Abstract
[Truncated abstract] Magnetic nanoparticles have several important biomedical applications including targeted drug delivery, hyperthermia treatment and MRI contrast enhancement. A magnetic nanoparticle suspension exposed to a uniformmagnetic field can result in linear agglomeration through a process known as chain formation. Importantly, the effects of magnetic nanoparticle chain formation on biomedical applications are not well understood and could be favourable or unfavourable depending on the specific application.
It has been observed in recent literature that chain formation can reduce the proton transverse relaxation rates of magnetic nanoparticle suspensions, affecting their performance as MRI contrast agents over time. The time dependent behaviour of relaxation rates presents challenges for interpreting data for applications such as quantitative MRI. Understanding the physics behind chain formation and its effects on proton transverse relaxation rates is an important area of study that could lead to the development of enhanced magnetic nanoparticle systems for biomedical applications.
A major aim of the research was to study the effects of magnetic nanoparticle parameters such as concentration and size on the rate and extent of chain formation. This was achieved through the application of a coarse-grain chaining simulation model across an array of magnetic nanoparticle suspension parameters. The simulation results led to the development of an analytical model that predicts the dynamic exponent of a system from its volume fraction and magnetic coupling parameter.
It has been observed in recent literature that chain formation can reduce the proton transverse relaxation rates of magnetic nanoparticle suspensions, affecting their performance as MRI contrast agents over time. The time dependent behaviour of relaxation rates presents challenges for interpreting data for applications such as quantitative MRI. Understanding the physics behind chain formation and its effects on proton transverse relaxation rates is an important area of study that could lead to the development of enhanced magnetic nanoparticle systems for biomedical applications.
A major aim of the research was to study the effects of magnetic nanoparticle parameters such as concentration and size on the rate and extent of chain formation. This was achieved through the application of a coarse-grain chaining simulation model across an array of magnetic nanoparticle suspension parameters. The simulation results led to the development of an analytical model that predicts the dynamic exponent of a system from its volume fraction and magnetic coupling parameter.
Original language | English |
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Qualification | Doctor of Philosophy |
Publication status | Unpublished - 2014 |