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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 OSTI2026

Fuel Performance Modeling Internship Final Presentation

This study examines the performance of U-Zr and U-Pd-Zr annular metallic fuel rodlets and details the current status of modeling efforts regarding U-Pu-Zr solid metallic fuel rodlets which were experimentally evaluated as part of the Advanced Fuels Campaign (AFC). The AFC mission is to develop novel fuel technologies and facilitate the implementation of those technologies by industry partners. A key objective is to improve steady-state and transient performance over current fuel types. The experiments of interest in this study included metallic fuel rodlets within HT-9 cladding which were placed in SS-316 capsules and inserted in the Advanced Test Reactor (ATR). Certain mechanical and thermal conditions cannot be directly evaluated through experiments and fuel performance modeling is used to shed light on this evolution over time. In this study, BISON Multiphysics simulations are leveraged to investigate the state of the fuel system throughout and after the experimental conditions.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Extension of Virtual Test Bed Advanced Modeling and Simulation Capabilities for Fusion Energy

The National Reactor Innovation Center (NRIC) was established to accelerate the deployment of novel reactor concepts. This is achieved by providing physical and virtual spaces for building and testing reactor experiments. The Virtual Test Bed (VTB) represents the virtual counterpart to the physical test beds. It is a collaboration with the Department of Energy’s (DOE) Nuclear Energy Advanced Modeling and Simulation (NEAMS) program with the mission to accelerate the deployment of advanced reactors by facilitating the adoption of advanced modeling and simulation (M&S) tools developed by the DOE. This mission has been carried out by the VTB since 2020 by hosting and featuring dozens of advanced fission nuclear reactor models developed by national laboratories and academia. The charter of the NRIC’s definition of advanced reactors also includes fusion nuclear reactors. As the tools developed by the NEAMS program are increasingly used for modeling fusion energy devices, there is an increasing need to host fusion reactor models on the VTB repository. The VTB will be extended in 2024 to support fusion energy modeling and simulation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Small arms suppression project (LLNL final report)

US Special Operations Command (USSOCOM) was seeking a technological leap in small firearms weapon suppressor technology, because anticipated enemy capabilities are requiring the operators to have smaller detection cross sections to ensure the safe execution of missions. Suppressors have been developed almost exclusively through trial-and-error methods since the time of the original design by Hiram Maxim over one hundred years ago. Consequently USSOCOM deemed it prudent to perform a physicsbased study of weapon suppression to understand performance limits and possibly identify breakthrough technologies. Lawrence Livermore National Laboratory’s (LLNL’s) high performance production level computational tool called ALE3D (Arbitrary Lagrangian-Eulerian 3D and 2D) has unique physics models and numerical algorithms for modeling suppressor dynamics. The flexible and extendable code framework supports fully integrated hydrodynamics, heat transfer, solid and fluid dynamics, and chemistry that can be applied to simulating propellant-driven motion of a bullet down a gun barrel, the transfer of heat from the burning propellant to the barrel and suppressor, the chemistry of muzzle flash, and the shock/acoustic/optical signatures in the near-field. LLNL’s originally anticipated role was to augment ALE3D for this task, by developing the software and analysis methodologies specific to the simulation of blast and muzzle flash phenomena. It was believed that insights provided by our ALE3D simulations in tandem with a coordinated experimental component by our other team members from Oak Ridge National Laboratory (ORNL) and the U. S. Army Armament, Research, Development and Engineering Center (ARDEC), would have excellent prospects of yielding useful suppressor design improvements that could be transitioned to industry and utilized by US Special Operations Command. The three year effort has come to fruition with the development of revolutionary suppressor designs that far outperform any previous or current design by anyone outside this multi-lab team.

