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Size-exclusion chromatography (SEC) hyphenated to pyrolysis-gas chromatography (Py-GC) has been demonstrated as a powerful tool in polymer analysis. A main limitation to the wider application of the method are the long second-dimension Py-GC analysis times, resulting in limited first-dimension sampling and/or long overall run times. Therefore, we set out to develop an online hyphenated SEC×Py-MS/FID method, removing the GC separation and allowing for a drastically reduced second-dimension analysis time compared to SEC-Py-GC. The pyrolysis method had a cycle time of 1.31 min, which was facilitated by liquid nitrogen cooling of the programmable temperature vaporizer (PTV) used for pyrolysis. The developed method featured no molar mass discrimination for masses above ±1.3 kDa, rendering it applicable to most commercial polymer systems. The method was demonstrated on multiple samples, including a complex industrial sample, yielding chemical composition heterogeneity and in some cases sequence heterogeneity information over the molar mass distribution.

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An understanding of the composition and molecular heterogeneities of complex industrial polymers forms the basis of gaining control of the physical properties of materials. In the current work we report on the development of an online method to hyphenate liquid polymer chromatography with pyrolysis-GC (Py-GC). The designed workflow included a 10-port valve for fractionation of the first-dimension effluent. Collected fractions were transferred to the Py-GC by means of a second LC pump, a 6-port valve was used to control injection in the Py-GC, allowing the second pump to operate continuously. The optimized large volume injection (LVI) method was capable of analyzing 117 µL of the LC effluent in a 6 min GC separation with a total cycle time of 8.45 min. This resulted in a total run time of 2.1 h while obtaining 15 Py-GC runs over the molar mass separation. The method was demonstrated on various real-life samples including a complex industrial copolymer with a bimodal molar mass distribution. The developed method was used to monitor the relative concentration of 5 different monomers over the molar mass distribution. Furthermore, the molar mass-dependent distribution of a low abundant comonomer (styrene, <1% of total composition) was demonstrated, highlighting the low detection limits and increased resolving power of this approach over e.g. online NMR or IR spectroscopy. The developed method provides a flexible and widely applicable approach to LC-Py-GC hyphenation without having to resort to costly and specialized instrumentation.

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Many industrial polymers which find application in contemporary materials are copolymers. Copolymers feature multiple distributions, that govern their physical properties, including the sequence distribution. Styrene-acrylate copolymers are an important class of polymers, their monomer sequence is typically determined by 13C NMR which suffers from low sensitivity and spectral resolution. A series of studies have shown that Py-GC can be applied to determine the sequence length of copolymers. The accuracy of the trimer assignments and the appropriate calibration approaches yielding reliable data have however not yet been validated. In the present study we propose a comprehensive workflow to ensure the accuracy of the sequence determination by Py-GC, next to NMR. In-depth analysis of the trimers observed in the Py-GC pyrograms of model styrene-acrylate copolymers was performed and specific MS fragments relating to the trimer sequence were assigned. A comparison of a series of copolymers yielded reliable assignments for the trimer signals. The obtained sequence lengths were in agreement with those calibrated with the benchmark method, 13C NMR. Py-GC was found to consistently underestimate the acrylate sequence length. Py-GC calibration with 13C NMR was thus found to be indispensable for the accurate absolute quantification of the sequence length by Py-GC. The calculated randomness did not vary significantly after NMR calibration, indicating that NMR calibration might not be required in all cases to obtain (relative) information on the sequence of a copolymer.

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The chain sequence of co-polymers strongly affects their physical properties. It is, therefore, of crucial importance for the development and final properties of novel materials. Currently however, few analytical methods are available to monitor the sequence of copolymers. The currently preferred method in copolymer-sequence determination, nuclear-magnetic-resonance spectroscopy (NMR), is insensitive (especially when 13C-NMR is required) and often offers little spectral resolution between signals indicative of different subunits. These limitations are especially challenging when one is interested in monitoring the sequence across the molar-mass distribution or in quantifying low abundant subunits. Therefore, we set out to investigate pyrolysis - gas chromatography (Py-GC) as an alternative method. Py-GC is more sensitive than NMR and offers better resolution between various subunits, but it does require calibration, since the method is not absolute. We devised a method to fuse data from NMR and Py-GC to obtain quantitative information on chain sequence and composition for a set of random and block poly(methyl methacrylate-co-styrene) copolymer samples, which are challenging to analyse as MMA tends to fully depolymerize. We demonstrated that the method can be successfully used to determine the chain sequence of both random and block copolymers. Furthermore, we managed to apply Py-GC to monitor the sequence of a random and a block copolymer across the molar-mass distribution.

