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Chemical Bonds02:40

Chemical Bonds

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Atoms participate in a chemical bond formation to acquire a completed valence-shell electron configuration similar to that of the noble gas nearest to it in atomic number. Ionic, covalent, and metallic bonds are some of the important types of chemical bonds. Bond energy and bond length determine the strength of a chemical bond.
Types of Chemical Bonds
An ionic bond is formed due to electrostatic attraction between cations and anions. Often, the ions are formed by the transfer of electrons...
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MO Theory and Covalent Bonding02:40

MO Theory and Covalent Bonding

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The molecular orbital theory describes the distribution of electrons in molecules in a manner similar to the distribution of electrons in atomic orbitals. The region of space in which a valence electron in a molecule is likely to be found is called a molecular orbital. Mathematically, the linear combination of atomic orbitals (LCAO) generates molecular orbitals. Combinations of in-phase atomic orbital wave functions result in regions with a high probability of electron density, while...
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Valence Bond Theory02:45

Valence Bond Theory

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Overview of Valence Bond Theory
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Molecular Orbital Theory II03:51

Molecular Orbital Theory II

19.0K
Molecular Orbital Energy Diagrams
19.0K
Types of Chemical Bonds02:37

Types of Chemical Bonds

75.5K
Chemical bonding theories were pioneered by American chemist Gilbert N. Lewis. He developed a model called the Lewis model to explain the type and formation of different bonds. Chemical bonding is central to chemistry; it explains how atoms or ions bond together to form molecules. It explains why some bonds are strong and others are weak, or why one carbon bonds with two oxygens and not three; why water is H2O and not H4O. 
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Bond Energies and Bond Lengths02:49

Bond Energies and Bond Lengths

25.1K
Stable molecules exist because covalent bonds hold the atoms together. The strength of a covalent bond is measured by the energy required to break it, that is, the energy necessary to separate the bonded atoms. Separating any pair of bonded atoms requires energy — the stronger a bond, the greater the energy required to break it.
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科学领域:

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

背景情况:

  • 传统的化学键分析与来自电子结构计算的大量信息作斗争,面临着简洁性,通用性和描述性的"三难题".
  • 当前的方法在分析复杂的化学键时,往往无法同时实现高通用性和描述性.

研究的目的:

  • 引入基于机器学习 (ML) 的一般框架,将化学键信息压缩成详细的残留物"基因组".
  • 克服传统方法的局限性,通过在化学键分析中实现极端的通用性和描述能力.
  • 证明框架在分析黄金纳米集群中的关键S-Au和Au-Au债券方面的能力.

主要方法:

  • 开发了一个通用的ML框架,融合了量子力学,自动特征提取,模拟 (例如密度函数理论) 和生成模型.
  • 将化学键信息编码为具有8个值的"基因组",表示玻色-费米子特征.
  • 在来自DFT模拟的26528个电子定位函数图像上训练了ML模型.

主要成果:

  • 机器学习框架产生了信息密集,可解码的基因组,具有100%的通用性和广泛的描述性,超越了现有的模型.
  • 在金纳米集群中对S-Au和Au-Au键的分析揭示了诸如键极化,杂交和原子相互作用等细节.
  • 证明了分子和固体的整合到基因组中,使结合复杂性的可视化和与现实指数的关联成为可能.

结论:

  • 拟议的ML框架为分析化学键提供了一个强大的,通用的和描述性的方法,特别是在像纳米集群这样的复杂系统中.
  • "基因组"的表现为"理解"化学键提供了一种新的方法,在化学吸收,分子动力学和超快速过程中具有潜在的应用.
  • 这种方法意味着计算化学的飞跃,使得我们能够更深入地了解原子间相互作用和材料特性.