Observation of the hexatic phase in a two-dimensional complex plasma using machine learning

XC Du and W Yang and V Nosenko and Y Miao and WX Li and JY Yu and H Huang and CR Du, SOFT MATTER, 20, 7362-7366 (2024).

DOI: 10.1039/d4sm00929k

Complex plasmas consist of ionized gas and charged solid microparticles, representing the plasma state of soft matter. We apply machine learning methods to investigate a melting transition in a two-dimensional complex plasma. A convolutional neural network is constructed and trained with the numerical simulation. The hexatic phase is successfully identified and the evolution of topological defects is studied during melting transition in both simulations and experiments. It is challenging to identify the hexatic phase in melting experiments with 2D complex plasmas due to the limited size of the particle suspension. A machine learning method makes up for such shortcomings and successfully identifies the hexatic phase.

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