Unlike low-molecular-weight chemicals, polymers are not single compounds. In a polymeric sample many different molecules are
present that derive from the same building blocks, but differ in chain length, degree of branching, end-groups, and so on.
For a thorough understanding of the properties of a copolymer, detailed knowledge of all these features is crucial. It is
generally not sufficient to just know the average distribution of single parameters, for example, the molecular weight or
the composition. Detailed knowledge on the various distributions is necessary for a true understanding of the polymer, its
properties and the mechanisms of its synthesis. To study composition drift in copolymerization reactions, for example, a technique
that allows monitoring of the chemical composition as a function of the molecular weight is needed. Clearly, only multi-dimensional
analytical techniques can provide this multi-dimensional information. To effectively analyse composition drift, a combination
of a size-based separation technique, such as size exclusion chromatography (SEC) and a method for obtaining information on
the chemical composition is needed.
Numerous authors have addressed this question. The most logical route is to couple SEC with a spectroscopic detector. Indeed,
SEC has been coupled to a wide range of spectroscopic and spectrometric detectors, including ultraviolet (UV), infrared (IR)
or nuclear-magnetic-resonance (NMR) spectroscopy, and mass spectrometry (MS).1–4 Unfortunately, each of these methods suffers from its own disadvantages. UV detection, for example, is not truly specific
and it is difficult to obtain rigorous quantitative information from IR detection.5 Pyrolysis-GC (Py-GC) presents an attractive alternative for spectroscopic detection after SEC. So far, however, Py-GC has
rarely been used as a compositional detector after SEC.
We believe that this is mainly because of difficulties encountered in automating the combination of these techniques and the
time-consuming nature of the experiments. The main difficulty in automating SEC–Py-GC–MS experiments lies in the solvent-elimination
step required. Previously, this had to be performed manually. Moreover, it is thought to be difficult to obtain truly quantitative
information from Py-GC. With the advent of high-temperature programmed-temperature vapourization (PTV) injectors it is now
possible to perform both automated solvent elimination of large SEC fractions and pyrolysis of the retained polymer in one
device.6–9 A large-volume fraction of the SEC effluent is introduced into the PTV injector. After the solvent has been eliminated,
the retained polymer is pyrolysed by rapidly heating the PTV injector to a high final temperature.
The goal of the present report is to describe our fully automated system for SEC–Py-GC and to demonstrate the potential of
this new set-up in copolymer analysis. In our instrument the entire SEC effluent is on-line divided into multiple fractions
for subsequent Py-GC–MS characterization. Fast GC–MS is used to reduce the total time required for the full characterization
of the polymeric sample. The quantitative performance of the PTV injector as a pyrolyser is evaluated. The conditions for
solvent elimination and pyrolysis are optimized and fast-GC–MS settings for the identification and quantification of the pyrolysis
fragments are determined. The system is applied for the combined size/composition characterization of various polymers, including
random copolymers of styrene and methylmethacrylate (MMA) and tri-block copolymers consisting of caprolacton (CL), MMA and
butylacrylate (BA).
Experimental
Samples and materials: Low dispersity polystyrene (PS) and polymethylmethacrylate (PMMA) standards and poly(styrene-co-methyl methacrylate) [PS-PMMA]
diblock copolymers with different styrene contents and molecular weights were obtained from PSS (Mainz, Germany). Four different
PS-PMMA random copolymers were provided by DSM Neoresins (Waalwijk, The Netherlands). Several terpolymers consisting of the
monomers MMA, BA and CL were prepared at the Technical University of Eindhoven, The Netherlands. The preparation of these
terpolymers has been described in detail by van Hulst et al.10 All polymers were dissolved in tetrahydrofuran [THF] (Biosolve, Valkenswaard, The Netherlands) before analysis.
