A Short-Cut Data Mining Method for the Mass Spectrometric Characterization of Block Copolymers

Kuki, Ákos and Róth, Gergő and Nagy, Anna and Zsuga, Miklós and Kéki, Sándor and Nagy, Tibor (2022) A Short-Cut Data Mining Method for the Mass Spectrometric Characterization of Block Copolymers. PROCESSES, 10 (42). ISSN 2227-9717

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Abstract

A new data mining approach as a short cut method is proposed for the determination of the copolymer composition from mass spectra. Our method simplifies the copolymer mass spectra by reduction of the number of mass peaks. The proposed procedure, namely the selection of the mass peaks, which is based on the most intense peak of the mass spectrum, can be performed manually or more efficiently using our recently invented Mass-remainder analysis (MARA). The considerable reduction of the MS spectra also simplifies the calculation of the copolymer quantities such as the number-average molecular weight (Mn), weight-average molecular weight (Mw), polydispersity index (PDI = Mw/Mn), average molar fraction (cA) and weight fraction (wA) of unit A in the copolymer, and so on. These copolymer properties are in line with those calculated by a reference method taking into account all the mass peaks of the copolymer distribution. We also suggest a highly efficient method and template for the determination of the composition drift by processing the reduced mass spectra.

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