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Polypy: A Framework to Interpret Polymer Properties from Mass Spectroscopy Data

Vlnieska, Vitor ; Khanda, Ankita; Gilshtein, Evgeniia; Beltrán, Jorge Luis 1,2; Heier, Jakob; Kunka, Danays ORCID iD icon 1,2
1 Karlsruhe School of Optics & Photonics (KSOP), Karlsruher Institut für Technologie (KIT)
2 Institut für Mikrostrukturtechnik (IMT), Karlsruher Institut für Technologie (KIT)

Abstract:

Mass spectroscopy (MS) is a robust technique for polymer characterization, and it can provide the chemical fingerprint of a complete sample regarding polymer distribution chains. Nevertheless, polymer chemical properties such as polydispersity (Pd), average molecular mass (M$_n$), weight average molecular mass (Mw) and others are not determined by MS, as they are commonly
characterized by gel permeation chromatography (GPC). In order to calculate polymer properties from MS, a Python script was developed to interpret polymer properties from spectroscopic raw data. Polypy script can be considered a peak detection and area distribution method, and represents the result of combining the MS raw data filtered using Root Mean Square (RMS) calculation with
molecular classification based on theoretical molar masses. Polypy filters out areas corresponding to repetitive units. This approach facilitates the identification of the polymer chains and calculates their properties. The script also integrates visualization graphic tools for data analysis. In this work, aryl resin (poly(2,2-bis(4-oxy-(2-(methyloxirane)phenyl)propan) was the study case polymer molecule,
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Verlagsausgabe §
DOI: 10.5445/IR/1000172225
Veröffentlicht am 08.07.2024
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Mikrostrukturtechnik (IMT)
Karlsruhe School of Optics & Photonics (KSOP)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2024
Sprache Englisch
Identifikator ISSN: 2073-4360
KITopen-ID: 1000172225
Erschienen in Polymers
Verlag MDPI
Band 16
Heft 13
Seiten Art.-Nr.: 1771
Vorab online veröffentlicht am 22.06.2024
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