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Related Concept Videos

IR Spectrum Peak Intensity: Amount of IR-Active Bonds00:55

IR Spectrum Peak Intensity: Amount of IR-Active Bonds

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When infrared radiation is passed through a molecule, absorption occurs if the molecule's vibration leads to a substantial change in its bond dipole moment. Transitions between vibrational energy levels, typically corresponding to infrared frequencies (4000–400 cm−1), allow absorption if the vibration significantly alters the dipole moment, making the molecule infrared active. The molecular bonds have different stretching and bending vibrations, resulting in various peaks with...
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IR Spectrum Peak Broadening: Hydrogen Bonding01:23

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The vibrational frequency of a bond is directly proportional to its bond strength. As a result, stronger bonds vibrate at higher frequencies, while weaker bonds vibrate at lower frequencies. The stretching vibration of the strong O–H bond in alcohols and phenols (very dilute solution or gas phase) appears as a sharp peak at 3600–3650 cm−1.
However, the extent of hydrogen bonding influences the observed stretching frequency and band broadening. Intermolecular or intramolecular...
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IR Spectrum Peak Intensity: Dipole Moment01:20

IR Spectrum Peak Intensity: Dipole Moment

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The dipole moment of a bond is the product of the partial charge on either atom and the distance between them. Dipole moments influence the efficiency of IR absorption and the peak intensity. When a bond with a dipole moment is placed in an electric field, the direction of the field determines if the bond is compressed or stretched. Electromagnetic radiation consists of an electric field component that rapidly reverses direction. It follows that polar bonds are alternately stretched and...
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IR Spectrum Peak Splitting: Symmetric vs Asymmetric Vibrations01:08

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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...
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2D NMR: Heteronuclear Single-Quantum Correlation Spectroscopy (HSQC)01:19

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

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.
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Structure and Coordination Determination of Peptide-metal Complexes Using 1D and 2D 1H NMR
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Reaching the sparse-sampling limit for reconstructing a single peak in a 2D NMR spectrum using iterated maps.

Robert L Blum1, Jared Rovny1, J Patrick Loria2,3

  • 1Department of Physics, Yale University, 217 Prospect St., New Haven, CT, 06511, USA.

Journal of Biomolecular NMR
|July 12, 2019
PubMed
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This study refines the DiffMap algorithm for accelerating biomolecular NMR experiments. By understanding reconstruction errors, we developed a bottom-up approach for accurate spectral reconstruction with fewer samples.

Keywords:
DiffMapDifference mapNonuniform samplingReconstructionSparse sampling

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Area of Science:

  • Biomolecular Nuclear Magnetic Resonance (NMR) Spectroscopy
  • Computational Chemistry
  • Data Science

Background:

  • Many biomolecular NMR experiments acquire repeated 2D spectra under varying conditions.
  • These experiments can be accelerated using non-uniform sampling (NUS) and spectral reconstruction methods.
  • Previous work introduced the DiffMap algorithm for 2D NMR spectral reconstruction.

Purpose of the Study:

  • To gain an in-depth understanding of the DiffMap algorithm's performance.
  • To identify factors contributing to reconstruction errors at different undersampling fractions.
  • To develop a bottom-up approach for optimizing sparse sampling in DiffMap.

Main Methods:

  • Analysis of the DiffMap algorithm's mechanics and error sources.
  • Formulation of a bottom-up strategy for determining minimal sparse samples.
  • Application to 2D NMR spectral reconstruction, including relaxation dispersion data.

Main Results:

  • Identified key factors influencing DiffMap reconstruction accuracy.
  • Developed a method to determine the minimum number of sparse samples for accurate spectral feature reconstruction.
  • Demonstrated improved understanding of the algorithm's limitations and potential.

Conclusions:

  • The refined understanding of DiffMap enables more efficient spectral reconstruction.
  • A bottom-up approach allows for accurate reconstruction of individual spectral features with minimal data.
  • Further research is needed to extend this method for reconstructing multiple spectral features simultaneously.