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DOE OSTI2025

R&D Effort of Geologic Hydrogen Production at the National Renewable Energy Lab (NREL)

Geologic hydrogen (geoH2) is an emerging technology with massive current market interest and distinct potential to change the paradigm of hydrogen production. Two major subsurface processes influence the amount of geoH2 that are available for energy extraction: 1) geochemical reactions of H2O and Fe2+-bearing rocks which can produce hydrogen in the subsurface environment, where 2) various active microbial communities consume hydrogen as an energy source before the hydrogen reaches the surface. The net gain of hydrogen from these two competing processes dictates the production rate of geoH2. A recent study (Templeton et al., 2024) suggested that for most natural geoH2 systems, five orders of magnitude of production rate enhancement are needed to make geoH2 production economical in the near term. Effective enhancement of the production rate requires an in-depth understanding of the two geoH2 processes, in order to promote the H2-generating geochemical processes and suppress the H2-consuming microbial processes. However, current significant knowledge gaps in these two processes hinders the efforts to formulate strategies to enhance geoH2 production. The National Renewable Energy Laboratory (NREL) is a U.S. Department of Energy National Laboratory with the core mission of leading research, innovation, and strategic partnership to deliver solutions for a clean energy based economy. NREL's extensive research portfolio in hydrogen, bioenergy, geothermal, industrial decarbonization, and energy analysis makes us well positioned to conduct interdisciplinary research and facilitate technology deployment in the geoH2 space. In this presentation, we will discuss ongoing geoH2 research and engagement efforts at NREL, including: 1) geochemical investigation to understand the reaction mechanisms and production rate and potential of different source minerals and rocks, 2) microbiological investigation to understand methanogenesis and acetogenesis in the subsurface geoH2 environment, and identify effective inhibitors for these microbial processes, and 3) preliminary analysis for geoH2 production in the State of Minnesota, where abundant Fe-rich rocks for stimulated geoH2 production and ample opportunity to utilize geoH2 in transforming iron and steel industries are currently available.

08 HYDROGEN↗

DOE OSTI2023

The role of nonequilibrium LO phonons, Pauli exclusion, and intervalley pathways on the relaxation of hot carriers in InGaAs/InGaAsP multi-quantum-wells

Under continuous-wave laser excitation in a lattice-matched In 0.53 Ga 0.47 As/In 0.8 Ga 0.2 As 0.44 P 0.56 multi-quantum-well (MQW) structure, the carrier temperature extracted from photoluminescence rises faster for 405 nm compared with 980 nm excitation, as the injected carrier density increases. Ensemble Monte Carlo simulation of the carrier dynamics in the MQW system shows that this carrier temperature rise is dominated by nonequilibrium LO phonon effects, with the Pauli exclusion having a significant effect at high carrier densities. Further, we find a significant fraction of carriers reside in the satellite L-valleys for 405 nm excitation due to strong intervalley transfer, leading to a cooler steady-state electron temperature in the central valley compared with the case when intervalley transfer is excluded from the model. Good agreement between experiment and simulation has been shown, and detailed analysis has been presented. This study expands our knowledge of the dynamics of the hot carrier population in semiconductors, which can be applied to further limit energy loss in solar cells.

42 ENGINEERING↗

DOE OSTI2026

Vanderbilt CMS Heavy-Ion Tier-2 Facility (Final Report)

The CMS experiment at the LHC at CERN in Geneva, Switzerland spends a portion of its running time colliding heavy ions. These heavy ion collisions are a key probe of a state of matter known as a Quark Gluon Plasma, which is a state of matter found in the very early universe 10s of microseconds after the big bang. These collision data are recorded by the CMS experiment and then undergo several stages of refinement to extract physics properties of the collisions from the raw data recorded by the various detector subsystems in CMS. In addition, copies of these datasets are stored on tape archival storage for data preservation. This award funds the deployment, maintenance, and operation of a computing facility at Vanderbilt University which processes, stores, and analyzes these collision data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Automation of Vulnerability and Patch Management: Information Extraction, Association, and Optimization

