Studying branching with OMNISEC
When working with current and future OMNISEC users, a topic that frequently arises is whether or not OMNSIEC can assist with studying the branching in their samples. And since OMNISEC is a versatile, multi-detector GPC/SEC instrument, the answer is “yes!”
There are different ways to identify branching in using GPC/SEC and some of the common methods include observing various features in chromatograms, calculated numerical data, and visual representations of results. In this post I’ll use a series of four polystyrene samples to discuss and highlight how OMNISEC can help you study branching in your samples.
But first, what is a branched polymer?
A polymer that is branched is one that has multi-functional points along its backbone from which new polymer chains may propagate. A simpler description is: a polymer that has side chains, and some of those side chains may be long enough to have side chains of their own.
These branch points mean that the sample’s mass is held closer together than a linear analogue. The result is a smaller molecular size when compared to a linear sample of the same molecular mass. Since the molecular density of the branched sample is higher when compared to a linear sample at the same molecular mass, that means the intrinsic viscosity (IV) of the branched sample is lower than the linear version at the same point.
These concepts are summarized in the image below and detailed in my previous post on branching.
Chromatograms
The following chromatograms present the refractive index (red), right angle (green) & low angle (black) light scattering, and viscometer (blue) detector responses for four polystyrene samples. The calculated molecular weight and intrinsic viscosity at each data point is overlaid in gold and light blue, respectively. Sample 1 is linear, while samples 2, 3, and 4 display varying amounts of branching.
The chromatograms for sample 1 are mostly Gaussian, symmetrical, and similar throughout all detectors. This is typical of a linear sample. The chromatograms of samples 2, 3, and 4 begin to display greater differences between each detectors’ response. Most notably, the light scattering responses begin rising steeper and at lower retention volumes (earlier retention times). This change in the light scattering response is due to the greater intensity of light scattered by the highest molecular weight fractions. These fractions contain branched material that possesses more mass than a linear sample of the same size. Samples 2 and 3 show a shift in the light scattering response, but in sample 4 the peak shape changes drastically.
In contrast, the RI detector responses for samples 2, 3, and 4 don’t look that different than that of sample 1. This is because the RI detector responds to sample concentration, whereas the light scattering detector responds to molecular weight. Similar to the profile of aggregates, a small concentration of branched material produces a larger response in the light scattering detector than the RI detector.
Looking for evidence of branching in a sample’s chromatogram can be tricky. I would never look at only a chromatogram and conclude that a sample is branched. However, if the sample is designed to be branched or another piece of information indicates the sample is branched, then the responses of a multi-detector analysis can support that claim.
If you are working with branched samples, a multi-detector GPC/SEC with at least RI, viscometer, and light scattering detectors is critical. An RI-only instrument would not be able to differentiate these samples and highlight their branched nature.
Numerical data
Examining the calculated molecular data for samples is another way to seek evidence for branching within your samples. The calculated data for samples 1-4 is presented in the table below.
The first value to notice is the peak retention volume (RV), and how similar it is for all four samples. This underscores the inability of an RI-only system with a conventional calibration curve, which determines molecular weight based on retention volume, to distinguish the samples.
The second point of interest is the molecular weight values. The Mn and Mw values trend upward from sample 1 through sample 4, but they’re still the same order of magnitude. The values for sample 4 are less than double those of sample 1. However, if we look at the Mz values, you can see that they increase at a faster rate from sample 1 through sample 4, indicating something is going on with the highest molecular weight fractions of the samples. The Mz value of sample 4 is approximately four times that of sample 1, which is especially interesting considering the retention volume of the RI signal’s peak is about the same (17.13 mL for sample 1; 17.10 mL for sample 4). A difference in molecular weight values, specifically Mz, at the same retention volume indicates either a difference in dispersity (Mw/Mn aka molecular weight distribution), or a difference in molecular structure. The dispersity values for samples 1 and 4 are only a bit different, 2.271 for sample 1 and 2.645 for sample 4. Which means there must be a structural difference between the samples, potentially branching, especially in the highest molecular weight fractions of the sample.
Like with the chromatograms above, the calculated molecular data on its own will not tell you whether a sample is branched. But comparison of the numbers determined for various samples can provide evidence that branching is present.
Mark-Houwink plots
As I described in my previous post on branching, the best way to study a sample’s molecular structure is through the Mark-Houwink (MH) plot, which plots a sample’s IV on the y-axis against its molecular weight on the x-axis. Polymers with consistent structures throughout their molecular weight range have MH plots that appear as straight lines, as their molecular size, and thus IV, increases at a consistent rate with increasing molecular weight. Samples with similar structures will have MH plots that overlay or exist along the same line. Samples with different molecular densities will appear “stacked,” with the densest material situated lowest in the plot. If a material is branched, its MH plot will appear to curve downward with increasing molecular weight, as compared to a linear analogue.
The MH plot of samples 1-4 below shows the linear nature of sample 1 (red & purple), and the curved plots of samples 2-4. It’s worth noting that the molecular structures of the samples don’t deviate significantly until they approach 1 MDa. This suggests that most of the branched material resides in the highest molecular weight fractions of the samples, which concurs with the chromatograms and calculated numerical data.
Final thoughts
I hope the information in this post helps the next time you want to use your OMNISEC system to study the branching in your samples. Once you know what to look for, the OMNISEC software provides multiple ways to find evidence of branching in your samples. If you have any questions, please don’t hesitate to contact us or email me directly at kyle.williams@malvernpanalytical.com.
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