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相关概念视频

Double Resonance Techniques: Overview01:12

Double Resonance Techniques: Overview

213
Double resonance techniques in Nuclear Magnetic Resonance (NMR) spectroscopy involve the simultaneous application of two different frequencies or radiofrequency pulses to manipulate and observe two distinct nuclear spins. One important application of double resonance is spin decoupling, which selectively suppresses coupling with one type of nucleus while observing the NMR signal from another nucleus, simplifying the spectrum and enhancing resolution.
Spin decoupling is usually achieved by...
213
¹H NMR: Interpreting Distorted and Overlapping Signals01:02

¹H NMR: Interpreting Distorted and Overlapping Signals

1.0K
Spin systems where the difference in chemical shifts of the coupled nuclei is greater than ten times J are called first-order spin systems. These nuclei are weakly coupled, and their chemical shifts and coupling constant can generally be estimated from the well-separated signals in the spectrum.
As Δν decreases and the signals move closer, the doublets appear increasingly distorted. The intensities of the inner lines increase at the cost of those of the outer lines as the signals are...
1.0K
Spin–Spin Coupling: Two-Bond Coupling (Geminal Coupling)01:20

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

1.0K
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...
1.0K

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两步机器学习方法用于与结构多样化的数据进行电荷转移合.

Hung-Hsuan Lin1,2, Chun-I Wang1,3, Chou-Hsun Yang1

  • 1Institute of Chemistry, Academia Sinica, 128 Section 2 Academia Road, Nankang, Taipei 115, Taiwan.

The journal of physical chemistry. A
|December 29, 2023
PubMed
概括

我们开发了一种新的机器学习方法,可以准确预测分子对中的电子合. 这种方法改善了电荷转移速率的预测,特别是在复杂的无形系统中.

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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:

  • 电子合决定了电荷转移速率,受到分子间和分子内因素的影响.
  • 准确的预测是很困难的,特别是对于具有不同配置的无形材料.

研究的目的:

  • 开发一种强大的机器学习算法,用于预测分子对中的电子合.
  • 为了提高电荷转移动态建模的准确性.

主要方法:

  • 采用了一种两步的内核回归模型 (KRR).
  • 第一个KRR模型从结构变化中预测分子轨道 (MO).
  • 第二个KRR模型使用MO重叠积分来预测合强度.

主要成果:

  • 获得的平均绝对误差为0.27meV的乙烯二次体和1.99meV的乙烯对.
  • 证明了显著的错误减少 (分别是14倍和3倍).
  • 预测的MO可以作为其他量子化学属性计算的输入.

结论:

  • 新的两步KRR方法显著提高了电子合预测的准确性.
  • 这种方法提供了一种更可靠的方式来建模电荷转移动态,特别是在无形系统中.
  • 该方法具有适应性,并且与其他准确的MO预测器兼容.