42 ENGINEERING↗
DOE OSTI2024

Probing photochemical kinetics and mechanisms using photoNMR

Nuclear magnetic resonance spectroscopy (NMR) is a form of spectroscopy that yields detailed mechanistic information about chemical structures, reactions, and processes. Photochemistry has widespread use across many industries and holds excellent utility for additive manufacturing (AM) processes. Here, we use photoNMR to investigate three photochemical processes spanning AM relevant timescales. We first investigate the photodecomposition of a photobase generator on the slow timescale, then the photoactivation of a ruthenium catalyst on the intermediate timescale, and finally the radical polymerization of an acrylate system on the fast timescale. In doing so, we gain fundamental insights to mission relevant photochemistries and develop a new spectroscopic capability at SNL.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Cluster Dynamics Modeling Needs for the Advanced Materials and Manufacturing Technologies Program

This milestone report aims to identify and assess the cluster dynamics (CD) modeling requirements within the Department of Energy's Office of Nuclear Energy (DOE-NE) Advanced Materials and Manufacturing Technologies (AMMT) program and to communicate these needs to the DOE-NE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. The goal is to ensure NEAMS is well-informed about the CD modeling requirements to support AMMT's mission of accelerating the development, qualification, demonstration, and deployment of advanced structural materials and manufacturing for nuclear energy applications. CD modeling is an essential tool for predicting the degradation of structural materials under irradiation, which is a key component of AMMT's accelerated qualification process. The AMMT program focuses on both additively manufactured and wrought structural alloys, such as laser powder-bed fusion 316H austenitic stainless steel, alloy 709, Haynes 244, and alloy 617. These materials require a generalized CD modeling framework to facilitate rapid model development and computational simulation. A flexible, generalized CD software, similar to the Multiphysics Object-Oriented Simulation Environment (MOOSE) finite element framework, would enable modeling of various cluster types, including defect clusters, defect-solute clusters, and multicomponent clusters, incorporating thermodynamics and kinetics parameters. Radiation effects, microstructural feature evolution, and multi-dimensional modeling are critical considerations for the CD model. The usability of the CD code should allow for easy modification and coupling with MOOSE-based simulations. Additionally, the software should adhere to Nuclear Quality Assurance-1 standards, include a testing suite for verification and validation, and be version-controlled within a national laboratory-managed Git repository. Benchmark problems are needed to assess code predictions and performance.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Assessment of ROI for Workforce Development Efforts National & Homeland Security

The IDEAL Professional Engagement project at Idaho National Laboratory (INL) aims to enhance the laboratory's workforce diversity and inclusivity efforts, focusing on the U.S. National and Homeland Security mission areas. This project involves researching and evaluating opportunities for INL to engage in various professional events, particularly cyber conferences, to support recruitment and professional development. The project involved several key tasks: compiling comprehensive information on national laboratories and their mission statements, developing a deep understanding of INL’s role and efforts in national and homeland security, and identifying and engaging key stakeholders. Interviews were conducted with a set of targeted questions, and the findings were analyzed to identify common themes, insights, and actionable recommendations. Additionally, relevant upcoming cyber conferences were identified, various sponsorship levels and their associated benefits were evaluated, and the recruitment potential of these conferences was assessed. A detailed cost analysis was performed, including registration fees and travel expenses, and a cost-benefit analysis was conducted to evaluate the financial viability and potential return on investment (ROI) of conference participation and sponsorship. Based on the research and analysis, actionable recommendations for conference participation and sponsorship were formulated, ensuring alignment with INL’s mission and diversity goals. Preliminary results include a comprehensive list of relevant cyber conferences, a detailed cost analysis, and a set of actionable recommendations for future conference participation and sponsorship. The analysis highlights the financial requirements and geographical distribution of these conferences, providing valuable insights for INL's engagement strategies. This project underscores the importance of strategic engagement in professional events to attract and develop a diverse and skilled workforce, ultimately supporting INL’s mission areas in U.S. National and Homeland Security.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

An Open Source Perovskite Solar Cell Curve Tracer

When developing systems for perovskite solar cells (PSCs), it is important to have a testing platform that closely resembles your deployed systems. While developing a 1 U CubeSat, the Big Red Sat-1 at the University of Nebraska-Lincoln, we found a lack of passive curve tracing instrumentation, which we needed for our mission. To that end, we developed a benchtop passive curve tracer that leverages the Ossila Solar Simulator as an AM1.5 light source. This device utilizes a ladder of switched resistors and a precision voltage and current measurement to achieve the curve tracing. It also integrates a common-anode multiplexer to switch through multipixel PSCs. Finally, the solar cell holder is separate from the main measurement system, so various substrates sizes and pixel counts can be supported. This system is tested using various PSCs. It has been open sourced to enable reuse in future systems that may benefit from the lower power consumption and flight heritage.

