Whether your samples are synthetic polymers, natural materials such as polysaccharides, or proteins, antibodies, or other biological samples, gel permeation / size exclusion chromatography (GPC/SEC) is the ideal technique for characterizing those and other types of macromolecules.  The information offered from GPC/SEC analysis includes molecular weight (MW), molecular size in the form of hydrodynamic radius (Rh) and radius of gyration (Rg), intrinsic viscosity (IV), concentration, compositional analysis, and branching data, among other parameters.  The data available is dependent on the detector combination present, as various detectors combine to offer different pieces of the characterization puzzle.  This post will break down how the different detectors, available in the OMNISEC and Viscotek TDA platforms, work together to provide a comprehensive characterization of a sample.  For more details (and equations!), please see our white paper on the principles of multi-detector GPC/SEC.

The detector and molecular parameter relationships are summarized graphically in the figure above.  The chart starts at the bottom with the sample attribute directly measured by each detector, then moves up to values that are directly calculated from the observed detector responses and ends at the top with information computed from the directly calculated data.

The four detectors most commonly associated with a fully-loaded multi-detector GPC/SEC system are a differential refractive index (RI) detector, a light scattering detector (RALS/LALS or MALS), a differential viscometer detector, and a UV detector.  The specific feature of a sample to which these detectors respond is listed on the bottom row of the figure above.  The RI detector is responsive to the change in refractive index between the sample solution and the blank solvent.  The light scattering detector responds most strongly to a sample’s molecular weight, with higher molecular weight samples eliciting a more intense response.  The differential viscometer detector’s signal is based on the difference in solution viscosity of the sample solution as compared to the blank solvent.  And the UV detector’s response is based on the sample’s absorbance level.  A sample without a chromophore that does not absorb UV light produces no UV signal.

All GPC/SEC systems must have at least one concentration detector, regardless of what other detectors are present.  The RI and UV detectors are considered concentration detectors because their responses are directly proportional to the sample’s concentration.  Most systems utilize an RI detector as not all samples are UV active.  With knowledge of a sample’s dn/dc value, or refractive index increment, the exact concentration of a sample at every data slice can be calculated from the RI detector.  Likewise, if using a UV detector, knowledge of the sample’s dA/dc value, which is related to its molar extinction coefficient, will allow for the calculation of the sample’s concentration at each data slice.  With both RI and UV detectors, the composition of a sample comprised of two components can be determined.

Knowing the sample’s exact concentration at each recorded data slice is critical, as it is required to determine molecular weight and intrinsic viscosity, two of the prominent molecular parameters included in the directly calculated middle section of the previous hierarchy figure.  An examination of the equations governing the detector responses listed above reveals why the sample’s concentration is essential.  If we focus on the light scattering equation, the detector output is observed, the KLS represents the detector constant obtained by analyzing a narrow standard, the molecular weight is unknown, the dn/dc value is known as it is used in the equation for the RI detector to calculate the concentration, which is then plugged into the light scattering equation, and the injection volume is known as it is set by the user.  That leaves the molecular weight as the single unknown.  Through the combination of RI and light scattering detectors, the molecular weight of a sample can be calculated at each data slice.  The calculated molecular weights are then integrated over the defined sample peak and the molecular weight moments are calculated based on the relative concentrations of each fraction.

An analogous process occurs with the RI and viscometer detectors to directly calculate the IV of the sample at each data slice and produce a weight-average IV value.

Moving from the directly calculated data in the middle, the top level of the hierarchy figure shows that the molecular weight and IV of a sample can be combined to indirectly calculate parameters that offer insight to the molecular structure of the sample.

The size of a sample is typically second only to molecular weight in terms of frequently sought characterization data, and Rh is the size parameter best suited for all sample types.  It should be noted that Rg can be calculated from a light scattering detector with at least two angles and a concentration detector (hence its placement in the middle tier), however the sample needs to be sufficiently large enough to exhibit angular dependence.  Many samples, including proteins, are not large enough to do so and thus Rg cannot be calculated for these samples.  In contrast, Rh can be calculated as long as there is data from a concentration detector, a light scattering detector, and a viscometer detector sufficient to produce molecular weight and IV data.  The Rh represents the radius of the theoretical sphere occupied by a sample with the calculated molecular weight and IV.  Since IV is described in terms of dL/g, or volume divided by mass, it can be combined with the molecular weight mass term to calculate a theoretical volume for the sample.  A spherical model based on (4/3)πr3 is applied to determine r, which ultimately is the Rh of the sample.

The Mark-Houwink (MH) parameters are calculated from the MH plot, which charts the sample’s IV against its molecular weight to provide a visual representation of the relationship between the two.  These MH plots use data acquired by three detectors (concentration, light scattering, and viscometer) and can illustrate changes in molecular structure within a single sample or highlight differences between multiple samples.  A frequent use of these plots is to identify and quantify the extent of branching within a sample’s distribution.

Multi-detector GPC/SEC analysis offers a range of characterization data regarding various aspects of a sample by employing a series of detectors that measure different molecular parameters.  With a full suite of detectors operating in concert, the result is a collection of data that amounts to far more than would be accessible to a single detector system.  Through the direct measurements of the individual detectors certain parameters can be directly calculated.  And from that, the software can further obtain additional indirectly calculated data, culminating in information offering structural insight to the sample.  All of that from a single injection of your sample!

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