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Related Concept Videos

Two-Dimensional (2D) NMR: Overview01:12

Two-Dimensional (2D) NMR: Overview

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

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

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 others.
¹H NMR Signal Integration: Overview00:58

¹H NMR Signal Integration: Overview

The intensity of a signal, which can be represented by the area under the peak, depends on the number of protons contributing to that signal. The area under each peak is shown as a vertical line called an integral, with the integral value listed under it, as seen in the proton NMR spectrum of benzyl acetate. Each integral value is divided by the smallest integral value to obtain the ratio of the number of protons producing each signal. The ratio reveals the relative number of protons and not...

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Related Experiment Video

Updated: Jun 24, 2026

Structure and Coordination Determination of Peptide-metal Complexes Using 1D and 2D 1H NMR
14:44

Structure and Coordination Determination of Peptide-metal Complexes Using 1D and 2D 1H NMR

Published on: December 16, 2013

Analytical solution to the coupled evolution of multidimensional NMR data.

Geoffrey A Mueller1

  • 1National Institute of Environment Health Sciences, 111 T.W. Alexander Drive, MD-MR-01, Research Triangle Park, NC 27709, USA. Mueller3@niehs.nih.gov

Journal of Biomolecular NMR
|March 25, 2009
PubMed
Summary

This study introduces a novel method using circulant matrices for analyzing multidimensional NMR data, significantly reducing acquisition time by directly processing spectra and enabling artifact-free separation of coupled frequencies.

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Related Experiment Videos

Last Updated: Jun 24, 2026

Structure and Coordination Determination of Peptide-metal Complexes Using 1D and 2D 1H NMR
14:44

Structure and Coordination Determination of Peptide-metal Complexes Using 1D and 2D 1H NMR

Published on: December 16, 2013

15N CPMG Relaxation Dispersion for the Investigation of Protein Conformational Dynamics on the µs-ms Timescale
08:09

15N CPMG Relaxation Dispersion for the Investigation of Protein Conformational Dynamics on the µs-ms Timescale

Published on: April 19, 2021

Area of Science:

  • Nuclear Magnetic Resonance (NMR) Spectroscopy
  • Computational Chemistry
  • Data Analysis

Background:

  • Multidimensional NMR data collection is time-consuming due to incomplete sampling of indirect dimensions.
  • Existing methods for separating coevolved frequencies often rely on peak coordinates and can introduce artifacts.
  • Developing efficient algorithms is crucial for extracting meaningful information from complex NMR datasets.

Purpose of the Study:

  • To present a new method for analyzing coupled evolution in multidimensional NMR data using circulant matrices.
  • To provide an exact inversion solution for extracting orthogonal vectors directly from spectral data.
  • To develop a robust algorithm for separating overlapped signals and validating results.

Main Methods:

  • Utilizing circulant matrices to model coupled evolution as convolutions.
  • Developing an exact inversion solution that processes spectra directly, avoiding peak picking.
  • Implementing a sampling scheme involving N orthogonal spectra and N+1 projections.
  • Presenting a cross-validation algorithm involving forward and back calculations.

Main Results:

  • Demonstrated the effectiveness of the circulant matrix method on simulated and real NMR data.
  • Showcased an exact inversion solution for extracting orthogonal vectors from coupled dimensions.
  • Developed a robust algorithm for separating overlapped signals with rigorous cross-validation.
  • The proposed method significantly reduces data acquisition time while minimizing artifacts.

Conclusions:

  • Circulant matrices offer an exact and efficient solution for analyzing coupled evolution in multidimensional NMR.
  • Direct spectral processing bypasses the limitations of traditional peak-picking methods.
  • The developed algorithm provides a robust and verifiable approach for spectral analysis and signal separation.