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DOE OSTI2022

Identification of a new circulating recombinant form of human immunodeficiency virus type 1, CRF124_cpx involving subtypes A, G, H, and CRF27_cpx in Angola

Angola, located in Central Africa, has around 320,000 (270,000–380,000) people living with human immunodeficiency virus (HIV)/AIDS, equivalent to 1% of the country’s population at the end of 2021. A previous study conducted in 2012, using Angolan samples collected between 2008 and 2010 revealed a high prevalence of HIV-1 recombinants, around 42% of sequences, with 21% showing the same UH profile in partial pol region which were grouped into a monophyletic cluster with high bootstrap support. Thus, the objective of the present work was to obtain complete genomes of those sequences and characterize them, aiming at a description of a new circulating recombinant form (CRF). Whole blood from nine HIV-1 UH pol -infected individuals had their genomic DNA extracted, and nested PCR was used to amplify seven overlapping fragments targeting the full-length HIV-1 genome. The final classification was based on maximum likelihood trees, and recombination analyses were performed using a bootscan from the Simplot program. BLAST and Los Alamos Database inspections were used to search other similar H-like pol sequences. Complete genome amplification was possible for three samples, partial genomes were obtained for the other three, and only pol was available for the remaining three sequences. Bootscan analysis of the two whole-genome and three partial genome sequences retrieved from people living with HIV/AIDS (PLHIVA) without epidemiological linkage showed the same complex recombination profile involving HIV-1 subtypes A/G/H/CRF27_cpx, with a total of six recombinant breakpoints, aiming to classify a new HIV-1 CRF124_cpx. We found no other full-length HIV-1 genomes with the same mosaic profile; however, we identified 33 partial pol sequences, mainly sampled from Angola between 2001 to 2019, with the same H-like profile. Bayesian analysis of H and H-like pol sequences indicates that CRF124_cpx probably originated in Angola at mid-1970s, indicating that this CRF has been circulating in the country for a long time. In summary, our study describes a new CRF circulating principally in Angola and highlights the importance of continuing molecular surveillance studies, especially in countries with high molecular diversity of HIV.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

HFTS-1 Natural Joint Data and Engineering Summary

This report provides an analysis of engineering and geologic data collected from the Hydraulic Fracturing Test Site #1 (HTSF-1) project in the southern Midland Basin, Reagan County, Texas. The site is being studied as part of the Science-informed Machine Learning for Accelerating Real-Time Decisions in Subsurface Applications (SMART) Initiative at the National Energy Technology Laboratory (NETL). The data collected is intended to provide a basis of understanding of the site and to construct simulation models. This report provides a summary analysis of the engineering and geologic data collected from the project to provide a basis of understanding of the site and to construct simulation models. The report examines various possible correlations in engineering properties based on natural fracture data from the program, which consisted of 11 horizontal wells, one vertical well, and one slant well. The horizontal wells are in two horizons: 1) Upper and 2) Middle Wolfcamp formations. Program data include: fracture frequency and fracture orientation data from four core runs in a slant well; fracture spacing and orientation from a vertical pilot well; laboratory triaxial testing and mineralogical determinations; and porosity results from magnetic resonance analyses from various wells, together with observations based on the data collection. In addition, available references were reviewed on the site for additional insights. As the focus of the report is on the natural system, hydraulic fracture data from the site were not examined in detail in this report. Data variability is the chief observation in examination of the database. Fracture frequency in the slant well can range from sections with values as high as five fractures per ft to sections up to 100+ ft in length with no natural observed fractures. Fracture spacing across is typically less than 10 ft, but can range up to hundreds of feet. Apparent fracturing shows the trends in two predominate orientations, E-SW and WNW-ESE, but minor variations exist. The rock units vary across the site from siliceous mudstones to calcareous mudstones, showing a general layering with depth. The laboratory properties such as strength and modulus show no apparent trend with depth, but appear to correlate with rock mineralogy with high strength and modulus values where calcium content is high. In addition, an attempt to examine variability and mineralogy on a larger scale was made using a color-coded system based on gamma ray measurements. A staged colored approach was adopted, presuming that lower gamma ray values indicate higher value of calcium content (blue scale) and that higher gamma ray values indicate higher clay mineral content (orange scale). As provided in report appendices, the system correlated well with visual examination of the slant core and the petrofabric analyses of the vertical pilot well. The results showed large variability in mineral content along the horizontal plane across the site. The change in mineral content was also rapid, on a scale less than that of the average hydraulic fracture stage length of about 180 ft.

42 ENGINEERING↗
DOE OSTI2023

Trends in Light and Temperature Sensitivity Recommendations among Licensed Biotechnology Drug Products

Inherent structural and functional properties of biotechnology-derived therapeutic biologics make them susceptible to light- and temperature-induced degradation and consequently can influence their quality. Photosensitivity of therapeutic proteins continues to be examined, but the commonalities and trends of storage conditions and information about light and temperature sensitivity among currently licensed therapeutic proteins has not been previously surveyed. Using a comprehensive and relational database approach, we conducted a scientific survey of all licensed biotechnology-derived drug products with the goal of providing evidence-based information about recommended storage conditions of formulations sorted by light- and temperature-related attributes as described for each product at licensure. We report the prevalence of indications for light and temperature sensitivity in formulations categorized by their presentation type, number of doses, container type, dosage form and active molecule type. We also report the storage temperature range across formulations and diluents for reconstitution and dilution. Formulations with excipients that potentially facilitate light-induced and thermal degradation were also noted. The result of our analysis indicates that light and temperature sensitivity are prevalent across therapeutic protein formulations. However, when a formulation is reconstituted or diluted, both light and temperature sensitivity are less clear. In addition, light and temperature sensitivity are more well defined in liquid formulations than lyophilized powder formulations, and more well defined in products manufactured in autoinjectors, prefilled-syringes, and pens than products in vials. Overall, our report provides a data-driven summary of storage conditions among therapeutic protein formulations to support the development of future biologic drug products.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Describing patterns of familial cancer risk in subfertile men using population pedigree data

