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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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DOE OSTI2018

The Michigan New Technology Training and Research (MNTR) Translational Program in Nuclear Medicine (Final Report)

The Michigan New Technology Training and Research (MNTR) Translational Program in Nuclear Medicine and Molecular Imaging This project established the Michigan New Technology Training and Research (MNTR) translational program, focused on the acceleration of new clinical molecular imaging methods. Molecular imaging approaches to imaging are a very flexible and powerful development, with many recent examples advancing the diagnosis and guiding the management of human disease. These methods depend on the design, synthesis and testing of new radiotracers (molecules designed to target specific cells or tissues in the body), labeled with short-lived radioactive atoms (positron emitters). The new radiotracers are imaged in the human body using positron emission tomography (PET) imaging. The University of Michigan PET Center has considerable experience in the discovery, development, refinement and initial human applications of new PET radiotracers. An emerging impediment to efficient availability of new PET radiotracers, however, involves the regulatory environment at multiple levels. Many potentially successful ideas are delayed or even prevented from entering human use by these barriers. In the current grant, we provided hands-on experience for the next generation of young scientists working in molecular imaging so that they are equipped to effectively move new ideas and radiotracers from the research laboratory to the nuclear medicine clinic (bench-to-bedside). For new radiotracer development, oversight by the Food and Drug Administration (FDA), the Nuclear Regulatory Commission (NRC), and local institutional committees and reviews are required. These aspects of translation from laboratory to clinic are often omitted from the formal training of new scientists, but were provided to three trainees via direct mentorship in the MNTR program. The MNTR training program built on the translational successes of the University of Michigan Division of Nuclear Medicine and capitalized on our strengths (facilities, faculty, a wide-ranging selection of projects, and the experience and commitment to bring new radiotracers into human studies) to systematically train three fellows in radiochemistry and nuclear medicine. Integrated training in development, validation and clinical translation of new PET radiotracers occurred through practical involvement in multiple research projects, each at a different stage along the pathway from bench-to-bedside. Each trainee obtained experience of the entire process over about 2 years. Projects involved development of new radiotracers for neurodegenerative disorders (e.g. Alzheimer disease), movement disorders (e.g. Parkinson disease, progressive supranuclear palsy) and neurodevelopmental syndromes (e.g. Tourette syndrome) as well as new radiochemistry methods for synthesizing radiotracers. Each project was pursued in a close collaboration between the fellow trainee and both the clinical and basic science faculty at the University of Michigan PET Center, and provided an unprecedented opportunity for the highest-level training in academic radiochemistry and nuclear medicine research. The project has resulted in 17 peer-reviewed publications to date, and at least 4 more are in preparation. Additionally, 1 book chapter and 26 conference presentations have resulted from this grant. Upon completion of the MNTR Program, the trainees have emerged as translational scientists wielding the necessary skill-set (practical research experience, multidisciplinary training, regulatory know-how) to embark on successful careers in translational molecular imaging, bringing continued advances in the field to bear on important human disorders. As a metric of the Program’s success, one fellow has already secured employment in the field, while the other two are finishing writing papers; they wish to also stay in the radiochemistry and nuclear medicine community, and are currently applying for jobs.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2018

Carbon Capture Multidisciplinary Simulation CenterTrilab Support Team Fall Meeting 2018 Report

The TST continues to be very impressed with the quality of work presented and the rapid progress made by the CCMSC on a highly complex multiphysics problem domain. The Center is gathering increasing expertise and experience in multiple areas likely to be of broad interest to DOE and the greater HPC community, particularly in the areas of programming models and DSLs, I/O, V&V/UQ, and visualization/data analytics. This year in particular saw very impressive results in their task graph algorithms, strong and weak scaling of their overall code, and sophistication of their physics models and V/UQ analysis and approach. The team was particularly impressed with the depth of engagement and quality of discussion at the V/UQ deep dive. There are very few organizations outside of NNSA doing multiphysics simulation at this level of accuracy, efficiency, scale and sophistication and DOE would be well-advised to actively work to maintain a close collaborative relationship with this team after the completion of the PSAAP II program if at all possible.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2020

