Principles and potential of solvent gradient size-exclusion chromatography for polymer analysis.

The properties of a polymeric material are influenced by its underlying molecular distributions, including the molecular-weight (MWD), chemical-composition (CCD), and/or block-length (BLD) distributions. Gradient-elution liquid chromatography (LC) is commonly used to determine the CCD. Due to the limited solubility of polymers, samples are often dissolved in strong solvents. Upon injection of the sample, such solvents may lead to broadened or poorly shaped peaks and, in unfavourable cases, to "breakthrough" phenomena, where a part of the sample travels through the column unretained. To remedy this, a technique called size-exclusion-chromatography gradients or gradient size-exclusion chromatography (gSEC) was developed in 2011. In this work, we aim to further explore the potential of gSEC for the analysis of the CCD, also in comparison with conventional gradient-elution reversed-phase LC, which in this work corresponded to gradient-elution reversed-phase liquid chromatography (RPLC). The influence of the mobile-phase composition, the pore size of the stationary-phase particles, and the column temperature were investigated. The separation of five styrene/ethyl acrylate copolymers was studied with one-dimensional RPLC and gSEC. RPLC was shown to lead to a more-accurate CCD in shorter analysis time. The separation of five styrene/methyl methacrylate copolymers was also explored using comprehensive two-dimensional (2D) LC involving gSEC, i.e. SEC × gSEC and SEC × RPLC. In 2D-LC, the use of gSEC was especially advantageous as no breakthrough could occur.

Recycling gradient-elution liquid chromatography for the analysis of chemical-composition distributions of polymers.

Synthetic polymers typically show dispersity in molecular weight and potentially in chemical composition. For the analysis of the chemical-composition distribution (CCD) gradient liquid chromatography may be used. The CCD obtained using this method is often convoluted with an underlying molecular-weight distribution (MWD). In this paper we demonstrate that the influence of the MWD can be reduced using very steep gradients and that such gradients are best realized utilizing recycling gradient liquid chromatography (LC↻LC). This method allows for a more-accurate determination of the CCD and the assessment of (approximate) critical conditions (if these exist), even when high-molecular-weight standards of narrow dispersity are not readily available. The performance and usefulness of the approach is demonstrated for several polystyrene standards, and for the separation of statistical copolymers consisting of styrene/methyl methacrylate and methyl methacrylate/butyl methacrylate. For the latter case, approximate critical compositions of the copolymers were calculated from the critical compositions of two homopolymers and one copolymer of known chemical composition, allowing for a determination of the CCD of unknown samples. Using this approach it is shown that the copolymers elute significantly closer to the predicted critical compositions after recycling of the gradient. This is most clear for the lowest-molecular-weight copolymer (Mw = 4.2 kDa), for which the difference between measured and predicted elution composition decreases from 7.9% without recycling to 1.4% after recycling.

Determination of chemical composition distributions in synthetic polymers.

A characteristic feature of synthetic polymers is their dispersity in molar mass and, in many cases, chemical composition. Since dispersity is highly relevant in relation to polymer properties, ongoing efforts are being put in the development of appropriate analysis methods. In this respect, size-exclusion chromatography (SEC) is well known for the determination of molar mass distributions. Methods for chemical composition distributions are less mature than SEC and mainly include liquid chromatography and mass spectrometry and the combination of these techniques. The term chemical composition distribution is considered broad in this paper, i.e. for the chemical composition distribution of a (co)polymer backbone, for the functionality type distribution of a polymers' functional end groups, for the block length distribution of a block copolymer, for the branching distribution and for the tacticity distribution. In this paper, analysis methods for all types of chemical composition distributions are reviewed. Special attention is paid to practical requirements and common misconceptions that sometimes arise. Applications within the last 5 years are summarized.