STUDY QUESTION Can we simultaneously assess risk for multiple cancers to identify familial multicancer patterns in families of azoospermic and severely oligozoospermic men? SUMMARY ANSWER Here, distinct familial cancer patterns were observed in the azoospermia and severe oligozoospermia cohorts, suggesting heterogeneity in familial cancer risk by both type of subfertility and within subfertility type. WHAT IS KNOWN ALREADY Subfertile men and their relatives show increased risk for certain cancers including testicular, thyroid, and pediatric. STUDY DESIGN, SIZE, DURATION A retrospective cohort of subfertile men (N = 786) was identified and matched to fertile population controls (N = 5674). Family members out to third-degree relatives were identified for both subfertile men and fertile population controls (N = 337 754). The study period was 1966–2017. Individuals were censored at death or loss to follow-up, loss to follow-up occurred if they left Utah during the study period. PARTICIPANTS/MATERIALS, SETTING, METHODS Azoospermic (0 × 10 6 /mL) and severely oligozoospermic (<1.5 × 10 6 /mL) men were identified in the Subfertility Health and Assisted Reproduction and the Environment cohort (SHARE). Subfertile men were age- and sex-matched 5:1 to fertile population controls and family members out to third-degree relatives were identified using the Utah Population Database (UPDB). Cancer diagnoses were identified through the Utah Cancer Registry. Families containing ≥10 members with ≥1 year of follow-up 1966–2017 were included (azoospermic: N = 426 families, 21 361 individuals; oligozoospermic: N = 360 families, 18 818 individuals). Unsupervised clustering based on standardized incidence ratios for 34 cancer phenotypes in the families was used to identify familial multicancer patterns; azoospermia and severe oligospermia families were assessed separately. MAIN RESULTS AND THE ROLE OF CHANCE Compared to control families, significant increases in cancer risks were observed in the azoospermia cohort for five cancer types: bone and joint cancers hazard ratio (HR) = 2.56 (95% CI = 1.48–4.42), soft tissue cancers HR = 1.56 (95% CI = 1.01–2.39), uterine cancers HR = 1.27 (95% CI = 1.03–1.56), Hodgkin lymphomas HR = 1.60 (95% CI = 1.07–2.39), and thyroid cancer HR = 1.54 (95% CI = 1.21–1.97). Among severe oligozoospermia families, increased risk was seen for three cancer types: colon cancer HR = 1.16 (95% CI = 1.01–1.32), bone and joint cancers HR = 2.43 (95% CI = 1.30–4.54), and testis cancer HR = 2.34 (95% CI = 1.60–3.42) along with a significant decrease in esophageal cancer risk HR = 0.39 (95% CI = 0.16–0.97). Thirteen clusters of familial multicancer patterns were identified in families of azoospermic men, 66% of families in the azoospermia cohort showed population-level cancer risks, however, the remaining 12 clusters showed elevated risk for 2-7 cancer types. Several of the clusters with elevated cancer risks also showed increased odds of cancer diagnoses at young ages with six clusters showing increased odds of adolescent and young adult (AYA) diagnosis [odds ratio (OR) = 1.96–2.88] and two clusters showing increased odds of pediatric cancer diagnosis (OR = 3.64–12.63). Within the severe oligozoospermia cohort, 12 distinct familial multicancer clusters were identified. All 12 clusters showed elevated risk for 1–3 cancer types. An increase in odds of cancer diagnoses at young ages was also seen in five of the severe oligozoospermia familial multicancer clusters, three clusters showed increased odds of AYA diagnosis (OR = 2.19–2.78) with an additional two clusters showing increased odds of a pediatric diagnosis (OR = 3.84–9.32). LIMITATIONS, REASONS FOR CAUTION Although this study has many strengths, including population data for family structure, cancer diagnoses and subfertility, there are limitations. First, semen measures are not available for the sample of fertile men. Second, there is no information on medical comorbidities or lifestyle risk factors such as smoking status, BMI, or environmental exposures. Third, all of the subfertile men included in this study were seen at a fertility clinic for evaluation. These men were therefore a subset of the overall population experiencing fertility problems and likely represent those with the socioeconomic means for evaluation by a physician. WIDER IMPLICATIONS OF THE FINDINGS This analysis leveraged unique population-level data resources, SHARE and the UPDB, to describe novel multicancer clusters among the families of azoospermic and severely oligozoospermic men. Distinct overall multicancer risk and familial multicancer patterns were observed in the azoospermia and severe oligozoospermia cohorts, suggesting heterogeneity in cancer risk by type of subfertility and within subfertility type. Describing families with similar cancer risk patterns provides a new avenue to increase homogeneity for focused gene discovery and environmental risk factor studies. Such discoveries will lead to more accurate risk predictions and improved counseling for patients and their families. STUDY FUNDING/COMPETING INTEREST(S) This work was funded by GEMS: Genomic approach to connecting Elevated germline Mutation rates with male infertility and Somatic health (Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD): R01 HD106112). The authors have no conflicts of interest relevant to this work.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Energy-Flow-Environment Linkage Map