The Impact of Nuclear Physics Uncertainties on Galactic Chemical Evolution Predictions

Modeling the evolution of the elements in the Milky Way is a multidisciplinary and challenging task. In addition to simulating the ~13 billion years evolution of our Galaxy, chemical evolution simulations must keep track of the elements synthesized and ejected from every astrophysical site of interest (e.g., supernova, compact binary merger). The elemental abundances of such ejecta, which are a fundamental input for chemical evolution codes, are usually taken from theoretical nucleosynthesis calculations performed by the nuclear astrophysics community. Therefore, almost all chemical evolution predictions rely on the nuclear physics behind those calculations. In this proceedings article, we highlight the impact of nuclear physics uncertainties on galactic chemical evolution predictions. We demonstrate that nuclear physics and galactic evolution uncertainties both have a significant impact on interpreting the origin of neutron-capture elements in our Solar System. Those results serve as a motivation to create and maintain collaborations between the fields of nuclear astrophysics and galaxy evolution.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Aquatic Carbon-Nutrient Dynamics as Emergent Properties of Hydrological, Biogeochemical, and Ecological Interactions: Scientific Advances

Carbon and nutrient dynamics in aquatic systems often emerge as the result of hydrological, biogeochemical, and ecological interactions. Due to the multiscale and multidisciplinary nature of these process interactions, research into aquatic carbon and nutrient dynamics is becoming increasingly interdisciplinary. The motivation for this special issue came from an international workshop titled "Hydro-Biogeochemical Processes: Mechanisms, Coupling, and Impact, " which took place from 27 to 31 October 2015 at China University of Geosciences, Wuhan, China. During this workshop, scientists from various countries and disciplines met to discuss current work and future advances on topics such as the hydro-biogeochemistry of Earth's critical zone, stream-groundwater interaction zones, aquatic ecosystem processes, and dynamics at land-atmosphere, land-ocean, and human-natural interfaces. Contributions to this special issue on "Emergent aquatic carbon-nutrient dynamics as products of hydrological, biogeochemical, and ecological interactions" include papers from authors who attended the workshop and from those who responded to the open solicitation for papers. Finally, our aim in organizing this special issue is to stimulate continued discussion and collaboration across disciplinary boundaries in order to further our collective understanding of aquatic carbon-nutrient dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Exploring life’s hidden majority: microbial dark matter symposium highlights

The Microbial Dark Matter Symposium held on August 28–29, 2025, in Laguna Beach, Orange County, CA, convened a multidisciplinary group of scientists to address the vast unknowns in microbial life—from uncultured taxa and uncharacterized proteins to elusive viruses and spacefaring microbes. Set against a scenic coastal backdrop, the symposium highlighted advances in single-cell genomics, proximity ligation sequencing, and artificial intelligence-ready bioinformatics, while also probing the limits of microbial persistence, metabolism, and ecological distribution. Sessions explored microbial dark matter from multiple dimensions: cultivability, where new strategies are enabling recovery of elusive microbes; functional ambiguity, where metagenomic dark zones are illuminated by computational annotation; and genomic representation, where single-cell methods bridge gaps left by shotgun community sequencing. Researchers shared breakthroughs in identifying atmospheric microbiomes, “dark oxygen” production in groundwater ecosystems, and microbial survival on the International Space Station. The symposium emphasized integration of methods, disciplines, and ecosystems, advancing a collective push to illuminate the microbial dark matter on Earth and beyond. By highlighting emerging tools, pressing questions, and cross-domain insights, the symposium underscored the need for collaborative, open, and adaptive approaches to study the microbial unknown. The meeting marks a pivotal moment in microbiology, where cultivating knowledge of the uncultivated promises transformative understanding of life, everywhere.

