Water splitting is important to a green energy future. Current issues with efficient water splitting include degradation of the fuel cell materials, thermal expansion, and transport through the material. Precise control of nanomaterial composition and morphology are among a materials scientist's tools to design novel low-cost and efficient materials. One way to improve material performance through controlling the composition is to create a high entropy oxide. There has been great interest in high entropy oxide systems because of the ability to combine multiple well-performing cations into one oxide phase, taking advantage of the synergistic effect. This work focuses on Ba, Sr, Ca, Co, Fe, and Mn cations (promising candidates for solid oxide fuel cell electrodes) in the perovskite ABO3 structure. Controlling the synthesis method to achieve single-phase, high entropy materials and maintaining nanomorphology will be discussed in this presentation. Aerogel synthesis is done in an autoclave with pseudo supercritical fluid drying, which allows immediate departure of the solvent and promotes nanomaterial production, resulting in a dry powder. However, subsequent calcination steps to achieve a single-phase oxide often sinters the materials, which removes the desired morphology. Different morphologies are of interest to be used in solid oxide fuel cells because it may improve performance depending on the unique surfaces that are exposed with different free energies.

Updates to the EPA's Greenhouse Gas Reporting Program Subpart W will come into effect in January 2025, which include a requirement to report all "maintenance or abnormal emission events." Estimating the duration of emission events is critical for accurate reporting, as the total emitted volume depends heavily on the length of the emission. If an operator is unable to estimate a start and end date for a given emission, a duration of 6 months must be assumed. Infrequent sampling surveys via, e.g., an airplane can provide rough estimates of emission duration, but the minimum duration estimate from this method is bounded by the sampling frequency, which is often quarterly at best. Continuous monitoring systems (CMS), on the other hand, measure methane concentrations in near-real time and hence provide a promising avenue for more robust, measurement-informed emission duration estimates. Here we present a method for creating duration estimates using CMS data. Our proposed method uses a gradient-based spike detection algorithm to cluster enhancements in the concentration time series into events and quantifies uncertainty by assessing the information content of the underlying concentration data as a function of wind direction. We present an evaluation of the method on controlled release data and apply it to a production oil and gas site in the Appalachian basin. We compare duration estimates from our method to estimates provided by infrequent aerial sampling.

In geostatistics, traditional spatial models often rely on the Gaussian Process (GP) to fit stationary covariances to data. It is well known that this approach becomes computationally infeasible when dealing with large data volumes, necessitating the use of approximate methods. A powerful class of methods approximate the GP as a sum of basis functions with random coefficients. Although this technique offers computational efficiency, it does not inherently guarantee a stationary covariance. To mitigate this issue, the basis functions can be "normalized" to maintain a constant marginal variance, avoiding unwanted artifacts and edge effects. This allows for the fitting of nearly stationary models to large, potentially non-stationary datasets, providing a rigorous base to extend to more complex problems. Unfortunately, the process of normalizing these basis functions is computationally demanding. To address this, we introduce two fast and accurate algorithms for the normalization step, allowing for efficient prediction on fine grids. The practical value of these algorithms is showcased on both simulated and observed climate data, where significant computational speedups are achieved. While implementation and testing is done specifically within the LatticeKrig framework, these algorithms could be adapted to other basis function methods operating on regular grids.

Acid mine drainage (AMD) and acid rock drainage (ARD) pose significant environmental challenges, as the acidic, metal-laden drainage seeps into surface and groundwater systems, often resulting in substantial ecological damage. The hyporheic zone, where surface and groundwater meet, serves as a natural filtration system, where biogeochemical reactions occur that influence metal retention and transformation. By analyzing changes in metal concentrations and phases throughout time and space, valuable information can be gained in regards to the mechanisms at work within the hyporheic zone. This knowledge is critical for the development of remediation plans for AMD and ARD affected sites, such as Coal Creek, the source of drinking water for the town of Crested Butte, Colorado. The ability to protect the potability of Coal Creek is vital for both safeguarding public health as well as maintaining ecosystem integrity. In order to better understand the complexities of this dynamic system, hyporheic sediment and sediment from planted control soil columns were sampled on a seasonal basis. Samples were analyzed for phase changes via XRD and sequential extractions created using the samples were analyzed via ICP-OES for elemental fraction concentrations. Preliminary results show the retention and release of metals, particularly iron, through various phase changes occurring within the hyporheic zone. These changes are seasonally dynamic and vary from site to site along the creek, illustrating the capacity of the hyporheic zone to act as a filter for AMD at different points throughout the year.

Modern technologies are heavily dependent on the critical material (CM) used to construct them. Emerging CMI research evaluates the effectiveness of new recovery and treatment processes, but there is some concern about the waste generated from these efforts. Our project goal is to assess the environmental toxicity of the newly developed CM processing and recovery technologies to avoid producing emerging environmental contaminants. Our experimental platform includes a series of ecological toxicity tests to assess the potential environmental impacts of new critical material recovery or recycling technologies. This will include rare earth element complexing DGAs such as TODGA, DGA6, DMODGA, and the process-relevant solvents, Isopar-L and 1-octanol. The ecotoxicity indicators chosen include the wastewater bacerium Nitrosomonas europaea, the small crustacean Daphnia magna, and the green alga Raphidocelis subcapitata (formerly known as Selenastrum capricornutum). Preliminary data on the ecotoxicity impacts of DGAs and a comparative analysis of complexants will be presented. This data will be benchmarked against the current standard of CM recovery that uses reagent PC-88A. This knowledge can be used to identify critical material processing techniques with a lower impact and / or waste remediation strategies to reduce environmental toxicity. Our project benefits society by providing a basis for understanding how critical material recovery affects the environment and how remediation strategies can aid in the detoxification of processing waste.

Ancient lakes on Mars and the deltas that occur along their shorelines offer attractive targets for mission landing sites due to their habitability and biosignature preservation potential. Furthermore, the presence of deltas is used to map paleoshorelines for paleo-oceans and lakes on Mars. Jezero Crater was chosen as the NASA Perseverance landing site because the fan-shaped channel network here was interpreted as a delta. However, on Earth, fan-shaped channel networks may also form in fluvial fans which are inland terrestrial landforms that can form 1000s of kilometers from shorelines. We demonstrate that morphometric criteria are needed to identify fan-shaped landforms for potential future landing sites accurately. The goal of this research project is to differentiate deltas and fluvial fans on Mars by quantifying fan-shaped paleochannel network morphometrics. We map Martian fan-shaped paleochannel networks using images from the Mars Reconnaissance Orbiter (MRO) photomosaics using ArcGIS. The outcomes of this project will improve our ability to choose appropriate landing sites in search of life and to map paleo-shorelines on Mars. Preliminary results suggest that most fan-shaped channel networks on Mars resemble fluvial fans, while the channel network at the Eberswalde crater resembles a delta. Fluvial fan formation has been linked to large sediment and water discharges, and to fluctuations in discharge because of highly seasonal precipitation in climatic settings that promote marked seasonal and interannual hydrological changes, leading to variable discharge regimes and exceptional flood events. Alternative evidence is required to identify paleo-shorelines as fluvial fans may also form along shorelines.