Understanding how flexibility in environmental requirements can facilitate co-optimization of hydropower production outcomes and environmental outcomes is critical for future grid decision-making and operations as renewable energy resources increase. The environmental and power system outcomes connectivity linkage maps presented here provide a framework for conceptually and quantitatively linking power system outcomes to environmental outcomes through hydropower flow decisions. The Executive Summary Map serves as a starting for exploring the links between hydropower system performance outcomes and environmental outcomes. The centralized topic is “Flow from Hydropower System,” and connects the hydropower operations through “Flow through turbines” and “Non-turbine flows”, and to environmental outcomes through Reservoir elevation” and “Flow downstream of the hydropower system”. To the left of these central topics, “Hydro-mechanical operations” are linked through “Hydro-electrical operations” to “Hydropower performance outcomes” (“Reliability”, “Resilience”, “Revenue”, “Emissions”). On the right, environmental outcomes are grouped together by their physical location: “Upstream Outcomes” (“Upstream geomorphology”, “Upstream recreation”, “Upstream habitat”, “Upstream biota and biodiversity”, “Upstream water quality and greenhouse gas”), Outcomes relevant to both “Upstream/downstream or dam interface” (“Navigation”, “Dam safety and maintenance", “Human health”, “Water supply”, “Flood control”, ”Fish passage”), and “Downstream outcomes“ (e.g., “Downstream geomorphology”, “Downstream recreations”, “Downstream habitat”, “Downstream biota and biodiversity”, “Downstream water quality and greenhouse gas”). Each of these subtopics (e.g., “Hydro-mechanical operations”, “Hydro-electrical operations”, “Upstream geomorphology”, “Upstream recreation”) is further explored through their corresponding submaps. The “Read Me” file provides more detail information on map navigation. The “Models and tools database” file provides detailed information of models and tools presented in the maps.

13 HYDRO ENERGY↗
DOE OSTI2022

GROWdb US River Systems - Samples

GROW Overview We developed the Genome Resolved Open Watersheds database (GROWdb), which aims to increase genomic sampling and understanding of global river microbiomes. An emphasis of GROWdb is to create a publicly available and ever-expanding microbial genome database that is focused on rivers while being interoperable with databases from other ecosystems. GROWdb is based on a network-of-networks approach to move beyond a small collection of well-studied rivers, towards a spatially distributed, global network of systematic observations. GROWdb represents the first microbial, river-focused resource parsed at various scales from genes to MAGs to community level including expression and potential based measurements that will be of interest to microbiologists, ecologists, geochemists, hydrologists, and modelers. Dataset Acknowledgement GROWdb contains data from various research campaigns, please acknowledge the following data generators, as appropriate: WHONDRS derived genomes or samples - include this statement in your acknowledgements: “This study used data from the Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) under the River Corridor Science Focus Area (SFA) at the Pacific Northwest National Laboratory (PNNL) that was generated at the U.S. Department of Energy (DOE) Joint Genome Institute User Facility. PNNL is operated by Battelle Memorial Institute for the U.S. DOE under Contract No. DE-AC05-76RL01830. The SFA is supported by the U.S. DOE, Office of Biological and Environmental Research (BER), Environmental System Science (ESS) Program.” Total Samples loaded onto this Narrative: 178 Note: Not all GROW samples may be loaded into KBase Data Availability The data underlying GROWdb are accessible across various platforms to ensure all levels of data structure are widely available. First, all reads and MAGs are publicly hosted on National Center for Biotechnology (NCBI) under Bioproject PRJNA946291. Second, all data related data presented here including MAG annotations, extended data tables, phylogenetic tree files, antibiotic resistance gene database files, and MAG abundance tables are available in Zenodo (link). Beyond the flat database files listed above, our aim for GROWdb was to maximize data use by making the data available in searchable and interactive platforms including the National Microbiome Data Collaborative (NMDC) data portal, the Department of Energy’s Systems Biology Knowledgebase (KBase), and a GROW specific user interface released here, GROWdb Explorer. Each platform provides different ways to interact with GROWdb: NMDC GROWdb formed a pilot project for the NMDC. Specifically, individual GROWdb datasets (metagenomes, metatranscriptomes, etc) are easily accessible and searchable through the NMDC data portal, where they are systematically connected to each other and to a rich suite of sample information and standard analysis results, following Findable, Accessible, Interoperable, and Reusable (FAIR) data practices. KBase GROWdb is publicly available within KBase, including samples (this Narrative), MAGs, and corresponding genome scale metabolic models. Access within KBase allows for immediate access and reuse of data, including comparison to private data using KBase’s 500+ analysis tools. Other linked narratives in KBase: GROW Metagenome Assembled Genomes (MAGs) GROW Metabolic Models GROWdb Explorer GROWdb data is also explorable through a graphical user interface built through the Colorado State University Geospatial Centroid (https://geocentroid.shinyapps.io/GROWdatabase/), allowing users to search and graph microbial and spatial data simultaneously. In summary, this microbial genome resource represents the first publicly available genome collection from rivers and offers data that can be leveraged across microbiome studies. GROWdb is an expanding repository to incorporate and unify global river multi-omic data for the future.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

FOILPOLARS (Grassmannian Foil Shape Sweeps for Polar Generation) [SWR-26-095]

FOILPOLARS (Grassmannian Foil Shape Sweeps for Polar Generation): Multifidelity aerodynamic polar data generation for hydrofoil/tidal-turbine airfoil sections. Foilpolars ties together three pieces: *AeroSandbox supplies the baseline airfoil coordinates (UIUC database). *G2Aero parameterizes those shapes on a Grassmannian manifold (Karcher mean + PGA basis) and samples new perturbed shapes around that basis. *XFoil (panel method) and NeuralFoil (neural-network surrogate, shipped with AeroSandbox) each solve the resulting shapes for lift, drag, moment, and pressure at the swept angles of attack, Reynolds numbers, and n_crit values. Design optimization of foil shapes in a computationally efficient way requires polars data across many candidate shapes, not just a handful of baseline foils. However, high-fidelity CFD at that scale is too costly, and naive shape perturbation strays from realistic geometries. FOILPOLARS addresses this by loading baseline airfoils (via AeroSandbox) and mapping them onto a Grassmannian manifold (via G2Aero), computing a Karcher mean and principal geodesic analysis (PGA) basis. New shapes are sampled by perturbing PGA coefficients, keeping them close to the manifold of realistic foils. Each sampled shape is evaluated across a configurable sweep of angle of attack, Reynolds number, and critical amplification factor using two solvers: XFoil (panel method) and NeuralFoil (neural-network surrogate), producing a paired dataset of lift, drag, moment, pressure, convergence, and confidence, indexed alongside each shape's PGA coefficients and shared Grassmannian basis in a single xarray dataset. From this, FOILPOLARS produces convergence summaries and comparison plots per shape, Reynolds number, and n_crit. A command-line interface exposes each pipeline stage independently, supporting data-driven design, optimization, and machine-learning workflows for foils.