Podar, Mircea [ORNL] (ORCID:0000000327760205)↗
DOE OSTI2026

Cooperative Education

Los Alamos National Laboratory (LANL) is a multidisciplinary national laboratory that conducts research and development in national security, engineering, materials science, computational modeling, and advanced manufacturing. The laboratory develops innovative technologies to address complex scientific and engineering challenges. This project focuses on the development and evaluation of high-performance absorbing structures through computational design, simulation, and engineering analysis. Absorbing structures are used in applications where damage mitigation, structural protection, and material efficiency are critical performance requirements. The increasing demand for lightweight, high-strength, and highly efficient structural systems has created a need for improved design methodologies capable of maximizing absorption while minimizing weight and material usage. The project utilizes advanced engineering software, including 3D CAD software and FEA, to generate and optimize structural concepts. Computational simulations are performed to evaluate structural behavior under loading conditions, while mathematical analyses are conducted using Python-based tools as well as established analytical equations from material and structural mechanics. The project benefits LANL by supporting the development of advanced design methodologies and improving the understanding of material and structural performance. During the internship term, a significant portion of the design development, simulation, and data analysis activities will be completed. Success of the project depends on collaboration among engineering mentors and technical staff members. Work will be conducted at Los Alamos National Laboratory using laboratory computing resources and engineering software.

42 ENGINEERING↗
DOE OSTI2018

The Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAIC) Atmosphere Science Plan

Arctic climate change is amplified relative to global change, and is embodied by a dramatic decline in the perennial sea-ice pack. These cryospheric transitions carry significant implications for regional resource development, geopolitics, and global climate patterns. Indeed, the changing arctic cryosphere is considered a grand challenge for global climate research. Arctic change, and its linkages with the global system, must be understood. Additionally, there is a growing stakeholder community that requires improved sea-ice forecasting for many applications. To make progress on these important issues requires developing a detailed, process-level understanding of the coupled climate system that can help to address the numerous deficiencies in numerical model representations of the Arctic. Such an understanding is only possible by making targeted, interdisciplinary measurements within the central arctic sea-ice environment. The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) initiative has been developed in response to these great challenges. It comprises three parts: 1) An intensive, icebreaker-based observatory that will freeze in, and drift with, the arctic sea ice for a full annual cycle making interdisciplinary measurements in the atmosphere, sea ice, upper ocean, and biosphere; 2) A distributed network of targeted, autonomous measurements to characterize spatial variability on model grid-box scales; and 3) Coordinated, multiscale analysis and modeling activities. MOSAiC is a major, international effort that will involve participation of many different agencies and entities. The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility is uniquely positioned to play a critical role in this initiative by providing a comprehensive instrument suite to characterize the atmosphere and its interactions with the sea-ice surface. ARM will deploy its second Mobile Facility (AMF2) and Mobile Aerosol Observing System (MAOS) at the MOSAiC central observatory as it drifts through the central Arctic for a 13-month campaign starting in September 2019. Sea-ice is an integrator of energy fluxes in the coupled arctic climate system; thus, atmosphere-ice-ocean processes impacting the flow of energy through this system in all seasons are the primary target of MOSAiC. The broader, collaborative MOSAiC initiative will allow for many interdisciplinary studies along this theme. ARM’s involvement will target specific areas related to the atmosphere and atmosphere-surface interactions that are critically under-observed in the Arctic, are leading contributors to model uncertainties in the region, and are programmatically important to DOE research and modeling programs. The guiding science themes for this project include: (1) The surface energy budget of sea ice; (2) Clouds and precipitation; (3) Aerosols; and (4) The atmospheric boundary layer. Many fundamental issues concerning these themes are lacking in observational constraints, particularly in the arctic winter and through consecutive seasons. For example, little is known about the energy budget of first-year sea ice, the annual cycle of central arctic aerosol concentrations, the spatial organization of cloud-precipitation systems relative to sea-ice heterogeneity, the winter boundary-layer evolution, or cloud-surface coupling processes over sea ice. The proposed ARM observations will be groundbreaking in many ways, and will ultimately have a dramatic impact on the arctic research community and its ability to represent coupled arctic processes in numerical models.

