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  1. Metabolic flux, metabolite, and transcript analysis uncover reprogramming of metabolism toward higher seed oil

    Overexpression of WRINKLED1 (WRI1), a master regulator of glycolysis and fatty acid biosynthesis, together with DIACYLGLYCEROL ACYLTRANSFERASE1 (DGAT1), which catalyzes the final step of triacylglycerol assembly, is a promising strategy for enhancing seed oil content. However, how these regulators coordinate system-wide metabolic reprogramming at the levels of gene expression, metabolite pools, and fluxes remains poorly understood. To address this, we performed 13C-metabolic flux analysis, metabolomics, and transcriptomics on in vitro cultured pennycress (Thlaspi arvense L.) embryos overexpressing the native WRI1 and DGAT1 homologs. Here, in cultured embryos, WRI1/DGAT1 overexpression increased triacylglycerol accumulation by 28% while reducing protein content by 34%,more » relative to the wild type. Embryos showed ∼20-fold and 50-fold upregulation of WRI1 and DGAT1 along with induction of WRI1 target genes in glycolysis and fatty acid biosynthesis. Genes associated with photosynthesis and Calvin cycle functions were also upregulated, whereas genes encoding ribosomal proteins and seed storage proteins were strongly repressed, consistent with the observed lipid–protein tradeoff. Flux analysis revealed that enhanced triacylglycerol biosynthesis is supported by increased flux through the Rubisco shunt and cytosolic pyruvate kinase, while the oxidative pentose phosphate pathway and malic enzyme contributed little to NADPH or pyruvate supply. Metabolomic profiling revealed extensive perturbations in glycolytic intermediates, tricarboxylic acid cycle metabolites, and amino acids. In plant grown seeds, WRI1/DGAT1 lines also showed a modest but significant increase in total lipid content. Collectively, these findings reveal how WRI1 and DGAT1 reprogram central metabolism to enhance oil accumulation, with relevance to mature seeds.« less
  2. Evaluating opportunity for distributed wind energy in rural and agricultural areas

    Wind energy is among the most mature renewable energy technologies, accounting for 11% of the current US electricity generation in 2024, with the lowest average levelized cost. While it is known that substantial opportunity exists for further development, a key question has been where wind energy is best suited compared to other technologies. This study leverages an immense dataset of parcel-resolved technoeconomic potential for the contiguous United States, focusing on distributed wind (DW) energy—a configuration where one or more turbines, typically 30–60 m in height are used to satisfy nearby energy needs. The analysis is conducted at multiple spatial scalesmore » and considers land use, crop land, census, and incentive program data to determine the most opportune areas for market development. The results show that rural, agricultural and residential areas are most suited to DW. Connection type (in front of, or behind the meter) and regulations determine the best application, while siting constraints, economics, demand and the wind resource determines the optimal size of turbine.« less
  3. Geochemical Assessment for Carbon Sequestration in the Conasauga Group, Northwest Georgia, USA

    Sedimentary geological formations are known to be great candidates for geological carbon sequestration. Published studies suggest the southeast of the United States contains many formations suitable for carbon storage. The Cassville 1 Stratigraphic Borehole well could act as a potential carbon reservoir for nearby energy resource facilities in Georgia, United States. Although studies have shown that porous formations are adequate for geological carbon sequestration, it is important to understand possible geochemical reactions between CO2 and the targeted geological formation before injecting any fluids. In this study, a sandstone sample from the Cassville 1 well is being considered for geological carbonmore » sequestration in the Conasauga Group in Northwest Georgia. Here, the collected sandstone sample, consisting of quartz, K-feldspar, micas, kaolinite, and carbonate minerals such as calcite and dolomite, has a 6% porosity. Leveraging the formation composition and porosity, a one-dimensional continuum reactive transport model was built using CrunchFlow to assess possible geochemical reactions between injected CO2 and the geological formation. Simulation results show that the carbonate minerals, calcite and dolomite, dissolve during the injection period of 10,000 days, increasing formation porosity from 6% to as much as 30%. The rate and extent of carbonate mineral dissolution and resulting porosity increase are highly sensitive to mineral reactive surface area values. No evidence of mineral precipitation was observed, suggesting that dissolution reactions will control porosity evolution during the CO2 injection period.« less
  4. Automated pipeline processing X-ray diffraction data from dynamic compression experiments on the Extreme Conditions Beamline of PETRA III

