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Understanding and Addressing Low Permeability in Heap Leaching
No full textThis paper was presented at the Heap Leach Solutions Conference, October 19-21, 2025, Sparks, Nevada.Heap leaching has experienced substantial growth in recent decades, driven by various factors including declining grades, water supply challenges, stricter environmental regulations and perceived investment risks. Heap permeability often serves as the limiting factor, particularly in African ores characterised by high clay content. Laboratory test protocols have been established to assess the physical and hydraulic properties of crushed ores and agglomerates for heap leaching purposes. Traditional capillary flow models such as Brooks-Corey (BC) or van Genuchten-Mualem (VGM) were used to describe unsaturated flow in the ore bed. However, these models exhibit discontinuity, with an inflection point corresponding to the air entry point. This suggests that at higher moisture contents, all pores connected to flow channels become saturated. Residual moisture content in the bed was found to increase with surface area, which correlated to the percentage sandy (<4 mm material) material present. Silt and clay particles (<150 microm) were found not to individually contribute to the surface area but bind together as clay lumps or adhere to larger rocks. During irrigation, clay lumps tend to break apart and obstruct flow channels if present in sufficient quantities. Low permeability resulting from this phenomenon contributed to high steady-state moisture hold-up, causing the bed to operate near saturation. Poor permeability was addressed in acidic heap leaching by agglomeration with an acid-resistant cementitious binder. The binder formed stable bonds that endured prolonged exposure to sulphuric acid and reduced slumping in 1 m leach columns from 20% to zero. This allowed an increase in the irrigation rate from 1.4 L/m2/h to the target of 6 L/m2/h in a system where the leach rate was limited by the supply of acid from irrigation. To date test work has been limited to a laboratory scale (4 m tall, 320 mm ID leach columns). It is expected that agglomeration with the cementitious binder may provide a cost-effective method for whole-ore leaching of low-permeability ores at scale as an alternative to fines removal
Dissecting Slit Signaling: Regulating Stem Cells, Proteolytic Cleavage and its Emerging Roles in Metabolism
No full textStem cells, immune cells, and metabolic tissues rely on tightly coordinated signaling pathways to maintain homeostasis and respond to stress and environmental changes. The Slit family of secreted proteins — originally identified as axon guidance cues — has emerged as a multifaceted signaling system beyond the nervous system. Full-length Slit (Slit-FL) is a large, secreted axon guidance molecule that functions as a chemorepellent by signaling through Robo receptors on migrating neurons. This thesis explores how Slit proteins, their proteolytic fragments, and corresponding receptors regulate stem cell behavior, intercellular communication, and lipid metabolism in Drosophila, with mechanistic insights into the regulation of immune-metabolic communication.Chapter 1 reviews the conserved roles of Slit/Robo signaling in diverse stem cell populations. From regulating hematopoietic stem cells in both Drosophila and mammals, to maintaining niche adhesion in the testis and controlling asymmetric cell division in mammary and intestinal stem cells, Slit/Robo signaling governs critical fate decisions across multiple cell types. This chapter highlights how Slit signaling influences self-renewal and differentiation. It also underlines broader implications in development, disease biology, and potential therapeutic applications.
In Chapter 2, building on our previous identification of the Tolloid family metalloprotease, Tok, as the Drosophila protease for Slit cleavage, we sought to identify the vertebrate counterpart involved in SLIT2 processing. Towards this, demonstrate that proteolytic cleavage of SLIT2 generates functionally distinct fragments. Using Drosophila and mammalian systems, we show that Tolloid-like 1 (TLL1) is the vertebrate protease responsible for cleaving SLIT2, and that this cleavage is regulated by proprotein convertase 2 (PC2) via activation of TLL1. These findings clarify the mechanisms by which Slit proteolysis diversifies signaling, suggesting receptor-specific and context-dependent functions.
Chapter 3 investigates the non-neural functions of Slit fragments in metabolic regulation. Slit-C, produced through Tok-mediated cleavage, promotes hemocyte dispersal in a Pvr (PDGFR/VEGFR)-dependent manner, while Slit-FL retains hemocytes in hematopoietic niches. Starvation induces Tok expression in the fat body, enhancing Slit cleavage and modifying systemic immune and metabolic responses. Slit-C also physically interacts with Pvr in Drosophila and with PDGFR-α in vertebrates, suggesting conserved roles in lipid metabolism and immune regulation.
