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Related Concept Videos

NMR Spectrometers: Overview01:20

NMR Spectrometers: Overview

NMR spectrometers consist of a strong magnet, a radiofrequency transmitter, and a detector attached to a computer console for recording spectra of samples containing NMR-active nuclei. In first-generation NMR instruments called continuous-wave spectrometers, the resonance frequencies of the nuclei are determined by frequency-sweep or field-sweep methods. The magnetic field strength is fixed and the rf signal is swept in the former, while the radiofrequency signal is fixed and the magnetic field...
Applications Of NMR In Biology01:25

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.
The...
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...
NMR Spectrometers: Resolution and Error Correction01:14

NMR Spectrometers: Resolution and Error Correction

When magnetic nuclei in a sample achieve resonance and undergo relaxation, the signal detected in NMR is an approximately exponential free induction decay. Fourier transform of an exponential decay yields a Lorentzian peak in the frequency domain. Lorentzian peaks in an NMR spectrum are defined by their amplitude, full width at half maximum, and position, where the peak width is governed by the spin-spin relaxation time alone. In real experiments, however, the applied magnetic field is rendered...

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NMR-Based Fragment Screening in a Minimum Sample but Maximum Automation Mode
09:19

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Published on: June 4, 2021

Optimization and automation of quantitative NMR data extraction.

Michael A Bernstein1, Stan Sýkora, Chen Peng

  • 1Mestrelab Research, S.L Feliciano Barrera 9B - Baixo, 15706 Santiago de Compostela, Spain. mike@mestrelab.com

Analytical Chemistry
|May 17, 2013
PubMed
Summary

This study introduces an automated expert system for Nuclear Magnetic Resonance (NMR) spectroscopy. It accurately quantitates chemical species by analyzing complex spectra, improving concentration determination for large datasets.

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Area of Science:

  • Analytical Chemistry
  • Spectroscopy
  • Computational Chemistry

Background:

  • Nuclear Magnetic Resonance (NMR) is a standard technique for chemical species quantitation.
  • Current NMR data processing and analysis methods lack robust automation.
  • Challenges exist in handling complex spectra with overlapping signals.

Purpose of the Study:

  • To develop a robust expert system for automated NMR spectral analysis.
  • To enable accurate and efficient concentration determination of chemical species.
  • To improve the processing of large NMR datasets.

Main Methods:

  • Developed an expert system based on complete spectral deconvolution.
  • Implemented automatic classification of NMR resonances.
  • Integrated automatic molecule-to-spectrum multiplet assignments.
  • Utilized all accepted methods for analyte concentration determination.

Main Results:

  • The system automatically selects optimal signals for concentration determination.
  • Achieved tolerance for spectra with closely overlapping signals.
  • Demonstrated robust automatic classification and assignment of NMR resonances.
  • Enabled fully automatic data processing for large sample sets.

Conclusions:

  • The developed expert system provides a robust and automated solution for quantitative NMR analysis.
  • This approach enhances the efficiency and accuracy of determining chemical species concentrations.
  • The system is highly applicable to large-scale NMR data analysis.