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NMR Spectroscopy of Aromatic Compounds01:14

NMR Spectroscopy of Aromatic Compounds

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Aromatic compounds can be identified or analyzed using proton NMR and carbon‐13 NMR. Typically, aromatic hydrogens or hydrogens directly bonded to the aromatic rings are strongly deshielded by the aromatic ring current. Therefore, they absorb in the range of 6.5–8.0 ppm in proton NMR spectra. For instance, aromatic hydrogens directly bonded to the benzene ring absorb at 7.3 ppm. However, aromatic hydrogens of larger rings absorb farther upfield or downfield than the ideal range.
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Properties of Organometallic Compounds01:23

Properties of Organometallic Compounds

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Organometallic compounds are compounds that contain a carbon–metal bond. Carbon belongs to an organyl group like alkyl, aryl, allyl, or benzyl groups. The metal can be from Group I or Group II of the periodic table, a transition metal, or a semimetal.
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Applications Of NMR In Biology01:25

Applications Of NMR In Biology

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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.
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Other Nuclides: 31P, 19F, 15N NMR01:16

Other Nuclides: 31P, 19F, 15N NMR

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Many organic, inorganic, and biological molecules contain spin-half nuclei such as nitrogen-15, fluorine-19, and phosphorus-31. As a result, NMR studies of these nuclei have found extensive applications in chemical and biological research.
While fluorine-19 and phosphorous-31 have high natural abundances (100%) and positive gyromagnetic ratios, nitrogen-15 has a low natural abundance and a negative gyromagnetic ratio. However, nitrogen-15 is still preferred over nitrogen-14 (which has a...
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NMR Spectroscopy and Mass Spectrometry of Aldehydes and Ketones01:15

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In aldehydes, the hydrogen atom connected to the carbonyl carbon helps distinguish aldehydes from other carbonyl compounds using ¹H NMR spectroscopy. The closeness of aldehydic hydrogen to the electrophilic carbonyl carbon highly deshields the hydrogen atom causing its signal to appear around 10 ppm in the ¹H NMR spectra. α hydrogens split the aldehydic proton signal, which helps identify the number of α hydrogens in the molecule. For instance, one α hydrogen creates a...
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NMR and Mass Spectroscopy of Carboxylic Acids01:30

NMR and Mass Spectroscopy of Carboxylic Acids

4.2K
In ¹H NMR spectroscopy, acidic protons (–COOH) of carboxylic acids are highly deshielded and absorb far downfield, at around 9–12 ppm. The chemical shift value depends on the concentration and solvent used.
While α protons of carboxylic acids absorb at 2–2.5 ppm, β protons absorb further upfield.
Carboxylic acids are easily identified by dissolving them in deuterium oxide, which results in a rapid exchange of the acidic protons with deuterium. This leads to the...
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An NMR Database for Organic and Organometallic Compounds.

Stefan Kuhn1, Markus Fischer2, Herman Rull1

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This study shows that chemical databases can seamlessly include organometallic compounds. Minor modifications allow existing algorithms to process both organic and organometallic compounds, enhancing data management.

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Area of Science:

  • Chemistry
  • Chemical Informatics
  • Computational Chemistry

Background:

  • Chemical databases traditionally store organic compounds using graphical representations.
  • Established software and standards facilitate machine and human readability of organic compound data.
  • Organometallic compounds, featuring coordination bonds, present unique structural characteristics.

Purpose of the Study:

  • To propose and demonstrate a method for extending chemical databases to include organometallic compounds.
  • To ensure seamless integration without compromising existing database functionalities.
  • To enable unified algorithmic treatment of both organic and organometallic compounds.

Main Methods:

  • Modification of existing chemical database formats to accommodate organometallic structures.
  • Utilizing a nuclear magnetic resonance (NMR) data database for validation.
  • Applying established algorithms to both organic and organometallic compound data.

Main Results:

  • Demonstrated the feasibility of incorporating organometallic compounds into existing chemical databases with minimal changes.
  • Showcased that the same algorithms can effectively process both organic and organometallic compounds.
  • Validated the approach using a nuclear magnetic resonance (NMR) database.

Conclusions:

  • Chemical databases can be effectively extended to include organometallic compounds.
  • Minor database modifications are sufficient for seamless integration.
  • Unified algorithmic processing of diverse chemical compound types is achievable.