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Related Concept Videos

2D NMR: Overview of Heteronuclear Correlation Techniques01:18

2D NMR: Overview of Heteronuclear Correlation Techniques

Heteronuclear correlation spectroscopy is an analytical technique that investigates the coupling between different types of nuclei, often a proton and an X-nucleus, such as carbon-13 or nitrogen-15. This method is commonly used in nuclear magnetic resonance (NMR) spectroscopy to gain insights into complex chemical compounds' structural and compositional aspects. A typical heteronuclear correlation spectrum displays X-nucleus chemical shifts on one axis and a proton spectrum on the other axis.
¹H NMR: Interpreting Distorted and Overlapping Signals01:02

¹H NMR: Interpreting Distorted and Overlapping Signals

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 slanted or...
2D NMR: Overview of Homonuclear Correlation Techniques01:16

2D NMR: Overview of Homonuclear Correlation Techniques

Homonuclear correlation spectroscopy (COSY) is a powerful technique used in Nuclear Magnetic Resonance (NMR) spectroscopy to study the correlations between nuclei of the same type within a molecule. It provides information about scalar couplings between adjacent nuclei, which helps determine connectivity and structural information. There are several COSY variants, each with its unique strengths and experimental parameters.
COSY90 is the standard two-dimensional (2D) COSY experiment that...
2D NMR: Heteronuclear Single-Quantum Correlation Spectroscopy (HSQC)01:19

2D NMR: Heteronuclear Single-Quantum Correlation Spectroscopy (HSQC)

Heteronuclear single-quantum correlation spectroscopy (HSQC) is a 2D NMR technique that reveals one-bond correlations between hydrogen and a heteronucleus. The HSQC experiment is similar to the heteronuclear correlation experiment (HETCOR) but is more sensitive. In the HSQC spectrum, the proton chemical shift is plotted on the horizontal F2 axis, while the 13C chemical shift is plotted on the vertical F1 axis. The corresponding proton and 13C spectra are also shown. The HSQC contour plot does...
IR Spectrum Peak Splitting: Symmetric vs Asymmetric Vibrations01:08

IR Spectrum Peak Splitting: Symmetric vs Asymmetric Vibrations

Identical bonds within a polyatomic group can stretch symmetrically (in-phase) or asymmetrically (out-of-phase). Similar to hydrogen bonding, these vibrations also influence the shape of the IR peak. Generally, asymmetric stretching frequencies are higher than symmetric stretching frequencies. For example, primary amines exhibit two distinct IR peaks between 3300–3500 cm−1 corresponding to the symmetric and asymmetric N-H stretching, while secondary amines exhibit a single stretching vibration...
2D NMR: Homonuclear Correlation Spectroscopy (COSY)01:06

2D NMR: Homonuclear Correlation Spectroscopy (COSY)

Homonuclear correlation spectroscopy, or COSY, is a 2-dimensional NMR technique that provides information about coupled protons. Typically, the geminal and vicinal coupling are observed. For example, consider the COSY spectrum of ethyl acetate, where its 1D proton NMR spectrum is plotted along the vertical and horizontal axes with their corresponding chemical shift scale. Three spots on the diagonal corresponding to the three peaks in the 1D proton spectrum are called diagonal peaks. The COSY...

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Updated: Jun 1, 2026

Pure Shift Nuclear Magnetic Resonance: a New Tool for Plant Metabolomics
13:16

Pure Shift Nuclear Magnetic Resonance: a New Tool for Plant Metabolomics

Published on: July 31, 2021

Improved identification of noisy spectra using higher-ordered correlation spectral analysis.

S P Kozaitis1, B S Bradshaw

  • 1Division of Electrical, Computer Science, and Engineering, Florida Institute of Technology, 150 West University Boulevard, Melbourne, Florida 32901.

Analytical Chemistry
|May 31, 2011
PubMed
Summary

This study introduces a third-order correlation technique for improved spectral identification. This method enhances the detection of infrared spectra in noisy conditions, outperforming traditional second-order methods, especially at low signal-to-noise ratios.

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Last Updated: Jun 1, 2026

Pure Shift Nuclear Magnetic Resonance: a New Tool for Plant Metabolomics
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ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis
07:11

ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis

Published on: August 19, 2021

Area of Science:

  • Spectroscopy
  • Signal Processing
  • Analytical Chemistry

Background:

  • Second-order cross-correlation functions are commonly used for spectral identification.
  • These methods can be limited by noise of unknown spectral density.
  • Higher-order correlations offer a theoretical advantage in noise reduction.

Purpose of the Study:

  • To apply a third-order correlation technique for identifying similar infrared (IR) spectra.
  • To evaluate the effectiveness of this method in reducing noise compared to second-order techniques.
  • To determine if the third-order method improves spectral detection probability, particularly in noisy environments.

Main Methods:

  • Utilized a higher-order correlation-based comparison for spectral identification.
  • Applied a third-order correlation technique to IR spectra analysis.
  • Reduced noise effects by processing second-order correlation measurements with third-order autocorrelation.
  • Averaged results from multiple experiments to enhance findings.

Main Results:

  • The third-order correlation method significantly reduced the impact of noise on spectral identification.
  • Compared to second-order techniques alone, the third-order method increased the probability of detecting spectra in noisy conditions.
  • Performance gains were particularly notable at low signal-to-noise ratios.

Conclusions:

  • Third-order correlation is a valuable technique for spectral identification in the presence of noise.
  • This method offers a viable alternative when second-order correlation techniques are insufficient.
  • Averaging multiple experimental results further improves the efficacy of the third-order correlation technique.