Size fractionation of magnetic nanoparticles by using continuous flow low gradient magnetic separation technique
Colloidal instability has prevented widespread usage of magnetic nanoparticles (MNPs) in a variety of engineering applications. The colloidal stability of MNPs can be enhanced by surface modification or functionalization with polyelectrolytes, however it is still difficult to determine the ideal fun...
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| Format: | Final Year Project / Dissertation / Thesis |
| Published: |
2023
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| Online Access: | http://eprints.utar.edu.my/5618/1/fyp_PE_2023_CWJ.pdf http://eprints.utar.edu.my/5618/ |
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| Summary: | Colloidal instability has prevented widespread usage of magnetic nanoparticles (MNPs) in a variety of engineering applications. The colloidal stability of MNPs can be enhanced by surface modification or functionalization with polyelectrolytes, however it is still difficult to determine the ideal functionalization conditions for generating the most stable MNP systems. This research overcomes this obstacle by examining the average particle size and particle size distribution of MNP systems produced by altering the mass ratio of polyelectrolyte (PSS) to MNPs during surface functionalization. According to the results, the lowest average hydrodynamic size and narrowest particle size distribution were achieved in an MNP system where the mass ratio of MNPs to polyelectrolyte (PSS) was 1:1. Also, the study presented the Continuous-Flow Low-Gradient Magnetic Separation (CF-LGMS) method of making MNPs with enhanced monodispersity. This investigation conducted an experimental investigation into how flowrate and magnet configurations affect the monodispersity of CF-LGMS-fractionated systems of magnetic nanoparticles. The results demonstrated that the size fractionation of MNPs via the CF-LGMS process was greatly enhanced by a slower flowrate (5 ml/min) and a higher quantity of magnets (dual pair magnet arrangement), resulting in a monodispersed MNP system. Eventually, the study used COMSOL Multiphysics to create a mathematical model of the CF-LGMS fractionation process. The model's ability to predict and optimise the performance of the CF-LGMS process was demonstrated by the high degree of agreement between the simulated and experimental findings. Many engineering applications, including as MRI, drug administration, and magnetic hyperthermia, rely ix on MNPs with high colloidal stability and monodispersity, and this work contributes to that knowledge |
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