    Presented and discussed here is the implementation of a software solution that provides prompt X-ray diffraction data analysis during fast dynamic compression experiments conducted within the dynamic diamond anvil cell technique. It includes efficient data collection, streaming of data and metadata to a high-performance cluster (HPC), fast azimuthal data integration on the cluster, and tools for controlling the data processing steps and visualizing the data using the DIOPTAS software package. This data processing pipeline is invaluable for a great number of studies. The potential of the pipeline is illustrated with two examples of data collected on ammonia–water mixtures and multiphasemore » mineral assemblies under high pressure. The pipeline is designed to be generic in nature and could be readily adapted to provide rapid feedback for many other X-ray diffraction techniques, e.g. large-volume press studies, in situ stress/strain studies, phase transformation studies, chemical reactions studied with high-resolution diffraction etc.« less
  5. A Review of Coupled Geochemical–Geomechanical Impacts in Subsurface CO2, H2, and Air Storage Systems

    Increased demand for decarbonization and renewable energy has led to increasing interest in engineered subsurface storage systems for large-scale carbon reduction and energy storage. In these applications, a working fluid (CO2, H2, air, etc.) is injected into a deep formation for permanent sequestration or seasonal energy storage. The heterogeneous nature of the porous formation and the fluid–rock interactions introduce complexity and uncertainty in the fate of the injected component and host formations in these applications. Interactions between the working gas, native brine, and formation mineralogy must be adequately assessed to evaluate the efficiency, risk, and viability of a particular storagemore » site and operational regime. This study reviews the current state of knowledge about coupled geochemical–geomechanical impacts in geologic carbon sequestration (GCS), underground hydrogen storage (UHS), and compressed air energy storage (CAES) systems involving the injection of CO2, H2, and air. Specific review topics include (1) existing injection induced geochemical reactions in these systems; (2) the impact of these reactions on the porosity and permeability of host formation; (3) the impact of these reactions on the mechanical properties of host formation; and (4) the investigation of geochemical-geomechanical process in pilot scale GCS. This study helps to facilitate an understanding of the potential geochemical–geomechanical risks involved in different subsurface energy storage systems and highlights future research needs.« less
  6. Alternate Analysis of an In Vitro Solubility Study on the Lung Dissolution Rate of 238PuO2 Material Involved in the 2020 Incident at Los Alamos National Laboratory

    Here this work presents an alternate analysis of an in vitro solubility study on the lung dissolution rate of 238PuO2 material involved in a recent inhalation incident at Los Alamos National Laboratory (LANL). The original dataset used in this work was retrieved from a recently published report. The present work shows an analysis of the same dataset by modeling the dissolution in separate time intervals rather than modeling the cumulative dissolution.
  7. Can machine learning accelerate process understanding and decision‐relevant predictions of river water quality?

    Abstract The global decline of water quality in rivers and streams has resulted in a pressing need to design new watershed management strategies. Water quality can be affected by multiple stressors including population growth, land use change, global warming, and extreme events, with repercussions on human and ecosystem health. A scientific understanding of factors affecting riverine water quality and predictions at local to regional scales, and at sub‐daily to decadal timescales are needed for optimal management of watersheds and river basins. Here, we discuss how machine learning (ML) can enable development of more accurate, computationally tractable, and scalable models formore » analysis and predictions of river water quality. We review relevant state‐of‐the art applications of ML for water quality models and discuss opportunities to improve the use of ML with emerging computational and mathematical methods for model selection, hyperparameter optimization, incorporating process knowledge into ML models, improving explainablity, uncertainty quantification, and model‐data integration. We then present considerations for using ML to address water quality problems given their scale and complexity, available data and computational resources, and stakeholder needs. When combined with decades of process understanding, interdisciplinary advances in knowledge‐guided ML, information theory, data integration, and analytics can help address fundamental science questions and enable decision‐relevant predictions of riverine water quality.« less
  8. An ad hoc performance comparison of candidate technologies for rural broadband deployment

    The need for network connectivity in rural and underserved areas is well known. An ad hoc comparison of data throughput for various broadband technologies is reported.
  9. Preliminary Thermoluminescent Dosimeter Glow Curve Analysis with Automated Glow Peak Identification for LiF Mg,Ti

    When appropriately analyzed, thermoluminescent dosimeter glow curve analysis allows for improved quantification of thermoluminescent material behavior while flagging abnormalities. The mathematical separation of a glow curve into contributions from energetically unique trap states, or glow curve analysis, may be used to remove undesired effects of signal fading for complex materials. A generalized glow curve analysis software for the separation of glow curves is presented in this paper. Written in C++, the software uses the first-order kinetics model with automatic peak identification. The automatic identification of peaks is achieved through a unique peak-finding algorithm. Here, the program was performance tested usingmore » experimental glow curve data from LiF:Mg,Ti, and comparative results are presented.« less
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