BIBLIOGRAPHY ON MASS SPECTROMETRY 1938–1957 inclusive

doi:10.1016/b978-0-08-009210-2.50047-x

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“…Charlesbby and Callaghan (1958) mentioned the advent of mass spectroscopy as an auxiliary method for analyzing side chains of polyethylene [9]. It is also interesting to note the "Bibliography on Mass Spectroscopy" , in which most of the MS applications in "Section D-Applications to Organic Chemistry" were oriented to the petroleum industry [10]. Additionally, in the 1940s and 1950s, several reports present MS applications for polymer characterization; for example, Madorsky and Straus (1948) [11] describe a characterization method using mass spectroscopy for polystyrene pyrolysis fractions, Ciapetta et al (1948) utilize mass spectroscopy to evaluate fractions of butylene polymers [12], and Wall (1948) presents a mass spectrometric investigation of the thermal decomposition of several vinyl and diene polymers [13].…”

Section: Introductionmentioning

confidence: 99%

“…Molecular ions are chemical species missing electrons at the valence electron shell, which means that no chemical bond cleavage happens. In cases where sufficient energy is available during the ionization process, the majority of organic molecules do not lose a second electron at the valence shell; instead, they undergo a fragmentation process, splitting the molecules into several other chemical species and resulting in a fragmentation pattern known as the 'fingerprint' of the initial molecule species [10,11,15,16].…”

Section: Introductionmentioning

confidence: 99%

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

Vlnieska,

Khanda,

Gilshtein

et al. 2024

Polymers

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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 (Mn), 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, and is composed of oligomer chains distributed mainly in the range of dimers to tetramers, in some cases presenting traces of pentamers and hexamers in the distribution profile of the oligomeric chains. Epoxy resin has Mn = 607 Da, Mw = 631 Da, and polydispersity (Pd) of 1.015 (data given by GPC). With Polypy script, calculations resulted in Mn = 584.42 Da, Mw = 649.29 Da, and Pd = 1.11, which are consistent results if compared with GPC characterization. Additional information, such as the percentage of oligomer distribution, was also calculated and for this polymer matrix it was not possible to retrieve it from the GPC method. Polypy is an approach to characterizing major polymer chemical properties using only MS raw spectra, and it can be utilized with any MS raw data for any polymer matrix.

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