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相关概念视频

Crystal Growth: Principles of Crystallization01:25

Crystal Growth: Principles of Crystallization

1.9K
Crystallization is a phase transformation process in which crystals are precipitated from a supersaturated solution or formed from other sources. During crystallization, atoms or molecules arrange themselves into a well-defined, rigid crystal lattice to minimize energy.
Initiating crystallization involves manipulating the concentration of the solute and the temperature of the solution. Since crystal growth occurs when the ratio of concentration and solubility of the solute in the solvent...
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Molecular Models02:00

Molecular Models

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Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.
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Crystal Field Theory - Octahedral Complexes02:58

Crystal Field Theory - Octahedral Complexes

26.5K
Crystal Field Theory
To explain the observed behavior of transition metal complexes (such as colors), a model involving electrostatic interactions between the electrons from the ligands and the electrons in the unhybridized d orbitals of the central metal atom has been developed. This electrostatic model is crystal field theory (CFT). It helps to understand, interpret, and predict the colors, magnetic behavior, and some structures of coordination compounds of transition metals.
CFT focuses on...
26.5K
X-ray Crystallography02:18

X-ray Crystallography

23.9K
The size of the unit cell and the arrangement of atoms in a crystal may be determined from measurements of the diffraction of X-rays by the crystal, termed X-ray crystallography.
Diffraction
Diffraction is the change in the direction of travel experienced by an electromagnetic wave when it encounters a physical barrier whose dimensions are comparable to those of the wavelength of the light. X-rays are electromagnetic radiation with wavelengths about as long as the distance between neighboring...
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Polymer Classification: Crystallinity01:21

Polymer Classification: Crystallinity

2.9K
Unlike ionic or small covalent molecules, polymers do not form crystalline solids due to the diffusion limitations of their long-chain structures. However, polymers contain microscopic crystalline domains separated by amorphous domains.
Crystalline domains are the regions where polymer chains are aligned in an orderly manner and held together in proximity by intermolecular forces. For example, chains in the crystalline domains of polyethylene and nylon are bound together by van der Waals...
2.9K
Crystal Field Theory - Tetrahedral and Square Planar Complexes02:46

Crystal Field Theory - Tetrahedral and Square Planar Complexes

42.6K
Tetrahedral Complexes
Crystal field theory (CFT) is applicable to molecules in geometries other than octahedral. In octahedral complexes, the lobes of the dx2−y2 and dz2 orbitals point directly at the ligands. For tetrahedral complexes, the d orbitals remain in place, but with only four ligands located between the axes. None of the orbitals points directly at the tetrahedral ligands. However, the dx2−y2 and dz2 orbitals (along the Cartesian axes) overlap with the ligands less than the dxy,...
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Derivatization of Protein Crystals with I3C using Random Microseed Matrix Screening
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Derivatization of Protein Crystals with I3C using Random Microseed Matrix Screening

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扩散概率模型增强了晶体结构生成建模的变化自编码器.

Teerachote Pakornchote1, Natthaphon Choomphon-Anomakhun1, Sorrjit Arrerut1

  • 1Extreme Conditions Physics Research Laboratory and Center of Excellence in Physics of Energy Materials (CE:PEM), Department of Physics, Faculty of Science, Chulalongkorn University, Bangkok, 10330, Thailand.

Scientific reports
|January 13, 2024
PubMed
概括

一个新的扩散概率CDVAE模型产生了现实的晶体结构. 这种改进的模型产生了更接近地面状态的结构,与原始CDVAE相比,能量差异明显较低.

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On-Chip Crystallization and Large-Scale Serial Diffraction at Room Temperature
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Optimizing the Growth of Endothiapepsin Crystals for Serial Crystallography Experiments
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Optimizing the Growth of Endothiapepsin Crystals for Serial Crystallography Experiments

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科学领域:

  • 材料科学 材料科学 材料科学
  • 计算化学的计算化学
  • 机器学习 机器学习

背景情况:

  • 晶体结构的生成对于材料的发现至关重要.
  • 现有的模型,如晶体扩散变异自编码器 (CDVAE),使用得分匹配.
  • 在产生的结构中保持对称性和准确性是关键的挑战.

研究的目的:

  • 引入一种新的扩散概率CDVAE (DP-CDVAE) 模型.
  • 提高生成的晶体结构的精度,特别是它们的基本状态配置.
  • 为了比较DP-CDVAE与原始CDVAE的性能.

主要方法:

  • 利用扩散概率 (DP) 模型来否定原子坐标.
  • 用DP模型取代CDVAE中的标准分数匹配方法.
  • 使用DP-CDVAE框架生成和评估晶体结构.

主要成果:

  • DP-CDVAE可以重建并产生与CDVAE相当的质量的晶体结构.
  • DP-CDVAE产生的碳结构显著接近它们的地面状态.
  • 与真实基态的能量差异平均比CDVAE低68.1 meV/原子.

结论:

  • 该DP-CDVAE模型有效地产生精确的晶体结构.
  • 使用扩散概率模型可以提高生成结构中的能量精度.
  • 对于发现具有更稳定的配置的材料,DP-CDVAE显示出前景.