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At least 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Groundwater Monitoring Report, U.S. Department of Energy Y-12 National Security Complex, Oak Ridge, Tennessee

This report contains the groundwater and surface water monitoring data obtained during calendar year (CY) 2019 at the U.S. Department of Energy (DOE) Y-12 National Security Complex (Y-12) on the DOE Oak Ridge Reservation (ORR) in Oak Ridge, Tennessee. The monitoring data were obtained from wells, springs, and surface water sampling locations in three hydrogeologic regimes at Y-12. The Bear Creek Hydrogeologic Regime (Bear Creek Regime) encompasses a section of Bear Creek Valley (BCV) between the west end of Y-12 and the west end of the Bear Creek Watershed (directions are in reference to the Y-12 grid system, shown as Plant North. The Upper East Fork Poplar Creek Hydrogeologic Regime (East Fork Regime) encompasses the Y-12 industrial facilities and support structures in BCV. The Chestnut Ridge Hydrogeologic Regime (Chestnut Ridge Regime) encompasses a section of Chestnut Ridge directly south of Y-12. Background information in Section 2 of this report outlines the hydrogeologic framework for groundwater and surface water quality monitoring at Y-12 and includes an overview of the groundwater contamination in each hydrogeologic regime. Section 3 provides details regarding the groundwater and surface water sampling and analysis activities implemented under the Y-12 GWPP, including sampling locations and frequency, sample collection and handling, field measurements and laboratory analytes, quality assurance (QA)/quality control (QC) sampling, data management, and data quality assessment (DQA). However, the equivalent QA/QC or DQA information for the groundwater and surface water data associated with the monitoring programs implemented by UCOR are not included in this report and instead are deferred to referenced programmatic plans and reports issued by OREM and UCOR. Section 4 of this report presents a summary evaluation of the CY 2019 monitoring data with regard to the respective objectives of surveillance monitoring and exit pathway/perimeter monitoring. The evaluation is based primarily on the analytical results for the following principal groundwater contaminants at Y-12: nitrate, uranium, gross alpha activity, gross beta activity, and volatile organic compounds (VOCs). Section 5 summarizes the most significant findings with respect to the principal contaminants along with recommendations for any proposed changes to the ongoing groundwater and surface water quality monitoring performed under the Y-12 GWPP. Technical reports and plans cited in the narrative sections of the report are listed in Section 6. Narrative sections of this report reference several appendices. Figures (maps and diagrams) and data tables (excluding data summary tables incorporated in the narrative sections) are in Appendix A and Appendix B, respectively. Appendix C contains construction details for each well sampled during CY 2019 by either the Y-12 GWPP or UCOR, along with schematic diagrams for wells equipped with Westbay™ multiport sampling equipment or Barcad® pump systems. Appendix D supports the background summary discussion in Section 2 and provides more detailed information about the hydrogeologic framework for groundwater and surface water monitoring at Y-12, including the primary sources of groundwater contamination in each hydrogeologic regime. Results for all field measurements and laboratory analyses obtained by the Y-12 GWPP and UCOR are presented in Appendix E, which also includes the sample numbers for the QA/QC samples associated with groundwater and surface water monitoring performed by the Y-12 GWPP.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Evaluating the Utility of Permethylated Polysaccharide Solution NMR Data for Characterization of Insoluble Plant Cell Wall Polysaccharides

