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    Additive Manufacturing of Batteries and IR-Active Microparticles: Polyborane-Based Electrolytes for Solid State Batteries and Additively Manufactured, TiN-Coated Microbridges

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    Advances in additive manufacturing (AM) processes are continuously opening up the material design space, providing scientists with opportunities to explore the relationship between structure, processing, and materials properties in new contexts. The first project presented in this thesis presents the design and refinement of a novel, polyborane-based solid electrolyte, whose design and investigation were motivated by the advent of additively manufactured, 3D electrodes, which could play a pivotal role in enabling next-generation batteries that can store more energy without sacrificing power. The first iteration of this electrolyte was synthesized by hydroborating polybutadiene with 9-borabicyclo(3.3.1)nonane (9-BBN). The resultant poly(9-BBN) was then reacted with precise amounts of n-butyllithium (n-BuLi), an organolithium reagent, to create the final polymer electrolyte. The polymer electrolyte films were assembled into a custom apparatus for impedance measurements, and though found to be ionically conductive, these measurements were not consistent, even within films made from the same batch of polymer in solution. This necessitated the modification of the electrolyte into a UV-cured version, which was achieved by hydroboration of polybutadiene using 9-BBN. The resulting poly(9BBN)-co-polybutadiene is treated with lithium tert-butoxide (LiOtBu) and crosslinked to produce a precursor resin, which is then drop cast onto PTFE spacers, UV-cured for 5 minutes, dried, and assembled into coin cells for electrochemical impedance spectroscopy (EIS) and into pans for differential scanning calorimetry (DSC). The ionic conductivity of the PBEs as measured by EIS as a function of molar salt ratio, r = molLi/molB, does not track with their measured glass transition temperatures, Tg or the activation energies, Ea, extracted from fitting the Vogel-Tammann-Fulcher (VTF) equation to the conductivity data. Beyond r = 0.33, values for Tg and Ea demonstrate insensitivity to increasing concentration, while conductivity continues to change with concentration and reaches a maximum at r = 0.75. Moreover, measurement of ionic conductivity of control PBE films without boron on the polybutadiene backbone confirms that the presence of Lewis-acidic boron groups is necessary for ionic solvation and conduction. Further analysis that compared the PBEs to a well-studied PEO-based electrolyte in the literature through the calculation of a reduced conductivity to control for polymer viscosity and segmental motion revealed that PBEs obtain optimal conductivity at higher salt concentrations than PEO, and that their ionic conductivities are far below that of PEO. We posit that we are observing a mechanism of ionic conduction in a glassy regime partially decoupled from the relaxation of the polymer host. We attribute these effects to the strong interaction between the Lewis-acidic boron centers and the strongly Lewis-basic tert-butoxide anions, which limits ionic conductivity by suppressing motion of the anions and presenting a large activation barrier for motion of Li+, which is optimized at high concentrations where the distance between the boron-anion centers is sufficiently small to increase the probability of a hopping event from one center to another. Nanorods fashioned from noble metals are ideal for maximizing extinction of electromagnetic radiation, which is necessary for plasmonically active materials in numerous applications, from contrast agents for biological imaging to effective obscurants. Key challenges that prevent nanorods from being employed for these technological applications include the prohibitively expensive cost of Au and Ag, their lack of requisite thermal and chemical stability, and the limitations in resolution and attainable feature sizes produced by existing wet chemistry techniques. The second project in this thesis focuses on the development of an AM process to create arrays of TiN-coated microbridges with lengths of 4.749 microns, cross-sections with dimensions of 0.692 by 2.256 microns, and effective aspect ratios of 3.368, that are capable of attenuating light reflected from a TiN-coated sapphire substrate by more than 80% in the mid-infrared (mid-IR), as measured by Fourier Transform Infrared (FTIR) spectroscopy. FTIR spectroscopy measurements further reveal attenuation of light transmitted through the same TiN-coated structures by up to 35% in the near- to mid-IR. These results indicate a promising pathway for AM of plasmonically active microparticles with broad reflectance and transmittance attenuation of light in the near- and mid-IR.</p

