Development of Plasmonic Nanoplatforms for Diagnostics, Therapy, and Sensing

Recent advances in nanotechnology have led to the application of nanoparticles in a wide variety of fields. In the field of nanomedicine, there is great emphasis on combining diagnostic and therapeutic modalities into a single nanoparticle construct (theranostics). In particular, anisotropic nanoparticles have shown great potential for surface-enhanced Raman scattering (SERS) detection due to their unique optical properties. Gold nanostars are a type of anisotropic nanoparticle with one of the highest SERS enhancement factors in a non-aggregated state. By utilizing the distinct characteristics of gold nanostars, new plasmonic materials for diagnostics, therapy, and sensing can be synthesized. The work described herein is divided into two main themes. The first half presents a novel, theranostic nanoplatform that can be used for both SERS detection and photodynamic therapy (PDT). The second half involves the rational design of silver-coated gold nanostars for increasing SERS signal intensity and improving reproducibility and quantification in SERS measurements.

The theranostic nanoplatforms consist of Raman-labeled gold nanostars coated with a silica shell. Photosensitizer molecules for PDT can be loaded into the silica matrix, while retaining the SERS signal of the gold nanostar core. SERS detection and PDT are performed at different wavelengths, so there is no interference between the diagnostic and therapeutic modalities. Singlet oxygen generation (a measure of PDT effectiveness) was demonstrated from the drug-loaded nanocomposites. In vitro testing with breast cancer cells showed that the nanoplatform could be successfully used for PDT. When further conjugating the nanoplatform with a cell-penetrating peptide (CPP), efficacy of both SERS detection and PDT is enhanced.

The rational design of plasmonic nanoparticles for SERS sensing involved the synthesis of silver-coated gold nanostars. Investigation of the silver coating process revealed that preservation of the gold nanostar tips was necessary to achieve the increased SERS intensity. At the optimal amount of silver coating, the SERS intensity is increased by over an order of magnitude. It was determined that a majority of the increased SERS signal can be attributed to reducing the inner filter effect, as the silver coating process moves the extinction of the particles far away from the laser excitation line. To improve reproducibility and quantitative SERS detection, an internal standard was incorporated into the particles. By embedding a small-molecule dye between the gold and silver surfaces, SERS signal was obtained both from the internal dye and external analyte on the particle surface. By normalizing the external analyte signal to the internal reference signal, reproducibility and quantitative analysis are improved in a variety of experimental conditions.

Effects of Natural Organic Matter on the Dissolution Kinetics and Bioavailability of Metal Oxide Nanoparticles

The rapid development of nanotechnology and wider applications of engineered nanomaterials (ENMs) in the last few decades have generated concerns regarding their environmental and health risks. After release into the environment, ENMs undergo aggregation, transformation, and, for metal-based nanomaterials, dissolution processes, which together determine their fate, bioavailability and toxicity to living organisms in the ecosystems. The rates of these processes are dependent on nanomaterial characteristics as well as complex environmental factors, including natural organic matter (NOM). As a ubiquitous component of aquatic systems, NOM plays a key role in the aggregation, dissolution and transformation of metal-based nanomaterials and colloids in aquatic environments.

The goal of this dissertation work is to investigate how NOM fractions with different chemical and molecular properties affect the dissolution kinetics of metal oxide ENMs, such as zinc oxide (ZnO) and copper oxide (CuO) nanoparticles (NPs), and consequently their bioavailability to aquatic vertebrate, with Gulf killifish (Fundulus grandis) embryos as model organisms.

ZnO NPs are known to dissolve at relatively fast rates, and the rate of dissolution is influenced by water chemistry, including the presence of Zn-chelating ligands. A challenge, however, remains in quantifying the dissolution of ZnO NPs, particularly for time scales that are short enough to determine rates. This dissertation assessed the application of anodic stripping voltammetry (ASV) with a hanging mercury drop electrode to directly measure the concentration of dissolved Zn in ZnO NP suspensions, without separation of the ZnO NPs from the aqueous phase. Dissolved zinc concentration measured by ASV ([Zn]ASV) was compared with that measured by inductively coupled plasma mass spectrometry (ICP-MS) after ultracentrifugation ([Zn]ICP-MS), for four types of ZnO NPs with different coatings and primary particle diameters. For small ZnO NPs (4-5 nm), [Zn]ASV was 20% higher than [Zn]ICP-MS, suggesting that these small NPs contributed to the voltammetric measurement. For larger ZnO NPs (approximately 20 nm), [Zn]ASV was (79±19)% of [Zn]ICP-MS, despite the high concentrations of ZnO NPs in suspension, suggesting that ASV can be used to accurately measure the dissolution kinetics of ZnO NPs of this primary particle size.

