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Optimization for size separation of graphene oxide sheets by flow/hyperlayer field-flow fractionation
- Source :
- Journal of chromatography. A. 1681
- Publication Year :
- 2022
-
Abstract
- Graphene oxide (GO)-a chemical derivative of graphene with numerous oxygen functional groups on its surface-has attracted considerable interest because of its intriguing properties in relation to those of pristine graphene. In addition to the inherent wide lateral size distribution of GO sheets arising from the typical oxidative exfoliation of graphite, control of the lateral size of GO is critical for desired GO-based applications. Herein, flow/hyperlayer field-flow fractionation (flow/hyperlayer FFF) is optimized to separate GO sheets by lateral dimensions. Optimized fractionation is achieved by investigating the influences of carrier solvent, channel thickness, and flow rate conditions on the steric/hyperlayer separation of GO sheets by flow FFF. Due to the strong hydrodynamic lift forces of extremely thin GO sheets, a thick flow FFF channel (w = 350 μm) and a very low field strength are required to retain the GO sheets within the channel. GO sheets with narrow size fractions are successfully collected from two different graphite sources during flow/hyperlayer FFF runs and are examined to verify the size evolution. Considering the average lateral diameter of the GO fraction calculated on the basis of the assumption of a circular disk shape, the retention of the GO sheets is 2.2-5.0 times faster than that of spherical particles of the same diameter. This study demonstrates that through flow/hyperlayer FFF, the size distribution of GO sheets can be determined and narrow size fractions can be collected (which is desirable for GO-based applications), which are commonly influenced by the GO lateral dimension.
- Subjects :
- Organic Chemistry
General Medicine
Biochemistry
Analytical Chemistry
Subjects
Details
- ISSN :
- 18733778
- Volume :
- 1681
- Database :
- OpenAIRE
- Journal :
- Journal of chromatography. A
- Accession number :
- edsair.doi.dedup.....d0cfa9bf4e717da156a4e528acc499ea