Chapter 4 discusses the findings from Chapter 3 in greater depth, addressing experimental caveats, challenges in interpreting ligand-receptor interactions with matricellular proteins and directions for future research to expand on Slit’s function in metabolic tissues. The chapter also connects this work to emerging clinical studies that highlight SLIT’s therapeutic potential in treating metabolic and immune disorders.
Together, this thesis uncovers novel roles for Slit signaling beyond axon guidance, highlighting its emerging function as a regulator of immune-metabolic crosstalk and laying the groundwork for future investigation into its physiological and therapeutic relevance
Shaping the Future of Heap Leach Facility Management: Closing the Governance Gap
No full textThis paper was presented at the Heap Leach Solutions Conference, October 19-21, 2025, Sparks, Nevada.Heap leach facilities (HLFs) are essential to the economic viability of modern gold, silver, and copper mining, yet they operate in a regulatory and governance vacuum. While tailings storage facilities (TSFs) have come under increased global scrutiny following catastrophic failures, HLFs remain largely unaddressed in global risk management frameworks. This oversight is not only technically unjustified, but it is also ethically indefensible. In the past year alone, multiple incidents have demonstrated the significant and often underestimated risks of HLFs. In February 2024, a catastrophic collapse at the Çöpler Gold Mine in Turkey claimed nine lives and exposed critical design flaws in the heap leach pad. Just four months later, the Eagle Gold Mine in Canada experienced a major landslide of leached material, raising alarms about environmental contamination. Most recently, in February 2025, a leach-related dam failure at the Sino-Metals operation in Zambia released 50 million liters of toxic solution into the Kafue River, threatening the health and livelihoods of millions. These incidents are not outliers, they are warnings. This paper issues a call to action: it is time to bring JHLFs out of the regulatory blind spot and into the light of global standards. Building on the principles of the Global Industry Standard on Tailings Management (GISTM), we propose a comprehensive governance framework tailored to HLFs that centers values such as zero harm, lifecycle accountability, independent technical oversight, and public transparency. More than just technical structures, HLFs must be managed as ethical commitments, requiring executive-level accountability and trust-based stakeholder engagement. The message is clear: if the mining sector is serious about responsible and sustainable practices, governance of HLFs must no longer be optional. It must be global, enforceable, and built on the same moral foundation that is now shaping the future of tailings management. The time to act is now
Electrochemical Carbon Dioxide Conversion to Multi-Carbon Products: Strategies for Enhancing Selectivity and Efficiency
No full textThe electrochemical reduction of carbon dioxide (CO2) offers a promising method for tackling the interconnected global challenges of climate change and the demand for sustainable energy. As a significant greenhouse gas, the rising concentration of CO2 in the atmosphere plays a major role in global warming and environmental degradation. Electrochemical CO2 reduction (CO2RR) provides a viable solution by converting CO2 into valuable fuels and chemicals using electricity, ideally sourced from renewable resources. This approach not only helps mitigate the environmental issues caused by excess CO2 emissions but also facilitates the production of energy-dense products such as ethylene, ethanol, methanol, and methane, which can be integrated into existing industrial and energy infrastructures. In this dissertation, I explored various electrocatalyst design strategies aimed at enhancing the selectivity, efficiency, and stability of CO2RR systems. The work presented here builds a foundation for scalable and tunable approaches to CO2 utilization through advanced electrochemical technologies.First, I demonstrated a tandem electrocatalysis approach utilizing Ag-Cu nanoparticle electrodes coupled with proton-permeable membranes to selectively produce ethylene (C2H4) with Faradaic efficiencies of up to 80%. In this system, CO2 is initially reduced to CO on the Ag electrodes, which is subsequently converted to C2H4 on the Cu-based nanoparticles. I systematically studied key variables, including membrane thickness, applied voltage, and the oxidation state of Cu, to understand their roles in improving selectivity.
Building on this work, I employed membrane-modified Ag-Cu bimetallic catalysts to enable switchable selectivity between C₂ products. By adjusting the catalyst composition and the hydrophobicity of the membrane, I was able to shift the dominant product from ethylene to ethanol (C2H5OH), achieving a maximum Faradaic efficiency of 72% for ethanol-the highest reported for Ag-Cu systems to date.