Sandhu, Rimple [National Laboratory of the Rockies↗
DOE OSTI2025

EVs@Scale Next-Gen Profiles - EV Profile Capture 2024

As part of the U.S. DOE EVs@Scale consortium Next-Gen Profiles (NGP) project, the profile capture and analysis of production electric vehicles undergoing high power charging (HPC) is conducted over a wide range of conditions to explore variance and performance. Charge session parameters are collected from both the electric vehicle (EV) and electric vehicle supply equipment (EVSE) at a rate of 10Hz and entered into a time-series database for analysis. These charge profiles are captured under nominal and off-nominal conditions, exploring the impact of battery state of charge (SOC), battery temperature, vehicle condition, smart charge management (SCM), and EVSE limitations. Nominal conditions are defined to be ideal conditions that should transfer the maximum allowable energy in the minimum possible amount of time. Nominal condition profiles are compared across EVs to characterize state-of-the-art EV charging performance against one another. Off-nominal condition profiles are compared against its nominal condition profile counterpart to highlight the variance across less desirable starting conditions within a single EV. This EV Profile Capture 2024 report stands as an update from the EV Profile Capture 2023 report to include the additional EV & EVSE assets tested and analyzed in 2024. The major updates within this report include the addition of three next-generation electric vehicles, added test cases, and further analysis. This expansion of analysis includes power profiles, power distribution, quantifying SOC, energy and range performance, EVSE limitation impacts, boost converter performance, etc. Additionally, NGP time-series data has been used as input towards three national laboratory-led grid modelling efforts: ANL’s IEEE-37 HIL model, INL’s Caldera model, and NREL’s EVI-X model. A summary of these platforms and how NGP has worked to improve their effectiveness has also been added to this years’ report.

Thurston, Sam↗
DOE OSTI2022

Introduction to an MCGIDI Mini-App and Performance Comparisons with XSBench

In high-performance Monte Carlo (MC) radiation transport codes, cross section lookups often account for the majority of computational expens. In response to this observation, a number of nuclear data mini-apps have been developed to profile and optimize the lookup process. A review of these mini-apps can be found in Ref. In contrast to a fully fledged MC code, nuclear data mini-apps do not feature particle tracking; instead, the cross section lookup process is considered in isolation, a simplification that allows for easier implementation and evaluation of various lookup schemes and techniques. GIDI+, as described on its public repository1, is ...a collection of C++ libraries for accessing evaluated and processed nuclear data stored in the Generalized Nuclear Database Structure (GNDS). In addition to reading GNDS files, GIDI+ has functions to sum and collapse multi-group data as needed by deterministic transport codes, and to sample GNDS data as needed by Monte Carlo transport codes. Certain modes of Mercury, a LLNL-developed MC radiation transport code, utilize GIDI+ for cross section lookups. Specifically, Mercury uses the MCGIDI library contained within GIDI+ to perform lookups on GPUs. A mini-app exercising MCGIDI’s cross section lookup capabilities would prove useful for optimization, which in turn could improve the performance of client codes such as Mercury. Such a mini-app could also be used to assess the performance of MCGIDI compared to other nuclear data mini-apps. In this document, we introduce a nuclear data mini-app built with the MCGIDI library. The MCGIDI mini-app (MCGIDI-MA) was developed to closely resemble the methodology present in XSBench, a nuclear data mini-app developed at Argonne National Laboratory. The remainder of this section provides an overview on XSBench. Section 2 describes MCGIDI-MA and its usage. Section 3 contains performance results of MCGIDI-MA on LLNL’s Lassen and Quartz compute platforms, as well as comparisons to XSBench performance where appropriate. In Section 4, we present a summary of our findings.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Verification of RESRAD-OFFSITE Code (V.4)

This report documents the verification of RESRAD-OFFSITE Version 4.0 and describes, where necessary, the verification of the following: • The data comprising the standard dose and risk coefficient libraries in the RESRAD database files Master_dcf_ICRP07.mdb and Master_dcf_2k.mdb. • The extraction and transfer of the data from the selected database file to the computational code by the RESRAD-OFFSITE 4.0 interface, ResOWin.exe. • The different processes that are modeled by the main computational code in RESRAD OFFSITE 4.0, ResOMain.exe. • The data displayed in the graphical and text reports. Many verifications were performed as part of the quality assurance quality control program associated with the development and release of RESRAD-OFFSITE 4.0, namely: • developer testing, • internal independent testing, and • release testing. Some were also performed in response to questions from users regarding the performance of the code. The main text of the report focuses on summarizing a subset of those tests, both independent and developer tests that verified the computations performed by the code. The verifications included in this report served as the basis for the development of the release tests of the computational executables and provided the quantitative results to be compared with the code output. The input and output interfaces and the data transfers between the various executables of the code were tested while performing the verification testing. They were tested intentionally during release testing. This report also provides some basic information to help in understanding the activities that were verified. The report: • outlines the components of RESRAD-OFFSITE 4.0 and the interconnections between these components, • outlines the processes modeled by the computational code, • provides summary figures and tables to offer confirmation of the verification of the computational components of the code, • reproduces the verifiers’ reports, if available, in individual appendices, • refers to the previous verification report (Yu et al. 2011) for more details about some of the verifications, and • reproduces the test cases and the testers’ reports from the release testing in individual appendices, when possible.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Changes to virus taxonomy, the international code of virus classification and nomenclature, and the ICTV statutes ratified by the International Committee on Taxonomy of Viruses (2025)

