<p>Alzheimer’s disease (AD) is a progressive neurodegenerative disease affecting more than 6 million individuals in the United States and more than 50 million worldwide. Currently, there exists no cure for AD and there are very few treatments to limit disease progression. Understanding the mechanisms through which AD develops and the risk factors associated with disease onset and progression is imperative in diagnosis and treatment of AD. Metal dysregulation has been implicated in disease pathogenesis through a number of mechanisms. Toxic heavy metals, such as lead (Pb) and mercury (Hg) are known to have deleterious effects on the central nervous system (CNS) and have been shown to increase AD pathology in animal models. However, there are significant knowledge gaps on how these metals deposit in human and animal brains at the microscopic scale, how they interact with essential metals in brain, and the relation of heavy metal exposure and AD. In this project, we aimed to investigate the distribution of heavy metals and their interactions with essential elements in transgenic mouse and human brain tissue models. We report, for the first time, Pb distribution and its co-deposition with Se in mouse brains following subchronic Pb exposure, Hg distribution and its co-deposition with Se in post-mortem AD and no cognitive impairment (NCI) brains, and the association of Pb, Hg, and other metals in these brains. All the data were obtained using synchrotron x-ray fluorescence (XRF), a powerful technique that allows for localization and quantification of multiple biological elements, as well as heavy metals, with a high spatial resolution and low detection limit. The work will shed light on the role essential metals, especially Se, play in neurotoxicity of Pb and Hg, and pave the way for potential future directions on heavy metal exposure and neurodegeneration.</p>

Lake Victoria, the second largest freshwater body in the world is affected by rise in eutrophication. This is mainly due to anthropogenic activities happening in the catchment. In this study, distribution of six elements (Cu, Zn, N, C, P, and Si) in sediments were studied from the five sites in Kenya namely Kisumu (DK2, OK2), Busia (KK2), Siaya (SPK2 and Kapsabet (KP1A). The elemental flux values were correlated with historical changes in the catchment to see if it can influence the eutrophication in Lake Victoria. Flux calculated for these elements show a strong correlation with anthropogenic activities associated with land-use changes ushered after building of the railroads, agricultural practices and urban development in the catchment. The spatial and temporal changes in distribution of these elements have a distinct signature on the metal flux. The metal flux are correlated with change in trophic conditions in the lake. There is also a distinct difference in metal flux into the lake derived from urban versus rural areas.

