Identifying Complex Plasma Crystals using Digital Image Analysis

Complex (dusty) plasmas are the mixture of electrons, ions, and neutral atoms with the addition of charged macroscopic dust particles of nanometer to micrometer size. These systems exhibit gaseous, fluidic, and crystal-like phases depending on the electrostatic and kinetic energies of the system. Previously, these systems have been characterized using spatial correlation functions, particle dynamics, and calculation of the rotational invariance maps through using particle tracking velocimetry (PTV). This article aims to expand on that work to further identify specific crystal structures such as face centered cubic (fcc) by calculating the rotational invariance maps directly from digital images, sidestepping the need for PTV data. This technique has potential advantages for real time analysis and experimental control. We present a Python library package workflow for identifying the different phases; as well, we show preliminary results of the temporal evolution of crystal formation in a dusty plasma cross section.