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相关概念视频

Solubility of Ionic Compounds02:55

Solubility of Ionic Compounds

66.5K
Solubility is the measure of the maximum amount of solute that can be dissolved in a given quantity of solvent at a given temperature and pressure. Solubility is usually measured in molarity (M) or moles per liter (mol/L). A compound is termed soluble if it dissolves in water.
66.5K
Trends in Lattice Energy: Ion Size and Charge02:54

Trends in Lattice Energy: Ion Size and Charge

23.4K
An ionic compound is stable because of the electrostatic attraction between its positive and negative ions. The lattice energy of a compound is a measure of the strength of this attraction. The lattice energy (ΔHlattice) of an ionic compound is defined as the energy required to separate one mole of the solid into its component gaseous ions. For the ionic solid sodium chloride, the lattice energy is the enthalpy change of the process:
23.4K
Molecular and Ionic Solids02:54

Molecular and Ionic Solids

16.5K
Crystalline solids are divided into four types: molecular, ionic, metallic, and covalent network based on the type of constituent units and their interparticle interactions.
Molecular Solids
Molecular crystalline solids, such as ice, sucrose (table sugar), and iodine, are solids that are composed of neutral molecules as their constituent units. These molecules are held together by weak intermolecular forces such as London dispersion forces, dipole-dipole interactions, or hydrogen bonds, which...
16.5K
Intermolecular Forces and Physical Properties02:56

Intermolecular Forces and Physical Properties

23.3K
23.3K
Lattice Energies of Ionic Crystals01:27

Lattice Energies of Ionic Crystals

20
Lattice energy represents the energy released when gaseous cations and anions combine to form an ionic solid, reflecting the strength of electrostatic interactions within the crystal. This process is fundamentally governed by Coulombic attraction between oppositely charged ions, where the potential energy varies inversely with the interionic distance and directly with the product of ionic charges. As ions approach one another, the electrostatic energy becomes increasingly negative, indicating a...
20

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Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package
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Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package

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使用机器学习的原子间潜能,研究无形LiPON中的离子扩散性.

Aqshat Seth1, Rutvij Pankaj Kulkarni1, Gopalakrishnan Sai Gautam1

  • 1Department of Materials Engineering, Indian Institute of Science, Bengaluru 560012, India.

ACS materials Au
|May 19, 2025
PubMed
概括

机器学习的潜能准确地模拟了氧化 (LiPON) 的无形结构和离子运输. 这种方法克服了计算挑战,揭示了薄膜电池应用的微小接口阻抗.

科学领域:

  • 材料科学 材料科学 材料科学
  • 计算化学计算化学
  • 固态电化学 固态电化学

背景情况:

  • 氧化 (LiPON) 对于薄膜固态电池至关重要,因为它具有无形固体电解质特性.
  • 在无形LiPON中以及跨LiLiLiLiPON接口的Li+运输模型是具有计算挑战性的,因为材料复杂性和尺度要求.

研究的目的:

  • 开发和验证一种机器学习的原子间潜力 (MLIP),用于精确模拟LiPON.
  • 通过使用开发的MLIP来研究散装LiPON中的Li+运输和LiLiLiPON接口中的Li.

主要方法:

  • 通过使用13,454个密度函数理论 (DFT) 结构的大数据集,训练了一个神经等价原子间潜力 (NequIP) 框架.
  • 通过低能量和力误差验证了MLIP的准确性,与DFT相比.
  • 利用训练的潜力进行分子动力学模拟的批量LiPON和LiHideLiPON接口.

主要成果:

  • 生成的无形LiPON结构与ab initio分子动力学一致,显示的结合.
  • 在散装LiPON中模拟Li+扩散性,与现有文献有很好的一致性.
  • 观察到Li+运输在Li(110) 下载的LiPON和Li(111) 下载的LiPON接口是比散装相缓慢一个数量级,但具有较小的异构性和没有显著的阻抗积累.

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相关实验视频

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A Package of Established Analytical Tools to Investigate the Solid-State Alteration of Lipid-Based Excipients
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结论:

  • 机器学习潜能,特别是NequIP,对于像LiPON这样复杂无形材料的高保真大规模建模是非常有效的.
  • 开发的MLIP允许在基于LiPON的系统中有效调查Li+运输机制.
  • 结果表明界面阻抗最小,支持LiPON在先进的薄膜设备中的使用.