Multi-Detector GPC and Rheometry for Characterization of PLA and PLGA

Poly(lactic acid) (PLA), which has received a lot of interest in recent years, is a biodegradable polymer obtained from natural resources (corn starch). It is one among the most common biodegradable polymers in the market place owing to its low cost of production and availability, and when derived from natural sustainable sources, this polymer is truly renewable. Copolymer poly(lactic-co-glycolic acid) (PLGA), which is formed by combining lactic acid with glycolic acid, can have different composition of glycolic and lactic acids. It is a versatile polymer and is used in an extensive range of applications from disposable cutlery to additive manufacture (3D printing), biodegradable packaging, drug delivery, or as biodegradable sutures.

It is well acknowledged that the bulk properties of polymers depend greatly on their molecular properties. It is widely believed that the molecular weight of the polymer is the strongest determinant of its strength. However, it is also possible that copolymer composition will also strongly influence those properties where copolymers such as PLGA are concerned.

This article uses two Malvern technologies to investigate the relationship between the bulk and molecular properties of PLA and PLGA. Multi-detector GPC is used for measuring intrinsic viscosity (which is dependent on copolymer composition) and molecular weight, and rotational rheology is used for studying melt-viscosity. The two results are subsequently compared to examine which molecular properties best correlate with melt-viscosity.


Six samples of commercially available PLGA and PLA were measured including:

  • PLA
  • Three samples of PLGA with 50% LA and 50% GA (PLGA (50:50)) with different molecular weights.
  • PLGA with 65% LA and 35% GA (PLGA (65:35))
  • PLGA with 75% LA and 25% GA (PLGA (75:25))

The samples were dissolved in THF and separated across two Malvern T6000M mixed-bed SVB columns for the multi-detector GPC. A Malvern OMNISEC system including viscometer detectors, low-angle light scattering (LALS)), light scattering (right-angle light scattering (RALS), and refractive index (RI), was used to run GPC.

For the rotational rheology, characterization of the samples was achieved using a Malvern Kinexus Ultra+ rotational rheometer. An active hood peltier plate cartridge with a parallel plate 20 mm geometry was used to measure the samples at 150 °C. As PLA is biodegradable, it is susceptible to degradation and hence measurements were carried out while purging with nitrogen to lower the risk of oxidative degradation during analysis.


Two experiments were conducted. In the first experiment, three PLGA (50:50) samples were determined by rotational rheometry and by multi-detector GPC. Figure 1 shows a representative chromatogram of ‘PLGA (50:50) 2’.

Representative chromatogram of PLGA (50:50) 2, showing RI (red), light scattering (green and black) and viscometer (blue) detector responses.

Figure 1. Representative chromatogram of PLGA (50:50) 2, showing RI (red), light scattering (green and black) and viscometer (blue) detector responses.

Table 1. Measured molecular data for the three PLGA (50:50) samples in the first experiment.

  PLGA (50:50) 1 PLGA (50:50) 2 PLGA (50:50) 3
Measurement Mean % RSD Mean % RSD Mean % RSD
RV (mL) 20.03 0 18.53 0.05088 18.17 0.01297
Mn (g/mol) 7,860 8.801 24.850 0.3569 37,010 5.037
Mw (g/mol) 11,350 1.394 45,650 0.3572 68,980 0.7617
Mw/Mn 1.449 7.411 1.837 3.69E-04 1.866 4.276
IVw (dL/g) 0.1463 0.5835 0.3343 0.1945 0.429 0.7332
Rh(η)w (nm) 2.871 1.432 5.949 0.1864 7.436 0.8545
M-H a 0.6633 8.223 0.5424 14.6 0.5521 0.515
M-H log K (dL/g) -3.507 -6.258 -2.975 -12.36 -3.012 -0.4615
Recovery (%) 106.3 0.2094 103.6 0.5221 102.9 0.04942


The results of the three samples are summarized in Table 1. Samples were measured in duplicate. As can be observed, there were considerable differences in the molecular weights of the three samples, ranging from 11 KDa to 69 KDa. The Kinexus rotational rheometer was subsequently used to study ‘zero-shear’ melt viscosity, which is normally supposed to correlate with the molecular weight of a sample. Figure 2 shows how the viscosity curves trend well with the molecular weight of the three samples. Sample 1 has the lowest viscosity and the lowest molecular weight. Samples 2 and 3 have higher molecular weights and correspondingly higher viscosities. This kind of molecular weight trend is typical and adheres well to expectations.

Viscosity data for the three PLGA (50:50) samples showing sample 1 in red, sample 2 in green and sample 3 in blue.

Figure 2. Viscosity data for the three PLGA (50:50) samples showing sample 1 in red, sample 2 in green and sample 3 in blue.

Following this, a study was performed on PLA and three different copolymers - PLGA (50:50), PLGA (75:25), and PLGA (65:25) – from the previous sample set. Table 2 shows the molecular weight data. The molecular weights for the samples are observed to vary between 11 KDa and 64 KDa.