    Asymmetric Pericyclic Transformations from Reactive Palladium Intermediates

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    The Pd-catalyzed decarboxylative asymmetric allylic alkylation of enolate nucleophiles is a cornerstone of our groups’ efforts to develop methodologies that directly facilitate the synthesis of stereochemically complex molecular building blocks. This thesis first focuses on our efforts to deepen our mechanistic understanding of these transformations. We then employ our insights as a base from which we expand the scope of the decarboxylative asymmetric allylic alkylation reaction, as well as develop entirely novel reaction paradigms

    Development and Applications of Imaginary Time Path Integral Methods

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    Recent engineering advances have opened up avenues to novel technologies that bridge the gap between the quantum and the classical. In order to understand large-scale quantum systems, a variety of approximate theoretical treatments have been proposed. This thesis focuses on development and applications of path-integral methods, which have enjoyed broad applicability in recent years for exploring nuclear quantum effects in the domains that span physical, bio-, geo-, and materials chemistry. Feynman's path-integral formulation of quantum statistical mechanics offers powerful and widely used strategies for including nuclear quantum effects in complex chemical systems. These strategies are based on the observation that the quantum Boltzmann statistical mechanics of a quantum system is exactly reproduced by the classical Boltzmann statistical mechanics of an isomorphic ring-polymer system. For the numerically exact calculation of quantum Boltzmann statistical properties, the classical Boltzmann distribution of the ring-polymer system can be sampled using Monte Carlo (i.e., path-integral Monte Carlo, or PIMC) or molecular dynamics (PIMD). Chapters 1 and 2 of this thesis identify and &#8212; with no computational overhead &#8212; eliminate the issues in virtually all previous numerical implementations of PIMD that stem from time discretization. The resultant integration scheme requires only a small modification to existing PIMD algorithms and provides accurate statistical and dynamical data in a single-shot simulation with an up to 3-fold increase in the timestep duration. Chapter 3 transitions from the PIMD method development to the applications of the related PIMC method to understand equilibrium of stable heavy isotopes (D, 13C, 17, and 18O in small gaseous molecules. We present a collaborative experiment-theory calibration of the temperature dependence of the clumped isotope effect in methane in Chapter 4. We continue in Chapter 5, adding the study of isotopic fractionation between methane, water, and molecular hydrogen. Here we present the first concrete example of the effect of Born-Oppenheimer approximation on PI calculations. Finally, Chapter 6 extends our treatment to ethane and propane. For propane, in addition to multiple clumped isotope effects, there is also a strong site preference for the heavy isotopes to occupy the central (methylene) group. All the isotopic equilibrium calculations utilize accurate potential energy surfaces and are validated against experimental data in close collaboration with Daniel Stolper's experimental group at Berkeley, representing (to the best of our knowledge) the most accurate reference data available to date.</p

    Acquiring Enzyme Sequence-Fitness Data at Scale Toward Predictive Methods for Enzyme Engineering

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    The emergence of machine learning methods for expediting directed evolution via protein fitness prediction has recently shed light on the need for more, high quality sequence-fitness data from which to learn the mapping from sequence to fitness. Enzymes specifically are highly selective catalysts and engineered enzymes are becoming increasingly important for human applications such as pharmaceutical synthesis. This thesis thus focuses on the collection of enzymatic sequence-fitness data to enable both development and validation of emerging approaches. Chapter 1 describes the process of traditional directed evolution as well as ways that machine learning methods have been used to accelerate it. It also discusses the experimental considerations for applying machine learning to the various steps of protein engineering campaigns, as the experimental constraints are not always obvious to the machine learning community. One of the major constraints for the application of machine learning methods is the requirement to sequence all variants required for model training, a step that is often skipped by traditional, lab-only directed evolution due to it not being worth the time and cost. Chapter 2 introduces a solution to this problem with “every variant sequencing” (evSeq), which enables higher throughput collection of sequencing data for a similar time and cost as commonly used Sanger sequencing methods. This method not only enables implementation of ML methods such as machine learning-assisted directed evolution (MLDE) and focused training MLDE (ftMLDE) by sequencing variants during an evolution campaign, but also offers promise to fill existing protein sequence-fitness databases with protein engineering datasets. This type of data collection can enable the development of newer, more accurate ML methods, and was an inspiration for the work presented in Chapter 3, which details the collection of a combinatorially complete, epistatic sequence-fitness landscape in an enzyme active site. Oftentimes, the effects of mutations on protein fitness can be considered largely independent and laboratory recombination of them can find an optimal variant. This general principle breaks down when the effects of mutations are not independent, termed epistasis, and sequence-fitness landscapes with these interactions are difficult to traverse. Thus, collection of this dataset provides a challenging task for the development of both ML and physics-based models and pushes the boundary of predictive methods for protein engineering