North Slope of alaska, Arctic sea ice, Barrow, Arc↗
DOE OSTI2017

Steady-State Subchannel Thermalhydraulic Assessment of Thorium-Based Fuel Concepts for Use in Pressure Tube Heavy Water Reactors

Thorium is an abundant alternative fertile nuclear fuel that could potentially be implemented in pressure tube heavy water reactors (PT-HWR) in the near future. One of the key stages in developing the thorium-based fuels for PT-HWRs is the reactor core concept, which requires the collaboration of different disciplines, such as neutron physics, thermal-hydraulics, materials, chemistry, safety, and others. Currently there are numerous core concepts under investigation at the Canadian Nuclear Laboratories that involve several types of thorium-based fuels, and that could be implemented in a 700-MWe-class PT-HWR. Four fuel bundle concepts are considered, including i) the reference (or nominal) 37-element bundle; ii) a 37-element modified bundle, with the center element using a different fuel material; iii) a 35-element bundle design, and iv) an 18-element internally cooled annular fuel (ICAF-18) fuel bundle. This study presents preliminary results of the steady-state thermalhydraulic subchannel analyses of the hot channels of different PT-HWR core concepts using thorium-augmented or thorium-based fuels. A follow up study will be initiated to improve the assessment of the proposed cores and associated fuel bundle concepts for thorium-augmented and thorium-based fuels. The computational model will be revisited to include; - Expanding the analysis to cover different power profiles at different burnup stages of the bundle. - Expand the analysis to cover 28.5 kg/s. - Reduce the eccentricity of the 35-element fuel bundle. - Assess the effect of the phenomena not yet included in the subchannel model (such as the effect of cold wall, and gamma heat). - Expand the analysis to include the effect of spacers and junctions. - Compare bundle concepts using other performance indicators (such as burnup, breeding ratio), as optimizing the fuel bundle geometry is a multidisciplinary problem.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

2019 Budget Request for the DOE Computational Science Graduate Fellowship (CSGF) Grant

The Department of Energy Computational Science Graduate Fellowship (DOE CSGF) is necessary to meet the continual challenging national workforce needs that arise as computational science and engineering problems continue to grow in scope and complexity. Computational science and engineering (CSE) is a multidisciplinary approach that uses scientific computing to solve practical problems methods and to supply technical tools across the scientific discovery spectrum. In particular, the DOE CSGF emphasizes high-performance computing (HPC) that enables CSE that advances science and engineering in directions important to the DOE and the economy in general. Over the past half-century, HPC has been an essential tool for DOE’s success. During this period, important missions, such as nuclear stockpile stewardship, have turned to HPC as an essential technology. Entire science disciplines, such as biology and cosmology, have been transformed through the augmentation of scientific observation via HPC. At government laboratories and in industry, DOE CSGF alumni are helping push traditional HPC boundaries while contributing to discoveries in high-energy physics, renewable energy, fusion-reactor design, additive manufacturing, nanomaterials for next-generation batteries and transistors, and turbine and advanced nuclear reactor modeling. In addition, HPC is used to address national health needs that will eventually point to cures both by helping cancer researchers manage and analyze huge troves of data, by simulating biological mechanisms, and by accelerating drug development — including continuing to rise to the challenge of pandemic-related research. A 2023 report from the ASCAC Subcommittee on American Competitiveness and Innovation to the ASCR office, “Can the United States Maintain Its Leadership in High-Performance Computing?” says of the Program, “The CSGF program provides a barometer for disciplines that will be of interest to future DOE computing.” An explosion in scientific and technological data has driven the need for increasingly sophisticated HPC to transform those data into scientific understanding. With access to more and more data and the proliferation of HPC, Machine Learning and Artificial Intelligence are experiencing a renaissance, complementing the now well-established use of computational simulation. Indeed, in its September 2020 subcommittee report on “AI/ML, Data Intensive Science and High-Performance Computing”, the DOE Advanced Scientific Computing Advisory Committee (ASCAC) explicitly called for a fellowship program to train computational and data scientists to tackle exascale and data-intensive computing challenges. This collaboration of empirical and theory-based modeling will increasingly inform federal policymakers whose decisions affect American society and future generations, and it requires highly skilled and intellectually agile computational scientists who can support the fast-moving DOE National Laboratory research environment. In fact, the DOE CSGF program has explicitly and consistently addressed this need.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