14 SOLAR ENERGY↗
DOE OSTI2026

Final DOE-ASR Report for the Project “Using LASSO to bridge the gap between model and observations and to learn about atmospheric convection”

Atmospheric convection spans a wide range of spatial and temporal scales and involves complex interactions with the surrounding dynamic and thermodynamic environment, particularly over tropical continental regions. These processes remain a major source of uncertainty in weather and climate models, including persistent biases in the diurnal cycle of convective precipitation that directly affect estimates of climate sensitivity. Addressing these challenges requires the combined use of high-resolution observations and cloud-resolving modeling frameworks. In this context, the DOE Atmospheric Radiation Measurement (ARM) program’s Large-Eddy Simulation ARM Symbiotic Simulation and Observation (LASSO) activity provides a powerful platform that pairs comprehensive observations with numerical simulations to enable process-level understanding of atmospheric convection. Within this context, this Research and Development Partnership Pilot (RDPP) project was designed to initiate and expand DOE ARM/ASR research capacity at minority-serving institutions, while advancing scientific understanding of convective processes over the Amazon rainforest. Consistent with the RDPP mission, the project emphasized partnership development, training, and workforce capacity building alongside exploratory research activities. On the scientific side, the project produced two peer-reviewed journal articles, and one manuscript currently under review (see list in section 3.1). Together, these studies combine long-term ARM observations and cloud-resolving and convection-permitting modeling to investigate the environmental controls on the shallow-to-deep convective transition during the Amazon wet season. The results demonstrate the central role of early-day moisture preconditioning and large-scale dynamical forcing in regulating isolated deep convection, provide mechanistic insight into convective evolution, and establish physically informed modeling frameworks for future sensitivity experiments. These scientific outcomes are described in sections 2.1 to 2.3 and were disseminated in 8 conference presentations (see section 3.2) and 5 invited talks (see section 3.3), reflecting broad engagement with our community. Equally important, the project achieved its RDPP capacity-building objectives (see section 2.4). A sustained research partnership was established among the University of Maryland, Baltimore County (UMBC), Morgan State University (MSU), and Howard University (HU), and extended to include collaboration with Pacific Northwest National Laboratory (PNNL). The project organized multiple multi-day training events focused on ARM data, LASSO simulations, and quantitative analysis methods, directly engaging students, postdoctoral researchers, and faculty across institutions. These activities broadened participation in ASR research and led to independent adoption of LASSO workflows by students beyond the immediate project team. Finally, the project successfully positioned the participating institutions to pursue future DOE research. Preliminary scientific results, coupled with strengthened partnerships and technical capacity, enabled the submission of follow-on proposals to DOE ASR funding opportunities. In this way, the project fulfilled the RDPP goal of seeding durable research capacity and laying the foundation for larger-scale, sustained engagement with DOE ARM and ASR programs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

In situ Detection of Plasma Induced Surface Interaction based on Deep Learning based Visual Diagnostics (Technical Report)

