Stacey Marie Louie

Extended Derjaguin–Landau–Verwey–Overbeek (EDLVO) and empirical models are implemented to predict the attachment efficiencies of titanium dioxide nanoparticles with eco-coronas of varied composition and degree of saturation in moderately hard water.

The aggregation behavior of ferrihydrite nanoparticles (FNPs) can control the fate of associated aqueous contaminants, trace elements, and organic compounds. However, FNP aggregation is difficult to predict in the presence of organic matter (OM), given the heterogeneity in the OM properties. Five model OMs based on (poly)acrylic acid (PAA or AA) and polyethylene glycol with or without terminal carboxyl groups (PEG or PEGbis, respectively) were chosen to probe the influence of key OM properties─specifically, carboxyl richness and molecular weight (MW)─and the dominant mechanisms by which they influence OM adsorption onto FNPs and the resulting aggregation. For OMs with similar MWs, those with a higher carboxyl richness adsorbed more extensively onto FNPs: PAA_2k > PEGbis > PEG. Meanwhile, for OMs with the same carboxyl richness, higher MW OMs adsorbed more: PAA_25k > PAA_2k > AA. Furthermore, the subsequent aggregation of FNPs was largely controlled by the adsorbed mass. OMs with negligible adsorption (i.e., PEG and AA) did not change the aggregation behavior of FNPs. For OMs with low carboxyl richness (PEGbis), accelerated aggregation occurred through a bridging effect with low adsorbed mass. For OMs with high carboxyl richness (PAA_2k and PAA_25k), aggregation was accelerated at moderate adsorbed OM masses by patch-charge attraction and was inhibited with high adsorbed OM mass due to steric repulsion. This study provided new insights into understanding and predicting the transport and fate of FNPs and natural organic matter (NOM) in natural environments with various NOM compositions.

Enrofloxacin release from PLGA nanocarriers was evaluated in simulated saliva and gastric fluid. AF4 and DFT analyses revealed that acidic solvent intrusion above T_g induced faster diffusive release, whereas media proteins had no significant effect.

There has been limited research into arsenolipid toxicological risks and health-related outcomes due to challenges with their separation, identification, and quantification within complex biological matrices (e.g., fish, seaweed). Analytical approaches for arsenolipid identification such as suspect screening have not been well documented and there are no certified standard reference materials, leading to issues with reproducibility and uncertainty regarding the accuracy of results. In this study, a detailed workflow for the identification of arsenolipids utilizing suspect screening coupled with data independent analysis is presented and applied to three commercially available standard reference materials (Hijiki seaweed, dogfish liver, and tuna). Hexane and dichloromethane/methanol extraction, followed by reversed-phase high-performance liquid chromatography-inductively coupled plasma mass spectrometry and liquid chromatography-electrospray ionization-quadrupole time-of-flight mass spectrometry. Using the workflow developed, mass fragmentation matching, mass error calculations, and retention time matching were performed to identify suspect arsenolipids. Arseno-fatty acids (AsFAs), arsenohydrocarbons (AsHCs), and arsenosugar phospholipids (AsSugPLs) were identified with high confidence; AsHC332, AsHC360, and AsSugPL720 in seaweed, AsHC332 in tuna, and AsFA474 and AsFA502 in the dogfish liver. AsHC332, AsHC360, and AsFA502 were identified as promising candidates for further work on synthesis, quantification using MS/MS, and toxicity testing.

The adsorption of foulants on photocatalytic nanoparticles can suppress their reactivity in water treatment applications by scavenging reactive species at the photocatalyst surface, screening light, or competing for surface sites. These inhibitory effects are commonly modeled using the Langmuir-Hinshelwood model, assuming that adsorbed layer compositions follow Langmuirian (equilibrium) competitive adsorption. However, this assumption has not been evaluated in complex mixtures of foulants. This study evaluates the photoreactivity of titanium dioxide (TiO₂) nanoparticles toward a target compound, phenol, in the presence of two classes of foulants ─ natural organic matter (NOM) and a protein, bovine serum albumin (BSA) ─ and mixtures of the two. Langmuir adsorption models predict that BSA should strongly influence the nanoparticle photoreactivity because of its higher adsorption affinity relative to phenol and NOM. However, model evaluation of the experimental phenol decay rates suggested that neither the phenol nor foulant surface coverages are governed by Langmuirian competitive adsorption. Rather, a reactivity model incorporating kinetic predictions of adsorbed layer compositions (favoring NOM adsorption) outperformed Langmuirian models in providing accurate, unbiased predictions of phenol degradation rates. This research emphasizes the importance of using first-principles models that account for adsorption kinetics when assumptions of equilibrium adsorption do not apply.

This research presents the first proof of principle of a hyphenated AF4-TOC method to selectively quantify nanoplastics in environmental matrices.