Kinetics of fluid demixing in complex plasmas: Domain growth analysis using Minkowski tensors

Abstract

The demixing process of a binary complex plasma, in particular its onset, is analysed and the role of distinct interaction potentials is discussed by using morphological Minkowski tensor analysis of the minority phase domain growth in a demixing simulated binary complex plasma. These Minkowski tensor methods are compared with previous results that utilized a power spectrum method based on the time-dependent average structure factor. It is shown that the Minkowski tensor methods are superior to the previously used power spectrum method in the sense of higher sensitivity to changes in domain size. It is found that increasing the tensor rank of the Minkowski methods from rank one to rank two and four results in ever decreasing sensitivity. However even the rank 4 Minkowski tensor method performs better in terms of sensitivity compared to the previously used power spectrum methods. By analysis of the slope of the temporal evolution of Minkowski tensor measures qualitative differences between the case of particle interaction with a single length scale compared to particle interactions with two different length scales (dominating long range interaction) are revealed: In the case of different length scales the slope grows fast until it reaches its maximal value and then decays whereas for a single length scale no decay is observed. After proper scaling the graphs for the two length scale scenario coincide, pointing towards universal behaviour. These differences are evidenced by distinct demixing behaviour: In the long range dominated cases demixing occurs in two stages. At first neighbouring particles agglomerate then domains start to merge in cascades. However in the case of only one interaction length scale only agglomeration but no merging of domains can be observed. Thus, Minkowski Tensor analysis are likely to become a useful tool for further investigation of this (and other) demixing processes. It is capable to reveal (nonlinear) local topological properties, probing deeper than (linear) global power spectrum analysis, however stillproviding easily interpretable results founded on a solid mathematical framework.