Xu, Zhuocheng, Tonry, Catherine E. H. ORCID: https://orcid.org/0000-0002-8214-0845, Beckwith, Christopher, Kao, Andrew ORCID: https://orcid.org/0000-0002-6430-2134, Wong, Hayley, Shaffer, Milo S. P., Pericleous, Koulis A ORCID: https://orcid.org/0000-0002-7426-9999 and Li, Qianqian (2022) High-speed imaging of the ultrasonic deagglomeration of carbon nanotubes in water. JOM (The Member Journal of The Minerals, Metals & Materials Society), 74 (6). pp. 2470-2483. ISSN 1047-4838 (Print), 1543-1851 (Online) (doi:10.1007/s11837-022-05274-4)

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Abstract

Ultrasonic treatment is effective in deagglomerating and dispersing nanoparticles in various liquids. However, the exact deagglomeration mechanisms vary for different nanoparticle clusters, owing to different particle geometries and inter-particle adhesion forces. Here, the deagglomeration mechanisms and the influence of sonotrode amplitude during ultrasonication of multiwall carbon nanotubes in de-ionized water were studied by a combination of high-speed imaging and numerical modeling. Particle image velocimetry was applied to images with a higher field of view to calculate the average streaming speeds distribution. These data allowed direct comparison with modeling results. For images captured at higher frame rates and magnification, different patterns of deagglomeration were identified and categorized based on different stages of cavitation zone development and for regions inside or outside the cavitation zone. The results obtained and discussed in this paper can also be relevant to a wide range of carbonaceous and other high aspect ratio nanomaterials.

Item Type:	Article
Uncontrolled Keywords:	ultrasonic treatment; cavitation; carbon nanotubes; metal matrix composites
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QC Physics T Technology > TC Hydraulic engineering. Ocean engineering
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science Faculty of Engineering & Science > Centre for Numerical Modelling & Process Analysis (CNMPA) Faculty of Engineering & Science > Centre for Numerical Modelling & Process Analysis (CNMPA) > Computational Science & Engineering Group (CSEG) Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS)
Last Modified:	06 Jun 2022 15:15
URI:	http://gala.gre.ac.uk/id/eprint/35892

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