Structural Characterization of Functional Polymers via Light Scattering and Differential Viscometry

July 21, 2020

Sponsored Content

Characterize functional polymers with advanced multi-detector analytical techniques. Live: Tuesday, Jul. 21, 2020 at 11am EDT | 8am PDT | 4pm BST | 5pm CEST On demand available after airing until Jul. 21, 2021 Register free

Register free: http://www.chromatographyonline.com/lcgc_w/structural_characterization

Event Overview:
Understanding the structure-function relationship of polymers is of critical importance for successful incorporation into commercial applications. In this webcast, we will explore polymer characterization by multi-angle light scattering (MALS) and differential viscometry, coupled with size-exclusion chromatography or field-flow fractionation, for enhanced studies of polymer structure-function. 

Case studies will illustrate the use of these analytical tools to unlock detailed information about molar mass distributions, size, structural conformation, and composition of a variety of functional polymers. Examples include nonwoven polymer fibers, formulation polymers, polymers for microneedles and polymers for other practical applications, all of which are often challenging to characterize fully by other methods.  

Key Learning Objectives:

  • Separation principles of size exclusion chromatography (SEC) and asymmetric flow field flow fractionation (AF4)

  • Theoretical background of multi-angle light scattering (MALS) detector and intrinsic viscosity (IV)

  • Determination of molar mass distributions, structural conformation, branching content, and other structural information in functional polymers using SEC-MALS-IV and FFF-MALS

Speaker: Nemal Gobalasingham, PhD, Global Training Manager and Application Scientist, Wyatt Technology

Time and Date: Tuesday, Jul. 21, 2020 at 11am EDT | 8am PDT | 4pm BST | 5pm CEST

On demand available after airing until Jul. 21, 2021

Sponsor: Wyatt Technology

Register free: http://www.chromatographyonline.com/lcgc_w/structural_characterization