了一种各向同性颗粒的系统，该系统可以在温度变化时形成层状结构或无序流体相。我们表明，在均衡时，层状结构结晶，而从平衡中，系统以不同的剪切速率和高于熔化的温度形成各种结构。通过主成分分析和人工神经网络对剪切诱导的顺序进行分析，这些分析应用于降低尺寸的数据。我们的结果揭示了通过剪切诱导顺序的可能性，有可能为从各向同性颗粒制造有序的层状结构的可行途径。
When short-range attractions are combined with long-range repulsions in colloidal particle systems, complex microphases can emerge. Here, we study a system of isotropic particles which can form lamellar structures or a disordered fluid phase when temperature is varied. We show that at equilibrium the lamellar structure crystallizes, while out of equilibrium the system forms a variety of structures at different shear rates and temperatures above melting. The shear-induced ordering is analyzed by means of principal component analysis and artificial neural networks, which are applied to data of reduced dimensionality. Our results reveal the possibility of inducing ordering by shear, potentially providing a feasible route to the fabrication of ordered lamellar structures from isotropic particles.
