Hyphenation of liquid chromatography and pyrolysis-flame ionization detection/mass spectrometry for polymer quantification and characterization.

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.

Online hyphenation of size-exclusion chromatography and pyrolysis-gas chromatography for polymer characterization.

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.

Packed modulation loops to reduce band broadening in two-dimensional liquid chromatography.

Modulation interfaces employing sample loops are applied in many hyphenated separations such as two-dimensional liquid chromatography (2D-LC). When the first-dimension effluent in 2D-LC is eluted from the modulation loop, dispersion effects occur due to differences in the laminar flow velocity of the filling and emptying flow. These effects were recently studied by Moussa et al. whom recommended the use of coiled loops to promote radial diffusion and reduce this effect. In the 1980s, Coq et al. investigated the use of packed loops, which also promote radial diffusion, in large volume injection 1D-LC. Unfortunately, this concept was never investigated in the context of 2D-LC modulation. Our work evaluates use of packed loops in 2D-LC modulation and compares them to unpacked coiled and uncoiled modulation loops. The effect of the solvents, loop volume, differences in filling and emptying rates, and loop elution direction on the elution profile was investigated. Statistical moments were used as a pragmatic tool to quantify elution profile characteristics. Decreased dispersion was observed in all cases for the packed loops compared to unpacked loops and unpacked coiled loops. In particular for larger loop volumes the dispersion was reduced significantly. Furthermore, countercurrent elution resulted in narrower elution profiles in all cases compared to concurrent elution. We found that packed modulation loops are of high interested when analytes are not refocussed in the second-dimension separation (e.g. for size-exclusion chromatography). Moreover, our work suggests that the use of packed loops may aid in prevention of loop overfilling.

Improving the accuracy of copolymer sequence length determination by pyrolysis gas chromatography: A comprehensive study.

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.

Co-Polymer sequence determination over the molar mass distribution by size-exclusion chromatography combined with pyrolysis - gas chromatography.

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.

Detection challenges in quantitative polymer analysis by liquid chromatography.

Accurate quantification of polymer distributions is one of the main challenges in polymer analysis by liquid chromatography. The response of contemporary detectors is typically influenced by compositional features such as molecular weight, chain composition, end groups, and branching. This renders the accurate quantification of complex polymers of which there are no standards available, extremely challenging. Moreover, any (programmed) change in mobile-phase composition may further limit the applicability of detection techniques. Current methods often rely on refractive index detection, which is not accurate when dealing with complex samples as the refractive-index increment is often unknown. We review current and emerging detection methods in liquid chromatography with the aim of identifying detectors, which can be applied to the quantitative analysis of complex polymers.

Recent applications of chemometrics in one- and two-dimensional chromatography.

The proliferation of increasingly more sophisticated analytical separation systems, often incorporating increasingly more powerful detection techniques, such as high-resolution mass spectrometry, causes an urgent need for highly efficient data-analysis and optimization strategies. This is especially true for comprehensive two-dimensional chromatography applied to the separation of very complex samples. In this contribution, the requirement for chemometric tools is explained and the latest developments in approaches for (pre-)processing and analyzing data arising from one- and two-dimensional chromatography systems are reviewed. The final part of this review focuses on the application of chemometrics for method development and optimization.