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Rationale: Synthesis of copolymer is one of the major approaches to establish sophisticated polymers. In copolymer analysis in mass spectrometry (MS), an increase in the number of monomer unit species and/or the polymer molecular weight results in complex mass spectra, and a method is required to solve this problem. Methods: In this study, electrospray ionization‐ion mobility spectrometry‐mass spectrometry was employed to analyze styrene/methyl methacrylate/n‐butyl acrylate (St/MMA/nBA) terpolymers via Kendrick mass defect (KMD) analysis. An expanded Fourier transform‐based noise reduction method for the copolymer was developed to improve the decrease in the signal/noise ratio observed in the higher m/z region. Results: Low‐mass terpolymers (0.7 kDa) were identified by comparing the observed and theoretical results using a two‐dimensional KMD plot. For the 1.5 kDa terpolymer, the signal overlap, of which KMD value was not matched with the theoretical one, was interpreted by the shift from the theoretical value in the KMD plot. For the 3.0 kDa terpolymers, the compositional candidates were determined by the prediction based on the compositional information of low‐mass terpolymers previously analyzed. The 4.5 kDa terpolymer was interpreted after the expanded noise filtering. Conclusions: The terpolymers, whose molecular weight was up to 4.5 kDa, were successfully characterized at a molecular level. The dependency of the St/MMA/nBA composition on molecular weight was observed; that is, the nBA content decreased with an increase in the molecular weight. [ABSTRACT FROM AUTHOR]

Rationale: We recently developed the characterization method for synthetic polymers weighing more than a few tens of kilodalton using electrospray ionization‐ion mobility spectrometry‐tandem mass spectrometry, in which the m/z value of the most abundant peak was used for characterization. However, the identification of the most abundant peak from the isotopic peaks was often difficult due to the background noise. Methods: Here, we employed a noise reduction method using Fourier transform (FT) filtering. In the power spectrum obtained using FT of the mass spectrum of the multiple charged analytes, the significant signals in the low‐frequency region and at frequency z are observed for the analytes of z charges. When the signals in both regions were used for inversed FT (i.e., the signals in other regions were zero padded), a noise‐filtered mass spectrum was obtained. Results: In the analysis of poly(methylmethacrylate)s weighing 13–17 kDa, mass spectra without noise filtering with relatively high‐intensity noise (than signal) were complicated to identify the most abundant peak. On the contrary, the most abundant peak was clearly identified from the mass spectra after FT‐based noise filtering, and end group composition was estimated successfully. Conclusions: The proposed FT‐based noise filtering for the mass spectrum is effective to characterize multiply charged synthetic polymers weighing more than a few tens of kilodalton using electrospray ionization‐ion mobility spectrometry‐tandem mass spectrometry. [ABSTRACT FROM AUTHOR]

Rationale: Analyzing polymer end groups using pyrolysis (Py) gas chromatography/mass spectrometry (GC/MS) in multi‐component polymer samples is not an easy task because of the insufficient sensitivity, selectivity, and mass resolution of conventional Py‐GC/MS systems. Methods: A new Py‐GC/MS system using an atmospheric pressure chemical ionization (APCI) source combined with high‐resolution time‐of‐flight mass spectrometry (TOFMS) was used for end‐group analysis of a methyl methacrylate (MMA)‐styrene (St)‐butyl acrylate (BA) terpolymer (P (MMA‐St‐BA)), which was radically polymerized using 2,2′‐azobis(2‐methylbutyronitrile) (AMBN) as an initiator. Results: Five possible pyrolyzates, comprising an AMBN fragment and a monomer unit, formed during the initiation reactions from one of the three types of end groups, were selectively detected and exclusively identified in their respective extracted ion chromatograms for molecule‐related ions, such as M+ and [M + H]+, with a narrow mass window of ±2 milli m/z units. Conclusions: It was demonstrated that Py‐APCI‐TOFMS is a powerful technique to characterize in detail the complex end groups in multi‐component polymer samples, because of the soft ionization nature of APCI and the high mass resolution of TOFMS. [ABSTRACT FROM AUTHOR]