<p>To sustain the upcoming paradigm shift in computations technology efficiently, innovative solutions at the lowest level of the computing hierarchy (the material and device level) are essential to delivering the required functionalities beyond what is available with current CMOS platforms. Motivated by this, in this dissertation, we explore ferroelectric-based devices for steep-slope logic and energy-efficient non-volatile-memory functionalities signifying the novel device attributes, possibilities for continual dimensional scaling with the much-needed enhancement in performance.</p> <p> </p> <p>Among various ferroelectric (FE) materials, Zr doped HfO₂ (HZO) has gained immense research attention in recent times by virtue of CMOS process compatibility and a considerable amount of ferroelectricity at room temperature. In this work, we investigate the Zr concentration-dependent crystal phase transition of Hf_1-xZ_xO₂ (HZO) and the corresponding evolution of dielectric, ferroelectric, and anti-ferroelectric characteristics. Providing the microscopic insights of strain-induced crystal phase transformations, we propose a physics-based model that shows good agreement with experimental results for 10 nm Hf_1-xZ_xO₂. Further, in a heterogeneous system, ferroelectric materials can exhibit negative capacitance (NC) behavior. Such NC effects may lead to differential amplification in local potential and can provide an enhanced charge and capacitance response for the whole system compared to their constituents. Such intriguing implications of NC phenomena have prompted the design and exploration of many ferroelectric-based electronic devices to not only achieve an improved performance but potentially also overcome some fundamental limits of standard transistors. However, the microscopic physical origin as well as the true nature of the NC effect, and direct experimental evidence remain elusive and debatable. To that end, in this work, we systematically investigate the underlying physical mechanism of the NC effect in the ferroelectric material. Based upon the fundamental physics of ferroelectric material, we investigate different assumptions, conditions, and distinct features of the quasi-static NC effect in the single-domain and multi-domain scenarios. While the quasi-static and hysteresis-free NC effect was initially propounded in the context of a single-domain scenario, we highlight that the similar effects can be observed in multi-domain FEs with soft domain-wall (DW) displacement. Furthermore, to obtain the soft-DW, the gradient energy coefficient of the FE material is required to be higher as well as the ferroelectric thickness is required to be lower than some critical values. Otherwise, the DW becomes hard, and their displacement would lead to hysteretic NC effects. In addition to the quasi-static NC, we discuss different mechanisms that can lead to the transient NC effects. Furthermore, we provide guidelines for new experiments that can potentially provide new insights on unveiling the real origin of NC phenomena.</p> <p> </p> <p>Utilizing such ferroelectric insulators at the gate stack of a transistor, ferroelectric-field-effect transistors (FeFETs) have been demonstrated to exhibit both non-volatile memory and steep-slope logic functionalities. To investigate such diverse attributes and to enable application drive optimization of FeFETs, we develop a phase-field simulation framework of FeFETs by self-consistently solving the time-dependent Ginzburg-Landau (TDGL) equation, Poisson’s equation, and non-equilibrium Green’s function (NEGF) based semiconductor charge-transport equation. Considering HZO as the FE layer, we first analyze the dependence of the multi-domain patterns on the HZO thickness (<i>T_FE</i>) and their critical role in dictating the steep-switching (both in the negative and positive capacitance regimes) and non-volatile characteristics of FeFETs. In particular, we analyze the <i>T_FE</i>-dependent formation of hard and soft domain-walls (DW). We show that, <i>T_FE</i> scaling first leads to an increase in the domain density in the hard DW-regime, followed by soft DW formation and finally polarization collapse. For hard-DWs, we describe the polarization switching mechanisms and how the domain density impacts key parameters such as coercive voltage, remanent polarization, effective permittivity and memory window. We also discuss the enhanced but positive permittivity effects in densely pattern multi-domain states in the absence of hard-DW displacement and its implication in non-hysteretic attributes of FeFETs. For soft-DWs, we present how DW-displacement can lead to effective negative capacitance in FeFETs, resulting in a steeper switching slope and superior scalability. In addition, we also develop a Preisach based circuit compatible model for FeFET (and antiferroelectric-FET) that captures the multi-domain polarization switching effects in the FE layer. </p> <p> </p> Unlike semiconductor insulators (e.g., HZO), there are ferroelectric materials that exhibit a considerably low bandgap (< 2eV) and hence, display semiconducting properties. In this regard, non-perovskite-based 2D ferroelectric -In₂Se₃ shows a bandgap of ~1.4eV and that suggests a combined ferroelectricity and semiconductivity in the same material system. As part of this work, we explore the modeling and operational principle of ferroelectric semiconductor metal junction (FeSMJ) based devices in the context of non-volatile memory (NVM) application. First, we analyze the semiconducting and ferroelectric properties of the α-In₂Se₃ van der Waals (vdW) stack via experimental characterization and first-principles simulations. Then, we develop a FeSMJ device simulation framework by self-consistently solving the Landau–Ginzburg–Devonshire equation, Poisson's equation, and charge-transport equations. Our simulation results show good agreement with the experimental characteristics of α-In₂Se₃-based FeSMJ suggesting that the FeS polarization-dependent modulation of Schottky barrier heights of FeSMJ plays a key role in providing the NVM functionality. Moreover, we show that the thickness scaling of FeS leads to a reduction in read/write voltage and an increase in distinguishability. Array-level analysis of FeSMJ NVM suggests a lower read-time and read-write energy with respect to the HfO₂-based ferroelectric insulator tunnel junction (FTJ) signifying its potential for energy-efficient and high-density NVM applications.