In another study, I examined the role of self-assembled monolayers (SAMs) on metal and metal oxide electrodes in CO2 reduction. SAM-modified ZnO electrodes demonstrated exceptional selectivity for methanol production, reaching Faradaic efficiencies of up to 92%. This high performance was attributed to the cooperative catalysis between thiolated surface sites and exposed defect sites, as supported by density functional theory calculations. The SAMs exhibit excellent stability under electrochemical conditions, maintaining their activity over prolonged operation.
Finally, I found that SAM-modified Cu electrodes can drive CO2 reduction to methane (CH4) with Faradaic efficiencies of up to 93%, using 3-mercapto-1-propane sulfonate as the modifying agent. The sulfonate group of the SAM molecule influences product selectivity, which was confirmed by comparative studies with Nafion-modified electrodes from previous studies and systematic variation of SAM tail groups.
Collectively, these studies offer novel insights into designing highly selective and tunable electrocatalysts for CO2 reduction. By leveraging tandem catalysis, membrane engineering, and surface modifications with SAMs, this work establishes an adaptable and durable platform for the sustainable production of energy-rich fuels and chemical feedstocks from CO2
Development of a State and Transition Model for Low Gradient, Perennial Streams in the Northern Great Basin Region
No full textLow-gradient, perennial riparian systems are underrepresented, unique settings in the arid Great Basin region and provide a wealth of uses and services including fertile soils, wildlife habitat, flood attenuation, livestock water, groundwater storage and wildfire buffering. Their desirability has, since the time of western colonization and settlement, led to extensive alterations ranging from channel straightening to displacement of stabilizing riparian vegetation through farming practices and widespread, continuous grazing. This has led to numerous incidences of bank erosion, channel widening and, in many cases, disconnection between the channel and floodplain, greatly reducing the extent of the riparian zone and leading to a shift in dominance from wetland-type species to more upland-preferring plants. These type conversions and degradation are of particular concern as riparian areas, which, despite making up less than one percent of the region, are crucial landscape elements, especially in the face of a warming climate trend. This places a substantial emphasis on maintaining and restoring riparian areas. This is a difficult task considering their complexity, but is considerably aided through the use of State and Transition models that are built around underlying riparian processes and provide a level of predictive power concerning various applications of disturbances, including restoration. This study was focused on developing a STM for low-gradient, perennial streams in the northern Great Basin with the express aim of using quantitative channel/vegetation data and pattern analysis. Chapter 1 provides background information on STM development and riparian theory as well the various elements examined during this project. Chapter 2 documents the process involved with achieving this goal, as well as descriptive elements of the model. Chapter 3 examines the application of remote sensing technology in the context of riparian monitoring and within the context of STM extrapolation across areas outside the study area
Aberrant Biochemistry of a Leucine Metabolism Intermediate
No full textUrinary organic acids are often associated with inborn errors of metabolism (IEM) or other disease states. For example, 3-methylglutaconic (3MGC) acid is excreted in IEMs associated with leucine degradation pathway enzyme deficiencies (primary 3MGC aciduria). Mutations in 3-hydroxy-3-methylglutaryl (HMG) CoA lyase (HMGCL) or 3MGC CoA hydratase (AUH) cause an accumulation of the upstream pathway intermediate, trans-3MGC CoA, the precursor of 3MGC acid. Alternatively, in secondary 3MGC aciduria, 3MGC acid excretion is associated with IEMs that affect mitochondrial energy metabolism. In these disorders, a previously unknown biosynthetic route termed the “acetyl CoA diversion pathway” leads to production of trans-3MGC CoA and excretion of 3MGC acid. Studies have shown that trans-3MGC CoA is an intrinsically unstable chemical entity that is susceptible to non-enzymatic isomerization to cis-3MGC CoA. Once produced, cis-3MGC CoA can undergo intramolecular cyclization, yielding 3MGC