Button to scroll to the top of the page.

Spring 2019 Colloquia: Graduate Portfolio in Applied Statistical Modeling






Lara Heersema

April 10


GDC 1.406

"Optimizing iron oxide nanoparticles for biomedical applications by statistical experimental design"

Lara Heersema

PhD student in Biomedical Engineering, advised by Dr. Claus Wilke

Title: "Optimizing iron oxide nanoparticles for biomedical applications by statistical experimental design"

Abstract: Iron oxide nanoparticles hold great potential for biomedical applications but are limited by a lack of understanding regarding efficient and scalable synthesis of monodisperse iron oxide nanoparticles. The important variables in the two-step high-temperature thermal decomposition of iron (III) oleate were identified and optimized using statistically designed experiments (DOE). Important variables in the thermal decomposition reaction of iron oxide nanoparticles were identified through statistical analysis of previously reported synthesis parameters and nanoparticle sizes. A definitive screening design (DSD) was used to evaluate six important synthesis parameters. The DSD model incorporated multiple factors at 2 or 3 levels with only 2k+1 experiments, where k is the number of factors. This allows for more efficient use of resources and time to build a better understanding of nanoparticle synthesis reactions compared to traditional one-at-a-time or fractional factorial studies. Forward regression was used with data generated according to the DSD to predict model coefficients. Equations were developed to predict nanoparticle hydrodynamic size based on synthesis parameters. These equations were compared with independent validation synthesis reactions. High-temperature thermal decomposition synthesis reaction time was the most influential synthesis parameter in dictating nanoparticle size. Other important parameters were thermal decomposition synthesis temperature, iron oleate generation atmosphere, and interactions between iron oleate generation atmosphere and drying conditions. These results agree well with overall trends for nanoparticle sizes reported in the literature synthesized from iron (III) oleate. The results of this study demonstrate the power of DOEs in identifying important parameters for nanoparticle synthesis in relatively few experiments and how studying these reaction parameters can be used to provide insight into nanoparticle formation