    Reputation and Accountability

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    In this thesis, I explore how accountability relationships affect policymaking in two institutional contexts: internal executive branch operations and electoral contests. The overarching insight is that the potential for removal creates reputation concerns to demonstrate skill that, in turn, affect policymaking. For political appointees serving at the pleasure of the president, this means a reputation for management skill or technocratic policy expertise, whereas for elected representatives, this means maintaining a reputation for competent leadership with voters. The main result is that oversight creates both pathological policymaking incentives for accountable officials, but also potentially unintuitive selection by a principal—either the president or voters. In Chapters 1 and 2, I explore political appointees’ dual roles as agents of the president and managers of the bureaucracy. This view of appointee-careerist relations complicates standard notions of presidential control and bureaucratic power, by recognizing that appointees are reliant on presidential support to maintain their position within an administration. To cultivate a good reputation with the president, appointees may cede control to the bureaucracy. However, to understand how control is transferred to the bureaucracy, I argue that we must fully account for appointees’ strategic roles in the administrative presidency—and that, to do so, requires differentiating between types of appointments. Presidential appointments that require Senate confirmation (PAS) and noncareer members of the Senior Executive Service (SES-NA) occupy positions that require direct oversight and management of subordinate career civil servants. As managers, these appointees must rely on the expertise, pragmatic or otherwise, and efforts of bureaucrats to implement the president’s policies. I argue that presidents select these appointees primarily on the basis of their management skills. In contrast, Schedule C appointees occupy confidential or policymaking roles and serve directly under a political appointee. These appointees may substitute for the expertise of career bureaucrats. I argue that presidents select these appointees on the basis of policy expertise. However, central to my argument is the idea that the president may still be uncertain of an appointee’s management skill or policy expertise—despite appointing him or her in the first place. This means there is scope for the president to learn about an appointee’s ability based on how they perform or behave on the job. It is this residual uncertainty about an appointee’s capabilities, along with the president’s formal removal power, that create reputation concerns for appointees: appointees care about maintaining their position and to do so they must preserve their reputation with the president. I argue that these reputation concerns shape how appointees manage interactions with the bureaucracy. Appointees in managerial roles may make more policy concessions to the bureaucracy than the president would like in order to ensure bureaucratic cooperation and avoid revealing managerial weaknesses. Instead, appointees in positions of policymaking authority may fail to empower or involve bureaucrats in policymaking. Both of these actions undermine the president’s policy goals by either creating policies that increasingly reflect the views of the bureaucracy or by failing to create policies that reflect bureaucratic expertise. This suggests limitations of political control over the bureaucracy that cannot be alleviated through the exercise of formal administrative powers, namely appointment and removal powers. Ultimately, the agency issues I explore in this context follow from a fundamental and immutable constraint on presidential control: the president simply cannot unilaterally manage the executive branch. The demands of the presidency are too great for the president to preside over all operations. This means delegation is necessary—and, even when the president delegates to advisors of “her own choosing,” some loss of control is inevitable. In Chapter 3, I explore how majority selection operates in an environment in which politicians prefer to pursue particularistic policies. If special interest coalitions are sufficiently strong, a majority may expect that political expertise will be used to select policies that generate rents for narrow constituencies at the expense of its own welfare. I develop a model in which a majority prefers to elect the less competent politician in order to undermine the incumbent’s ability to pursue the special interest agenda and derive the implications for accountability in this setting. The results demonstrate that the majority’s attempts to reassert control over policy through its retention decisions impede social welfare maximizing reform and distort aggregate welfare by either encouraging (i) inefficient policy selection or (ii) inefficient candidate selection. Even if politicians choose policies that maximize social welfare doing so may only worsen aggregate welfare by providing voters with more information about candidate competence, which enables the majority to better select inept politicians.</p

