The 72nd Annual Conference on Mass Spectrometry, Japan
Date:
Mon, Jun 10, - Wed, Jun 12, 2024
Venue:
Tsukuba International Congress Center (Takezono, Tsukuba City, Ibaraki Prefecture 305-0032, Japan)
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Abstract

Symposium Sessions

Day 2, June 11(Tue.) 10:25-10:45 Room D (Conference Room 202)

2D-S-1025
PDF

Automatic Data Separation of Multi-component Copolymer Mass Spectra

(Asahi Kasei)
oSatsuki Matsuura, Chiaki Yoshikawa

Mass spectrometry is a powerful method for the structural analysis of polymers, and the scope of its use is expanding along with the increasing performance of measurement devices. Conversely, the labor required for analysis is also increasing with data accumulation and the complexity of the measurement targets, making the development of advanced high-throughput analytical methods essential.
In this study, we introduce a novel analytical method based on KMD analysis that can be applied to mass spectrometric data of multi-component copolymers. The core idea of this method is data aggregation of the regularly arranged mass peaks derived from the repeating unit of the polymer, made possible by combining RE-KMD and RKM analytical techniques (each an improved version of KMD analysis). This method enables classification of mass spectrometry data for structures other than repeating units (e.g., end structures, additional ions), facilitating identification of end-groups, acquisition of molecular weight distribution for each polymer, and extraction of data for additives that do not have repeating units. Furthermore, automation of the workflow and development of the user interface, together lead to a more advanced, high-throughput analytical method.