Plant cell wall polysaccharide analysis encompasses the utilization of a variety of analytical tools, including gas and liquid chromatography, mass spectrometry (MS), and nuclear magnetic resonance (NMR) spectroscopy. These methods provide complementary data, which enable confident structural proposals of the many complex polysaccharide structures that exist in the complex matrices of plant cell walls. However, cell walls contain fractions of varying solubilities, and a few techniques are available that can analyze all fractions simultaneously. We have discovered that permethylation affords the complete dissolution of both soluble and insoluble polysaccharide fractions of plant cell walls in organic solvents such as chloroform or acetonitrile, which can then be analyzed by a number of analytical techniques including MS and NMR. In this work, NMR structure analysis of 10 permethylated polysaccharide standards was undertaken to generate chemical shift data providing insights into spectral changes that result from permethylation of polysaccharide residues. This information is of especial relevance to the structure analysis of insoluble polysaccharide materials that otherwise are not easily investigated by solution-state NMR methodologies. The preassigned NMR chemical shift data is shown to be vital for NMR structure analysis of minor polysaccharide components of plant cell walls that are particularly difficult to assign by NMR correlation data alone. With the assigned chemical shift data, we analyzed the permethylated samples of destarched, alcohol-insoluble residues of switchgrass and poplar by two-dimensional NMR spectral profiling. Thus, we identified, in addition to the major polysaccharide components, two minor polysaccharides, namely, <5% 3-linked arabinoxylan (switchgrass) and <2% glucomannan (poplar). In particular, the position of the arabinose residue in the arabinoxylan of the switchgrass sample was confidently assigned based on chemical shift values, which are highly sensitive to local chemical environments. Furthermore, the high resolution afforded by the 1H NMR spectra of the permethylated switchgrass and poplar samples allowed facile relative quantitative analysis of their polysaccharide composition, utilizing only a few milligrams of the cell wall material. As a result, the concepts herein developed will thus facilitate NMR structure analysis of insoluble plant cell wall polysaccharides, more so of minor cell wall components that are especially challenging to analyze with current methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

High Semi-Volatile Organic Aerosol Contributions Associated with Ammonium Nitrate in the Coastal Urban Environment

Organic components often contribute 50% or more of the submicron aerosol mass in coastal urban environments, but their partitioning between the gas and particle phases is controlled by a complex mixture of unidentified organic compounds that are poorly constrained by observations. This study compares daily filter organic functional groups (OFG) with online organic mass fragments from La Jolla, California, as part of the Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE), quantifying the contributions of four types of non-volatile (NV) organic emission sources to the submicron composition. Daily filters retained only 0.79–0.98 µg/m3 NV submicron organic mass concentration, even though 1.8–1.9 µg/m3 non-refractory (NR) submicron organic mass concentration was measured online. The 62–64% of measured NR submicron organic mass concentration that exceeded what remained on the filters after 23-hr sampling is interpreted as semi-volatile, consistent with the moderate correlation of the NR NV difference to NR ammonium, NR nitrate, and biomass burning-related NV and NR organic factors. The association between semi-volatile organic components and ammonium nitrate likely results from both co-emission and co-evaporation. Size-resolved filter analysis showed that NV organic mass concentration accounts for 68% of NR organic mass concentration for 0.5–1 µm dry diameter but account for 9.0% for 0.18–0.5 µm dry diameter showing the differences in volatility between particle modes. Importantly, volatility of organic components was size-dependent Information Classification: General and associated with ammonium nitrate and biomass burning, providing guidance for constraining atmospheric aerosol properties in global models.

Pelayo, Christian↗
DOE OSTI2022

Irradiation of Sintered Mo Disks with Presence of Organic Impurities in He Gas Flow

Argonne National Laboratory (Argonne) is assisting NorthStar Medical Technologies in the development of a domestic supply of 99 Mo. Specifically, the present study focuses on the production of 99 Mo-feed solution used by the RadioGenix™ 99m Tc generator. During the target-irradiation phase of production, impurities can potentially be introduced into the feed, and can lead to disturbance of ligand- 99m Tc complexation chemistry and contamination of the final radiopharmaceutical that directly interacts with the patient. To address this issue, Argonne performed irradiations and chemical processing to identify whether the potential contamination of He flow with hydrocarbon oil during irradiation affects the radiochemical purity of the final K 2 MoO 4 (K 2 TcO 4 ) in 5M KOH solution. To mimic the conditions of real irradiation at NorthStar, Argonne used its electron linear accelerator and Van de Graaff facilities, heated the target and oil source to >800°C, and controlled oxygen in the presence of He during irradiation. Following irradiation, scanning electron microscopy (SEM) and carbon analysis (CA) were used to detect carbon contamination on the solid targets. The radiochemical purity of the dissolved targets was studied via thin-layer paper chromatography (TLC). As a result of these experiments, small regions of the surface of some irradiated disks were found to be high in carbon, but the total carbon content was still negligible in comparison to the reference sample, which had experienced no irradiation or contact with oil. The summarized results from the SEM, CA, and TLC tests lead to the conclusion that even an excess of oil and heating during irradiation do not affect the radiochemical purity of the final product.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2021

Explaining and predicting human behavior and social dynamics in simulated virtual worlds: reproducibility, generalizability, and robustness of causal discovery methods

