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相关概念视频

Interpreting ¹H NMR Signal Splitting: The (n + 1) Rule01:10

Interpreting ¹H NMR Signal Splitting: The (n + 1) Rule

1.1K
In the AX proton spin system, proton A can sense the two spin states of a coupled proton X, resulting in a doublet NMR signal with two peaks of equal (1:1) intensity. When proton A is coupled to two equivalent protons (AX2 spin system), the spin states of each X can be aligned with or against the external field, creating three possible scenarios. This results in a 1:2:1  triplet signal, where the central peak corresponds to the chemical shift of A and is twice as large or intense as the...
1.1K
¹H NMR: Complex Splitting01:13

¹H NMR: Complex Splitting

1.2K
A proton M that is coupled to a proton X results in doublet signals for M. However, NMR-active nuclei can be simultaneously coupled to more than one nonequivalent nucleus. When M is coupled to a second proton A, such as in styrene oxide, each peak in the doublet is split into another doublet.
Splitting diagrams or splitting tree diagrams are routinely used to depict such complex couplings. While drawing splitting diagrams, the splitting with the larger coupling constant is usually applied...
1.2K
¹H NMR Signal Multiplicity: Splitting Patterns01:13

¹H NMR Signal Multiplicity: Splitting Patterns

4.9K
When protons A and X are coupled, their nuclear spin energy levels are slightly modified. This is because the energy required to excite proton A to a spin state parallel to proton X is slightly different from the energy required for it to become anti-parallel to spin X. Consequently, there are two possible excitation frequencies for A (A1 and A2), depending on the spin state of X, and vice versa. The mutual nature of coupling implies that the difference between frequencies A1 and A2, indicated...
4.9K
¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)01:20

¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)

999
When proton-coupled carbon-13 spectra are simplified by a broadband proton decoupling technique, structural information about the coupled protons is lost. Distortionless enhancement by polarization transfer (DEPT) is a technique that provides information on the number of hydrogens attached to each carbon in a molecule. While the DEPT experiment utilizes complex pulse sequences, the pulse delay and flip angle are specifically manipulated. The resulting signals have different phases depending on...
999
¹³C NMR: ¹H–¹³C Decoupling01:04

¹³C NMR: ¹H–¹³C Decoupling

994
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...
994
Double Resonance Techniques: Overview01:12

Double Resonance Techniques: Overview

179
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...
179

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一个深度学习框架用于H NMR中的多重分割分类.

Giulia Fischetti1, Nicolas Schmid2, Simon Bruderer3

  • 1School of Engineering, Zurich University of Applied Sciences (ZHAW), Technikumstrasse 9, Winterthur, 8401, Zurich, Switzerland; Dipartimento di Scienze Molecolari e Nanosistemi, Ca' Foscari Università Venezia, Via Torino 155, Mestre, 30172, Italy.

Journal of magnetic resonance (San Diego, Calif. : 1997)
|February 20, 2025
PubMed
概括
此摘要是机器生成的。

一个深度学习框架MuSe Net自动化了1D质子核磁共振 (NMR) 光谱的注释. 这种方法通过准确地分类光谱模式和识别异常来增强化学化合物特征.

关键词:
(1) H NMR 的时间.深度学习是一种深度学习.多重分割 分割 多重分割 分割模式识别 模式识别 模式识别

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科学领域:

  • 计算化学计算化学
  • 频谱学是一种光谱学.
  • 化学中的人工智能.

背景情况:

  • 一维质子核磁共振 (1D H NMR) 是一种用于化学化合物分析的快速技术.
  • 手动注释1DHNMR光谱是耗时的,可能导致不一致的解释.
  • 自动化光谱分析对于简化化学特征和确保全社区一致性至关重要.

研究的目的:

  • 介绍 MuSe Net,一个新的监督概率深度学习框架,用于自动化 1D H NMR 光谱注释.
  • 模拟专家光谱学家在识别和分类光谱特征方面的能力.
  • 使用NMR数据提高化学化合物表征的效率和可靠性.

主要方法:

  • 开发MuSe Net,一个深度学习框架,利用监督概率学习.
  • 该模型分析1D1HNMR光谱,以根据分裂模式 (最多四个合常量) 检测和分类多重光谱.
  • 实施不确定性量化以提供对分类可靠性和异常检测的信心评分.

主要成果:

  • MuSe Net成功地检测和分类1D H NMR光谱中的多重体.
  • 该框架在处理光谱异常和重叠的峰值方面表现出强大.
  • 对48个实验光谱的评估显示,与专家注释相比,准确的分类和可靠的信心评分.

结论:

  • MuSe Net为1DHNMR光谱注释提供了一个有效的自动化解决方案.
  • 深度学习方法提高了化学结构阐明的一致性和效率.
  • 在MuSe Net中,不确定性量化有助于评估光谱解释的可靠性和识别具有挑战性的信号.