Recovery of Rare Earth Elements from Coal Fly Ash Using Ionic Liquids

Rare earth elements (REEs), the 15 lanthanides and Sc and Y, have played an invaluable role in the progress of clean energy technology and high-tech manufacturing in past decades. Their high demand and global scarcity have led to disruptions in supply, exacerbated by the fact that there are no adequate replacements. Thus, it is crucial to develop alternative sources to secure a steady supply of REEs. Coal fly ash (CFA), a byproduct of burning coal for electricity, may be one such source. Conventional REE-CFA recovery methods are energy and material intensive and leach elements indiscriminately, generating impure mixtures of REEs. Ionic liquids (ILs) may be one solution, but to date, they have not been applied to CFA. This dissertation focuses on the IL betainium bis(trifluoromethylsulfonyl)imide ([Hbet][Tf2N]) for preferential extraction of REEs from different CFAs. Efficient extraction relies on [Hbet][Tf2N]’s thermomorphic behavior with water: upon heating, water and the IL form a single liquid phase, and REEs are leached from CFA via a proton-exchange mechanism. Upon cooling, the water and IL separate, and leached elements partition between the IL and aqueous (AQ) phases. REEs were preferentially extracted over bulk elements from CFAs into the IL phase then recovered in a subsequent mild acid stripping step, regenerating the IL. Two optimizations, alkaline pretreatment and adding supplement betaine, significantly improved REE leaching efficiency and separation between REEs and bulk elements. Significantly, this method consistently exhibits a particularly high extraction efficiency for scandium. The IL extraction process yields a mildly acidic REE-rich solution contaminated with Fe. To address this, three strategies for limiting Fe coextraction into the IL phase were investigated: magnetic separation, alternative salts, and ascorbic acid reduction. The latter two methods proved successful and should be used to generate an REE-rich acidic solution with very low concentrations of Fe. To gain a better understanding of CFA leaching behavior with [Hbet][Tf2N], eighteen additional elements were studied (29 total). It was found that in the IL phase, bulk elements were found in low concentrations, trace elements were not found, and of the actinides, Th was extracted into the IL phase and U was not leached at all. Other important optimizations were also studied, including pH, temperature, and duration of leaching. The process is also compared to several published CFA solid extraction methods and CFA leacheate separation methods to place this dissertation in context with existing literature. Finally, a number of process sustainability improvements are recommended, including the use of microwave heating, water and IL recovery strategies, and beneficial uses of residual solids. Finally, two other ILs were studied along with [Hbet][Tf2N] to investigate the effect of IL’s cation functional group modifications. The two ILs possess the same anion [Tf2N], but one with a less acidic cation having an alcohol group, choline [Chol], and one with a more acidic cation having an alkyl sulfonic acid group, trimethylammoniumethane hydrogen sulfate ([N111C2OSO3H]), in comparison with [Hbet], which has a carboxyl group. [Chol][Tf2N] was broadly unsuccessful at leaching almost all elements from all CFA samples tested. [N111C2OSO3H][Tf2N] was more successful, achieving greater or comparable leaching efficiencies but was not able to separate REEs from bulk and trace constituents. Overall, the research outcome of this dissertation filled several knowledge gaps in REE recovery. The method presented is novel and is among the first to demonstrate direct application of an IL to solid CFA for efficient recovery of REEs. The recyclability of IL and mild extraction conditions offer significant advantages for environmental sustainability. Altogether, this thesis builds a foundation for new IL-based strategies for future extractions from CFA and other REE-rich wastes.Ph.D

Modeling Structure-Function Relationships in Synthetic DNA Sequences using Attribute Grammars

Recognizing that certain biological functions can be associated with specific DNA sequences has led various fields of biology to adopt the notion of the genetic part. This concept provides a finer level of granularity than the traditional notion of the gene. However, a method of formally relating how a set of parts relates to a function has not yet emerged. Synthetic biology both demands such a formalism and provides an ideal setting for testing hypotheses about relationships between DNA sequences and phenotypes beyond the gene-centric methods used in genetics. Attribute grammars are used in computer science to translate the text of a program source code into the computational operations it represents. By associating attributes with parts, modifying the value of these attributes using rules that describe the structure of DNA sequences, and using a multi-pass compilation process, it is possible to translate DNA sequences into molecular interaction network models. These capabilities are illustrated by simple example grammars expressing how gene expression rates are dependent upon single or multiple parts. The translation process is validated by systematically generating, translating, and simulating the phenotype of all the sequences in the design space generated by a small library of genetic parts. Attribute grammars represent a flexible framework connecting parts with models of biological function. They will be instrumental for building mathematical models of libraries of genetic constructs synthesized to characterize the function of genetic parts. This formalism is also expected to provide a solid foundation for the development of computer assisted design applications for synthetic biology