Ground Truth program was designed to evaluate social science modeling approaches using simulation test beds with ground truth intentionally and systematically embedded to understand and model complex Human Domain systems and their dynamics Lazer et al. (Science 369:1060–1062, 2020). Our multidisciplinary team of data scientists, statisticians, experts in Artificial Intelligence (AI) and visual analytics had a unique role on the program to investigate accuracy, reproducibility, generalizability, and robustness of the state-of-the-art (SOTA) causal structure learning approaches applied to fully observed and sampled simulated data across virtual worlds. In addition, we analyzed the feasibility of using machine learning models to predict future social behavior with and without causal knowledge explicitly embedded. In this paper, we first present our causal modeling approach to discover the causal structure of four virtual worlds produced by the simulation teams—Urban Life, Financial Governance, Disaster and Geopolitical Conflict. Our approach adapts the state-of-the-art causal discovery (including ensemble models), machine learning, data analytics, and visualization techniques to allow a human-machine team to reverse-engineer the true causal relations from sampled and fully observed data. We next present our reproducibility analysis of two research methods team’s performance using a range of causal discovery models applied to both sampled and fully observed data, and analyze their effectiveness and limitations. We further investigate the generalizability and robustness to sampling of the SOTA causal discovery approaches on additional simulated datasets with known ground truth. Our results reveal the limitations of existing causal modeling approaches when applied to large-scale, noisy, high-dimensional data with unobserved variables and unknown relationships between them. We show that the SOTA causal models explored in our experiments are not designed to take advantage from vasts amounts of data and have difficulty recovering ground truth when latent confounders are present; they do not generalize well across simulation scenarios and are not robust to sampling; they are vulnerable to data and modeling assumptions, and therefore, the results are hard to reproduce. Finally, when we outline lessons learned and provide recommendations to improve models for causal discovery and prediction of human social behavior from observational data, we highlight the importance of learning data to knowledge representations or transformations to improve causal discovery and describe the benefit of causal feature selection for predictive and prescriptive modeling.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Development of Multiresolution Capabilities for the Holistic Energy Resource Optimization Network (HERON) tool A progress update

INL researchers work on technoeconomic analyses for integrated energy systems (IES) using the Framework for Optimization of ResourCes and Economics (FORCE). Within FORCE, researchers use the Holistic Energy Resource Optimization Network (HERON) tool to conduct optimization of grid portfolios under uncertain market conditions. These optimizations determine optimal capacities for all IES components and strategies for resource dispatch which maximize some economic metric (e.g., net present value). Resource dispatch occurs on finer timescales (typically hours) and thus are asked to respond to a given time series (e.g. hourly load demand profiles for a grid, or pre-determined electricity prices). Volatile and complex bidding dynamics as well as poorly forecasted weather events within deregulated markets add uncertainty to the time series; FORCE can address this uncertainty by training a reduced order model on historical time series and generate unique synthetic time series which represent individual scenarios or realizations of the market. The IES configuration can be simulated under these different sampled realizations and a stochastic optimization is conducted which optimizes the expected value of the desired economic metric. The training of a synthetic time series generator is limited by the chosen time resolution; dynamics can occur on different time scales. Seasonal demand trends can dominate faster dynamical events (such as power outages from certain sectors or severe weather events) which might not get captured correctly by the trained model. In this report, we investigate different ways of addressing the training and generation of time series on multiple time scales using three main algorithms: wavelet decomposition, dynamic mode decomposition, and generative adversarial networks for time series. We demonstrate a time series analysis that yields information on not just the frequency space but also temporal space: where a fast Fourier transform can provide what frequencies dominate, the new algorithms can provide when the frequencies dominate as well. These analyses can help improve IES optimization by allowing researchers to couple simulations at different timescales when it is most needed - seasonal, day-ahead, and real time optimization - with greater computational efficiency. Future work will include implementation of a subset of the proposed algorithms into the FORCE toolset and application of these analyses into multiple timescale optimization.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Optical vibrational spectroscopic signatures of ammonium diuranate process parameters

