Search

Based on the statistical analysis of particles hopping outside the cages formed by their nearest neighboring particles, a new diagnostic of the hopping particle (HP) percentage is proposed to identify the solid–liquid phase transition in two-dimensional (2D) dusty plasmas. To demonstrate the effectiveness of the HP percentage, Langevin dynamical simulations of 2D Yukawa systems under various conditions are performed to mimic 2D dusty plasmas. It is found that the HP percentage exhibits a significant jump while decreasing the coupling parameter around the melting point, just corresponding to the solid–liquid phase transition. As compared with other traditionally used diagnostics, the HP percentage diagnostic is sensitive enough, and the dynamical information is incorporated inside. By comparing to the most widely used diagnostic of the bond-angular order parameter, the melting criterion of this HP percentage diagnostic is determined to be about 30% for the suitable time interval, which is general for the 2D Yukawa systems with different screening parameters. [ABSTRACT FROM AUTHOR]

The evolution of unsupported shocks is theoretically investigated using the method of characteristics. It is found that the location and the speed of the generated non-uniform shock (NUS) front vary with the propagation time and the initial compression strength. The relationship between the NUS front location and the propagation time is asymptotically parabolic, while the speed of the NUS front decreases gradually with the propagation time. These analytical derivations are verified using computer simulations of unsupported shocks in 2D dusty plasmas performed here. The transition of the NUS front speed found previously [Sun et al., Phys. Plasmas 28, 103703 (2021)] using data fitting with the simulation data is re-investigated and further confirmed with the theoretical derivation of the NUS front in the current investigation. [ABSTRACT FROM AUTHOR]

Using the machine learning method, the screening parameter κ and the coupling parameter Γ of two-dimensional (2D) dusty plasma are determined simultaneously purely from position fluctuations of individual particles using both simulation and experiment data. To train, validate, and test convolutional neural networks (CNNs), Langevin dynamical simulations are performed with different κ and Γ values to obtain position fluctuation data of individual particles. From the test with the simulation data, the trained CNNs are able to accurately determine the values of κ and Γ simultaneously, with the typically averaged mean relative error varying between 10 % and 17 %. While using the trained CNN with the 2D dusty plasma experiment data, the distribution of the determined κ NN or Γ NN values always exhibits one prominent peak, and the peak locations well agree with the κ and Γ values determined from the widely accepted phonon spectra fitting method. The obtained results clearly demonstrate that, using machine learning methods, the two global characterization parameters of κ and Γ in 2D dusty plasmas are able to be accurately determined simultaneously purely from the position fluctuations of local individual particles. [ABSTRACT FROM AUTHOR]

This article, titled "Derivation of shock front evolution with rarefaction wave and its verification in dusty plasma simulations," was published in the journal Physics of Plasmas. It discusses the correction of an error in the math equation on page 3 of the online version of the article, which has been rectified in all online versions as of February 9, 2024. The corrected equation is now accurately represented in the printed version of the journal. The authors of the article are Xin Chen, Chen Liang, Shaoyu Lu, Dong Huang, and Yan Feng. [Extracted from the article]

Hydration of TiO 2 facets controls the reactions occurring at the mineral-water interfaces. However, the underlying mechanism of the facet-dependent hydration and the effect of hydration on contaminant adsorption are still ambiguous. Herein, arsenite [As(III)] adsorption on hydrated {001}, {100}, {101}, and {201} TiO 2 was explored by integrating multiple characterizations and density functional theory (DFT) calculations. Our macroscopic adsorption results show an As(III) adsorption density order of {201} > {100} > {101} > {001}, though As(III) on each facet formed a bidentate binuclear structure, as evidenced by the extended X-ray absorption fine structure analysis. The in situ diffuse reflectance infrared Fourier transform spectroscopy analysis identified distinctive surface hydroxyls on four-faceted TiO 2 upon water adsorption. The hydrated surface regulated the subsequent As(III) adsorption, giving an As(III) adsorption energy order of {201} (-0.95 eV) < {100} (-0.38 eV) < {101} (-0.005 eV) < {001} (0.04 eV) according to DFT calculations. The As(III) adsorption energy on hydrated facets was linearly correlated with the macroscopical As(III) adsorption density ( R 2 = 0.99, p < 0.05), revealing that the impregnable water binding highly suppressed the exchange of As(III) molecules with adsorbed water. Our study provided a novel insight into the facet-dependent interfacial adsorption.