Abstract The 56th meeting of the Executive Committee (EC) of the International Committee on Taxonomy of Viruses (ICTV) was held in Bari, Italy, in July/August, 2024, and 115 submitted taxonomy proposals were reviewed. A total of 112 were subsequently ratified by the ICTV membership. An additional 9 error correction proposals were also approved in August 2025. This article lists the taxonomy proposals that have now been incorporated into release 40 version v2 of the Master Species List ( https://ictv.global/msl ), the Virus Metadata Resource ( https://ictv.global/vmr ), and associated ICTV databases. In addition to the assignments of 1,563 new virus species, 243genera, 55 families, 11 orders, and 8 classes, there were substantial additions to higher taxonomic ranks. These include the creation of a new realm ( Singelaviria ), which is based on the recognition of a separate evolutionary origin for the hallmark capsid genes of members of the kingdom Helvetiavirae. These express capsid proteins forming a single jelly-roll fold that is structurally and evolutionarily distinct from those of members of the family Bamfordvirae , assigned to the realm Varidnaviria . Furthermore, the realm Varidnaviria underwent a major reorganization, including the addition of a new kingdom, Abadenavirae . Another notable change was the classification of the vertebrate-infecting single-stranded DNA anellovirids into a new phylum Commensaviricota (kingdom Shotokuvirae , realm Monodnaviria ). Archaeal viruses infecting the hyperthermophilic Archaeoglobi were assigned to a new phylum Calorviricota , in the kingdom Trapavirae (realm Monodnaviria ), whereas RNA viruses infecting hyperthermophilic bacteria were classified into a new phylum Artimaviricota (realm Riboviria ). In recognition of his extensive and valuable contributions to virus taxonomic developments in Study Groups and over the period of his EC membership, Stuart Siddell was honoured as a new life member of the ICTV. The ICTV has created a new strategy for disseminating information on taxonomy advances through annual open-access publication of citeable taxonomy proposal summaries from each ICTV Subcommittee. A collective total of 354 co-authors of the seven summaries were drawn from members of each Subcommittee, the EC, and a very large number of contributors from the wider virology community.

Simmonds, Peter (ORCID:0000000279644700)↗
DOE OSTI2023

University Coalition for Fossil Fuel Energy Research

Following a nationwide open competition, the University Coalition for Fossil Energy Research (UCFER) was established in October 2015 through a cooperative agreement between Penn State and the Department of Energy (DOE) National Energy Technology Laboratory (NETL). Penn State lead UCFER with the objective of advancing basic and applied research for clean and low-carbon energy based on fossil fuels in support of the DOE’s mission. UCFER focused on research that improves the efficiency of production and use of fossil energy resources, while minimizing the environmental impacts and reducing greenhouse gas emissions. Penn State lead a team of nine universities (Massachusetts Institute of Technology, The Pennsylvania State University, Princeton University, Texas A&M University, University of Kentucky, University of Southern California, The University of Tulsa, University of Wyoming, and Virginia Polytechnic and State University) during the competition stage, adding seven more universities in 2017 (Carnegie Mellon University, Louisiana State University, The Ohio State University, University of North Dakota, University of Pittsburgh, University of Utah, and West Virginia University). This Coalition exhibited a wide geographical distribution across the U.S. bringing a wide variety of fossil energy expertise. This national university alliance was a major collaborative effort with NETL to address specific topics of R&D in NETL’s mission area, which involved one or more of NETL’s five core competencies (Geologic and Environmental Systems, Materials Engineering and Manufacturing, Energy Conversion Engineering, Systems Engineering and Analysis, and Computational Science and Engineering). The first five to six months of the project was the definitization stage. During this period, Penn State worked closely with NETL to finalize the Coalition organizational structure and By- Laws, prepare a statement of substantial involvement and a statement of project objectives, and develop operations and membership plans. A major component of this stage included preparing an execution plan to solicit research, evaluate proposals, recommend selected projects to NETL, and award projects. In addition, a plan was prepared to monitor projects, review projects, disseminate knowledge from research projects and develop an online system for Coalition research portfolio management. This included developing a website and several databases. The first of six rounds of solicitations started in mid-2016. Projects from the sixth solicitation started February 1, 2021, and ended January 31, 2023. Projects that were selected represented twelve technology lines. Approximately $16.6 million in funding was available for the six solicitations. Most of the funding was provided by DOE, Office of Fossil Energy (DOEFE) with the DOE Fuel Cells Technologies Office (DOE-FCTO) providing funding for a few projects. Coalition universities submitted 259 proposals in response to the solicitations, requesting approximately $67.0 million in funding, and forty-three projects were selected. However, one project withdrew after the principal investigator left the university. The management of the Coalition projects was a major activity by Penn State. Managing the Coalition projects consisted of monitoring the projects, reviewing the projects through annual technical review meetings, disseminating knowledge from the research projects, and developing an online system for Coalition research portfolio management. Penn State’s OMT monitored projects to ensure that all milestones (technical, schedule, budget) were met, expenditures were allowable, cost share (when applicable) were reported, and all technical reports were submitted. The OMT also posted the technical reports electronically on a secure members-only website for access and review by the Coalition members. Disseminating knowledge from the research projects was done through a website, newsletters, various meetings, conferences, journal articles, publicity/press releases, and project summaries that were prepared after each project was completed. Penn State kept NETL apprised of UCFER progress through quarterly reports (thirtyone were submitted by Penn State), verbal and written communications, yearly updates at the annual technical review meetings, and cost accrual reports. The UCFER project had a significant impacty. The UCFER program established the first national university alliance in fossil energy research with a major collaboration effort with DOE NETL that addressed specific topics in NETL’s research and development mission areas. It generated inter-university collaborations, which was another program interest. Twenty-two out of 259 proposals contained collaborations (≈8.5%) and three of forty-two funded projects involved inter-university collaborations (≈7.0%). The forty-two funded projects provided support at fourteen universities involving 269 personnel. Research was conducted by 106 faculty, 115 graduate and undergraduate students, forty-six research staff and post-doctoral scholars, and two visiting scholars. Students and post-doctoral scholars were also on-site at NETL through CRADAs. In addition, non-Coalition participants included six universities and sixteen companies and national laboratories. The non-Coalition participants were involved as subcontractors, providers of cost share, performed unpaid consultation and sample analysis, served as advisory board members, or were providers of samples and materials for testing. UCFER also produced visibility in that fifty-six refereed journal articles were published, fifty-seven conference papers and twenty-three posters were prepared, 190 presentations were given, eight patent applications were filed, two books/book chapters were written, and ten software codes were developed. Collaboration between NETL and the individual projects was a major requirement for all funded projects. This included NETL staff time to support collaboration, consultation, technical guidance, sample preparation and analysis, internships at NETL, on-site testing and equipment usage by Coalition participants at NETL, co-mentoring students, and coauthoring journal articles and conference papers. Collaboration was impacted by COVID-19 in that not all on-site activities could be performed. NETL personnel were coauthors on eight of the conference papers (fourteen percent of the conference papers that were prepared) and seventeen of the journal articles (thirty percent of the journal articles that were prepared). A website was developed for an online proposal solicitation and review process and to provide exposure to UCFER. A website analysis highlighted the large amount of member and general public interest in UCFER by interpreting access statistics from March 2016 through June 2023. Visitors to the site originated from many different organizations, businesses, and countries. The website provided a means to disseminate information to both the general public and the UCFER members and was successfully used for outreach activities. In addition, NETL required that RFP release, proposal submission, and proposal reviews all be performed online. Penn State successfully developed these capabilities in a secure section of the website, which were used throughout the UCFER project. It is recognized that each project had its technical successes. In addition, highlighted successes were compiled and summarized from the research projects. Information was requested from the PIs of completed projects. In addition, Penn State’s Operations Management Team reviewed subcontract reports to identify project successes. Examples of information requested from PIs included (not all-inclusive): new projects that have been funded as a result of UCFER funding; new commercial products; establishment of a new center; new patent; new software; best paper awards; highly-cited work; and graduate student successes. A total of forty-eight highlighted successes were reported.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