Using the ASV technique to directly measure dissolved zinc concentration, we examined the effects of 16 different NOM isolates on the dissolution kinetics of ZnO NPs in buffered potassium chloride solution. The observed dissolution rate constants (kobs) and dissolved zinc concentrations at equilibrium increased linearly with NOM concentration (from 0 to 40 mg-C L-1) for Suwannee River humic acid (SRHA), Suwannee River fulvic acid and Pony Lake fulvic acid. When dissolution rates were compared for the 16 NOM isolates, kobs was positively correlated with certain properties of NOM, including specific ultraviolet absorbance (SUVA), aromatic and carbonyl carbon contents, and molecular weight. Dissolution rate constants were negatively correlated to hydrogen/carbon ratio and aliphatic carbon content. The observed correlations indicate that aromatic carbon content is a key factor in determining the rate of NOM-promoted dissolution of ZnO NPs. NOM isolates with higher SUVA were also more effective at enhancing the colloidal stability of the NPs; however, the NOM-promoted dissolution was likely due to enhanced interactions between surface metal ions and NOM rather than smaller aggregate size.

Based on the above results, we designed experiments to quantitatively link the dissolution kinetics and bioavailability of CuO NPs to Gulf killifish embryos under the influence of NOM. The CuO NPs dissolved to varying degrees and at different rates in diluted 5‰ artificial seawater buffered to different pH (6.3-7.5), with or without selected NOM isolates at various concentrations (0.1-10 mg-C L-1). NOM isolates with higher SUVA and aromatic carbon content (such as SRHA) were more effective at promoting the dissolution of CuO NPs, as with ZnO NPs, especially at higher NOM concentrations. On the other hand, the presence of NOM decreased the bioavailability of dissolved Cu ions, with the uptake rate constant negatively correlated to dissolved organic carbon concentration ([DOC]) multiplied by SUVA, a combined parameter indicative of aromatic carbon concentration in the media. When the embryos were exposed to CuO NP suspension, changes in their Cu content were due to the uptake of both dissolved Cu ions and nanoparticulate CuO. The uptake rate constant of nanoparticulate CuO was also negatively correlated to [DOC]×SUVA, in a fashion roughly proportional to changes in dissolved Cu uptake rate constant. Thus, the ratio of uptake rate constants from dissolved Cu and nanoparticulate CuO (ranging from 12 to 22, on average 17±4) were insensitive to NOM type or concentration. Instead, the relative contributions of these two Cu forms were largely determined by the percentage of CuO NP that was dissolved.

Overall, this dissertation elucidated the important role that dissolved NOM plays in affecting the environmental fate and bioavailability of soluble metal-based nanomaterials. This dissertation work identified aromatic carbon content and its indicator SUVA as key NOM properties that influence the dissolution, aggregation and biouptake kinetics of metal oxide NPs and highlighted dissolution rate as a useful functional assay for assessing the relative contributions of dissolved and nanoparticulate forms to metal bioavailability. Findings of this dissertation work will be helpful for predicting the environmental risks of engineered nanomaterials.

Bridging the Scale Gap from Leaf to Canopy in Biosphere-Atmosphere Gas and Particle Exchanges

Terrestrial ecosystems, occupying more than 25% of the Earth's surface, can serve as

`biological valves' in regulating the anthropogenic emissions of atmospheric aerosol

particles and greenhouse gases (GHGs) as responses to their surrounding environments.