Vulnerability and patch management is an integral part of a robust cybersecurity program, yet it grows increasingly complex due to the sheer amount of data that must be analyzed. Particularly in Operational Technology (OT) environments, analysis must be done manually because of the lack of automated solutions. Additionally, there are many steps in this process, from the initial discovery of the vulnerability to the implementation of its remediation, and each step in the process requires different data in order to be performed effectively. In this work, we provide approaches and strategies to assist operators in industrial or OT environments throughout the vulnerability management cycle. Security advisories provide key information about mitigation strategies, or actions that can be taken when a patch is unavailable or cannot be installed. Details of these strategies are not shared in public vulnerability databases and must be found manually. We approach this problem by designing a solution to automatically identify that information within vendor security advisories and retrieve it for operator use. We start with an approach that requires domain-specific knowledge of certain frequently-seen reference websites. Next, an approach that can work on an arbitrary website but relies on certain keywords. Finally, an approach that uses Natural Language Processing (NLP) methods and does not require specific knowledge or keywords. Each of these approaches is more general than its predecessor; we demonstrate high accuracy for all approaches Advisories also often contain details of affected products in non-standard or natural language formats. While this information can be easily understood when read by an operator, the non-standard format acts as a barrier to effective automation. We provide an approach for the first step in this process: identifying vendors in security advisories and mapping them to a standard framework for representing digital assets and software products. We evaluate five established string similarity algorithms, plus one of our own design that combines string similarity and information theory, on the task of mapping vendors to their corresponding entries in the Common Platform Enumeration (CPE) repository. Our results show that our proposed metric outperforms all others. Due to the constraints on time, finances, and personnel for organizations, Large Language Models (LLMs) may seem like attractive opportunities for security operators to speed up information gathering; however, it is still not clear whether LLMs can handle vulnerability management tasks well. To answer this question, we perform an empirical study of LLMs’ ability to provide consistent, accurate information about vulnerabilities in order to guide organizations in their adoption of LLMs. We observe poor performance for all models tested, suggesting that these models are not well-suited to the consistent retrieval of accurate vulnerability information. Finally, once vulnerabilities have been identified and any additional information has been obtained, operators must decide which remediation actions to implement based on their available resources. This already-complex problem becomes even more so when we consider that a vulnerability may have multiple avenues for remediation. We formulate this scenario as two knapsack problems and provide solutions, which we then compare against several existing strategies for vulnerability prioritization seen in real operational environments.

McClanahan, Kylie↗

DOE OSTI2025

Data from TropiRoot 1.0 database: tropical root characteristics across environments

TropiRoot 1.0 is a new tropical root database with root characteristics across environment gradients. It has data extracted from 104 new sources, resulting in more than 8000 rows of data (either species or community data). Most of the data in TropiRoot 1.0 includes root characteristics such as root biomass, morphology, root dynamics, mass fraction, architecture, anatomy, physiology and root chemistry. This initiative represents an approximately 30% increase in the currently available data for tropical roots in the Fine Root Ecology Database (FRED). TropiRoot 1.0, contains root characteristics from 25 different countries where seven are located in Asia, six in South America, five in Central America and the Caribbean, four in Africa, two in North America, and 1 in Oceania. Due to the volume of data, when ancillary data was available, including soil data, these data was either extracted and included in the database or their availability was recorded in an additional column. Multiple contributors checked the entries for outliers during the collation process to ensure data quality. For text-based observations, we examined all cells to ensure that their content relates to their specific categories. For numerical observations, we ordered each numerical value from least to greatest and plotted the values, checking apparent outliers against the data in their respective sources and correcting or removing incorrect or impossible values. Some data (soil and aboveground) have different columns for the same variable presented in different units, including originally published units, but root characteristics data had units converted to match the ones reported in FRED. By filling a gap from global databases, TropiRoot 1.0 expands our knowledge of otherwise so far underrepresented regions, and our ability to assess global trends. This advancement can be used to improve tropical forest representation in vegetation models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Comparison of basin-scale in situ and meteoric 10 Be erosion and denudation rates in felsic lithologies across an elevation gradient at the George River, northeast Tasmania, Australia