    Vibrational Imaging for Chemical Biology: from Label-Free to Molecular probes

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    Since the invention of stimulated Raman scattering (SRS) microscopy in 2008, vibrational imaging is increasingly recognized as a powerful tool for biological investigation. As the most suitable far field vibrational imaging modality for live biological studies, SRS microscopy is taking the lead role within its vibrational counterparts with desired sensitivity and image quality. The totally different mechanism of generating vibration signals from fluorescence signals determines the special features of vibrational imaging. Bond vibration originating signals provide inherent optical contrast for every molecule and the quantitative manner allows straightforward quantification. Since the inception, SRS microscopy has achieved large success in label-free imaging. Label-free imaging avoids tedious labeling step and has the least perturbation to the biological samples but with limited sensitivity and specificity. The introducing of labeling starting about 10 years ago opens up a new avenue for SRS microscopy to tackle the fundamental limitations of label-free approaches. Whether to use label-free or molecular probes for SRS microscopy depends on the specific studies. This thesis aims to utilize SRS microscopy (both label-free and minimally labeling) for metabolic study and develop new molecular probes for SRS microscopy. We start from comparing different vibrational imaging modality and fluorescence imaging and conclude that SRS is the best vibrational imaging technique for biological samples. Then we discuss the features of label-free, bioorthogonal labeling and super-multiplexed SRS imaging. The minimally perturbative triple bond tagging and isotope labeling makes SRS especially suitable for tracking metabolites and accessing metabolic pathways. Furthermore, we also summarize the design principles for functional Raman imaging probe development based on their spectroscopic signatures. (Chapter 1). Non-invasively probing metabolites within single live cells is highly desired but challenging. We explored Raman spectro-microscopy towards spatially-resolved single cell metabolomics, with the specific goal of identifying druggable metabolic susceptibilities from a series of patient-derived melanoma cell lines. The chemical composition analysis of single cell and single organelle lipid droplets identified the fatty acid synthesis pathway and lipid mono-unsaturation as druggable susceptibility. More importantly we revealed that inhibiting lipid mono-unsaturation leads to cellular apoptosis accompanied by the formation of phase-separated intracellular membrane domains. (Chapter 2). Next, we established a first-in-class design of multi-color photoactivatable Raman probes for subcellular imaging and tracking. The fast photochemically generated alkynes from cyclopropenones enable background-free Raman imaging with desired photocontrollable features. After necessary molecule engineering to improve the biocompatibility and sensitivity, we generated organelle-specific probes for targeting mitochondria, lipid droplets, endoplasmic reticulum, and lysosomes. Multiplexed photoactivated imaging and tracking at both subcellular and single-cell levels was also demonstrated to monitor the dynamic migration and interactions of the cellular contents. (Chapter 3). Further improvement of the Raman signal with molecular probes is a central topic for Raman imaging. Recently developed electronic preresonance (epr) probes boost Raman signals and pushed SRS sensitivity close to that offered by confocal fluorescence microscopy. To guide the development of even stronger Raman probes and fill the final gap between epr-SRS probes and single molecule imaging, the structure-function relationship of epr-SRS probes is indispensable. We therefore used ab initio approach employing the displaced harmonic oscillator (DHO) model for calculating the epr-SRS signals, which proves to provide a consistent agreement between simulated and experimental SRS intensities of various triple-bond bearing epr-SRS probes. The theory also allows us to illustrate how the observed intensity differences between molecular scaffolds stem from the coupling strength between the electronic excitation and the targeted vibrational mode. Utilizing the discovered structure-function relationship of epr-SRS probes, we engineered MARS palette for higher sensitivity. With chemical modification to improve Raman mode displacement or enhance transition dipole moment or adjust detuning, we enhance the signal of alkynyl pyronins and nitrile pyronins, setting the current sensitivity records for small molecule far-field Raman probes. (Chapter 4 and 5).</p

    Numerical Simulations of Cavitating Bubbles in Elastic and Viscoelastic Materials for Biomedical Applications