Ammonium diuranate (ADU) is commonly encountered in the nuclear fuel cycle; however, previous investigations have shown that ADU is a complex mixture of distinct compounds. Moreover, production parameters are known to heavily influence the composition of the resulting ADU. Here, we examine four samples of ADU prepared at Oak Ridge National Laboratory (ORNL), and one sample of ADU made at Pacific Northwest National Laboratory (PNNL), with the goal of further characterizing and elucidating the effect of processing parameters such as stir rate, strike direction, and temperature on material composition. Process parameters during ADU precipitation at ORNL and PNNL were well documented, and we relate process variables to optical vibrational spectroscopic signatures observed using Raman and infrared (IR) spectroscopy. In addition, powder X-ray diffraction (PXRD) reveals differences in the solid-phase composition of ADU precipitates, but we find that the primary phase is similar to the uranyl oxyhydroxyhydrate mineral metaschoepite. Despite the significant phase contributions of a metaschoepite-like phase, spectroscopic evidence of both nitrate and ammonium are observed for all samples. To gain a more holistic understanding of spectroscopic features of process parameters in ADU, principal component analysis (PCA) is employed and results in observable signatures that relate to the stir rate used during synthesis. These results provide further information about the process-dependence of ADU precipitate composition.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Brought to Light. I. Quantification of Disk Substructure in Dwarf Early-type Galaxies

Dwarf early-type galaxies (ETGs) display a rich diversity in their photometric, structural, and dynamical properties. In this work, we address their structural complexity by studying with deep imaging a sample of nine dwarf ETGs from the Virgo galaxy cluster, characterized by having faint disk features such as bars and spiral arms, that lie mostly hidden within the bright diffuse light of the galaxies. We present a new, robust method that aims to identify and extract the disk substructure embedded in these dwarf ETGs. The method consists in an iterative procedure that gradually separates a galaxy image into two components: the bright, dominant, diffuse component, and the much fainter, underlying disk component. By applying it to the dwarf ETG sample, we quantify their disk substructure and find that its relative contribution to the total galaxy light ranges between 2.2% and 6.4% within two effective radii. We test the reliability of the method, and prove that it is accurate in recovering the disk substructure we introduce in mock galaxy images, even at low disk-to-total light fractions of a few percent. As a potential application of the method, we perform a Fourier analysis on the extracted disk substructures and measure the orientation, length, and strength of the bars, as well as the pitch angle and strength of the spiral arms. We also briefly discuss a scenario based on the numerical simulations presented in our companion paper, Brought to Light II: Smith et al., in which we investigate the origins of the substructure in such dwarf systems.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Microphysics of liquid water in sub-10 nm ultrafine aerosol particles

Abstract. Ultrafine aerosol particles with sizes smaller than 50 nm have been shown in recent studies to serve as a large source of cloud condensation nuclei that can promote additional cloud droplet formation under supersaturation conditions. Knowledge of the microphysics of liquid water in these droplets remains limited, particularly in the sub-10 nm particle size range, due to experimental and theoretical challenges associated with the complexity of aerosol components and the small length scales of interest (e.g., difficulty of precisely sampling the liquid–air interface, questionable validity of mean-field theoretical representations). Here, we carried out molecular dynamics (MD) simulations of aerosol particles with diameters between 1 and 10 nm and characterized atomistic-level structure and water dynamics in well-mixed and phase-separated systems with different particle sizes, NaCl salinities, and pimelic acid (PML) organic surface loadings as a function of distance from the time-averaged Gibbs dividing interface or instantaneous water–air interface. We define a sphericity factor (ϕ) that can shed light on the phase-mixing state of nanodroplets, and we reveal an unexpected dependence of mixing state on droplet size. Our results also evidence an ion concentration enhancement in ultrafine aerosols, which should modulate salt nucleation kinetics in sub-10 nm droplets, and provide detailed characterization of the influence of droplet size on surface tension and on water self-diffusivity near the interface. Analysis of water evaporation free energy and water activity demonstrates the validity of the Kelvin equation and Köhler theory at droplet sizes larger than 4 nm under moderate salinities and organic loadings and the need for further extension to account for ion concentration enhancement in sub-10 nm aerosols, droplet-size-dependent phase separation effects, and a sharp decrease in the cohesiveness of liquid water in sub-4 nm droplets. Finally, we show that an idealized fractional surface coating factor (fs) can be used to categorize and reconcile water accommodation coefficients (α*) observed in MD simulations and experimental results in the presence of organic coatings, and we resolve the droplet size dependence of α*.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Geochemical Changes in Response to CO 2 Injection in a CO 2 -EOR Complex in Northern Michigan (Volume II.1)