Table 2. Measured molecular data for the four PLA and PLGA samples compared in the second experiment.

  PLA PLGA (50:50) 2 PLGA (65:35) PLGA (75:25)
Measurement Mean % RSD Mean % RSD Mean % RSD Mean % RSD
RV (ml) 20.01 0.08247 18.53 0.05088 18.66 0.06317 18.12 0
Mn (g/mol) 8,083 15.92 24,850 0.3569 19,240 10.25 40,110 1.745
Mw (g/mol) 10,950 2.807 45,650 0.3572 34,870 1.548 64,460 0.8879
Mw/Mn 1.369 13.14 1.837 3.69E-04 1.821 8.709 1.607 0.8569
IVw (dL/g) 0.1942 1.039 0.3343 0.1945 0.3497 1.279 0.5631 0.2247
Rh(η)w (nm) 3.134 1.886 5.949 0.1864 5.522 1.248 7.996 0.3095
M-H a 0.6553 1.96 0.5424 14.6 0.6835 10.72 0.6577 0.1613
M-H log K (dL/g) -3.344 -1.504 -2.975 -12.36 -3.534 -9.343 -3.39 -0.162
Recovery (%) 93.08 0.6369 103.6 0.5221 100 1.13 89.34 0.2382


With these samples having different compositions, their different structures can be compared on a Mark-Houwink plot. A Mark-Houwink plot depicts intrinsic viscosity as a function of molecular weight, making it possible to compare polymer structures at various molecular weights. It is generally used to examine polymer branching but also denotes differences between linear molecules with different compositions, as in the PLGA and PLA copolymers. The overlaid Mark-Houwink plots for the four samples are shown in Figure 3. Results are shown in duplicate.

Overlaid Mark-Houwink plots for the four PLA and PLGA copolymers.

Figure 3. Overlaid Mark-Houwink plots for the four PLA and PLGA copolymers.

As demonstrated, each polymer has its own line on the Mark-Houwink plot, which represents the molecule’s density, or conformation, in solution. The plot here illustrates that PLA is the most open/extended of the samples. With increase in the glycolic acid content, the polymers become increasingly, densely packed in solution.

Intrinsic viscosity is a measure of a sample’s contribution to solution viscosity and therefore may not correlate exactly with melt viscosity. However, a clear trend in conformation that is dependent on glycolic acid content is shown by the Mark-Houwink plot. Figure 4 shows the rheology results for these four samples.

Complex viscosity vs. Frequency

Figure 4. Rheology measurements for the four samples showing PLA (black), PLGA (75:25) (blue), PLGA (65:35) (green) and PLGA (50:50) 2 (red)

The data shows a clear trend in the melt viscosity measurements but this has no correlation with molecular weight. The PLA sample possesses the lowest viscosity and has the lowest molecular weight. However, the PLGA (75:25) sample with the highest molecular weight has the second lowest viscosity, while the PLGA (50:50) sample which despite having the second highest molecular weight has the highest viscosity.

In this case, the trend seems to be far more dependent on the glycolic acid content, with the sample possessing the highest glycolic acid content exhibiting the highest viscosity, and the sample showing the lowest viscosity (PLA), has the least glycolic acid.

While the melt viscosity will obviously depend on a combination of both of these parameters, the well-defined correlation between viscosity and glycolic acid content apparently dominates the overall relationship.

It is important to note that the sample which has the highest melt viscosity per the rheology data is the one with the lowest intrinsic viscosity in the Mark-Houwink plot. Although this was contrary to expectations, it does hint an explanation. With the molecules in the PLGA (50:50) sample being more compact and densely packed in the polymer, there is less free volume for the polymer chains to rotate and organize themselves. Hence, this increases their resistance to flow and subsequently, their melt viscosity.


The data given in this article effectively demonstrates how the use of complementary polymer characterization technologies can provide excellent insights into the behavior of polymers such as PLGA and PLA. While it is widely acknowledged that the bulk properties (such as melt viscosity) of polymers are strongly related to molecular properties (such as molecular weight), other factors, for instance, copolymer composition can also be important factors.

In this analysis, rotational rheology was used to study melt viscosity while multi-detector GPC was used to characterize the molecular properties of a series of PLA and PLGA samples. For PLGA samples of the same composition, a clear molecular weight correlation was observed but when the composition was also varied, a strong correlation was seen for glycolic acid content. Only a complete characterization of samples of interest can provide these kinds of insights. In doing such measurements, one can completely understand how the molecular properties influence the bulk performance.

By manipulating such parameters, it is possible for researchers and product developers to develop polymers with several ideal properties. For instance, for a drug delivery application, a PLGA copolymer could be chosen which has good melt viscosity for molding as well as the required degradation rates for a well-controlled timed release of the drug. In doing so, products that have higher value, reduced failure rates, and better controlled performance characteristics can be developed.

This information has been sourced, reviewed and adapted from materials provided by Malvern Panalytical.

For more information on this source, please visit Malvern Panalytical.


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