Uniformly Ordered Binary Decision Algorithm for Benchmark Experiment Correlations in Whisper Validation

When performing a validation exercise for determining the upper subcritical limit of a nuclear criticality safety application, an analyst should select and perform a statistical analysis on a population of benchmark experiments that are neutronically similar to the application. The size of this population should be sufficiently large such that the statistical analysis has a high degree of confidence that the bias plus bias uncertainty (calculational margin) has been accurately quantified. A complication arises because many benchmark experiments share common components, leading to correlations in their measured effective multiplication factors. Correlations between benchmark experiments within the population reduces its predictive power. This motivates the need for methods that consider benchmark experiment correlations and ensure adequate statistical significance of results. The Whisper code is a statistical analysis pack- age that incorporates nuclear data sensitivity coefficients from MCNP to assess benchmark experiment similarity and then performs an extreme-value analysis to estimate the bias plus bias uncertainty. The original methodology in Whisper does not consider the effect of benchmark experiment correlations when making this estimation, and this summary proposes the uniformly ordered binary decision algorithm to address this shortcoming. The original methodology in Whisper computes similarity coefficients ck for an application compared to all benchmark experiments in its library and develops weighting factors for a selected population proportional to the ck values. The methodology can be interpreted as statistically emulating a validation exercise for a particular application where the weighting factors may be viewed as the likelihood that an analyst would include a particular benchmark experiment within the population. The effective sample size of the population is the expected or mean number of benchmark experiments in the population. The uniformly ordered binary decision algorithm identifies clusters of correlated benchmark experiments within the population and then computes adjusted weighting factors based on the magnitude of the correlation coefficients within the cluster to compute a reduced effective sample size accounting for the lower information content because of correlations. Benchmark experiments within the cluster are ordered randomly with equal probability and probabilistic decisions are made as to whether a benchmark. experiment within the cluster should treated as redundant with a previous one; if two redundant benchmark experiments are included, then the conservative worst case bias plus bias uncertainty is used and the pair is counted as a single benchmark experiment in the population. Results are provided for HEU solutions in a research version of the Whisper software using benchmark experiment correlations provided by DICE, the Database for the International Criticality Safety Benchmark Evaluation Project (ICSBEP). These show that there can be a significant increase in the bias plus bias uncertainty because the effective sample size is reduced, and therefore the algorithm, needing to meet sample size requirements, expands the benchmark experiment population by accepting less similar benchmark experiments that would have otherwise not been included.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

1000 Soils Pilot Dataset, version 8, May 2025

This record hosts data generated by the 1000 Soils Pilot. Data will be updated as more become available. Please see the most recent data upload for current data. A beta visualization tool is available for some data types at https://shinyproxy.emsl.pnnl.gov/app/1000soils. Please submit any suggestions or comments through the 'contact' tab. We are actively working to improve visualizations and value all feedback. Data completed include: Geochemistry, texture, respiration, and enzyme activities FTICR-MS organic matter chemistry Microbial biomass C and N TOC/TDN of water-extractable OM X-ray computed tomography (derived metrics available here, raw data available upon request) Metagenomes; a variety of data formats are available upon request Soil hydraulic properties Data in progress: LC-MS/MS in development, timeline TBD, inquire for status 1000S_processed_BGC_summary.csv contains all available biogeochemical data; microbial biomass C and N; and TOC/TDN of water-extractable OM; and 1000S_Tomography.xslx contains a summary of data generated via X-ray computed tomography. icr_v2_corems2.csv contains FTICR-MS data processed by CoreMS version 2. These data are merged by formula across instrument runs to enable cross-sample comparisons. Technical replicates are merged by retaining peaks present in 2 out of 3 replicates. 1000Soils_Metadata_Site_Mastersheet_v1.csv contains site information. Soil Hydraulics_corrected_02042025.xlsx contains soil hydraulics information. Readme File_v4.xlsx is the readme file. Please contact the MONet project (monet.emsl@pnnl.gov) or Emily Graham (emily.graham@pnnl.gov) with questions. The following file and all raw data are available upon request: icr_by_mass_for_single_sample_analysis_only.csv contains FTICR-MS data processed by CoreMS and is intended for usage in the calculation of biochemical transformations within samples only. These data are not acceptable for cross-sample comparison of masses because they are from multiple instrument runs. For more information, please see: https://www.emsl.pnnl.gov/monet and https://sc-data.emsl.pnnl.gov/monet Acknowledgment: Soil data were provided by the Molecular Observation Network (MONet) at the Environmental Molecular Sciences Laboratory (https://ror.org/04rc0xn13), a DOE Office of Science user facility sponsored by the Biological and Environmental Research program under Contract No. DE-AC05-76RL01830. The work (proposal: 10.46936/10.25585/60008970) conducted by the U.S. Department of Energy, Joint Genome Institute (https://ror.org/04xm1d337), a DOE Office of Science user facility, is supported by the Office of Science of the U.S. Department of Energy operated under Contract No. DE-AC02-05CH11231. The Molecular Observation Network (MONet) database is an open, FAIR, and publicly available compilation of the molecular and microstructural properties of soil. Data in the MONet open science database can be found at https://sc-data.emsl.pnnl.gov/.

