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¹H NMR: Complex Splitting

¹H NMR: Complex Splitting

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...

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...

Chemical Shift: Internal References and Solvent Effects

Chemical Shift: Internal References and Solvent Effects

In an NMR sample, precise measurement of the absolute absorption frequencies of nuclei is difficult. A standard internal reference compound is added, and the frequency difference between the reference signal and sample signals is measured.
The internal reference compound generally used in NMR spectroscopy is tetramethylsilane (TMS). TMS is preferred because it is chemically inert, soluble in NMR solvents, and easily removable. Also, the highly shielded methyl protons in TMS yield an intense...

Applications Of NMR In Biology

Applications Of NMR In Biology

Nuclear magnetic resonance (NMR) spectroscopy is a very valuable analytical technique for researchers. It has been used for more than 50 years as an analytical tool. F. Bloch and E. Purcell formulated NMR in 1946 and won the 1952 Nobel Prize in Physics for their work. Biological macromolecules such as proteins, nucleic acids, lipids, and organic molecules including pharmaceutical compounds, can be studied using this versatile tool that exploits the magnetic properties of certain nuclei.

¹H NMR: Interpreting Distorted and Overlapping Signals

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...

Two-Dimensional (2D) NMR: Overview

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....

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Related Experiment Video

Updated: May 26, 2025

The Identification of Sea Lamprey Pheromones Using Bioassay-Guided Fractionation

The Identification of Sea Lamprey Pheromones Using Bioassay-Guided Fractionation

Published on: July 17, 2018

Network Flow Methods for NMR-Based Compound Identification.

Leonhard Lücken¹, Nico Mitschke¹, Thorsten Dittmar^1,2

¹Institute for Chemistry and Biology of the Marine Environment (ICBM), Carl von Ossietzky Universität Oldenburg, Ammerländer Heerstraße 114-118, 26129 Oldenburg, Germany.

Analytical Chemistry

|February 25, 2025

Summary

This summary is machine-generated.

This study presents a new method for identifying compounds in mixtures using nuclear magnetic resonance (NMR) spectra without needing to pick peaks. The minimum cost flow approach accurately identifies compounds and their concentrations, outperforming existing algorithms.

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Last Updated: May 26, 2025

The Identification of Sea Lamprey Pheromones Using Bioassay-Guided Fractionation

The Identification of Sea Lamprey Pheromones Using Bioassay-Guided Fractionation

Published on: July 17, 2018

NMR-Based Fragment Screening in a Minimum Sample but Maximum Automation Mode

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Published on: June 4, 2021

Metabolomic Analysis of Rat Brain by High Resolution Nuclear Magnetic Resonance Spectroscopy of Tissue Extracts

Metabolomic Analysis of Rat Brain by High Resolution Nuclear Magnetic Resonance Spectroscopy of Tissue Extracts

Published on: September 21, 2014

Area of Science:

Analytical Chemistry
Spectroscopy
Metabolomics

Background:

Compound identification in complex mixtures is crucial for various scientific disciplines.
Existing nuclear magnetic resonance (NMR) spectral analysis methods often rely on peak-picking, which can be a bottleneck and source of error.

Purpose of the Study:

To introduce a novel, peak-picking-free method for compound identification in NMR spectra of mixtures.
To simultaneously optimize the spectral fit of multiple compounds from a library.
To assess the performance and accuracy of the new method compared to existing algorithms.

Main Methods:

Development of a minimum cost flow (MCF) algorithm applied to spectral data.
Network construction where nodes represent spectral peaks from library compounds and the mixture.
Application to 2D ¹H,¹³C HSQC spectra of artificial and natural mixtures with a library of 501 compounds.

Main Results:

The MCF method outperforms popular algorithms in standard compound identification tasks.
Accurate identification of individual compounds within artificial mixtures.
Retrieval of semiquantitative accuracy for individual compound concentrations in mixtures up to 34 compounds.

Conclusions:

The novel MCF method provides a robust and accurate approach for compound identification and quantification in NMR spectra without peak-picking.
This method offers a significant advancement over traditional spectral deconvolution techniques.
A software implementation is publicly available, facilitating broader adoption and research.