2026-10-12T14:13:14Z https://www.scidb.cn/oai

10.57760/sciencedb.j00213.00190 2025-08-29T16:34:21Z

2025-08-29 The data of the article "Molecular Dynamics Simulation Study of Diffusion Dynamics in [EMIm]+Cl-+AlCl3 Ionic Liquid Based on Deep Learning Potential" doi:10.57760/sciencedb.j00213.00190 en This dataset includes the fundamental atomic structure models (in XYZ format, containing AlCl4.xyz, Al2Cl7.xyz, and EMIm.xyz) and the trained DeeP potential ([EMIm]Cl+AlCl3_ion_liquid_potential.pb) used in the article titled " Molecular Dynamics Simulation Study of Diffusion Dynamics in [EMIm]+Cl-+AlCl3 Ionic Liquid Based on Deep Learning Potential". All Deep Potential Molecular Dynamics (DPMD) simulations in this study were performed using this trained potential. This DeeP potential primarily focuses on ion transport mechanisms in [EMIm]+Cl-+AlCl3 ionic liquid systems within the temperature range of 300 K to 400 K. When utilizing this DeeP potential in LAMMPS (integrated with DeePMD-kit) or other molecular dynamics software, it is crucial to maintain the element order as C, N, H, Al, Cl to prevent computational errors. Ion liquid; Machine learning force field; molecular dynamics; Aluminum-ion batteries Liu Haoliang Zeng Chao He Huaxuan Wu Kai Cheng Yonghong Xiao Bing PUBLIC https://creativecommons.org/licenses/by/4.0/ dataset http://www.doi.org/10.7498/aps.74.20250818 Science Data Bank