Articles | Volume 17, issue 6
https://doi.org/10.5194/amt-17-1811-2024
https://doi.org/10.5194/amt-17-1811-2024
Research article
 | 
28 Mar 2024
Research article |  | 28 Mar 2024

Application of fuzzy c-means clustering for analysis of chemical ionization mass spectra: insights into the gas phase chemistry of NO3-initiated oxidation of isoprene

Rongrong Wu, Sören R. Zorn, Sungah Kang, Astrid Kiendler-Scharr, Andreas Wahner, and Thomas F. Mentel

Viewed

Total article views: 1,230 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
913 266 51 1,230 135 34 35
  • HTML: 913
  • PDF: 266
  • XML: 51
  • Total: 1,230
  • Supplement: 135
  • BibTeX: 34
  • EndNote: 35
Views and downloads (calculated since 30 Aug 2023)
Cumulative views and downloads (calculated since 30 Aug 2023)

Viewed (geographical distribution)

Total article views: 1,230 (including HTML, PDF, and XML) Thereof 1,207 with geography defined and 23 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 11 Dec 2024
Download
Short summary
Recent advances in high-resolution time-of-flight chemical ionization mass spectrometry (CIMS) enable the detection of highly oxygenated organic molecules, which efficiently contribute to secondary organic aerosol. Here we present an application of fuzzy c-means (FCM) clustering  to deconvolve CIMS data. FCM not only reduces the complexity of mass spectrometric data but also the chemical and kinetic information retrieved by clustering gives insights into the chemical processes involved.