Forensic anthropologists normally examine bone from a variety of medicolegal contexts. The skeletal remains may in some cases be highly fragmented or taphonomically modified, making it difficult to sort bone from non-bone material. In these cases, the forensic anthropologist may rely on microscopic or destructive chemical analyses to sort the material. However, these techniques are costly and time-intensive, prompting the use of nondestructive analytical methods in distinguishing bone and teeth from non-bone materials in a limited number of cases. The proposed analytical techniques are limited in that they rely on an examination of the major elements in the material, and do not sort out all materials with a similar chemical composition to bone/teeth. To date, no methods have been proposed for the use of handheld Xray fluorescence (HHXRF) spectrometry in discriminating human and nonhuman bone/teeth from non-bone materials. The purpose of this research was to develop a method for the use of HHXRF spectrometry in forensic anthropology specifically related to distinguishing human and nonhuman bone and teeth from non-bone materials of a similar chemical composition using multivariate statistical analyses: principal components analysis (PCA), linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), and hierarchical cluster analysis (HCA). This was accomplished in two phases. Phase 1 consisted of a Reliability Test and involved sampling a single human long bone in thirty locations. Multiple spectra were collected at each location to examine the reliability of the instrument in detecting the elements both within a single site and between multiple sites. The results of the Reliability Test indicated that HHXRF consistently detected the major and minor elements found on the surface of a human bone. iv These results were used for Phase 2, designated the Accuracy Test, which involved analyzing a set of materials compiled from the literature to test the accuracy of the technique in discriminating bone (human and nonhuman) and non-bone samples (other biological and nonbiological). The results of the Accuracy Test indicate that osseous and dental tissue can be distinguished from non-bone material of similar chemical composition with a high degree of accuracy (94%) when data is collected from several locations on a sample and analyzed separately during multivariate statistical analyses. Overall, it was not possible to discriminate rock apatite and synthetic hydroxyapatite (synthetic bone) from bone. However, this technique successfully discriminated other non-bone materials that are chemically similar to bone, such as ivory and octocoral, which previous methods focusing on only a comparison of Ca/P ratios were unable to distinguish from bone.

A method was developed for the determination of total arsenic in rice grain by microwave-assisted digestion inductively coupled plasma mass spectrometry. Standard calibration solutions were matrix-matched with respect to acid concentration and carbon content post-digest. The importance of eliminating the drying step during sample preparation procedures was investigated. The method was validated with spikes containing standard arsenate solutions into the rice matrix, and with certified reference material SRM1568a (rice flour) from NIST. The method was successfully applied to a commercially available rice sample. Four arsenic species [arsenate (As(V)), arsenite (As(III)), dimethylarsinic acid (DMA) and monomethylarsonic acid (MMA)] were extracted from rice grains by microwave-assisted extraction and separated with high performance liquid chromatography inductively coupled plasma mass spectrometry. The method includes a novel sample clean-up step involving a dialysis procedure to decrease the amount of large starch molecules in the injection solution, in order to minimize poor resolution of chromatographic peaks and maximize column life. The method was validated with spikes of standard arsenic solutions, added to the rice matrix before the extraction procedure. Literature reference values for arsenic species quantification in SRM1568a (rice flour) were also compared. This method was successfully applied to a commercially available rice sample. A study into improvements in reverse phase-HPLC separations of arsenic species was conducted. For the first time, a Sunfire C8 column from Waters (Milford, CT) was employed for the separation of arsenic species in rice extracts. This column was compared to a Symmetry C8 column with respect to total elution time, detection limits, interference effects, and column life, and evaluated with respect to peak resolution, shifts in retention times, and peak symmetry.

Fatal accidents on the road are an unfortunate daily occurrence, with almost 30,000 deaths resulting from hit-and-runs in the USA between 2006 and 2021. The identification of the driver responsible for this road crime can become a challenge. Nonetheless, the accident scene provides a large amount of trace evidence that can prove critical to this matter, one of them being the tire marks. While traditional tire mark analysis is full of physical information helping the reconstruction of the event, additional information can be extracted from the rubber left during the braking event. Each tire model is manufactured with a specific design, obtained by a chemical formulation that can become its signature. Supplemental to the molecular profile of the rubber itself, analysis of the trace and contaminant elements can help build the chemical signature for the tire rubber. This work consists of establishing the link between the tire and the skid mark and particles it left during a braking event. The difference between tire models was proved from the elemental analysis of the tire rubber itself, showing that the specific content of minor and trace elements is specific to the model. Expanding to the problem of tire marks, the first challenge consists in efficiently sampling the rubber from the road. The development of an effective procedure to lift the tire particles from the mark is demonstrated in this work. This does present some challenges, including removal of other particles present within the lift and extraction of the tire rubber for further analysis by ICP-MS, providing an elemental profile for the sampled skid mark. Finally, with the skid mark rubber analyzed, it is compared with the elemental profile of the rubber from the source tire. The results of this comparison will be discussed in both simulated (with a lab- made tire mark maker) and field cases (from braking tests performed by the Florida Highway Patrol (FHP)). The results of my research provide the forensic community with the first evaluation of elemental analysis of tire rubber to use this seldom used trace evidence, all along the analytical process, from sampling to analysis to attribution.

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