Long-term erosion rates in Tasmania, at the south ern end of Australia’s Great Dividing Range, are poorly known; yet, this knowledge is critical for making informed land-use decisions and improving the ecological health of coastal ecosystems. Here, we present quantitative, geologically relevant estimates of erosion rates for the George River basin, in northeast Tasmania, based on in situ-produced 10 Be ( 10 Be i ) measured from stream sand at two trunk channel sites and seven tributaries (mean: 24.1 ± 1.4 Mg km -2 yr -1 ; 1σ). These new 10 Bei-based erosion rates are strongly related to elevation, which appears to control mean annual precipitation and temperature, suggesting that elevation-dependent surface processes influence rates of erosion in northeast Tas mania. Erosion rates are not correlated with slope in contrast to erosion rates along the mainland portions of Australia’s Great Dividing Range. We also extracted and measured meteoric 10 Be ( 10 Be m ) from grain coatings of sand-sized stream sediment at each site, which we normalize to measured concentrations of reactive 9 Be and use to estimate 10 Be m -based denudation rates for the George River. 10 Bem/ 9 Be reac denudation rates replicate 10 Be i erosion rates within a factor of 3 but are highly sensitive to the value of 9 Be that is found in bedrock ( 9 Be parent ), which was unmeasured in this study. 10 Bem/ 9 Be reac denudation rates seem sensitive to recent mining, forestry, and agricultural land use, all of which resulted in widespread topsoil disturbance. Our findings suggest that 10 Bem/ 9 Be reac denudation metrics will be most useful in drainage basins that are geologically homogeneous, where recent disturbances to topsoil profiles are minimal, and where 9 Be parent is well constrained.

58 GEOSCIENCES↗

DOE OSTI2023

Uniqueness of relaxation times determined by dielectric spectroscopy

Dielectric spectroscopy is extremely powerful to study molecular dynamics, because of the very broad frequency range. Often multiple processes superimpose resulting in spectra that expand over several orders of magnitude, with some of the contributions partially hidden. For illustration, we selected two examples, (i) normal mode of high molar mass polymers partially hidden by conductivity and polarization and (ii) contour length fluctuations partially hidden by reptation using the well-studied polyisoprene melts as example. The intuitive approach to describe experimental spectra and to extract relaxation times is the addition of two or more model functions. Here, we use the empirical Havriliak-Negami function to illustrate the ambiguity of the extracted relaxation time, despite an excellent agreement of the fit with experimental data. We show that there are an infinite number of solutions for which a perfect description of experimental data can be achieved. However, a simple mathematical relationship indicates uniqueness of the pairs of the relaxation strength and relaxation time. Sacrificing the absolute value of the relaxation time enables to find the temperature dependence of the parameters with a high accuracy. For the specific cases studied here, the time temperature superposition (TTS) is very useful to confirm the principle. However, the derivation is not based on a specific temperature dependence, hence, independent from the TTS. We compare new and traditional approaches and find the same trend for the temperature dependence. The important advantage of the new technology is the knowledge of the accuracy of the relaxation times. Relaxation times determined from data for which the peak is clearly visible are the same within the experimental accuracy for traditional and new technology. However, for data where a dominant process hides the peak, substantial deviations can be observed. Finally, we conclude that the new approach is particularly helpful for cases in which relaxation times need to be determined without having access to the associated peak position.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Mark-18A Target Material Recovery Program: Initial Hot Startup

The Savannah River National Laboratory (SRNL) has been tasked by the National Nuclear Security Administration to recover highly valued isotopes from irradiated Mark-18A (Mk-18A) targets. The Savannah River Site (SRS) has sixty-five Mk-18A targets available for the recovery of the high valued materials. The Mk-18A targets were manufactured with Pu-242 then irradiated under high neutron flux in K-Reactor at the SRS from 1968 to 1978. The sixty-five Mk-18A targets are currently stored in the SRS L-Area Basin and will be removed one at a time and individually transported to SRNL. Upon receipt at SRNL, the Mk-18A target material will be removed from the confinement, dissolved, chemically separated, and calcined to a stable oxide. The flowsheet is designed to recover the plutonium as well as the trivalent actinides. The original targets were manufactured with varying quantities of Pu-242, ranging from 5.2 grams to 121.5 grams. Taking a graded approach to process start up, the lowest loaded target (FT-80-03) was selected as the first target to be received and processed at SRNL. As operational experience and knowledge is gained from processing targets, higher loaded targets will be selected for processing to increase the quantities of valuable isotopes recovered. Due to dose concerns, the receipt and processing of the Mk-18A targets is performed in the SRNL Shielded Cells Facility. The targets are stored in a double J-can confinement in the L-Area Basin. A specially designed cask was procured for transport of the targets from L-Area to SRNL. Once received at SRNL, the targets are loaded into the back of Cell 7 and resized as they enter the cell. The resized targets (1/4 length) are then processed one at a time through the following processes: caustic dissolution and filtration, acidic dissolution and filtration, elutable Reillex anion exchange, diglycolamide (DGA) resin extraction, and DGA calcination. This processing results in two product streams. The first is an aqueous plutonium solution which is removed from the shielded cells and taken to a glovebox for further purification and conversion to an oxide. The second is a calcined oxide product containing the Am and Cm as well as other lanthanide fission products which is removed from the shielded cells using a bagless transfer system. Both materials are packaged for shipment to Oak Ridge National Laboratory (ORNL). This paper will discuss the operating experience, lessons learned, and results from initial process hot startup.