INTEGRATE - Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements

The INTEGRATE (Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements) project is developing a new inverse-design capability for the aerodynamic design of wind turbine rotors using invertible neural networks. This AI-based design technology can capture complex non-linear aerodynamic effects while being 100 times faster than design approaches based on computational fluid dynamics. This project enables innovation in wind turbine design by accelerating time to market through higher-accuracy early design iterations to reduce the levelized cost of energy. INVERTIBLE NEURAL NETWORKS Researchers are leveraging a specialized invertible neural network (INN) architecture along with the novel dimension-reduction methods and airfoil/blade shape representations developed by collaborators at the National Institute of Standards and Technology (NIST) learns complex relationships between airfoil or blade shapes and their associated aerodynamic and structural properties. This INN architecture will accelerate designs by providing a cost-effective alternative to current industrial aerodynamic design processes, including: - Blade element momentum (BEM) theory models: limited effectiveness for design of offshore rotors with large, flexible blades where nonlinear aerodynamic effects dominate - Direct design using computational fluid dynamics (CFD): cost-prohibitive - Inverse-design models based on deep neural networks (DNNs): attractive alternative to CFD for 2D design problems, but quickly overwhelmed by the increased number of design variables in 3D problems AUTOMATED COMPUTATIONAL FLUID DYNAMICS FOR TRAINING DATA GENERATION - MERCURY FRAMEWORK The INN is trained on data obtained using the University of Marylands (UMD) Mercury Framework, which has with robust automated mesh generation capabilities and advanced turbulence and transition models validated for wind energy applications. Mercury is a multi-mesh paradigm, heterogeneous CPU-GPU framework. The framework incorporates three flow solvers at UMD, 1) OverTURNS, a structured solver on CPUs, 2) HAMSTR, a line based unstructured solver on CPUs, and 3) GARFIELD, a structured solver on GPUs. The framework is based on Python, that is often used to wrap C or Fortran codes for interoperability with other solvers. Communication between multiple solvers is accomplished with a Topology Independent Overset Grid Assembler (TIOGA). NOVEL AIRFOIL SHAPE REPRESENTATIONS USING GRASSMAN SPACES We developed a novel representation of shapes which decouples affine-style deformations from a rich set of data-driven deformations over a submanifold of the Grassmannian. The Grassmannian representation as an analytic generative model, informed by a database of physically relevant airfoils, offers (i) a rich set of novel 2D airfoil deformations not previously captured in the data , (ii) improved low-dimensional parameter domain for inferential statistics informing design/manufacturing, and (iii) consistent 3D blade representation and perturbation over a sequence of nominal shapes. TECHNOLOGY TRANSFER DEMONSTRATION - COUPLING WITH NREL WISDEM Researchers have integrated the inverse-design tool for 2D airfoils (INN-Airfoil) into WISDEM (Wind Plant Integrated Systems Design and Engineering Model), a multidisciplinary design and optimization framework for assessing the cost of energy, as part of tech-transfer demonstration. The integration of INN-Airfoil into WISDEM allows for the design of airfoils along with the blades that meet the dynamic design constraints on cost of energy, annual energy production, and the capital costs. Through preliminary studies, researchers have shown that the coupled INN-Airfoil + WISDEM approach reduces the cost of energy by around 1% compared to the conventional design approach. This page will serve as a place to easily access all the publications from this work and the repositories for the software developed and released through this pr...

aerodynamics↗
DOE OSTI2018

Developing Novel Multifunctional Materials for High-Efficiency Electrical Energy Storage

