The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Taming Azide Radicals for Catalytic C–H Azidation
Abstract
Reactions that directly transform aliphatic C–H bonds into alkyl azides are noticeably lacking in the repertoire of synthetic reactions, despite the importance of molecules containing C–N 3 bonds in organic synthesis, chemical biology, and drug discovery. Harnessing the ubiquity of C–H bonds in organic molecules and the versatility of the azide functional group, such transformations could have broad applications in various disciplines. Radical C–H activation represents an appealing strategy to achieve aliphatic C–H azidation, as it overcomes many drawbacks of conventional organometallic approaches in activating inert aliphatic C–H bonds. Novel C–H azidation methodologies could be realized by combining radical C–H activation via hydrogen atom abstraction with suitable azide-transfer reagents. In this perspective, we survey the history of radical C–H azidation and summarize several significant recent advances in the field. All radical C–H azidations to date follow a general approach comprising an initial radical C–H abstraction step and a subsequent azide transfer to the incipient carbon-centered radicals. A particular focus of this perspective is on the beneficial effects of using transition-metal catalysts in C–H azidation reactions, which have “tamed” azide radicals and led to reactions that proceed efficiently under much milder conditions and provide broader substrate scope and higher regioselectivities and stereoselectivities, compared to previous approaches.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Prier, C. K., Rankic, D. A., & MacMillan, D. W. C. (2013) · Chemical Reviews · doi:10.1021/cr300503r · Cited by 9,590
Cited by
Ravelli, D., Fagnoni, M., Fukuyama, T., Nishikawa, T., & Ryu, I. (2018) · ACS Catalysis · doi:10.1021/acscatal.7b03354 · Cited by 533
Metadata
- Authors
- Huang, X., & Groves, J. T.
- Venue
- ACS Catalysis
- Publisher
- American Chemical Society (ACS)
- Published
- 2015-12-31
- Volume
- 6
- Issue
- 2
- Pages
- 751-759
- ISSN
- 2155-5435 (ISSN-L)
- OpenAlex
- W2199406638
- Cited by
- 174
- References
- 1
- FWCI
- 8.39
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.