Researchers Develop Microfluidics-assisted Technique to Manufacture Macroscopic Graphene Fibers

Researchers Develop Microfluidics-assisted Technique to Manufacture Macroscopic Graphene Fibers

Researchers developed a microfluidics-assisted technique to manufacture macroscopic graphene fibers, according to a report published on January 15, 2019.

This technique was developed by researchers at Rensselaer Polytechnic Institute. Graphene fiber finds application in diverse technological areas, ranging from energy storage, electronics and optics, electro-magnetics, thermal conductor and thermal management, to structural applications.

Optimizing both the thermal/electrical and the mechanical properties of graphene fibers has been difficult. However, the research team has demonstrated their ability to do both. Manufacturing of macroscopic graphene fibers is possible by fluidics-enabled assembly from 2-D graphene oxide sheets that are dispersed in aqueous solutions forming lyotropic liquid crystal. Strong shape and size confinements are demonstrated for fine control of the graphene sheet alignment and orientation, critical for realizing graphene fibers with high thermal, electrical, and mechanical properties. Moreover, the microstructures of graphene fibers can be tailored using this method by controlling flow patterns.

Jie Lian, lead author of the article said, “The control of different flow patterns offers a unique opportunity and flexibility in tailoring macroscopic graphene structures from perfectly aligned graphene fibers and tubes to 3-D open architecture with vertically aligned graphene sheet arrangement.” This work is a collaboration with fellow MANE researchers, including Associate Professor Lucy Zhang and Professor Suvranu De, who heads the department.

According to the researchers, this study will be useful to optimize the fiber assembly and microstructure to develop high-performance graphene fibers. Furthermore, the same approach could be extended to other materials to manufacture hierarchical structures for diverse functional applications.

Emily Sanders

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