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Solving the Problem of Lignin Characterization - Malvern Presents Proven Strategies for Successful GPC/SEC Analysis

publication date: Jun 2, 2015
author/source: Malvern Instruments Ltd

 Malvern Instruments

Chromatography specialists from Malvern Instruments will present a reliable optimized solution for lignin characterization at a series of upcoming conferences in 2015, the first of which is Nordic Polymer Days, Denmark, June 1 – 3.

Lignin is a vital industrial polymer but presents significant challenges when it comes to measurement of the properties that define its performance. Through experimental study Malvern has identified the best strategy to apply when using gel permeation/size exclusion chromatography (GPC/SEC) to secure reliable information. The results of this work will also be presented at the 13th Annual UNESCO/IUPAC Conference on Macromolecules and Materials, South Africa, September 8 – 10; and the 18th International Symposium on Wood, Fiber and Pulping Chemistry, Austria, September 9 – 11.

Lignin is a natural polymer, derived from wood and other vascular plants, that finds application as, for example, a biofuel, a dispersant in high performance cement, and oilfield additive. GPC/SEC is used to measure the molecular weight (MW), MW distribution, viscosity and structural properties that control its performance. However, lignin has an unusual molecular structure in solution which compromises data accuracy when conventional, single detector, calibration-based GPC/SEC is applied.

Malvern’s solution exploits the capabilities of multi-detector GPC/SEC. This involves the use of a light scattering detector to directly measure MW without any requirement for calibration. Here though, the tendency for lignin to fluoresce in solution, thereby distorting light scattering data, can be problematic. The data from Malvern shows how careful choice of experimental conditions and methods can overcome challenges in the measurement of lignins and provide reliable results. A comparison of lignins from different sources, using a Mark-Houwink plot generated from the resulting data, highlights the robustness of the method in obtaining valuable insight into the structure of these polymers.

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