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    The interactions of cavitating bubbles with elastic and viscoelastic materials play a central role in many biomedical applications. This thesis makes use of numerical modeling and data-driven approaches to characterize soft biomaterials at high strain rates via observation of bubble dynamics, and to model burst-wave lithotripsy, a focused ultrasound therapy to break kidney stones. In the first part of the thesis, a data assimilation framework is developed for cavitation rheometry, a technique that uses bubble dynamics to characterize soft, viscoelastic materials at high strain-rates. This framework aims to determine material properties that best fit observed cavitating bubble dynamics. We propose ensemble-based data assimilation methods to solve this inverse problem. This approach is validated with surrogate data generated by adding random noise to simulated bubble radius time histories, and we show that we can confidently and efficiently estimate parameters of interest within 5% given an iterative Kalman smoother approach and an ensemble- based 4D-Var hybrid technique. The developed framework is applied to experimental data in three distinct settings, with varying bubble nucleation methods, cavitation media, and using different material constitutive models. We demonstrate that the mechanical properties of gels used in each experiment can be estimated quickly and accurately despite experimental inconsistencies, model error, and noisy data. The framework is used to further our understanding of the underlying physics and identify limitations of our bubble dynamics model for violent bubble collapse. In the second part of the thesis, we simulate burst-wave lithotripsy (BWL), a non- invasive treatment for kidney stones that relies on repeated short bursts of focused ultrasound. Numerical approaches to study BWL require simulation of acoustic waves interacting with solid stones as well as bubble clouds which can nucleate ahead of the stone. We implement and validate a hypoelastic material model, which, with the addition of a continuum damage model and calibration of a spherically- focused transducer array, enables us to determine how effective various treatment strategies are with arbitrary stones. We present a preliminary investigation of the bubble dynamics occurring during treatment, and their impact on damage to the stone. Finally, we propose a strategy to reduce shielding by collapsing bubbles ahead of the stone via introduction of a secondary, low-frequency ultrasound pulse during treatment.</p

    Additive Manufacturing of 3D Micro-Architected Materials for Device Applications

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    Natural cellular biomaterials typically consist of hard and soft constituent materials that are hierarchically ordered to achieve outstanding mechanical properties, e.g., light weight, mechanical resilience, multi-functionality, etc. Architected materials are a new class of engineered materials with meticulously controlled internal structures that produce properties that differ from or exceed those of their constituent materials. Recent developments in additive manufacturing offer an extraordinary opportunity to rationally design the structure and chemical composition of architected materials to optimize properties and functionalities for a wide range of device applications. Here we first present a framework that combines an artificial intelligence tool and two-photon lithography in order to design and fabricate optimal porous structure with the desired anisotropic mechanical properties. The biomimetic and extremely tunable natural of the structures generated by the framework enables the great potential to be used as the bone scaffold design strategy which meets the requirements of complex anisotropic and heterogeneous mechanical properties of the vivo environment. The designed the architectures are meticulously verified by in situ Nanomechanics. These theory-informed experiments revealed close agreement between experimental data and artificial intelligence-predicted stiffness anisotropy, which opens a pathway for uncovering previous unattainable design space of elasticity vs. 3D architecture mapping in quantifiable and deterministic way. Besides, we explore the structural and material effects of additively manufactured microrobots which is powered by external physical fields for complex therapeutic assignments. The excellent movability and controllability permit the microrobots to be used as minimal invasive instruments for precise application in healthcare. The synergistically optimized microstructures and chemical composition enables the microrobots great potential to be applied to in vivo clinical applications

    Depositional and Structural History of the Pavian and Kudu Nappes in the Naukluft Mountains, Namibia

