The DOI matches its Crossref record.
Collisional Activation Mass Spectrometry—A New Probe for Determining the Structure of Ions in the Gas Phase
Abstract
Organic ions with high translational energy colliding inelastically with neutral atoms or molecules become excited electronically at the expense of their translational energy. The excitation energy enables a wide range of dissociation reactions to occur and the intensity relationships yield information about the structure of the ions concerned and also permit conclusions to be drawn about the mechanism of their formation.
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Citations
Cited by
Triple quadrupole mass spectrometry for direct mixture analysis and structure elucidation
Yost, R. A., & Enke, C. G. (1979) · Analytical Chemistry · doi:10.1021/ac50048a002 · Cited by 337
The diverse and expanding role of mass spectrometry in structural and molecular biology
Lössl, P., van de Waterbeemd, M., & Heck, A. J. (2016) · The EMBO Journal · doi:10.15252/embj.201694818 · Cited by 222
Metadata
- Authors
- Levsen, K., & Schwarz, H.
- Venue
- Angewandte Chemie International Edition in English
- Publisher
- Wiley
- Published
- 1976-09
- Volume
- 15
- Issue
- 9
- Pages
- 509-519
- ISSN
- 0570-0833 (ISSN-L)
- OpenAlex
- W2021390244
- Cited by
- 242
- References
- 0
- FWCI
- 20.63
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Collisional Activation Mass Spectrometry—A New Probe for Determining the Structure of Ions in the Gas Phase. https://app.cochat.ai/papers/10.1002/anie.197605091
- The paper
- Levsen, K., & Schwarz, H. (1976). Collisional Activation Mass Spectrometry—A New Probe for Determining the Structure of Ions in the Gas Phase. Angewandte Chemie International Edition in English. https://doi.org/10.1002/anie.197605091
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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.