anhydride plus free CoA. The anhydride is reactive and has at least two potential fates including 1) hydrolysis to form 3MGC acid or 2) reaction with lysine side chain amino groups to covalently 3MGCylate proteins. In chapter 2, the reaction catalyzed by the leucine degradation pathway enzyme trans-3MGC CoA hydratase (AUH) was investigated. AUH-mediated dehydration of HMG CoA produces trans-3MGC CoA, which, in the presence of bovine serum albumin (BSA) leads to 3MGCylation of BSA. A polyclonal antibody directed against 3MGC moieties was generated and utilized in immunoblot experiments designed to detect protein 3MGCylation. In chapter 3, the effect of temperature and time on the non-enzymatic reaction sequence initiated by trans-3MGC CoA was examined. When AUH was included in incubations containing trans-3MGC CoA and BSA, the extent of BSA 3MGCylation was attenuated, indicating AUH activity protects against the aberrant non-enzymatic reaction sequence that leads to protein 3MGCylation / 3MGC acid production. Finally, evidence that protein 3MGCylation occurs in vivo was obtained in HMGCL knockout mice. In the studies presented in chapter 4, the metabolic origin of another organic acid derived from trans-3MGC CoA, 3-methylglutaric (3MG) acid, was investigated. Whereas these experiments provided preliminary evidence that 3MG CoA is formed by reduction of the double bond in trans-3MGC CoA, further studies are required to validate the underlying hypothesis. In summary, studies in this dissertation provide novel information regarding the biochemical origins of 3MGC acid and 3MG acid. This enhanced understanding of the metabolic origins of these organic acids is likely to improve their utility as disease biomarkers
Patient Specific Prediction of Parenchymal Molecular Dispersal Utilizing Medical Images Within Diffusion Modeling Environments
No full textKnowledge of solute dispersal within the brain is critically important for drug delivery for cancer treatment and for information of brain functioning. The delivery of drugs into the brain can be systemic or focal; however, for focal delivery, overdosing off-target tissue can induce excess damage. Brain conditions can result in bio-molecule imbalances which can be released into the interstitial matrix which knowledge of this dispersal illuminates location and magnitude of the condition. To predict solute dispersal, computational and in-vitro models of solute dispersal can aid surgical prediction and supplement investigatory work into the parenchymal biomolecular environment. Given the highly heterogeneous nature of the brain, use of individual specific brain tissue reduces error of molecular prediction. To that end, we construct in-vitro and in-silico models of the brain using multiple MRI types to inform individual specific brain structure to guide computational molecular dispersal following the individual’s specific environment. To do this we constructed a molecular dispersal model within a finite element analysis (FEA) software and validated with a hydrogel model to replicate perturbed infusion techniques. Subsequently, using neuro-imaging software, we extracted CAD objects of the pia mater to be reconstructed in-silico and in-vitro to provide the boundary of a molecular dispersal environment. To inform the internal tissue details, we further utilized neuro-imaging software to extract mass data from MRIs to be interpreted as tissue data providing structural details (MPRAGE) and tractography details (DTI). This data was subsequently imported into FEA to guide molecular dispersal
Computational Studies of Materials for Catalysis and Photocatalysis
No full textIn this dissertation, ab-initio computational chemistry methods are used to studya variety of systems. First, systems with inverted singlet-to-triplet gaps are investigated
for the purpose of photocatalytic water splitting. In addition to designing
molecules for this purpose, a machine learning model is also presented, allowing for
large volume screening of molecules for required photophysical properties. Second,
copper-exchanged zeolites, specifically their active sites and neighboring atoms, are
investigated. These active sites are responsible for catalyzing methane-to-methanol
conversion, an important process needed for transport. Third, the complexation of
SO3 with pyridine and bipyridine is studied. This process allows for recapture of
SO3, preventing detrimental environment impact. Further, these complexes have
photochromatic properties that are useful in a wide range of applications.