Connecting Land–Atmosphere Interactions to Surface Heterogeneity in CHEESEHEAD19

The Chequamegon Heterogeneous Ecosystem Energy-Balance Study Enabled by a High-Density Extensive Array of Detectors 2019 (CHEESEHEAD19) is an ongoing National Science Foundation project based on an intensive field campaign that occurred from June to October 2019. The purpose of the study is to examine how the atmospheric boundary layer (ABL) responds to spatial heterogeneity in surface energy fluxes. One of the main objectives is to test whether lack of energy balance closure measured by eddy covariance (EC) towers is related to mesoscale atmospheric processes. Finally, the project evaluates data-driven methods for scaling surface energy fluxes, with the aim to improve model–data comparison and integration. To address these questions, an extensive suite of ground, tower, profiling, and airborne instrumentation was deployed over a 10 km × 10 km domain of a heterogeneous forest ecosystem in the Chequamegon–Nicolet National Forest in northern Wisconsin, United States, centered on an existing 447-m tower that anchors an AmeriFlux/NOAA supersite (US-PFa/WLEF). The project deployed one of the world’s highest-density networks of above-canopy EC measurements of surface energy fluxes. This tower EC network was coupled with spatial measurements of EC fluxes from aircraft; maps of leaf and canopy properties derived from airborne spectroscopy, ground-based measurements of plant productivity, phenology, and physiology; and atmospheric profiles of wind, water vapor, and temperature using radar, sodar, lidar, microwave radiometers, infrared interferometers, and radiosondes. These observations are being used with large-eddy simulation and scaling experiments to better understand submesoscale processes and improve formulations of subgrid-scale processes in numerical weather and climate models

Vegetation type is an important predictor of the arctic summer land surface energy budget

Despite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994-2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm(-2)) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types.An international team of researchers finds high potential for improving climate projections by a more comprehensive treatment of largely ignored Arctic vegetation types, underscoring the importance of Arctic energy exchange measuring stations.Peer reviewe

Vegetation type is an important predictor of the arctic summer land surface energy budget

Despite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994–2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm−2) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types

Assessing and Modulating Kynurenine Pathway Dynamics in Huntington's Disease: Focus on Kynurenine 3-Monooxygenase.

The link between disturbances in kynurenine pathway (KP) metabolism and Huntington's disease (HD) pathogenesis has been explored for a number of years. Several novel genetic and pharmacological tools have recently been developed to modulate key regulatory steps in the KP such as the reaction catalyzed by the enzyme kynurenine 3-monooxygenase (KMO). This insight has offered new options for exploring the mechanistic link between this metabolic pathway and HD, and provided novel opportunities for the development of candidate drug-like compounds. Here, we present an overview of the field, focusing on some novel approaches for interrogating the pathway experimentally

Harmonized in-situ observations of surface energy fluxes and environmental drivers at 64 Arctic vegetation and glacier sites - Metadata

Despite the importance of surface energy budgets (SEBs) for land-climate interactions in the Arctic, uncertainties in their prediction persist. In situ observational data of SEB components - useful for research and model validation - are collected at relatively few sites across the terrestrial Arctic, and not all available datasets are readily interoperable. Furthermore, the terrestrial Arctic consists of a diversity of vegetation types, which are generally not well represented in land surface schemes of current Earth system models. This dataset contains metadata information about surface energy budget components measured at 64 tundra and glacier sites >60° N across the Arctic. This information was taken from the open-access repositories FLUXNET, Ameriflux, AON, GC-Net and PROMICE. The contained datasets are associated with the publication vegetation type as an important predictor of the Arctic Summer Land Surface Energy Budget by Oehri et al. 2022, and intended to support research of surface energy budgets and their relationship with environmental conditions, in particular vegetation characteristics across the terrestrial Arctic

Literature synthesis data of surface energy fluxes and environmental drivers from Arctic vegetation and glacier sites

Despite the importance of surface energy budgets (SEBs) for land-climate interactions in the Arctic, uncertainties in their prediction persist. In situ observational data of SEB components - useful for research and model validation - are collected at relatively few sites across the terrestrial Arctic, and not all available datasets are readily interoperable. Furthermore, the terrestrial Arctic consists of a diversity of vegetation types, which are generally not well represented in land surface schemes of current Earth system models. This dataset describes the data generated in a literature synthesis, covering 358 study sites on vegetation or glacier (>=60°N latitude), which contained surface energy budget observations. The literature synthesis comprised 148 publications searched on the ISI Web of Science Core Collection

Harmonized in-situ observations of surface energy fluxes and environmental drivers at 64 Arctic vegetation and glacier sites - Surface energy budget componenent data

Despite the importance of surface energy budgets (SEBs) for land-climate interactions in the Arctic, uncertainties in their prediction persist. In situ observational data of SEB components - useful for research and model validation - are collected at relatively few sites across the terrestrial Arctic, and not all available datasets are readily interoperable. Furthermore, the terrestrial Arctic consists of a diversity of vegetation types, which are generally not well represented in land surface schemes of current Earth system models. This dataset comprises harmonized, standardized and aggregated in-situ observations of surface energy budget components measured at 64 sites on vegetated and glaciated sites north of 60° latitude, in the time period from 1994 till 2021. The surface energy budget components include net radiation, sensible heat flux, latent heat flux, ground heat flux, net shortwave radiation, net longwave radiation, surface temperature and albedo, which were aggregated to daily mean, minimum and maximum values from hourly and half-hourly measurements. Data were retrieved from the monitoring networks FLUXNET, AmeriFlux, AON, GC-Net and PROMICE