The Midwest Regional Carbon Sequestration Partnership (MRCSP) was founded in 2003 as part of the U.S. Department of Energy’s (DOE’s) Regional Carbon Sequestration Partnership initiative. Since its founding, MRCSP has made significant strides toward making CCUS a viable option for states in the region. The public/private consortium, funded through the DOE Regional Carbon Sequestration Initiative, brings together nearly 40 industry partners and 10 states. Battelle, as the project lead, oversees research, development and operations and coordinates activities among the partners. The incremental, phased approach has built a valuable knowledge base for the industry and paved the way for commercial-scale adoption of CCUS technologies. From 2008 to 2020, MRCSP Phase III focused on the development of large-scale injection projects. This report is part of a series of reports prepared under the Midwestern Regional Carbon Sequestration Partnership (MRCSP) Phase III (Development Phase). These reports summarize and detail the findings of the work conducted under the Phase III project. The report describes the geochemical monitoring program under MRCSP to use stable and radiogenic isotope geochemistry in concert with analysis of general geochemical parameters of fluids and gases and analysis of core samples to determine geochemical processes occurring in the reef structure because of CO 2 injection. Specifically, brine and gas samples were collected and analyzed to determine changes occurring between reefs prior to and following CO 2 injection. The analytical results for general geochemical parameters were modeled with chemical equilibrium models to determine if the injection of CO 2 resulted in the mineral dissolution or precipitation. Finally, core samples were collected and analyzed to determine if there was evidence of dissolution features or mineral precipitation.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

Simultaneous x-ray and neutron 4D tomographic study of drying-driven hydro-mechanical behavior of cement-based materials at moderate temperatures

The drying of cement-based materials is intimately related to their durability, which has significant economic, social and environmental repercussions. The evolution of the saturation of the pore network and the associated drying shrinkage are in fact leading causes of cracking and of the ensuing penetration of aggressive chemicals. This process is highly heterogeneous, due to the thermo-hydric spatial gradients developing in the material from the exposed surfaces to its core and because of local effects, driven by the intrinsically heterogeneous micro-structure (e.g., by the distribution of pores and aggregates). It follows that macroscopic, sample-scale measurements cannot fully disclose the complexity of the underlying processes. In the last few decades, significant advances in full-field techniques have allowed an unprecedented insight into these local processes. For cement-based materials, x-ray and neutron tomography lend themselves as ideal, and highly complementary, tools for the study of their thermo-hydro-mechanical behavior. Notably, the high sensitivity to density variations of x-ray imaging gives access to the developments of fractures, in 4D (3D + time). On the other hand, neutron tomography allows the study of the evolution of the moisture field in 4D, thanks to its high hydrogen sensitivity. The combination of these two techniques provides a unique insight in thermo-hydro-mechanical couplings, e.g., the effect of cracks on the water content field. This contribution presents novel 5D datasets (3D tomographies along time, plus truly simultaneous x-ray and Neutron rapid acquisitions) in-operando of a cement paste and of a concrete sample heated at moderate temperatures (up to 140{sup ∘}C). The analysis of this 5D data-set (once aligned in time and across modalities) allows for example a quantification of the 4D moisture profiles which were found to predict an overall water loss at hydric equilibrium coherent with the corresponding analytical analysis. In the cement paste sample, the x-ray dataset captures the evolution of an extensive cracking network, opening and propagation toward the core of the sample. A novel analysis procedure is here proposed which allows the extraction of these fractures and the analysis of their interplay with local drying as captured through neutron imaging. This for example reveals the depth of penetration of drying in the vicinity of the fractures along time, which is essential for the assessment and calibration of hydro-mechanical coupled models.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Molecular Hypernetworks for Exploration of Multi-Dimensional Metabolomics Data (Chyper)

