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相关概念视频

Molecular and Ionic Solids02:54

Molecular and Ionic Solids

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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...
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Phase Transitions: Sublimation and Deposition02:33

Phase Transitions: Sublimation and Deposition

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Some solids can transition directly into the gaseous state, bypassing the liquid state, via a process known as sublimation. At room temperature and standard pressure, a piece of dry ice (solid CO2) sublimes, appearing to gradually disappear without ever forming any liquid. Snow and ice sublimate at temperatures below the melting point of water, a slow process that may be accelerated by winds and the reduced atmospheric pressures at high altitudes. When solid iodine is warmed, the solid sublimes...
19.6K
Network Covalent Solids02:18

Network Covalent Solids

16.0K
Network covalent solids contain a three-dimensional network of covalently bonded atoms as found in the crystal structures of nonmetals like diamond, graphite, silicon, and some covalent compounds, such as silicon dioxide (sand) and silicon carbide (carborundum, the abrasive on sandpaper). Many minerals have networks of covalent bonds.
To break or to melt a covalent network solid, covalent bonds must be broken. Because covalent bonds are relatively strong, covalent network solids are typically...
16.0K
Trends in Lattice Energy: Ion Size and Charge02:54

Trends in Lattice Energy: Ion Size and Charge

26.4K
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:
26.4K
Phase Transitions02:31

Phase Transitions

22.3K
Whether solid, liquid, or gas, a substance's state depends on the order and arrangement of its particles (atoms, molecules, or ions). Particles in the solid pack closely together, generally in a pattern. The particles vibrate about their fixed positions but do not move or squeeze past their neighbors. In liquids, although the particles are closely spaced, they are randomly arranged. The position of the particles are not fixed—that is, they are free to move past their neighbors to...
22.3K
Chemical Shift: Internal References and Solvent Effects01:17

Chemical Shift: Internal References and Solvent Effects

1.2K
In an NMR sample, precise measurement of the absolute absorption frequencies of nuclei is difficult. A standard internal reference compound is added, and the frequency difference between the reference signal and sample signals is measured.
The internal reference compound generally used in NMR spectroscopy is tetramethylsilane (TMS). TMS is preferred because it is chemically inert, soluble in NMR solvents, and easily removable. Also, the highly shielded methyl protons in TMS yield an intense...
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使用大型语言模型使用杂质阶段的固态合成的文本挖掘数据集.

Sanghoon Lee1,2, Kevin Cruse2,3, Viktoriia Baibakova1,2

  • 1Lawrence Berkeley National Laboratory, Energy Technologies Area, Berkeley, USA.

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|December 16, 2025
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概括

研究人员使用大型语言模型 (LLM) 创建了一大批固态合成反应数据集. 这一数据集有助于理解材料合成中的杂质形成,即使所需相位更稳定.

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科学领域:

  • 材料科学 材料科学 材料科学
  • 化学 化学 化学
  • 数据科学数据科学数据科学

背景情况:

  • 固态合成对于无机材料,如电池组件和热电材料至关重要.
  • 目前的合成方法缺乏一般理论和明确的反应机制,这带来了挑战.
  • 现有的文献数据集往往忽略了产品阶段的纯度和产量.

研究的目的:

  • 构建一个关于固态合成反应的全面数据集.
  • 在合成过程中分析杂质相位的形成.
  • 确定影响产品纯度和产量的因素.

主要方法:

  • 使用大型语言模型 (LLM) 来从科学文献中提取数据.
  • 编制了80806个固态合成的数据集.
  • 包括 18,869 个反应与已识别的杂质相.

主要成果:

  • 该数据集验证了对杂质形成的热力学预测.
  • 鉴定了污染物形成的情况,尽管目标阶段的热力学稳定性更高.
  • 为理解和优化固态合成提供了宝贵的资源.

结论:

  • 通过LLM提取的数据集为固态反应机制提供了新的见解.
  • 强调了杂质形成的复杂性,超出了简单的热力学稳定性.
  • 促进了对无机材料的更可靠,更有效的合成策略的开发.