In common, all of the content in this dissertation touches on the excited state
properties of molecules. In Chapters 2 and 3, materials with inverted S1 and T1
states are investigated for application in photocatalytic water splitting. This process
requires specific energies for low-lying excited states, as well as a correct ordering of
the S1 and T1 states. Chapter 4 uses excited states as reference values to contextualize
the accuracy of our !B88PTPSS density functional approximation (DFA). In Chapter
5, excited state spectra are calculated and compared to experimental data to identify
accurate computational methods for copper-exchanged zeolites. Lastly, Chapter 6
performs a similar analysis, but for pryridine and bipyridine complexes of SO3
Testing assisted gene flow in restoration of winterfat, Krascheninnikovia lanata, a Great Basin desert shrub
No full textClimate strongly influences the distribution of plant species, and as the climate has shifted, plants have historically responded by evolving, migrating, or perishing. However, anthropogenic climate change may be occurring at a rate such that local, native plant populations cannot respond. In addition to climate change, changes in disturbances such as wildfires and weed invasion can pose challenges for natural regeneration of native plant communities. To combat these challenges and increase the diversity and density of native plant communities, active restoration is used to restore landscapes, and increasingly, practitioners are considering the use of non-local seeds from warmer or drier locations in restoration. Here, focusing on the Great Basin and Mojave deserts, we focused on restoration of a widespread shrub, winterfat (Krascheninnikovia lanata), asking how seedling emergence and outplant seedling survival vary among 15 populations collected across both deserts. Populations were sampled across a 116,893 km2 boundary. We monitored seedling emergence in a greenhouse, grew plants for 9 months, and outplanted seedlings into two northern gardens and one container experiment. In the greenhouse, populations from cooler, wetter, northern and western populations emerged fastest, taking an average of 100 hours for the fastest population to emerge (relative to 158 hours for the slowest). Seedlings grown in the greenhouse differed in size among populations before outplanting, with southern populations tending to be larger. Regardless of source, larger outplanted seedlings had a higher probability of surviving the first growing season, and size, rather than population of origin, best predicted survival. However, after an herbivory event in the second growing season, there was a strong signal of local adaptation in one field garden, where non-local plants disproportionately experienced strong herbivory by native Mormon crickets, which increased mortality and resulted in a strong signal of local adaptation. Though an assisted gene flow strategy could potentially increase genetic diversity in Great Basin populations, our results suggest that more southern populations are not inherently able to survive the conditions in the northern Great Basin, and highlight the importance of field studies to identify barriers to assisted gene flow
Using population ecology to inform the conservation of Nevada’s rare plants
No full textPopulation ecology is a fundamental tenet of conservation biology. Estimating population size is a necessary first step in assessing species vulnerability, and to the subsequent examination of population viability, prediction of extinction risks, and evaluation of conservation objectives. Population censuses and demographic monitoring are important tools in illuminating overall population trajectories a species face, as well as reveal the mechanisms behind those trends. Plant species are facing a global biodiversity crisis, with almost two in five species of vascular plants at risk for extinction. Rare plants make up a nontrivial portion of that global diversity, but are disproportionately threatened by global change. Therefore, it is critical to effectively estimate population size as well as understand the drivers of rare plant populations in order to protect biodiversity globally. However, because species are often aggregated across landscapes, precisely estimating total population size can be surprisingly challenging. Incorporating this spatial heterogeneity into estimates of population size is necessary to increase confidence in population estimates. Methods in design-based approaches have attempted this by altering sampling designs to account for heterogeneity, however model-based approaches could also be useful to estimate population size of heterogeneously distributed species but have so far not been examined. In chapter 1, I tested the ability of a model-based approach to accurately estimate population size. I simulated several heterogeneous landscapes with various levels of autocorrelation and then sampled those landscapes with differing scenarios of sampling effort. I then used a Gaussian process model in a Bayesian framework to make predictions of population density in unsampled areas. I found that I was successfully able to recover total population size of landscapes that had high to mid-levels of autocorrelation regardless of sampling effort, but decreased sampling effort lead to wider uncertainty around population estimates. These results highlight the promise for model-based approaches utility in estimating population size of sessile species with heterogenous distributions. Future research should combine design and model-based approaches to increase precision of population size estimates.
Understanding the drivers of population trends is important in conservation of rare species, as well as in the ability to anticipate threats in how already vulnerable species may respond to global change. Both disturbance and climate have been shown to affect the population dynamics of plants, but the interaction between the two has been minimally explored in the context of rare alpine plants. In chapter 2, I quantify how ski resort impacts and climate effect the population growth and demographics of a rare alpine endemic, Draba asterophora, across a long-term study conducted from 2010-2024. Although populations in ski areas have experienced past declines as a direct result of ski resort activities, I found that population trends of Draba asterophora in ski areas were not different from those in less developed areas over our study period. On the other hand, the best supported climate model showed negative effects of winter warming and late snowmelt, and positive effects of summer precipitation on population trends, with no interactions with ski area impacts. We observed that these populations are often driven by high survival, with low recruitment. Lastly, we found that despite population growth rates recovering following periods of decline circa 2015-2020, population sizes never fully recovered by the end of the study period. Our results highlight the risk that rare alpine plants face, where populations may be unlikely to recover from increasingly common unfavorable climatic periods