Orthogonal separations of data from high-resolution mass spectrometry can provide insight into sample composition and help address the challenge of complete annotation of molecules in untargeted metabolomics. “Molecular networks” (MNs), as used, for example, in the Global Natural Products Social Molecular Networking platform, are an increasingly popular computational strategy for exploring and visualizing molecular relationships and improving annotation. MNs use graph representations to show the relationships between measured multidimensional data features. MNs also show promise for using network science algorithms to automatically identify targets for annotation candidates and to dereplicate features associated to a single molecular identity. However, more advanced methods may better represent the complexity present in samples. Our work aims to increase confidence in annotation propagation by extending molecular network methods to include “molecular hypernetworks” (MHNs), able to natively represent multiway relationships among observations supporting both human and analytical processing. In this paper we first introduce MHNs illustrated with simple examples, and demonstrate how to build them from liquid chromatography- and ion mobility spectrometry- separated MS data. We then describe a method to construct MHNs directly from existing MNs as their “clique reconstructions”, demonstrating their utility by comparing examples of previously published graph-based MNs to their respective MHNs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Microwave absorption behavior and electromagnetic properties of Ni-Zr doped La-Sr hexagonal ferrite synthesized by auto-combustion method

Highlights: • Quantitative analysis of Microwave Absorption for synthesized ferrites. • Maximum absorption was successfully predicted from quarter-wavelength method. • Minimum RL = −25.07 dB with 1.25 GHz bandwidth for composition x = 0.75. • Better gross loss tangent and Microwave Absorption in Ku-band. • Synthesized ferrites can be used as thin or thick sheet of microwave absorber. - Abstract: Strontium hexagonal ferrites with compositional formula Sr{sub 0.85}La{sub 0.15}(NiZr){sub x}Fe{sub 12-2x}O{sub 19}, where ‘x’ varies from 0.00 to 1.00 in steps of 0.25, were synthesized by auto-combustion method. Structural, magnetic, electromagnetic and microwave absorption properties of synthesized ferrites were studied. The vector network analyzer (VNA) was used to measure complex permittivity (ε′–jε′′) and complex permeability (μ′–jμ′′) in X-band (8–12.4 GHz) and Ku-band (12.4–18 GHz) frequency range. The minimum reflection loss curves were obtained using back metal plate method for analyzing absorption properties of the material. All the synthesized ferrites show maximum absorption in Ku-band for sample thickness in the range of 1.6–1.68 mm. These newly synthesized ferrites have great potential to be used as thin microwave absorber sheets with minimum reflection loss values in the range of –19.69 dB to −27.8 dB and bandwidth in the range of 680 MHz–1.25 GHz.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Chemical Disposition of Plutonium in Hanford Site Tank Wastes

This report examines the chemical disposition of plutonium (Pu) in Hanford Site tank wastes, by itself and in its observed and potential interactions with the neutron absorbers aluminum (Al), cadmium (Cd), chromium (Cr), iron (Fe), manganese (Mn), nickel (Ni), and sodium (Na). Consideration also is given to the interactions of plutonium with uranium (U). No consideration of the disposition of uranium itself as an element with fissile isotopes is considered except tangentially with respect to its interaction as an absorber for plutonium. The report begins with a brief review of Hanford Site plutonium processes, examining the various means used to recover plutonium from irradiated fuel and from scrap, and also examines the intermediate processing of plutonium to prepare useful chemical forms. The paper provides an overview of Hanford tank defined-waste–type compositions and some calculations of the ratios of plutonium to absorber elements in these waste types and in individual waste analyses. These assessments are based on Hanford tank waste inventory data derived from separately published, expert assessments of tank disposal records, process flowsheets, and chemical/radiochemical analyses. This work also investigates the distribution and expected speciation of plutonium in tank waste solution and solid phases. For the solid phases, both pure plutonium compounds and plutonium interactions with absorber elements are considered. These assessments of plutonium chemistry are based largely on analyses of idealized or simulated tank waste or strongly alkaline systems. The very limited information available on plutonium behavior, disposition, and speciation in genuine tank waste also is discussed. The assessments show that plutonium coprecipitates strongly with chromium, iron, manganese and uranium absorbers. Plutonium’s chemical interactions with aluminum, nickel, and sodium are minimal to non-existent. Credit for neutronic interaction of plutonium with these absorbers occurs only if they are physically proximal in solution or the plutonium present in the solid phase is intimately mixed with compounds or solutions of these absorbers. No information on the potential chemical interaction of plutonium with cadmium was found in the technical literature. Definitive evidence of sorption or adsorption of plutonium onto various solid phases from strongly alkaline media is less clear-cut, perhaps owing to fewer studies and to some well-attributed tests run under conditions exceeding the very low solubility of plutonium. The several studies that are well-founded show that only about half of the plutonium is adsorbed from waste solutions onto sludge solid phases. The organic complexants found in many Hanford tank waste solutions seem to decrease plutonium uptake onto solids. A number of studies show plutonium sorbs effectively onto sodium titanate. Finally, this report presents findings describing the behavior of plutonium vis-à-vis other elements during sludge dissolution in nitric acid based on Hanford tank waste experience gained by lab-scale tests, chemical and radiochemical sample characterization, and full-scale processing in preparation for strontium-90 recovery from PUREX sludges.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Development of Corrosion- and Erosion-Resistant Coatings for Advanced Ultra-Supercritical Materials