This is the final report for the program “Developing Novel Multifunctional Materials for High-efficiency Electrical Energy Storage”, funded by The U.S. Department of Energy’s (DOE) National Energy Technology Laboratory (NETL), and performed by University of Tennessee, from September 01, 2013 to August 31, 2018. Securing a sustainable energy economy by developing affordable and clean energy from renewable energy is a central element to the mission of DOE/NETL. To further this mission, NETL funds research and development of novel multifunctional materials that can be used for high-efficiency electrical energy storage. The main objective of this research program is to conduct fundamental and applied research that lead to successful development and demonstration of novel multifunctional materials, which can improve the efficiency and reduce the cost of hydrogen production with water electrolysis. The specific objectives of this research program include: 1) Design, fabrication and demonstration of thin/well-tunable liquid/gas diffusion layer (TT-LGDLs) with different pore morphologies, including pore sizes and pore porosities. 2) Development of comprehensive computational models of proton exchange membrane water electrolyzer cell (PEMECs) for the investigation of influence of different operating conditions and physical design parameters on its performance. 3) Surface modification of TT-LGDLs for better catalyst access and product/reactant removal, and smaller interfacial contact resistance (ICR). To achieve the above challenging goals, a multidisciplinary research team was formed to work on fundamental and applied research on the following three major technical areas: 1) Design, fabrication and demonstration of thin/well-tunable LGDLs (TT-LGDLs) by using photolithography and wet etching of thin titanium (Ti) foils. During the project period, the team has successfully fabricated TT-LGDLs with different pore morphologies, including pore sizes and pore porosities. The manufacturing steps mainly include cleaning thin Ti foil, supporting the foils, applying photoresist, patterning the photoresist with designed mask, exposing and developing, etching, removing photoresist, and lift-off and cleaning. The manufactured TT-LGDLs were characterized with optical microscopies and scanning electron microscopies. Their pore morphologies, including pore size and porosity, were derived based on advanced image process. The feasibility for scale-up manufacturing has been demonstrated. The TT-LGDLs have been successfully investigated for water splitting in PEMECs, which showing better performance than their counterparts fabricated with the traditional fiber-based materials. 2) Comprehensive computational modeling of a PEMEC. A comprehensive computational model has been successfully developed, and the influence of different operating conditions and physical design parameters on its performance has been investigated, including operating temperature, pressure, exchange current density, electrode thickness, membrane thickness, and interfacial resistance. Results obtained from the present model provide a comprehensive understanding of design parameter effects and consequently improve the design/performance in a PEMEC. 3) Surface modification of TT-LGDLs. The proposed surface modifications of TT-LGDLs by sputter coating and/ electroplating have been successfully demonstrated. It has been found that the performance of PEMECs can be improved by both methods, and the thickness of the electroplated gold thin layer has limited effects on the performance. With the help of the surface modifications, the PEMECs achieved the best ever performance compared with the public literatures. In addition to completion of the proposed method, microporous layers (MPLs) with both irregular micro and sphere nano titanium particles on novel TT-LGDLs was developed for the first time. The MPLs were fabricated by a low-temperature air spraying method, which provide a better catalyst access and product/reactant removal. In summary, under the close collaborations among the research team, all the tasks have been completed and the proposed research objectives have been fulfilled. All the technical milestones have been achieved and the project has been completed successfully. The technical breakthroughs obtained under this project provide novel LGDLs with well-tunable pore morphologies that can significantly improve the performance of water splitting and energy storage. This development can be directly used in existing and next generation energy storage and fuel systems.

