MLchartDataset catalogue

Incredible natural-abundance double-quantum transfer experiment

Term · Chemistry · MLC-T-CHM-005763

A two-dimensional NMR experiment that detects double-quantum coherence between directly bonded carbon-13 nuclei at natural abundance, thereby revealing the carbon-carbon connectivity of a molecule. Because only about 0.01% of molecules carry carbon-13 at both ends of a given C-C bond, the signals are very weak and need concentrated samples or long acquisition times. Coupled pairs appear at the same double-quantum frequency, the sum of their two shifts.

Table 1. Record
IdentifierMLC-T-CHM-005763
FieldChemistry
SubjectAnalytical Chemistry
ReferencesPAC, 2021, 93, 647. 'Glossary of methods and terms used in analytical spectroscopy (IUPAC Recommendations 2019)' on page 693 (https://doi.org/10.1515/pac-2019-0203)
See alsoNuclear magnetic resonance spectroscopy; Nuclear magnetic resonance spectrum
Record as JSON
{
  "id": "MLC-T-CHM-005763",
  "term": "Incredible natural-abundance double-quantum transfer experiment",
  "field": "Chemistry",
  "definition": "A two-dimensional NMR experiment that detects double-quantum coherence between directly bonded carbon-13 nuclei at natural abundance, thereby revealing the carbon-carbon connectivity of a molecule. Because only about 0.01% of molecules carry carbon-13 at both ends of a given C-C bond, the signals are very weak and need concentrated samples or long acquisition times. Coupled pairs appear at the same double-quantum frequency, the sum of their two shifts.",
  "subject": "Analytical Chemistry",
  "see_also": [
    "nuclear magnetic resonance spectroscopy",
    "nuclear magnetic resonance spectrum"
  ],
  "references": [
    "PAC, 2021, 93, 647. 'Glossary of methods and terms used in analytical spectroscopy (IUPAC Recommendations 2019)' on page 693 (https://doi.org/10.1515/pac-2019-0203)"
  ],
  "url": "https://mlchart.com/terminology/chemistry/incredible-natural-abundance-double-quantum-transfer-experiment/"
}

Record 6,112 of 13,676 in Chemistry terminology (MLC-0109). Request the full dataset.