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    The termination of the Marinoan Snowball Earth glacial epoch was one of the most extreme climate events in Earth history. Yet, the transition from global glaciation to an ice-free warmer climate is still poorly constrained. The Naukluft Nappe Complex of south-central Namibia contains several stratigraphic formations that record the environmental and tectonic transitions of the Neoproterozoic, including glaciogenic deposits and basal-Ediacaran cap carbonate of the Marinoan Snowball Earth. This stratigraphic record has the potential to provide a critical record of the climate, sea-level history, ocean chemistry, and time frames across the climate transition of the Marinoan Snowball deglaciation. We first show a detailed study of the sedimentology and stratigraphy of the upper BlÀsskranz Formation and Tsabisis Formation cap carbonate to develop an environmental and sequence stratigraphic history spanning and following the deglaciation. In downdip areas Marinoan diamictite transitions upward into dolostone intermixed with sandstone and extrabasinal clasts that is gradually overlain by fine grained laminated dolostone. Updip localities show the diamictite is overlain by intercalated sandstones, gravels, and shales before an abrupt change to laminated dolostone of the cap carbonate. A succession of stromatolites, which become strongly elongate upward, prograde into the laminated dolostone in the updip localities. The stromatolites are overlain by laminated dolostone that grades upward into rhythmite with intercalations of shale. Near the top of the cap, rhythmites may be reworked into tabular intraclast conglomerate, locally intercalated with hummocky cross stratified sandstone, which passes upward into the shale and limestone members of the Tsabisis Formation. The lateral and vertical distribution of facies indicate a retreat of the shoreline and glacially sourced siliciclastics near the base of the cap carbonate, a shallowing succession to fair-weather wave base at the top of the stromatolite facies, and a second shallowing succession to storm wave base near the top of the cap carbonate. Maximum flooding occurred soon after the initiation of carbonate deposition and two sequence boundaries mark higher stratigraphic levels within the cap carbonate. With a sea-level history and chronological framework inferred from the sequence stratigraphy we can consider different mechanisms of sea-level change, which may reflect the timescale and synchronicity of deglaciation. Next, we consider the structural and stratigraphic relationships between the Neoproterozoic units of the Naukluft Mountains to define and contextualize the extent of the terminal Marinoan geologic record. We show that the Northern Pavian Nappe, which includes the Marinoan-associated BlÀsskranz and Tsabisis formations, is stratigraphically succeeded by the dolostone dominated Kudu Nappe and is not correlated or genetically related to the nearby Southern Pavian Nappe. Additionally, the modified stratigraphic and structural relationships allow for a simplified nappe emplacement history that reduces the magnitude of shortening associated with convergence along the Damara Orogen. Finally, we use sea-level modeling of the Naukluft Marinoan record to constrain the duration of global deglaciation. Using a range of reconstructed synchronous and continuous deglaciation models, we evaluate if the observed sea-level patterns of the Naukluft can be fully explained by glacial isostatic mechanisms driven by the deglaciation. Short Snowball deglaciation durations, on the order of ~2 kyr, result in exclusive sea-level rise, or sea-level rise followed by sea-level fall, but cannot drive two distinct phases of sea-level fall. However, for longer duration snowball deglaciations, of ~10-30 kyr, we can drive two distinct intervals of sea-level rise and fall across much of the width of a continental margin, consistent with the stratal patterns observed in Naukluft Mountains cap carbonate succession. Our spatially varying sea-level predictions resulting from longer duration deglaciations may be applicable in interpreting stratal patterns of other cap carbonate successions. Furthermore, this work underlines the need for better constraints on the areal distribution and volume of Marinoan ice sheets, including improved understanding of plausible deglacial durations using updated global climate models.</p

