High Throughput Measurements of Polymer Fluids for Formulations

Published

January 1, 2004

Author(s)

Kathryn Beers, J Cabral, H J. Walls, Eric J. Amis

Abstract

Rapid prototyping of microfluidic handling devices has gained popularity due to the ability to quickly test and modify new design features several times in one day. At the NIST Combinatorial Methods Center (NCMC), we have modified common microfluidic fabrication techniques to extend their use to organic fluids. UV curable adhesives were used to create molded resins with increased solvent resistance. This has allowed the preparation of new types of combinatorial libraries and development of new measurement methods to complement the small sample sizes of these libraries. Most importantly, it can be used to tie together multiple stages of the formulation process, from the synthesis of polymers to the measurement of complex-fluid properties, in small and inexpensive platforms.Our first demonstrations of this technology are in the areas of emulsions and polymer blends. Measurement techniques include light and x-ray scattering and rheology. Milli-fluidic handling and measurements will increase the dimensions of parameter space that are available to accurate and systematic study of polymer solutions. These capabilities will also enable the generation of new information in the field of polymer formulations, which is presently dominated by empirical knowledge.

Proceedings Title

Combinatorial and Artificial Intelligence Methods in Materials Science, Symposium| |Combinatorial and Artificial Intelligence Methods in Materials Science|Materials Research Society

Volume

804

Conference Dates

December 1, 2003

Conference Location

Undefined

Conference Title

Materials Research Society Symposium Proceedings

Pub Type

Conferences

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Keywords

high-throughput, microfluidics, polymer formulations, prototyping, rheology

Citation

Beers, K. , Cabral, J. , Walls, H. and Amis, E. (2004), High Throughput Measurements of Polymer Fluids for Formulations, Combinatorial and Artificial Intelligence Methods in Materials Science, Symposium| |Combinatorial and Artificial Intelligence Methods in Materials Science|Materials Research Society, Undefined, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=852285 (Accessed December 26, 2024)