While the signicance of quantifying the exchange rates of GHGs and atmospheric

aerosol particles between the terrestrial biosphere and the atmosphere is

hardly questioned in many scientic elds, the progress in improving model predictability,

data interpretation or the combination of the two remains impeded by

the lack of precise framework elucidating their dynamic transport processes over a

wide range of spatiotemporal scales. The diculty in developing prognostic modeling

tools to quantify the source or sink strength of these atmospheric substances

can be further magnied by the fact that the climate system is also sensitive to the

feedback from terrestrial ecosystems forming the so-called `feedback cycle'. Hence,

the emergent need is to reduce uncertainties when assessing this complex and dynamic

feedback cycle that is necessary to support the decisions of mitigation and

adaptation policies associated with human activities (e.g., anthropogenic emission

controls and land use managements) under current and future climate regimes.

With the goal to improve the predictions for the biosphere-atmosphere exchange

of biologically active gases and atmospheric aerosol particles, the main focus of this

dissertation is on revising and up-scaling the biotic and abiotic transport processes

from leaf to canopy scales. The validity of previous modeling studies in determining

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the exchange rate of gases and particles is evaluated with detailed descriptions of their

limitations. Mechanistic-based modeling approaches along with empirical studies

across dierent scales are employed to rene the mathematical descriptions of surface

conductance responsible for gas and particle exchanges as commonly adopted by all

operational models. Specically, how variation in horizontal leaf area density within

the vegetated medium, leaf size and leaf microroughness impact the aerodynamic attributes

and thereby the ultrane particle collection eciency at the leaf/branch scale

is explored using wind tunnel experiments with interpretations by a porous media

model and a scaling analysis. A multi-layered and size-resolved second-order closure

model combined with particle

uxes and concentration measurements within and

above a forest is used to explore the particle transport processes within the canopy

sub-layer and the partitioning of particle deposition onto canopy medium and forest

oor. For gases, a modeling framework accounting for the leaf-level boundary layer

eects on the stomatal pathway for gas exchange is proposed and combined with sap

ux measurements in a wind tunnel to assess how leaf-level transpiration varies with

increasing wind speed. How exogenous environmental conditions and endogenous

soil-root-stem-leaf hydraulic and eco-physiological properties impact the above- and

below-ground water dynamics in the soil-plant system and shape plant responses

to droughts is assessed by a porous media model that accommodates the transient

water

ow within the plant vascular system and is coupled with the aforementioned

leaf-level gas exchange model and soil-root interaction model. It should be noted

that tackling all aspects of potential issues causing uncertainties in forecasting the

feedback cycle between terrestrial ecosystem and the climate is unrealistic in a single

dissertation but further research questions and opportunities based on the foundation

derived from this dissertation are also brie

y discussed.

A New Method for Modeling Free Surface Flows and Fluid-structure Interaction with Ocean Applications

The computational modeling of ocean waves and ocean-faring devices poses numerous challenges. Among these are the need to stably and accurately represent both the fluid-fluid interface between water and air as well as the fluid-structure interfaces arising between solid devices and one or more fluids. As techniques are developed to stably and accurately balance the interactions between fluid and structural solvers at these boundaries, a similarly pressing challenge is the development of algorithms that are massively scalable and capable of performing large-scale three-dimensional simulations on reasonable time scales. This dissertation introduces two separate methods for approaching this problem, with the first focusing on the development of sophisticated fluid-fluid interface representations and the second focusing primarily on scalability and extensibility to higher-order methods.

We begin by introducing the narrow-band gradient-augmented level set method (GALSM) for incompressible multiphase Navier-Stokes flow. This is the first use of the high-order GALSM for a fluid flow application, and its reliability and accuracy in modeling ocean environments is tested extensively. The method demonstrates numerous advantages over the traditional level set method, among these a heightened conservation of fluid volume and the representation of subgrid structures.

Next, we present a finite-volume algorithm for solving the incompressible Euler equations in two and three dimensions in the presence of a flow-driven free surface and a dynamic rigid body. In this development, the chief concerns are efficiency, scalability, and extensibility (to higher-order and truly conservative methods). These priorities informed a number of important choices: The air phase is substituted by a pressure boundary condition in order to greatly reduce the size of the computational domain, a cut-cell finite-volume approach is chosen in order to minimize fluid volume loss and open the door to higher-order methods, and adaptive mesh refinement (AMR) is employed to focus computational effort and make large-scale 3D simulations possible. This algorithm is shown to produce robust and accurate results that are well-suited for the study of ocean waves and the development of wave energy conversion (WEC) devices.