A mass defect-based approach for the automatic construction of peak lists for databases of mass spectra with limited resolution: Application to time-of-flight secondary ion mass spectrometry data.
Journal
Rapid communications in mass spectrometry : RCM
ISSN: 1097-0231
Titre abrégé: Rapid Commun Mass Spectrom
Pays: England
ID NLM: 8802365
Informations de publication
Date de publication:
15 Aug 2024
15 Aug 2024
Historique:
revised:
06
05
2024
received:
14
03
2024
accepted:
07
05
2024
medline:
27
5
2024
pubmed:
27
5
2024
entrez:
27
5
2024
Statut:
ppublish
Résumé
This study has developed a data processing protocol based on mass defect analysis for the automatic construction of unique peak lists addressing the need for the fast and efficient treatment of databases of mass spectra with limited mass resolution. The data processing protocol, implemented in MATLAB, is tested on a database of 126 mass spectra obtained from time-of-flight secondary ion mass spectrometry analysis of the exhaust of a laboratory diesel miniCAST burner deposited on Ti substrates. The data processing protocol converts the mass spectra into a data matrix suitable for chemometrics (peak list) by combining mass defect analysis and multivariate analysis. In particular, the role of the mass defect analysis is expanded to improve mass calibration and automate the construction of the peak list. In this context, mass defect analysis becomes an invaluable technique for the efficient processing of databases of mass spectra with limited mass resolution by allowing the fast and automated construction of a peak list common to all mass spectra, by improving the mass calibration, and finally by reducing the number of molecular formulae consistent with a given accurate mass, thus facilitating the identification of unknown ions.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
e9777Subventions
Organisme : Labex CaPPA
ID : ANR-11-LABX-0005-01
Informations de copyright
© 2024 John Wiley & Sons Ltd.
Références
Murray KK, Boyd RK, Eberlin MN, Langley GJ, Li L, Naito Y. Definitions of terms relating to mass spectrometry (IUPAC recommendations 2013). Pure Appl Chem. 2013;85(7):1515‐1609. doi:10.1351/PAC‐REC‐06‐04‐06
DeCarlo PF, Kimmel JR, Trimborn A, et al. Field‐deployable, high‐resolution, time‐of‐flight aerosol mass spectrometer. Anal Chem. 2006;78(24):8281‐8289. doi:10.1021/ac061249n
Müller M, Graus M, Ruuskanen TM, et al. First eddy covariance flux measurements by PTR‐TOF. Atmos Meas Tech. 2010;3(2):387‐395. doi:10.5194/amt‐3‐387‐2010
Junninen H, Ehn M, Petäjä T, et al. A high‐resolution mass spectrometer to measure atmospheric ion composition. Atmos Meas Tech. 2010;3(4):1039‐1053. doi:10.5194/amt‐3‐1039‐2010
Stark H, Yatavelli RLN, Thompson SL, et al. Methods to extract molecular and bulk chemical information from series of complex mass spectra with limited mass resolution. Int J Mass Spectrom. 2015;389:26‐38. doi:10.1016/j.ijms.2015.08.011
Timonen H, Cubison M, Aurela M, et al. Applications and limitations of constrained high‐resolution peak fitting on low resolving power mass spectra from the ToF‐ACSM. Atmos Meas Tech. 2016;9(7):3263‐3281. doi:10.5194/amt‐9‐3263‐2016
Madiona RMT, Welch NG, Russell SB, et al. Multivariate analysis of ToF‐SIMS data using mass segmented peak lists. Surf Interface Anal. 2018;50(7):713‐728. doi:10.1002/sia.6462
Sleno L. The use of mass defect in modern mass spectrometry. J Mass Spectrom. 2012;47(2):226‐236. doi:10.1002/jms.2978
Irimiea C, Faccinetto A, Carpentier Y, et al. A comprehensive protocol for chemical analysis of flame combustion emissions by secondary ion mass spectrometry. Rapid Commun Mass Spectrom. 2018;32(13):1015‐1025. doi:10.1002/rcm.8133
Duca D, Irimiea C, Faccinetto A, et al. On the benefits of using multivariate analysis in mass spectrometric studies of combustion‐generated aerosols. Faraday Discuss. 2019;218(0):115‐137. doi:10.1039/C8FD00238J
Irimiea C, Faccinetto A, Mercier X, et al. Unveiling trends in soot nucleation and growth: when secondary ion mass spectrometry meets statistical analysis. Carbon. 2019;144:815‐830. doi:10.1016/j.carbon.2018.12.015
Ngo LD, Duca D, Carpentier Y, et al. Chemical discrimination of the particulate and gas phases of miniCAST exhausts using a two‐filter collection method. Atmos Meas Tech. 2020;13(2):951‐967. doi:10.5194/amt‐13‐951‐2020
Daoudi M, Schiffmann P, Faccinetto A, Frobert A, Desgroux P. Comprehensive characterization of particulate matter emissions produced by a liquid‐fueled miniCAST burner. Aerosol Sci Tech. 2023;57(9):872‐889. doi:10.1080/02786826.2023.2228372
Mamyrin BA. Time‐of‐flight mass spectrometry (concepts, achievements, and prospects). Int J Mass Spectrom. 2001;206(3):251‐266. doi:10.1016/S1387‐3806(00)00392‐4