Optimization of Thermal Decomposition Synthesis of Iron Oxide Nanoparticles for Magnetic Particle Imaging (MPI) Ambar Velazquez-Albino Authors: Ambar C. Velazquez-Albino, Sitong Liu, Eric Imhoff, Carlos M. Rinaldi-Ramos Faculty Mentor: Carlos Rinaldi-Ramos, PhD College: College of Engineering Department: Chemical Engineering |
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AbstractInterest in magnetic nanoparticles has been on the rise, as a new imaging modality selective to these tracers has emerged. Magnetic particle imaging (MPI) is currently in the preclinical stage but has potential for medical applications such as blood pool imaging, lung perfusion, bleed detection, and tracking immunotherapies and labeled cells as they accumulate in tumors. Modeling of MPI physics suggests that to achieve optimal performance, magnetic nanoparticles should have uniform magnetic properties and low magnetocrystalline anisotropy. The problem is that as the nanoparticles become larger, typically these requirements are harder to meet. The addition of oxygen to the thermal decomposition synthesis of iron oxide nanoparticles achieved yields tracers with 4x better sensitivity than the commercial tracer Ferucarbotran, but the current approach using a semi-batch synthesis has had difficulty achieving particle size greater than 20 nm. Semi-batch thermal decomposition synthesis has many parameters to work with for optimization and due to the slow nature of these syntheses (2 days) and the subsequent characterization techniques (1+ week), studying these takes a long time. To overcome this limitation, we are starting to explore high throughput batch synthesis for iron oxide nanoparticles, with the goal of accelerating exploration of the effect of synthesis parameters on MPI performance.
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