Acoustic cavitation characterisation in viscous deep eutectic solvents for optimisation of sonoprocessing of technology critical materials

Jacobson, Ben (2023) Acoustic cavitation characterisation in viscous deep eutectic solvents for optimisation of sonoprocessing of technology critical materials. PhD thesis, University of Glasgow.

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The UK alone produced a total of 1.6 Mt of electronic waste in 2019, containing approximately 380,000 kg of technology critical metals worth $148 M per annum. Within this, printed circuit boards (PCBs) are the largest source of metals from electronic waste, containing up to 30-40 wt.% of technology critical metals. Traditional recycling techniques lack selectivity and have significant environmental and health impact. Ionometallurgy is a promising new technique for recovering metals from electronic waste using deep eutectic solvents (DESs). These solvents offer distinct advantage over traditional techniques, including much lower temperature requirements, avoidance of toxic reagents and reduced water consumption. DESs are cheap, readily available and can be adapted for selectivity. Despite these advantages, DESs are limited by slow dissolution kinetics primarily due to slow mass transport associated with their high viscosities. Power ultrasonics presents a useful solution to these issues. Sonication in DES is hypothesised to increase mass transport, remove passivating surface layers and promote cavitation-mediated effects. However, study into the cavitation activity in solutions other than water are limited. For efficient processing, cavitation generated at the tip of a sonotrode as a function of input power is required.

This work is the first comprehensive investigation of cavitation in DESs, for process optimisation to enhance precious metal recycling. Detailed characterisation of the cavitation generated by two sonotrodes in a number of DESs of varying viscosity and water is performed. High-speed imaging (HSI) and acoustic detection from a novel in-house constructed cavitation detector, characterised and validated against a commercially available cavitation sensor (NPL CaviSensorTM), identifies potentially optimal sonication parameters in each liquid. Detailed characterisation of each DES combining synchronised acoustic detection and HSI reveals generation of specific cavitation dynamics and associated cavitation structure, often characterised by a densely packed bulbous cavitation cloud, generating multi-fronted shockwaves. The sonotrode is deployed in DES for the delamination of technology critical metals from waste PCBs. Sonication was observed to delaminate the metals from the PCB at a rate over thirty times faster than in silent conditions. Furthermore, an optimally identified lower power sonication was shown to delaminate a greater quantity of metals from the PCB compared to a higher power sonication, over the same duration. The sonotrode is also deployed to investigate delamination of alternative technology critical resources; lithium-ion batteries and photovoltaics, as well as for rate enhancement of electrodissolution of copper. Further collaborative studies investigate single-bubble dynamics for validation of modelling in the audible frequency range, with interesting potential applications.

The results of the studies in this thesis demonstrate the utility and validity of proper cavitation characterisation in solutions intended for sonoprocessing. This characterisation can be performed simply, using bespoke, cheap passive cavitation detectors to gather acoustic measurements at sufficiently fine incremental input powers. Identification of optimal powers of any ultrasonic system for maximum cavitation efficiency is of relevance to many potential processes. In particular, the need for green technologies for electronic waste recycling, could present an ideal problem that can be tackled by ultrasonically enhanced ionometallurgy.

Item Type: Thesis (PhD)
Qualification Level: Doctoral
Subjects: T Technology > T Technology (General)
Colleges/Schools: College of Science and Engineering > School of Engineering
Supervisor's Name: Prentice, Dr. Paul
Date of Award: 2023
Depositing User: Theses Team
Unique ID: glathesis:2023-84020
Copyright: Copyright of this thesis is held by the author.
Date Deposited: 09 Jan 2024 10:42
Last Modified: 09 Jan 2024 10:43
Thesis DOI: 10.5525/gla.thesis.84020

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