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相关概念视频

Spin–Spin Coupling: Three-Bond Coupling (Vicinal Coupling)01:22

Spin–Spin Coupling: Three-Bond Coupling (Vicinal Coupling)

1.1K
Vicinal or three-bond coupling is commonly observed between protons attached to adjacent carbons. Here, nuclear spin information is primarily transferred via electron spin interactions between adjacent C‑H bond orbitals. This generally favors the antiparallel arrangement of spins, so 3J values are usually positive.
The extent of coupling depends on the C‑C bond length, the two H‑C‑C angles, any electron-withdrawing substituents, and the dihedral angle between the...
1.1K
¹H NMR: Long-Range Coupling01:27

¹H NMR: Long-Range Coupling

1.7K
The coupling interactions of nuclei across four or more bonds are usually weak, with J values less than 1 Hz. While these are usually not observed in spectra, the presence of multiple bonds along the coupling pathway can result in observable long-range coupling.
In alkenes, spin information is communicated via σ–π overlap, as seen in allylic (four-bond) and homoallylic (five-bond) couplings. These coupling interactions are stronger when the σ bond is parallel to the alkene...
1.7K
NMR Spectroscopy: Spin–Spin Coupling01:08

NMR Spectroscopy: Spin–Spin Coupling

1.3K
The spin state of an NMR-active nucleus can have a slight effect on its immediate electronic environment. This effect propagates through the intervening bonds and affects the electronic environments of NMR-active nuclei up to three bonds away; occasionally, even farther. This phenomenon is called spin–spin coupling or J-coupling. Coupling interactions are mutual and result in small changes in the absorption frequencies of both nuclei involved. While nuclei of the same element are involved...
1.3K
Spin–Spin Coupling: One-Bond Coupling01:17

Spin–Spin Coupling: One-Bond Coupling

951
Coupling interactions are strongest between NMR-active nuclei bonded to each other, where spin information can be transmitted directly through the pair of bonding electrons. While nuclei polarize their electrons to the opposite spins, the bonding electron pair has opposite spins. Configurations with antiparallel nuclear spins are expected to be lower in energy. When coupling makes antiparallel states more favorable, J is considered to have a positive value. The one-bond coupling constant, 1J,...
951
¹³C NMR: ¹H–¹³C Decoupling01:04

¹³C NMR: ¹H–¹³C Decoupling

1.1K
The probability of having two carbon-13 atoms next to each other is negligible because of the low natural abundance of carbon-13. Consequently, peak splitting due to carbon-carbon spin-spin coupling is not observed in spectra. However, protons up to three sigma bonds away split the carbon signal according to the n+1 rule, resulting in complicated spectra.
A broadband decoupling technique is used to simplify these complex, sometimes overlapping, signals. Broadband decoupling relies on a...
1.1K
Spin–Spin Coupling: Two-Bond Coupling (Geminal Coupling)01:20

Spin–Spin Coupling: Two-Bond Coupling (Geminal Coupling)

985
Two NMR-active nuclei bonded to a central atom can be involved in geminal or two-bond coupling. Geminal coupling is commonly seen between diastereotopic protons in chiral molecules and unsymmetrical alkenes, among others.
The central atom need not be NMR-active because its electrons are affected by the electron polarization of the spin-active atoms. However, spin information is transmitted less effectively than in one-bond coupling, and 2J values are usually weaker than 1J values. The energy of...
985

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机器学习大数据集分析揭示了C-C电联机制

Haobo Li1, Xinyu Li2, Pengtang Wang1

  • 1School of Chemical Engineering, the University of Adelaide, Adelaide SA 5005, Australia.

Journal of the American Chemical Society
|August 3, 2024
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概括
此摘要是机器生成的。

这项研究揭示了非对称的碳-碳合在减少二氧化碳方面更有效. 铜银 (CuAgNb) 催化剂提高了选择性,通过大数据和机器学习为绿色化学品生产提供了新的范式.

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科学领域:

  • 催化剂
  • 电催化
  • 绿色化学
  • 材料科学
  • 计算化学

背景情况:

  • 碳-碳 (C-C) 合对于电催化二氧化碳减少为绿色化学物质至关重要.
  • 对C-C合的反应机制和催化剂设计仍然是复杂的和有争议的.
  • 需要一个全面的数据集和先进的分析来理解和优化C-C合.

研究的目的:

  • 建立C-C合前体和活性部位组合的综合数据集.
  • 通过大数据分析探索反应机制和选催化剂.
  • 加速催化剂设计以实现高效的二氧化碳电解.

主要方法:

  • 开发了一种2D-3D整体机器学习策略,以扩展量子化学计算数据.
  • 创建了一个广泛的大数据集,包括C-C合前体和活性位点组成.
  • 分析数据集以确定最佳反应途径和催化剂组成.

主要成果:

  • 不对称的合机制 (例如,CHO与CH或CH2) 比对称的具有更高的潜在效率.
  • 基于Cu的催化剂的双金属注,特别是CuAgNb位点,增强了C-C合的选择性.
  • 实验验证证了CuAgNb催化剂显著提高了C-C合性能.

结论:

  • 通过机器学习加速的大数据分析,为复杂的催化系统提供实用洞察力.
  • 不对称的合路径和定制的双金属催化剂代表了二氧化碳电减的有前途方向.
  • 将大数据与计算化学和实验验证相结合, 建立了催化剂设计的新范式.