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The DOI matches its Crossref record; 101 of the 101 references it cites were found in a registry or an index.

Diffusion NMR Spectroscopy in Supramolecular and Combinatorial Chemistry: An Old Parameter—New Insights

Cohen, Yoram, Avram, Liat, Frish, Limor·2005·Angewandte Chemie International Edition

Abstract

Intermolecular interactions in solution play an important role in molecular recognition, which lies at the heart of supramolecular and combinatorial chemistry. Diffusion NMR spectroscopy gives information over such interactions and has become the method of choice for simultaneously measuring diffusion coefficients of multicomponent systems. The diffusion coefficient reflects the effective size and shape of a molecular species. Applications of this technique include the estimation of association constants and mapping the intermolecular interactions in multicomponent systems as well as investigating aggregation, ion pairing, encapsulation, and the size and structure of labile systems. Diffusion NMR spectroscopy can also be used to virtually separate mixtures and screen for specific ligands of different receptors, and may assist in finding lead compounds.

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Metadata

Authors
Cohen, Y., Avram, L., & Frish, L.
Venue
Angewandte Chemie International Edition
Publisher
Wiley
Published
2005-01-11
Volume
44
Issue
4
Pages
520-554
ISSN
  • 1433-7851 (ISSN-L)
  • 1521-3773
OpenAlex
W2170348191
Cited by
1,122
References
101
FWCI
17.21
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Diffusion NMR Spectroscopy in Supramolecular and Combinatorial Chemistry: An Old Parameter—New Insights. https://app.cochat.ai/papers/10.1002/anie.200300637
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Cohen, Y., Avram, L., & Frish, L. (2005). Diffusion NMR Spectroscopy in Supramolecular and Combinatorial Chemistry: An Old Parameter—New Insights. Angewandte Chemie International Edition. https://doi.org/10.1002/anie.200300637

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.