Armstrong, Christopher [Savannah River National La↗

DOE OSTI2024

Inaugural Molten Salt Technologies Workshop Powering the Future

The inaugural “Molten Salt Technologies – Powering the Future” Workshop marked a significant convergence of minds from diverse industries, each harnessing molten-salt technologies in innovative ways. Participants from sectors such as solar, geothermal, and advanced nuclear energy, as well as those involved in cutting-edge applications like thermal transport and rare-earth metals extraction, gathered to discuss their shared technical challenges and opportunities. Industry leaders in metal extraction and recycling, alongside experts in high-temperature sensor technology and advanced material manufacturing, also brought their unique perspectives to the table. This workshop served as a crucial platform for these varied industries to delve into the engineering intricacies that molten salt technologies entail. Common challenges such as understanding the thermophysical properties of salts, tackling corrosion mechanisms in harsh environments, and enhancing material resilience under extreme conditions were at the forefront of discussions. These technical sessions highlighted the critical need for cross-industry collaboration to address issues like salt life-cycle process engineering, impurity mitigation, and the development of durable, high-performance materials. By bringing together academia, industry, and representatives from national laboratories and the U.S. Department of Energy (DOE), the workshop facilitated a rich exchange of knowledge and experiences. This interaction not only fostered new partnerships but also strengthened the network among existing collaborators, setting the stage for joint solutions to the complex problems faced by all sectors using molten salt technologies. The event underscored the importance of collaborative efforts in overcoming common engineering challenges and advancing the application of molten-salt technologies across various industries. The workshop not only provided an essential forum for networking and idea exchange but also highlighted the collective drive towards innovative solutions that could benefit multiple fields.

Department of Energy↗

DOE OSTI2024

Inaugural Molten Salt Technologies Workshop Powering the Future

Department of Energy↗

DOE OSTI2022

Estimation of process steady state with autoregressive models and Bayesian inference

To improve efficiency, separations engineers will typically design process circuits containing recirculating streams, which mix one or more of the process outputs with the feed material. Doing so can improve efficiency, but will cause a delay in the system reaching steady state conditions until the recirculating load mass flows stabilize. In testing separation circuits, engineers will often test a variety of factors and complete an analysis from sample results. Knowledge of if a process is at steady state, as well as the steady state conditions of a process, is essential for a valid techno-economic analysis. However, the definition of process steady state is often poorly defined, or does not include uncertainty quantification. If the performance of a process operating under two different sets of conditions are compared, an engineer who does not test for steady state or quantify steady state conditions risks producing a faulty analysis. In this work, a Bayesian statistical method for testing if all streams are at steady state is further motivated and then derived. Then after testing for steady state, the same model is used with a prior distribution that enforces a steady state assumption to estimate steady state conditions. Further, these methods were validated in a solvent extraction pilot plant where steady state conditions for all outflows were inferred with uncertainty quantification. Analysis is completed with functions available to the reader as part of the BayesMassBal (V 1.1.0) software package written in R.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2022

Infrared-Fused Vision-Based Thermoregulation Performance Estimation for Personal Thermal Comfort-Driven HVAC System Controls

