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Atomic Orbitals02:44

Atomic Orbitals

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An atomic orbital represents the three-dimensional regions in an atom where an electron has the highest probability to reside. The radial distribution function indicates the total probability of finding an electron within the thin shell at a distance r from the nucleus. The atomic orbitals have distinct shapes which are determined by l, the angular momentum quantum number. The orbitals are often drawn with a boundary surface, enclosing densest regions of the cloud.
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An atom comprises protons and neutrons, which are contained inside the dense, central core called the nucleus, with electrons present around the nucleus. Taking into account the wave–particle duality of electrons and the uncertainty in position around the nucleus, quantum mechanics provides a more accurate model for the atomic structure. It describes atomic orbitals as the regions around the nucleus where electrons of discrete energy exist, characterized by four quantum...
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Electron configurations and orbital diagrams can be determined by applying the Aufbau principle (each added electron occupies the subshell of lowest energy available), Pauli exclusion principle (no two electrons can have the same set of four quantum numbers), and Hund’s rule of maximum multiplicity (whenever possible, electrons retain unpaired spins in degenerate orbitals).
The relative energies of the subshells determine the order in which atomic orbitals are filled (1s, 2s, 2p, 3s, 3p,...
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To determine the electron configuration for any particular atom, we can build the structures in the order of atomic numbers. Beginning with hydrogen, and continuing across the periods of the periodic table, we add one proton at a time to the nucleus and one electron to the proper subshell until we have described the electron configurations of all the elements. This procedure is called the aufbau principle, from the German word aufbau (“to build up”). Each added electron occupies the...
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周期性的希尔什菲尔德原子精炼

Kanghyun Chu1, Dylan Jayatilaka2,3, Lorraine A Malaspina1

  • 1Department of Chemistry, Biochemistry and Pharmaceutical Sciences, University of Bern, Freiestrasse 3, 3012 Bern, Switzerland.

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概括
此摘要是机器生成的。

周期性赫什菲尔德原子精炼 (pHAR) 将晶体分析扩展到周期网络,提高了X-H键的精度. 这种新方法显著增加了B-H债券可靠的实验数据.

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科学领域:

  • 晶体学 晶体学是指结晶学.
  • 量子化学 是一个量子化学.
  • 材料科学 材料科学 材料科学

背景情况:

  • 希什菲尔德原子精炼 (HAR) 精确地从X射线衍射数据中精炼原子参数.
  • 传统的HAR仅限于分子晶体,不包括周期网络结构.

研究的目的:

  • 引入适用于任何周期网络结构的周期性 HAR (pHAR) 的新变体.
  • 使用以原子为中心的高斯轨道和布洛赫波形式主义,确保与常规HAR的兼容性.

主要方法:

  • 开发了一种周期性HAR (pHAR) 的新变体.
  • 采用了以原子为中心的高斯轨道与布洛赫波形式主义.
  • 对和酸盐的单晶衍射数据进行pHAR测试.

主要成果:

  • pHAR显示了X-H键长度与中子衍射数据的密切一致.
  • 在周期性网络的结构参数中获得了更高的精度.
  • 几乎使B-H债券可用的可靠实验数据翻了一番.

结论:

  • pHAR成功地将HAR扩展到周期网络结构.
  • 该方法提供了非常精确的X-H债券长度,特别是B-H债券.
  • pHAR显著提高了晶体学中的结构分析能力.