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Copolymer products that result from grafting acrylic acid and other hydrophilic monomers onto polysaccharides have recently gained significant interest in research and industry. Originating from renewable sources, these biodegradable, low toxicity, and polar copolymer products exhibit potential to replace polymers from fossil sources in several applications and industries. The methods usually employed to characterize these copolymers are, however, quite limited, especially for the measurement of bulk properties. With more sophisticated applications, for example, in pharmaceutics requiring a more detailed analysis of the chemical structure, we describe a new approach for this kind of complex polymers. Our approach utilizes chromatography in combination with several detection methods to separate and characterize reaction products of the copolymerization of acrylic acid and chemically hydrolyzed starch. These samples consisted of a mixture of homopolymer poly (acrylic acid), homopolymer hydrolyzed starch, and - in a lower amount - the formed copolymers. Several chromatographic methods exist that are capable of characterizing either poly (acrylic acid) or hydrolyzed starch. In contrast, our approach offers simultaneous characterization of both polymers. The combination of LC and UV/RI offered insight into the composition and copolymer content of the samples. Size exclusion chromatography experiments revealed the molar mass distribution of homopolymers and copolymers. FTIR investigations confirmed the formation of copolymers while ESI-MS gave more details on the end groups of hydrolyzed starches and poly (acrylic acids). Evidence of copolymer structures was obtained through NMR measurements. Finally, two-dimensional chromatography led to the separation of the copolymers from both homopolymers as well as the additional separation of sodium clusters. The methods described in this work are a powerful toolset to characterize copolymerization products of hydrolyzed starch and poly(acrylic acid). Together, our approach successfully correlates the physicochemical properties of such complex mixtures with their actual composition.

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RATIONALE: Mass calibration in matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) is currently obtained using mixtures of individual peptides. This procedure has several drawbacks, including laborious preparation, limited shelf life and unequal calibration mass spacing. Polyalanine, a simple to prepare polydisperse molar mass standard, alleviates these problems. METHODS: Polyalanine is prepared by the typical protocols for biological sample analytics. RESULTS: Polyalanine is the first polymeric standard providing abundant signals in both, positive and negative polarity mode with the typical matrices DHB and HCCA. CONCLUSIONS: Facile MS as well as MS/MS calibration is thus enabled for the first time in both polarity modes by employing this polydisperse standard.

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Shining a light on click chemistry: The use of UV-radiation as trigger signal provides a facile means to obtain spatial and temporal control over polymer conjugation reactions in addition to providing a further means of achieving orthogonality in click transformations. In the current contribution, UV-radiation was employed to induce a highly efficient Diels-Alder conjugation of polymeric building blocks via the photo-induced in situ formation of highly reactive cis-dienes from a 2-methylbenzophenone precursor.

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Design of experiment (DoE) is applied to establish the optimum ionization conditions for analyzing synthetic polymers via coupled size exclusion chromatography electrospray ionization mass spectrometry (SEC-ESI-MS) yielding maximum ionization efficiency. The ion source conditions were optimized with regard to the ionization efficiency, the amount of fragmentation, as well as the formation of salt adducts. A D-optimal experimental design was employed for this purpose and the recorded data were evaluated by a quadratic response surface model, accounting for possible interactions between the individual source settings. It was established that the ionization efficiency can be improved by up to one order of magnitude without compromising the softness of the ionization process and that optimal ionization conditions are found at similar source settings regardless of the charge state. The present optimization exercise therefore provides a hands-on guide for the use of experimental design to determine optimum ionization conditions during the SEC-ESI-MS of functional polymers.

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We report on the successful application of size exclusion chromatography (SEC) combined with electrospray ionization mass spectrometry (ESI-MS) and refractive index (RI) detection for the determination of accurate molecular weight distributions of synthetic polymers, corrected for chromatographic band broadening. The presented method makes use of the ability of ESI-MS to accurately depict the peak profiles and retention volumes of individual oligomers eluting from the SEC column, whereas quantitative information on the absolute concentration of oligomers is obtained from the RI-detector only. A sophisticated computational algorithm based on the maximum entropy principle is used to process the data gained by both detectors, yielding an accurate molecular weight distribution, corrected for chromatographic band broadening. Poly(methyl methacrylate) standards with molecular weights up to 10 kDa serve as model compounds. Molecular weight distributions (MWDs) obtained by the maximum entropy procedure are compared to MWDs, which were calculated by a conventional calibration of the SEC-retention time axis with peak retention data obtained from the mass spectrometer. Comparison showed that for the employed chromatographic system, distributions below 7 kDa were only weakly influenced by chromatographic band broadening. However, the maximum entropy algorithm could successfully correct the MWD of a 10 kDa standard for band broadening effects. Molecular weight averages were between 5 and 14% lower than the manufacturer stated data obtained by classical means of calibration. The presented method demonstrates a consistent approach for analyzing data obtained by coupling mass spectrometric detectors and concentration sensitive detectors to polymer liquid chromatography.

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