Thermal comfort is one of the primary factors influencing occupant health, well-being, and productivity in buildings. Existing thermal comfort systems require occupants to frequently communicate their comfort vote via a survey which is impractical as a long-term solution. Here, we present a novel thermal infrared-fused computer vision sensing method to capture thermoregulation performance in a non-intrusive and non-invasive manner. In this method, we align thermal and visible images, detect facial segments (i.e., nose, eyes, face boundary), and accordingly read the temperatures from the appropriate coordinates in the thermal image. We focus on the human face since it is often clearly visible to cameras and is not merged into a hot background (unlike hands). We use a regularized Gaussian Mixture model to track the thermoregulation changes over time and apply a heuristic algorithm to extract hot and cold indices. We present a personalized and a generalized comfort modeling method, selected based on the availability of the occupant historical indices measurements in a neutral environment, and use the time-series of the hot and cold indices to define corrections to HVAC system operations in the form of setpoint constraints. To evaluate the efficacy of our proposed approach in responding to thermal stimuli, we designed a series of controlled experiments to simulate exposure to cold and hot environments. While applying personalized modeling showed an acceptable average accuracy of 91.3%, the generalized model’s average accuracy was only 65.2%. This shows the importance of having access to physiological records in modeling and assessing comfort. We also found that individual differences should be considered in selecting the cooling and heating rates when some knowledge of the occupant’s overall thermal preference is available.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Sources and Variability of Nitrate on an Alaskan Hillslope Dominated by Alder Shrubs, Kougarok, Alaska, 2017 and 2018

Data provided include results of analyses of soil pore-water, soil moisture, and leaf litter samples collected at a Kougarok Hillslope site dominated by alder shrubs (KG_MM64) in the Seward Peninsula, Alaska during July and September 2017 and 2018. Samples were from surface soils in close proximity to 5 alder patches, collected upslope, within, and downslope of the alder patches. Pore water was analyzed for a comprehensive set of anions, cations, elemental analyses, and oxygen and nitrogen isotopes. Soil samples were collected for soil moisture determination. Leaf litter extracts were analyzed for carbon and nitrogen content and carbon and nitrogen isotopes. This dataset contains 3 *.csv files and 1 *.pdf file. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Determination of Molecular Structure and Dynamics of Molten Salts by Advanced Neutron and X-ray Scattering Measurements and Computer Modeling

The design and development of fully functional Molten-Salt Reactors (MSR) require detailed knowledge of the molten salt properties in order to understand and predict the salt’s behavior. Fundamental properties of interest include molecular structure, speciation, and dynamics (such as diffusion coefficients) of salt components and dissolved corrosion and fission products. Computer modeling is necessary to predict changes in physical and chemical properties due to irradiation, burning of dissolved fuel, and corrosion. The modeling requires experimental data, and advanced neutron and x-ray scattering and spectroscopy provide the most reliable and direct determination of the structure (Pair-Distribution Functions, PDF), and dynamics of ions in the melt. This project dealt with both fluoride and chloride salts. The PDFs have been measured by a combination of neutron and x-ray diffraction. We utilized the techniques of isotope substitutions, a very powerful tool available for neutron-scattering, to extract the details of the liquid structure. Although similar measurements have been done before, modern advanced neutron and x-ray-scattering techniques allow collecting the data at much higher resolution and in a wider range of temperatures. Importantly, we were among the first to study fluoride salts by neutron scattering. The importance of impurities and their effects on salt properties have become apparent recently and so new methods of salt purification were developed. We took advantage of these developments to produce reliable data, which have been used for computer simulations of both clean salts and those with added fission and corrosion products most relevant for MSRs. Ab initio molecular dynamics simulations have been performed to understand the multi-component liquid solution, in particular solubility of impurities and thermodynamic interactions in relation to the ionic-cluster structure of the fluid. We applied machine learning to regress from the simulation and experimental data in order to develop a fast-acting model that can handle molten salt with an arbitrary (≥ 10) number of chemical elements and be able to predict chemical potential as a function of composition and temperature. This project resulted in a number of experimental and computer-simulation publications, a patent application, and numerous conference presentations (American Physical Society, American Chemical Society, and The Electrochemical Society among others). Multiple students and postdocs participated and collaborated on aspects of this project. This project seeded new collaborations between MIT and other institutions, such as the University of Massachusetts Lowell, the University of Illinois Urbana-Champaign, the University of California Berkeley, and Oak Ridge and Los Alamos National Labs. As such, this project has had a broad and lasting impact beyond its original scientific scope.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2026

MINERvA s Open Data Product: A First for Neutrino Data Preservation

Access to information on neutrino nucleus interactions is critical to the success of all neutrino oscillation experiments. MINERvA's rich dataset covers a range of energies and nuclei unique amongst experiments, and as such is critical to the community in building the important shared knowledge needed to unravel the mysteries of the neutrino. In particular, its dataset provides the greatest statistical coverage in in the range of neutrino energies pertinent for DUNE until DUNE's near detector begins operation. Historically, such significant datasets in neutrino physics have been preserved primarily through their published results. While meaningful and useful, this limits the ability to explore the data to its fullest extent as new perspectives continue to form. MINERvA has undertaken a major effort to break this trend and preserve its data in a format to be as analyzable as possible from outside the collaboration. This has culminated in the officially-released MINERvA Open Data Product for the community to take advantage of and utilize. Maintaining direct access to the dataset in an analyzable form will allow new insights to continue to be extracted indefinitely. This talk will cover the contents of this product, the information included (and excluded), the tools provided to utilize the product effectively, the support MINERvA intends to provide in its use, and some lessons learned through the process.