    Fluid-Rock Interactions from the Lithosphere to Earth’s Surface

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    Fluids can cycle and migrate through planetary bodies, transporting soluble ions and influencing physical properties of the surrounding rock or magma, such as fracture toughness, seismic wave velocity, melting point, viscosity, and more. Precipitated minerals, fluids trapped in inclusions, and free pore fluids can be used to constrain fluid provenance, mixing relationships, and paleoenvironmental information such as temperature, pressure, redox conditions, salinity, and pH. In my thesis, I discuss my research on topics pertaining to the geochemistry associated with fluid-rock interactions that occur from the depths of the lithospheric mantle to Earth’s surface. Broadly, these chapters address open questions pertaining to 1) the retention timescales and metasomatic overprinting of fluids sourced from the mantle in obducted peridotites, 2) the capacity for pedogenic Mg-carbonates to preserve palaeohydrological information with implications for Martian carbonates, and 3) the influences hydrous fluids have on lithospheric magmas and minerals. Helium isotopes are arguably the best tracer for fluid sources in Earth materials at the planetary scale. ÂłHe/⁎He ratios of the Earth’s 1) continental crust, 2) atmosphere, 3) upper mantle, and 4) core or deep isolated mantle (mantle plume source) vary by over two orders of magnitude, offering considerable dynamic range compared to measurement precision. While helium isotope signatures in Earth’s mantle have been determined almost exclusively by the analysis of helium retained in mantle xenoliths, phenocrysts, erupted glasses, and vent gases, this selection introduces a sampling bias towards fluids that have been transported to Earth’s surface by eruptive processes. In contrast, residual mantle peridotites take much longer to arrive at Earth’s surface and are therefore more susceptible to metasomatic processes that can overprint primary helium isotopic signatures. In Chapter 1, I use concentrations and isotopes of helium and argon along with concentrations of U and Th to place constraints on the sources and siting of helium retained in exhumed mantle peridotites collected from Twin Sisters Mountain of the Northern Cascades in Washington State, USA. Helium isotope ratios of peridotites from the Twin Sisters Mountain span from 0.8 to 6 times the atmospheric ratio (1RA=1.4*10⁻⁶ ÂłHe/⁎He). Fluid inclusions in these peridotites capture a two-component mixture that included a mantle-like endmember (~6 RA) and a serpentinizing endmember (1.0 ± 0.5 RA) that is consistent with a mixture of surface-derived groundwater, leached crustal radiogenic helium and reworked mantle helium. While these components are not effectively isolated by extraction using vacuum crushing and powder fusion, step-heating analysis reveals that the serpentinizing endmember is released at lower temperatures (&#60;1000°C) and the mantle-like endmember is released at higher temperatures. Results demonstrate that helium signatures can be retained in lithospheric peridotites against both diffusive loss and radiogenic ingrowth over at least 10⁞-year timescales but can be greatly modified by cryptic metasomatic processes during emplacement. Mg-carbonates have become increasingly relevant in the scientific community due to their orbital and in situ detection on the Martian surface. Like Ca-carbonate on Earth, Martian Mg-carbonates may preserve paleoenvironmental information associated with their formation on Mars billions of years ago, shedding light on habitability. Yet, unlike Ca-carbonates, the capacity for Mg-carbonates to preserve paleoenvironmental information through trace element signatures associated with their source fluids has not been well established for surficial magnesite samples on Earth. In Chapter 2, I 1) develop a digestion protocol to selectively digest Mg-carbonates (magnesite ± dolomite) while obviating influences of contaminant phases and ions adsorbed to mineral surfaces, 2) validate a method to analyze trace elements with Mg-matrix by solution ICP-MS, and 3) apply these procedures to determine trace element concentrations of pedogenic Mg-carbonates sampled along a depth profile in the Kunwarara open pit magnesite mine in Queensland, Australia. Results from this study confirm that the method we implemented selectively digests magnesite ± dolomite. A relationship between negative Ce anomaly in the carbonates and Fe/Mn-oxides/hydroxides in corresponding host sediment collected along the depth profile demonstrates that pedogenic magnesites can capture redox gradients in the soil column. This finding implies that Ce anomaly in carbonates can potentially be used to place constraints on the paleo-redox conditions associated with Mg-carbonate formation on ancient Mars. Numerous questions in Earth science depend on quantitative understanding of how elements fractionate during melting and crystallization. To name a few: assessment of how lithospheric fluids influence geodynamical processes, constraining mechanisms that led to the formation of the Earth’s continental crust, evaluation of elemental fluxes from the mantle to Earth's surface, calibration of a reliable crustal barometer, and gauging how magmatism and plate tectonics differed with the higher geothermal gradients of a younger Earth. MELTS thermodynamic software is a widely available free tool utilized by geoscientists to both test hypotheses and model the geochemistry of magmatic processes. However, minerals of the amphibole supergroup, although common in magmatic systems, rarely crystallize in MELTS simulations, even when well controlled experiments demonstrate that they should. The decrease in the Gibbs energy needed to stabilize amphibole in MELTS is often on the order of the configurational entropy contribution to the Gibbs energy associated with minor elements that are not present in any of the current amphibole solution models used in MELTS but are frequently incorporated in the amphibole crystal lattice. In Chapter 3, I outline a framework for a volume model for monoclinic amphiboles that can be used in an expanded amphibole solution model to be incorporated in MELTS software. A volume model is prerequisite to calibrating the other model terms because it accounts for differences in pressure among experimental constraints. The framework I develop extends the model to include minor components that are not present in existing versions of the MELTS amphibole models. I calibrate a preliminary model using a dataset composed of x-ray refinements that supply amphibole volume and site occupancy data. Results reveal regions in parameter space where data is limited and the sensitivity that model coefficients have to uncertainties in the data, suggesting that filtering the dataset to remove outliers may be necessary.</p

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