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

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