biogeochemistry↗
DOE OSTI2021

Computational Fluid Dynamics (CFD) Simulations of Taylor Bubbles in Vertical and Inclined Pipes with Upward and Downward Liquid Flow

Summary Two-phase flow is a common occurrence in pipes of oil and gas developments. Current predictive tools are based on the mechanistic two-fluid model, which requires the use of closure relations to predict integral flow parameters such as liquid holdup (or void fraction) and pressure gradient. However, these closure relations carry the highest uncertainties in the model. In particular, significant discrepancies have been found between experimental data and closure relations for the Taylor bubble velocity in slug flow, which has been determined to strongly affect the mechanistic model predictions (Lizarraga-García 2016). In this work, we study the behavior of Taylor bubbles in vertical and inclined pipes with upward and downward flow using a validated 3D computational fluid dynamics (CFD) approach with level set method implemented in a commercial code. A total of 56 cases are simulated, covering a wide range of fluid properties, pipe diameters, and inclination angles: Eo ∈ [10, 700]; Mo ∈ [1×10–6, 5×103]; ReSL ∈ [–40, 10]; θ ∈ [5°, 90°]. For bubbles in vertical upward flows, the simulated distribution parameter, C0, is successfully compared with an existing model. However, the C0 values of downward and inclined slug flows where the bubble becomes asymmetric are shown to be significantly different from their respective vertical upward flow values, and no current model exists for the fluids simulated here. The main contributions of this work are (1) the relatively large 3D numerical database generated for this type of flow, (2) the study of the asymmetric nature of inclined and some vertical downward slug flows, and (3) the analysis of its impact on the distribution parameter, C0.

Engineering↗
DOE OSTI2025

Summary of Analytical Services for the Hanford Site Radionuclide NESHAP Program

This document is a summary of the point source analytical requirements used to demonstrate compliance for the Department of Energy (DOE) Hanford Site operations with 40 Code of Federal Regulations (CFR) Part 61, “National Emission Standards for Hazardous Air Pollutants,” (NESHAP) Subpart H, “National Emission Standards for Emissions of Radionuclides Other Than Radon From Department of Energy Facilities,” and the Washington Administrative Code (WAC) 246-247, “Radiation Protection – Air Emissions.” This reference collects information from multiple source documents and is not intended to create, supersede, replace or over-ride any existing contractual, DOE, federal or state statutes, regulations, compliance agreements, orders, permits, licenses or other requirements. The requirement source document governs where any difference may exist. The Hanford Mission Integration Solutions (HMIS) Environmental organization has been contracted by DOE to manage and report data collected from the sampling and monitoring of radioactive air emissions point sources, colloquially called stacks. The Environmental organization coordinates the analyses and reporting of samples collected at various facilities across the Hanford Site. These facilities operate approximately 52 stacks that require sampling, monitoring or estimating radioactive air emissions. The stacks are operated by Bechtel National, Inc. (BNI), Central Plateau Cleanup Company (CPCCo), Hanford Tank Waste Operations & Closure (H2C), Hanford Laboratory Management and Integration (HLMI), and Pacific Northwest National Laboratory (PNNL). Stack samples from CPCCo, HLMI and H2C facilities are collected by the operating contractor staff, delivered to HMIS, and then shipped to an offsite contracted laboratory for analyses. The field and laboratory sample data uploaded into the Sample Management and Analytical Results Tracking (SMART) database are used to calculate sample volumes and concentrations. Sample concentrations are evaluated for compliance with federal and state regulations, permits, and license requirements. The SMART database also calculates total curies released for sampled point sources and stacks. Point source effluent concentrations and releases are published annually in publicly available reports. The BNI and PNNL operate several DOE-Hanford Field Office (HFO) stacks subject to the requirements of 40 CFR 61, Subpart H and WAC 246-247. The concentrations, curies released and dose modeling evaluation for these stacks are included in the DOE-HFO annual radionuclide NESHAP report. The sample collection, analyses and emissions estimates for these stacks are outside the scope of HMIS contracted responsibilities and not addressed further in this document.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Verification Testing of OLI Systems Mixed Solvent Electrolyte Model for the Na-K-Mg-Ca-H-Cl-SO 4 -OH-HCO 3 -CO 3 -CO 2 -H 2 ) System to High Ionic Strength at 25°C

