Characterisation of block copolymer self-assemblies by thermal field-flow fractionation
| Autor: | Harald Pasch, Guilaume Greyling |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
chemistry.chemical_classification
Field flow fractionation Molar mass Materials science Polymers and Plastics Organic Chemistry Analytical chemistry Nanotechnology 02 engineering and technology Fractionation Polymer 010402 general chemistry 021001 nanoscience & nanotechnology 01 natural sciences Micelle 0104 chemical sciences chemistry Thermal Materials Chemistry Copolymer Self-assembly 0210 nano-technology |
| Zdroj: | Polymer International. 66:745-751 |
| ISSN: | 0959-8103 |
| DOI: | 10.1002/pi.5350 |
| Popis: | The ability of block copolymers to self-assemble into various nanostructures (such as micelles) has attracted significant attention over the years as these block copolymers provide a versatile platform that can readily be modified for a wide range of applications. As such, the solution behaviour of block copolymers has been at the forefront of the modern nanotechnology revolution. However, these novel block copolymer-based self-assemblies lack suitable characterisation techniques to determine size, molar mass and compositional distributions simultaneously. This mini-review gives a short background on the current techniques used to determine important micelle properties as well as their limitations for characterising complex samples. Current column-based fractionation techniques used for determining property distributions are addressed. As a result of the limitations of column-based fractionations, a multidetector thermal field-flow fractionation (ThFFF) approach is put forward as a powerful alternative to determine not only size and molar mass distributions, but also other micelle properties as a function of temperature. More importantly, ThFFF is highlighted as the only current characterisation platform capable to address the analytical challenges associated with compositional distributions of polymer self-assemblies. |
| Databáze: | OpenAIRE |
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