Browsing by Author "Neal, Christopher A."

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    Analysis of iron(iii) doped silica nanorods synthesized with various iron reagents and TEOS ratios
    (2020-12) Quan, Michelle C.; Neal, Christopher A.; Calabrese, Michelle A.
    Silica nanorods integrated into materials, such as polymer matrices, may result in new or improved material properties. Desirable properties, like mechanical strength or thermal and electrical conductivity, can be enhanced by uniformly aligning nanorods. Magnetic fields are a promising and non-destructive way to orient nanorods embedded in a system, but silica itself has low magnetic susceptibility. This work investigates multiple reagents to synthesize iron-doped silica nanorods to increase the magnetic rearrangement of otherwise diamagnetic silica nanorods. A variety of nanorods are synthesized using different ratios of tetraethyl orthosilicate (TEOS) and iron-containing reagents. These nanorods are analyzed with scanning electron microscopy (SEM) and x-ray diffractometry (XRD). When compared to a control spectra of magnetite nanoparticles, some of the nanorods exhibit peaks characteristic of magnetite. However, SEM images indicate an amalgamation of rod shapes and irregular clumps. Samples synthesized with iron(iii) ethoxide and lower TEOS ratios demonstrate the most promise of compositional homogeneity and iron incorporation. Future work should harness analysis techniques that can provide compositional data of specific regions, such as backscattered electron imaging (BEI) or energy dispersive x-ray spectroscopy (EDX/EDS).
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    Automated quantitative analysis of silica nanorod dimensions via watershed segmentation
    (2020) Quan, Michelle C.; Neal, Christopher A.; Calabrese, Michelle A.
    Quantifying the dimensions of silica nanorods often requires manual analysis of their dimensions, but this method is time- consuming and tedious. This work explores the potential for an automated analysis with Matlab to improve the efficiency of this analysis. The program described is a preliminary proof-of-concept version of a nanorod analysis program. Watershed segmentation and minimum-area bounding boxes are viable tools for the automated quantitative analysis of nanorod dimensions, and the automated process saves nearly one minute per particle compared to manual analysis. While the automated process shows promise, the program functions best with minimal nanorod overlap and requires more extensive testing to become feasible for widespread use. Improvements to noise reduction and particle shape prediction will expand the scope of images that can be subject to automatic analysis.