08 HYDROGEN↗
DOE OSTI2024

Proceedings for the Workshop on Applied Nuclear Data Activities 2024

The Workshop for Applied Nuclear Data Activities (WANDA) is designed to increase communication among nuclear data (ND) users in multidisciplinary federal programs, ND producers, ND funders, and other ND experts. It also presents an opportunity to cross-pollinate ideas as well as introduce ND gaps identified by federal programs to ND experts and ND capabilities to the various federal ND users. WANDA 2024 included five technical sessions, three of which focused on Fusion Energy Sciences (FES)—FES Fusion Neutronics, FES Tritium Production, and FES Material Damage—and two stand-alone sessions—Isotopes and Targetry for Nuclear Data and Uncertainty Quantification. The FES sessions successfully brought new voices to the WANDA discussions, expanding the application space in which nuclear data are critical. FES programs need accurate nuclear data with realistic uncertainty quantification to properly estimate, for example, shielding, activation, tritium production, helium production, structural material integrity, and superconducting magnet operation. This includes a variety of projectile (neutrons, photons, charged particles) and target atoms. One of the action items common to all the FES sessions was a need to perform sensitivity studies to identify the prioritization of nuclear data needs. The Isotopes and Targetry session highlighted the many capabilities available to produce high-quality targets for nuclear data measurements, including 3D printing with spherical powders, combustion synthesis coupled with spin coating & electrospraying, inkjet printing, and isotopic doping. These new methods open doors for more accurate measurement, but it was also stressed that sample characterization following any method of fabrication is of the highest importance to accurately interpret nuclear data measurement results that used that sample. The Uncertainty Quantification (UQ) session was broken into two categories: nuclear data uncertainty quantification and the use of that uncertainty quantification. Thematic to the UQ session was the loss of information when going from nuclear data measurement, to evaluation, to evaluated file, and finally to neutron transport calculations. Current evaluated ND libraries typically only contain covariances, which assume that the probability distributions are Gaussian. Beyond being a simplified assumption for many evaluations, this can lead to negative values on many observables when attempting to sample the covariance. The covariance format, however, is very efficient in that a simple set of linear equations can transform uncertainty from parameters or cross sections to the application of interest. Focused collaboration is needed between nuclear data evaluators and nuclear data users to ensure that needs are being met.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

DOE new players Carbon cycle (2016-2021)

The overarching scientific goals of our multidisciplinary grant was to further expand understanding about the key microorganisms (players), metabolic strategies (processes), and interspecies relationships (interactions) involved in the formation and oxidation of methane in the environment. This research applied novel environmental metagenomics, transcriptomics, and proteomic techniques, state-of-the-art analytical imaging, stable isotope geochemistry, and reaction-transport modeling to address these goals and develop an ‘ecosystems level’ understanding of the factors which regulate microbial methane cycling in anoxic sedimentary ecosystems. For decades, it was believed that the obligate step in methanogenesis catalyzed by methyl coenzyme M reductase (Mcr) was limited to a specific branch of the archaeal Domain, formerly known as the Euryarchaeota. Less than a decade ago co-I Tyson’s team published a surprising metagenomic-based discovery of divergent Mcr genes in a novel uncultured phylum (Bathyarchaeota), catalyzing a major shift in thinking about the diversity of microorganisms that encode the potential for methane (or higher alkane) metabolism in anoxic environments (Evans et al., 2015). In our work here, we further expand on the groups of archaea harboring the genomic potential for methane or hydrocarbon metabolism using environmental metagenomics and new gene targeted bioinformatics techniques. We additionally advanced understanding about the terminal electron acceptors and metabolic potential supporting the anaerobic oxidation of methane (AOM) in terrestrial ecosystems, specifically focused on new lineages of ANME archaea capable of respiring manganese oxides with methane presumably using large extracellular multi-heme cytochrome complexes. New details about specific syntrophic mechanisms underlying the exchange of electrons during sulfate-coupled methane oxidation between ANME-2 archaea and their sulfate-reducing bacterial partners were also elucidated as part of this funded project. Through a series of experimental ‘omics and single cell stable isotope probing studies with incubated environmental sediment samples and a cultured model electrogenic microorganism combined with model-based predictions. Combined, this work provides strong support for the hypothesis of direct interspecies electron transfer (DIET) is the dominant syntrophic mechanism controlling the anaerobic oxidation of methane with sulfate over other proposed mechanisms and additionally illustrates important spatial constraints and the underlying physico-chemical factors influencing AOM syntrophic consortia structure for DIET and extracellular metal respiration. This collaborative multi-institutional project successfully advanced several of our milestone goals including the identification of new microbial players containing methyl coenzyme M reductases hypothesized to be central to methane or hydrocarbon cycling in anoxic environments and enhancing fundamental knowledge about the role extracellular electron transfer plays in the ecophysiology of methanotrophic archaea respiring metal oxides and in the physical and metabolic structuring of syntrophic interactions in methane-rich sedimentary ecosystems.

03 NATURAL GAS↗