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2D NMR: Overview of Heteronuclear Correlation Techniques

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.

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

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...

2D NMR: Homonuclear Correlation Spectroscopy (COSY)

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...

2D NMR: Overview of Homonuclear Correlation Techniques

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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...

Two-Dimensional (2D) NMR: Overview

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The 1D NMR spectrum of large and complex molecules like natural products has complicated splitting patterns and overlapping signals, which can be easily interpreted using 2-dimensional (2D) NMR. Unlike 1D NMR, 2D NMR has two frequency axes that provide the coupling information between the nucleus A and nucleus B in a molecule. The process from which 2D spectra are obtained has four steps.
The first step is the preparation period, during which nucleus A is excited with a radiofrequency pulse.

Classification of Signals

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Related Experiment Video

Updated: Jun 21, 2026

A Multimodal Wide-Field Fourier-Transform Raman Microscope

A Multimodal Wide-Field Fourier-Transform Raman Microscope

Published on: December 30, 2025

Quantitative classification of two-dimensional correlation spectra.

Jianbo Chen¹, Qun Zhou, Isao Noda

¹Key Laboratory of Bioorganic Phosphorus Chemistry & Chemical Biology (Ministry of Education), Department of Chemistry, Tsinghua University, Beijing 100084, China.

Applied Spectroscopy

|August 15, 2009

Summary

Quantitative analysis of 2D correlation spectra is now possible using Euclidian distance and correlation coefficient. These methods effectively differentiate wine samples based on sugar content, enhancing spectral analysis capabilities.

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Area of Science:

Analytical Chemistry
Spectroscopy

Background:

Two-dimensional (2D) correlation spectroscopy enhances spectral resolution for qualitative sample discrimination.
Quantitative classification of 2D correlation spectra is a significant but underexplored area.

Purpose of the Study:

To introduce and validate quantitative parameters for 2D correlation spectra analysis.
To demonstrate the utility of these parameters in classifying complex samples like red wines.

Main Methods:

Development of Euclidian distance and correlation coefficient metrics for 2D correlation spectra.
Application of these metrics to differentiate dry and sweet red wine samples using 2D infrared (IR) spectroscopy.

Main Results:

Euclidian distance between 2D IR spectra showed proportionality to sugar content differences in red wines.
Correlation coefficient also proved effective in evaluating spectral similarities.

Conclusions:

Euclidian distance and correlation coefficient are valuable for quantitative evaluation of sample similarity using 2D correlation spectra.
These parameters offer a robust method for objective classification and analysis in spectroscopy.