Measuring and predicting model and uranyl species using normal Raman and surface-enhanced Raman scattering

• Main Author: Lu, En Tzu
• Other Authors: Haes, Amanda J.
• Format: Others
• Language: English
• Published: University of Iowa 2017
• Subjects: Chemistry
• Online Access: https://ir.uiowa.edu/etd/5559; https://ir.uiowa.edu/cgi/viewcontent.cgi?article=7039&context=etd

This dissertation seeks to accurately and sensitively detect and estimate changes in molecule orientation of model and uranium species in complex samples. Currently available methods for detecting these molecules lack sensitivity, specificity, and/or require days to weeks to report trace chemical information. To overcome these limitations, normal Raman and surface-enhanced Raman scattering (SERS) are employed to gain molecular speciation. For instance, changes in uranium speciation depends on the pH and the ions present in solution. These ions form coordination complexes with uranyl, which influence the symmetric uranyl stretch that is Raman-active and can be used for the near real-time identification and relative abundance of uranium speciation in environmental samples. To accomplish this task, a strategy to extract uranyl speciation from Raman spectroscopy was developed. Important analysis methods were assessed using speciation modeling and protocols reported that minimize human subjectivity in spectral analysis. To improve detection limits of normal Raman spectroscopy, nanomaterials are employed for SERS. The adsorption of small aromatic molecules to gold coated silver nanoparticles encapsulated by internally etched silica membranes balances limitations of nanoparticle instability and orientation-dependent vibrational modes orientation relative to the plasmon resonance (electric field). Additionally, adsorption is monitored using localized surface plasmon resonance (LSPR) spectroscopy, SERS, and isotherm modeling. These combined approaches indicate that slight variations in molecular functional groups influence the free energies of adsorption of the target molecules. This provides an understanding of molecule-dependent SERS signals for sensitive, selective, and near real-time detection of small molecules in dynamic conditions. These findings support that nanomaterial surface chemistry greatly impacts molecular detection. As a result, gold nanostars functionalized with carboxyl groups are applied for uranyl detection. The distance dependent SERS response for uranyl is revealed by increasing the carbon chain length from 3-11 in the self-assembled monolayer. The shortest alkanethiol facilitated sensitive uranyl detection down to 120 nM. Finally, SERS detection is combined with electrospun amidoximated polyacrylonitrile (AO-PAN) mats to provide robust and reproducible detection of uranyl in complex matrices. AO-PAN mats are employed to initially extract and isolate uranyl while functionalized gold nanostars facilitate direct SERS detection. Characterization of AO-PAN mats uranyl uptake is examined by SEM, FT-IR and Raman spectroscopy. SERS measurements on the AO-PAN mats are obtained from matrices containing calcium and carbonate ions and synthetic urine with minimized matrix effects. Consequently, selective and sensitive detection of uranyl in environmental samples can be achieved thus broadening the scope of SERS for practical use.