This final report summarized the research efforts and major findings of the Phase I Project “Development of Corrosion- and Erosion-Resistant Coatings for Advanced Ultra-Supercritical Materials”, for the period of October 1, 2019 – Sept. 30, 2021. This project is a collaborative endeavor between Tennessee Tech University, Purdue University, Oak Ridge National Laboratory, Siemens Corporation, and Eastern Plating, LLC, aiming at improving the durability and lifetime of high-pressure (HP) steam turbine blades in advanced ultra-supercritical (A-USC) coal-fired power plants through the development of corrosion/erosion-resistant coatings manufactured via a low-cost electrolytic codeposition process. While Tribaloy alloy T-400C was identified by the U.S. A-USC Materials Consortium as a promising coating composition, further composition optimization is needed to enhance its corrosion and erosion resistance for protecting the A-USC Ni-base turbine components. An integrated computational and experimental approach was employed to optimize coating composition/microstructure and processing parameters. In order to identify candidate coating compositions that could offer balanced properties, thermodynamic calculations were performed to explore the γ+Laves composition space in the Co-Ni-Cr-Mo-Si system with different alloying additions at 600-800 °C. Guided by the calculation results, experimental assessment of selected alloys led to the development of a new generation of Tribaloy compositions with the optimal levels of Cr, Mo and Si, reactive element (e.g., 0.4-0.6 wt.% Y) and other alloying additions. The low-cost and non-line-of-sight electro-codeposition process was employed to deposit a Ni(Co)-CrMoSiY composite coating on commercial Haynes 282 (H282) Ni-base alloy. A diffusion treatment was subsequently applied to convert the composite to the Tribaloy-type coating. Both the codeposition parameters and heat treatment conditions were varied to achieve the desired coating composition, microstructure and phase constituents. In addition, since additive manufacturing (AM) may be an alternative cost-saving option for potential A-USC turbine repair, laser direct deposition was explored to fabricate the H282 alloy with minimal defects. The electro-codeposited Tribaloy coating was also applied to the AM H282 substrate to demonstrate the viability of the coating process in improving the surface finish of AM alloys. Both high-temperature oxidation performance and solid particle erosion (SPE) resistance of model alloys and electro-codeposited coatings were evaluated. About 25 model alloys with various Cr/Mo ratios and reactive element levels, as well as partial substitution of Mo with Nb were evaluated with regard to their oxidation resistance in both air and pure steam at 760-800°C. Compositions based on Ni(Co)-20Cr-18Mo-2.6Si-0.6Y (wt.%) showed significantly improved oxidation resistance over the baseline T400-C. Based on the alloy development results, three generations of new Tribaloy coatings (Gen-1, Gen-2, and Gen-3) with various Mo/Cr contents and Y levels were prepared via electro-codeposition and their microstructure/performance were evaluated. Outstanding air and steam oxidation resistance was achieved for the Gen-2 and Gen-3 coatings. Furthermore, while the SPE resistance of the coatings depended on many factors such as temperature, environment, erodent, velocity and impact angle, the coated samples exhibited similar or better SPE resistance compared to the H282 substrate when magnetite was used as erodent (which is a realistic erodent in A-USC steam turbines). The new Tribaloy coatings also had good long-term compatibility with the H282 alloy substrate. The two large-sized rotating barrels were designed, constructed, and employed to coat dummy HP blades. Uniform coating thickness and microstructure were achieved at various blade locations. Also, a preliminary techno-economic analysis of the proposed coating process was conducted to quantify the cost-effectiveness and to assess the commercial viability of the corrosion- and erosion-resistant coatings. It is estimated that a cost reduction of ~30% could be achieved with the electro-codeposition coating process over the state-of-the-art high velocity oxygen fuel (HVOF) thermal spray. Compared to the leading Tribaloy coating technologies such as HVOF and plasma transfer alloying, electro-codeposition based process has advantages such as low-cost process equipment, uniform deposition even for complex shapes, low levels of contaminants/porosities, reduction of powder waste, and potentially better surface finish and longer turbine service life. The Phase 1 study has demonstrated that it is feasible to develop an electro-codeposited Tribaloy coating with balanced corrosion and erosion properties, even though additional research efforts such as further coating process scale-up and longer-term performance evaluation under realistic A-USC conditions are clearly needed.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2023

