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A mass spectrometry imaging method for visualizing synthetic polymers by using average molecular weight and dispersity as indices
Author(s) -
Satoh Takaya,
Nakamura Sayaka,
Fouquet Thierry,
Sato Hiroaki,
Ueda Yoshihisa
Publication year - 2020
Publication title -
rapid communications in mass spectrometry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.528
H-Index - 136
eISSN - 1097-0231
pISSN - 0951-4198
DOI - 10.1002/rcm.8653
Subject(s) - dispersity , polymer , chemistry , mass spectrometry imaging , molar mass distribution , analytical chemistry (journal) , mass spectrometry , mass distribution , mass spectrum , pixel , chromatography , polymer chemistry , optics , organic chemistry , physics , quantum mechanics , galaxy
Rationale Matrix‐assisted laser desorption/ionization mass spectrometric imaging (MSI) is considered to be a powerful tool for visualizing the spatial distribution of synthetic polymers. However, a conventional method extracting an image of a specific m/z value is not suitable for polymers, which have a mass distribution. It is necessary to develop the visualization method to show the spatial distribution of entire polymer series. Methods The mass peaks included in polymer series were specified from the average mass spectrum of the entire MSI measurement region by using Kendrick mass defect analysis. The images of those mass peaks were extracted and the number average molecular weight ( M n ), the weight average molecular weight ( M w ) and dispersity (Đ) were calculated for each pixel. Finally, the spatial distribution of the polymer series was summarized to images using M n , M w and Đ as indices. Results The effects of the methods were investigated by (i) polymers with different mass distributions and (ii) polymers with different repeat units and end‐groups. In both cases, the spatial distribution of specific polymer series including several dozens to hundreds of mass peaks was summarized into three images related to M n , M w and Đ , which are familiar indices in polymer analysis. The results are able to provide an overview of the spatial variation of each polymer more intuitively. Conclusions The visualization of M n , M w and Đ will help provide an overview of the spatial distribution of polymer series combined with ion intensity distribution made by conventional methods. It can be also applied to other mass spectrometric imaging methods such as desorption electrospray ionization (DESI) or time‐of‐flight secondary ion mass spectrometry (TOF‐SIMS).