Last, David [Rochester U.] (ORCID:0000000245147183↗

DOE OSTI2020

Mercury Methylation and Soil Organic Matter Degradation in Incubations with Added Acetate, Isotope-Labeled Mercury, and Selective Microbial Inhibitors, Teller and Council Sites, Seward Peninsula, 2018-2019

This dataset provides the results of laboratory soil microcosm incubation experiments conducted under anaerobic conditions with added acetate, isotope-labeled mercury, and selective microbial inhibitors (2-bromoethanesulfonate and sodium molybdate). The microcosms contained soil collected in August 2018 from the NGEE Arctic Teller Road Site at mile marker 27 (TL_MM27) near Intensive Site 9 (TL_IS_9) and from the Council Road Site (CN_MM71). Incubations were conducted at 8°C for 180 days (Teller incubations) or 60 days (Council incubations). The microcosm headspace was sampled at designated intervals for greenhouse gas concentrations, then destructively harvested and extracted using ultrapure water and 0.1 M KCl for analysis of the porewater geochemistry. This dataset contains one pdf, two csv data files, and one zipped file with raw data.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Automated Scoring of Morphological Changes in Images of Pentaerythritol Tetranitrate

Recent advances in characterization techniques that generate large datasets of material microstructure images require robust, automated image-processing. We applied an unsupervised anomaly detection method called feature anomaly detection system (FADS) to automatically detect and quantify microstructure changes in images of the explosive pentaerythritol tetranitrate (PETN) aged at various temperatures. We demonstrated the FADS approach on two-dimensional images extracted from computed tomography scans, but the same technique can be readily applied to other imaging modalities. FADS calculates anomaly scores on the basis of differences in filter activations of nominal and test data in pretrained convolutional neural networks. The FADS scores successfully differentiated between pristine PETN and PETN aged at a temperature where material coarsening occurred. Morphological metric analysis of segmented images verified observed trends in FADS scores as a function of aging temperature and aging time, specifically by calculating volume fractions, specific boundary lengths, two-point correlation functions, and local thicknesses. Here, the FADS technique has two important advantages compared to traditional morphological analysis: First, it uses grayscale images as input, rather than images that are segmented to separate the appropriate phases; and second, FADS scores capture any type of changes among image sets, rather than requiring prior knowledge or selection of a relevant set of metrics.

Accelerated aging↗

DOE OSTI2023

Characterization of Rare-Earth Elements in Lignite Coal of the Williston Basin: Past Efforts and Ongoing Work

Rare-earth elements (REEs) have been a subject area of high interest for their unique properties. REEs are crucial materials used in an incredible array of consumer goods, energy system components, and military defense applications. While the United States has one operating REE mine, the product is sent overseas for refining into usable metals making the United States 100% import-reliant on these critical materials. This has led the Federal Government to declare the REE market an issue of national security. The Energy and Environmental Research Center (EERC) under funding provided by the Department of Energy (DOE) has undertaken efforts to determine if the lignite coal found in the Williston Basin has the potential to be an ore body containing sufficient quantities of REEs and Critical Minerals (CM) for extraction and processing. In one such effort, the EERC collected over 400 samples from the Williston Basin lignite coal seams including outcrops as well as active mines. Those efforts have been followed up with ongoing work under the U.S. DOE’s Carbon Ore, Rare Earth and Critical Minerals Initiative (CORE-CM) currently ongoing in the Williston Basin as well as other basins in the United States. This ongoing work in the Williston Basin characterizing REEs in coal has focused on the collection of new sampling and analysis of REEs in coal and building upon previous characterization work. This information is being used to understand the spatial distribution of REEs through mapping and 3D modeling. The goals of these efforts are to better understand the mechanisms for distribution of the REEs in lignite coal as well as their concentration and determine knowledge gaps in characterization and to start to build the database required to understand the potential resource in the Williston Basin.

Feole, Ian K.↗