This technical report summarizes model verification results and summary statistics for 41 evaporite mineral solubility cases evaluated by Savannah River National Laboratory using OLI Systems’ aqueous electrolyte thermodynamic modeling software. The 41 verification cases containing a total of 60 solubility curves comprise mineral solubility data from low to high ionic strength at 25°C for the eight-component system Na-K-Mg-Ca-H-Cl-SO 4 -OH-HCO 3 -CO 3 -CO 2 -H 2 O as reported by Harvie et al. (1984). Thermodynamic calculations were executed using OLI Systems’ Stream Analyzer computation module within the OLI Studio software platform (Ver. 11.0, Rev. 11.0.1.9). The Mixed Solvent Electrolyte (MSE) thermodynamic framework was chosen for this investigation because of its superiority in modeling high ionic-strength inorganic salt solutions and actinide redox chemistry and solubility, both of which are relevant to the geological repository conditions at the Waste Isolation Pilot Plant in Carlsbad, New Mexico. Mineral solubility data in various inorganic salt solutions were digitized and extracted from figures generated by Harvie et al. (1984). For each of the 60 solubility curves, a case-specific chemistry model and input file were generated in OLI Studio using OLI Stream Analyzer and the MSE (H 3 O + ion) public databank provided by OLI Systems. Model simulation results were exported to Microsoft Excel to calculate summary statistics and to generate graphs comparing the OLI model predictions to the solubility data. Summary statistics include residuals (model – data) and concordance (accuracy × precision, where precision is indicated by the Pearson correlation coefficient and accuracy accounts for bias and scale differential). Private databanks were not developed, and activity coefficient model regressions were not performed to improve OLI model fits to the data. Of the 41 model verification plots, 83% have a mean of the percent residuals less than or equal to 25%. Similarly, 75% display a concordance greater than or equal to 0.75. Only seven of the 41 verification plots fail to show good agreement between the model and data. Of these seven, three are relevant to the WIPP repository because they involve the Mg-OH-Cl-SO 4 -CO 3 aqueous system. The remaining four address salt solubilities at the pH extremes (strong acid and strong base). It should be noted that in two of the three Mg-OH-Cl-SO 4 -CO 3 system cases, the regressed Harvie et al. (1984) solubility curve also deviated from the data. Lack of agreement between the OLI model-predicted solubility curves and the data is attributable to one or more of the following: specific solid species are not included in the OLI MSE databank; there is significant variation among the different solubility datasets chosen by Harvie et al. (1984); the OLI MSE model’s thermodynamic parameters were determined using different solubility datasets; and the activity coefficient parameters for certain relevant ion-ion and ion-molecule pairs have not been optimized via data regression. Two recommendations for future work are to (1) evaluate solubility data for the Mg-OH-Cl-SO 4 -CO 3 system at high ionic strength and, if necessary, develop a private OLI MSE database that includes missing species and, where necessary, regressed standard state properties and interaction parameters; (2) perform similar verification testing of the OLI model for actinide solubility data.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

High Yield, Economical and Environmentally Benign Production of Rare Earth Elements from Coal Ash (Phase II Final Summary Report)

Fly ash stored in landfills and ponds across the United States is an attractive, abundant domestic resource for the cost-effective recovery of rare earth elements (REE) and other critical minerals (CM). Physical Sciences Inc. (PSI) and its team members, Winner Water Services (WWS) and University of Kentucky/Center for Applied Energy Research (UK/CAER) successfully executed a multiphase program that developed technologies and their implementation in a pilot plant. We demonstrated plant operations for cost-effective and environmentally-friendly production of rare earth element oxide (REO) concentrates, and the critical minerals scandium and aluminum (in the forms of salts or oxide products), from coal ash. We also constructed and demonstrated a research-scale (0.5 kg/day) micropilot facility to validate the key physical and chemical processing operations, predict yields, and troubleshoot process bottlenecks. The project team then designed, constructed and operated two decoupled pilot plants: (1) an operational pilot plant for physical separation processes with capacity of 0.4 metric tons per day (tpd), where we optimized processes to produce selected ash fractions as the feedstock for chemical processing and as valuable byproducts such as cenospheres, magnetic ash, and secondary fuel carbon, and (2) an operational pilot plant for chemical ash processing with a capacity of 0.5 tpd that developed optimized processes for the production of: (a) REO concentrates, (b) critical minerals (Sc, Al), and (c) beneficiated ash as a valuable byproduct suitable for cement applications. In Phase I, the project team (with Equinox Chemicals in place of WWS) developed and demonstrated the feasibility of the physical and chemical separation processes, developed the design of a pilot plant, and began the development of a preliminary techno-economic model. In the baseline (initial) Phase II program, the project team developed and demonstrated the above pilot scale plant, producing salable REE concentrates, including Y and Sc (REYSc), plus commercially viable byproducts, using environmentally safe and high-yield physical and chemical enrichment processes. The team successfully demonstrated chemical pilot design, construction, shakedown, and operations of the plant. We produced the Phase II deliverable REYSc concentrate ((50 g of >60 wt.% purity REYSc salts on elemental basis), generated the feed for the Phase II follow-on program, identified processing challenges for future optimizations, and refined the techno-economic model. In the Phase II follow-on program, the project team: (1) developed and demonstrated processes to increase the REE amount by 3X (content basis) and convert the Phase II REE salt mixture to an oxide mixture, (2) produced/delivered >38 g of REO mixture with >85 wt.% purity (elemental basis); (3) developed processes to recover critical minerals scandium and aluminum from intermediate streams; (4) produced/delivered > 1 g of scandium salt mixture with >85 wt. % purity (elemental basis); (5) produced/delivered > 100 g of aluminum oxide type material with >70% wt. purity (elemental basis); and (6) updated the techno-economic model from the baseline Phase II program to assess CAPEX and OPEX of a commercial operation. This program has developed extensive databases on process chemistry, unit operations, plant engineering, and techno-economics that will enable further scale-up toward commercial plant design. Specific future developments will be focused on achieving dramatic savings in energy, reagent usage, and operating costs. The combined results will contribute significantly for maturing the technologies of REE recovery from coal byproducts and promote the establishment of domestic REE and CM supply chains.

01 COAL, LIGNITE, AND PEAT↗