Bringing 2D Eclipse Mapping out of the Shadows with Leave-one-out Cross Validation

Abstract Eclipse mapping is a technique for inferring 2D brightness maps of transiting exoplanets from the shape of an eclipse light curve. With JWST’s unmatched precision, eclipse mapping is now possible for a large number of exoplanets. However, eclipse mapping has only been applied to two planets, and the nuances of fitting eclipse maps are not yet fully understood. Here, we use Leave-one-out Cross Validation (LOO-CV) to investigate eclipse mapping, with application to a JWST NIRISS/SOSS observation of the ultrahot Jupiter WASP-18b. LOO-CV is a technique that provides insight into the out-of-sample predictive power of models on a data-point-by-data-point basis. We show that constraints on planetary brightness patterns behave as expected, with large-scale variations driven by the phase-curve variation in the light curve and smaller-scale structures constrained by the eclipse ingress and egress. For WASP-18b we show that the need for higher model complexity (smaller-scale features) is driven exclusively by the shape of the eclipse ingress and egress. We use LOO-CV to investigate the relationship between planetary brightness map components when mapping under a positive-flux constraint to better understand the need for complex models. Finally, we use LOO-CV to understand the degeneracy between the competing “hot spot” and “plateau” brightness map models of WASP-18b, showing that the plateau model is driven by the ingress shape and the hot spot model is driven by the egress shape, but preference for neither model is due to outliers or unmodeled signals. Based on this analysis, we make recommendations for the use of LOO-CV in future eclipse-mapping studies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Bayesian calibration of terrestrial ecosystem models: a study of advanced Markov chain Monte Carlo methods

Calibration of terrestrial ecosystem models is important but challenging. Bayesian inference implemented by Markov chain Monte Carlo (MCMC) sampling provides a comprehensive framework to estimate model parameters and associated uncertainties using their posterior distributions. The effectiveness and efficiency of the method strongly depend on the MCMC algorithm used. In this work, a differential evolution adaptive Metropolis (DREAM) algorithm is used to estimate posterior distributions of 21 parameters for the data assimilation linked ecosystem carbon (DALEC) model using 14 years of daily net ecosystem exchange data collected at the Harvard Forest Environmental Measurement Site eddy-flux tower. The calibration of DREAM results in a better model fit and predictive performance compared to the popular adaptive Metropolis (AM) scheme. Moreover, DREAM indicates that two parameters controlling autumn phenology have multiple modes in their posterior distributions while AM only identifies one mode. The application suggests that DREAM is very suitable to calibrate complex terrestrial ecosystem models, where the uncertain parameter size is usually large and existence of local optima is always a concern. In addition, this effort justifies the assumptions of the error model used in Bayesian calibration according to the residual analysis. Here, the result indicates that a heteroscedastic, correlated, Gaussian error model is appropriate for the problem, and the consequent constructed likelihood function can alleviate the underestimation of parameter uncertainty that is usually caused by using uncorrelated error models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Controlling superconductivity of CeIrIn 5 microstructures by substrate selection

Superconductor/metal interfaces are usually fabricated in heterostructures that join these dissimilar materials. A conceptually different approach has recently exploited the strain sensitivity of heavy-fermion superconductors, selectively transforming regions of the crystal into the metallic state by strain gradients. The strain is generated by differential thermal contraction between the sample and the substrate. Here, we present an improved finite-element model that reliably predicts the superconducting transition temperature in CeIrIn 5 even in complex structures. Different substrates are employed to tailor the strain field into the desired shapes. Using this approach, both highly complex and strained as well as strain-free microstructures are fabricated to validate the model. This enables a high degree of control over the microscopic strain fields and forms the basis for more advanced structuring of superconductors as in Josephson junctions yet also finds natural use cases in any material class in which a modulation of the physical properties on a chip is desirable.

36 MATERIALS SCIENCE↗