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- W2989433385 abstract "As there are many different graphene production methods which vary in terms of quality, cost, production rate, yield, scalability, post-processing requirements, flake size distribution, and batch-to-batch repeatability, it has been challenging to develop commercial applications that exploit the extraordinary properties of graphene rather than purely using it as a marketing tool. This thesis reports on the study of ultrasonication, which is an established method to exfoliate graphene in the liquid phase, as well as a pre/post-processing technique in other graphene production methods. Due to a poor understanding of inertial cavitation, which is the fundamental mechanism driving graphene exfoliation during ultrasonication, this production method is commonly characterised by low exfoliation rates, reduced yields and limited scalability/controllability. By optimising the inertial cavitation dose, graphene yields of up to 19 ± 4 % can be exfoliated over just 3 hours of sonication at room temperature. Furthermore, inertial cavitation preferentially exfoliates larger flakes during ultrasonication and the size of the graphene flakes is correlated with, and therefore can be controlled by, inertial cavitation dose. Alongside small-scale exfoliation studies, a scalable graphene sonoreactor proof-of-concept (patent pending), has been designed and tested to generate high exfoliation rates and allow for in-situ size distribution control. More generally it is shown cavitation metrology is critical in developing efficient, controllable and repeatable ultrasonication strategies for the liquid phase exfoliation of 2D nanomaterials, and the many applications and industries in which ultrasonication is employed." @default.
- W2989433385 created "2019-11-22" @default.
- W2989433385 creator A5078719568 @default.
- W2989433385 date "2019-09-30" @default.
- W2989433385 modified "2023-09-28" @default.
- W2989433385 title "Optimised acoustic cavitation for the efficient liquid phase exfoliation of graphene." @default.
- W2989433385 doi "https://doi.org/10.15126/thesis.00852387" @default.
- W2989433385 hasPublicationYear "2019" @default.
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