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

IF 2.9 3区 化学 Q3 CHEMISTRY, PHYSICAL
Soft Matter Pub Date : 2024-09-03 DOI:10.1039/D4SM00929K
Xin-Chi Du, Wei Yang, Volodymyr Nosenko, Yang Miao, Wen-Xin Li, Jia-Yi Yu, He Huang and Cheng-Ran Du
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引用次数: 0

Abstract

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.

Abstract Image

Abstract Image

利用机器学习观测二维复杂等离子体中的六相
复杂等离子体由电离气体和带电固体微颗粒组成,代表了软物质的等离子状态。我们应用机器学习方法来研究二维复杂等离子体中的熔化转变。我们利用数值模拟构建并训练了一个卷积神经网络。在模拟和实验中,我们成功地识别了六相,并研究了熔化转变过程中拓扑缺陷的演变。
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来源期刊
Soft Matter
Soft Matter 工程技术-材料科学:综合
CiteScore
6.00
自引率
5.90%
发文量
891
审稿时长
1.9 months
期刊介绍: Where physics meets chemistry meets biology for fundamental soft matter research.
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