It is characteristic for many plasma devices to undergo plasma-material interaction leading to surface erosion. These processes, often not easily detectable, lead to changes in device performance and lifespan. State-of-the-art lifetime tests and wear experiments require over 1000s hours. A self-consistent model for accurately predicting the erosion's effects is not available. In situ detection of these processes is not a trivial task since the surface variations at the early stages have a micron scale. Such limitations not only restrict testing and prediction capabilities but also slow the development of new thrusters and limit mission duration. To address these challenges, an in-situ diagnostic for real-time erosion assessment has been developed, aiming to expedite lifetime testing and broaden experimental campaigns. Several works were dedicated to real-time and in situ monitoring of material erosion during plasma exposure using laser holography, microscopy, and with telemicroscopes. However, the applicability of these approaches is limited due to complexity, cost and less flexibility as they often require placing diagnostic equipment inside the vacuum chamber. In collaboration with Princeton Collaborative Research Facility (PCRF), Princeton Plasma Physics Laboratory (PPPL), a new diagnostic approach is developed, where geometry modifications to the ceramic channel walls were introduced that would result in accelerated channel erosion. We employed Long-distance microscope (LDM) imagery, combined with Deep-Learning based Shape from focus or depth from focus (DFF or SFF) approach, that provides an accessible and cost-effective solution. LDM employs focus variation techniques to continuously capture multiple images of the target object at distinct focal planes. DFF, an optical focus variation method, generates a 3D topographical surface depth map from a sequence of variably focused images. Combined with the developed diagnostic, this approach offers a controllable means to study erosion under accelerated conditions. In this work, we develop Neural Network-based DFF algorithm applicable for LDM data to quantitatively evaluate plasma induced surface modification from LDM data. Next, we develop Deep Learning-based super-resolution depth map image reconstruction technique to increase the resolution of depth maps obtained from DFF algorithm to improve the accuracy of erosion measurements. Thirdly, we develop several image processing techniques to remove noise and improve the quality of depth map image. Here we report the results of initial tests for this approach. An experimental setup designed and built in PPPL was employed that consists of a 3-cm gridded ion source that produces a neutralized argon beam with energies up to 600 eV. A hexagonal boron nitride (h-BN) ceramic target, designed based on computational predictions, was used. Tests were conducted to reconstruct the complex geometry of the target under the lighting conditions of the operated ion source.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Solar Resource Measurements in Eugene, OR: Cooperative Research and Development Final Report, CRADA Number CRD-07-00252

Site-specific, long-term, continuous, and high-resolution measurements of solar irradiance are important for developing renewable resource data. These data are used for several research and development activities consistent with the NLR mission: establish a national 3-year climatological database of measured solar irradiances; provide high quality ground-truth data for satellite remote sensing validation; support development of radiative transfer models for estimating solar irradiance from available meteorological observations; provide solar resource information needed for technology deployment and operations. Data acquired under this agreement will be available to the public through NLR's Measurement & Instrumentation Data Center – MIDC (http://www.nlr.gov/midc) Or the Renewable Resource Data Center - RReDC (http://rredc.nlr.gov). The MIDC offers a variety of standard data display, access, and analysis tools designed to address the needs of a wide user audience (e.g., industry, academia, and government interests).

14 SOLAR ENERGY↗
DOE OSTI2024

Potential Availability of Alternative Fuel to Supply Maritime Activities in Pacific Northwest Ports

The international shipping sector represented 3% of global greenhouse gas emissions in 2023 (Office of Energy Efficiency & Renewable Energy 2024). International shipping has been classified as a difficult-to-decarbonize industry (IRENA 2024). In an effort to drive decarbonization, the U.S. Department of Energy has partnered with Mission Innovation to co-lead the Zero-Emission Shipping Mission, which launched in 2021(Office of Energy Efficiency & Renewable Energy 2021). In addition, the U.S. Department of State partnered with Norway to launch the Green Shipping Challenge in 2022 (Office of the Spokesperson 2022b). As part of the ZESM and Green Shipping Challenge, the United States is collaborating with the Republic of Korea (ROK) to develop a green shipping corridor (U.S. Mission Korea 2023). The United States and ROK have conducted a pre-feasibility study as the first step in developing a green shipping corridor between the countries. The ports included in the study are Seattle, Tacoma, and Everette in the U.S. Pacific Northwest (PNW) and Busan, Ulsan, and Masan in ROK. The National Renewable Energy Laboratory's role in the study was to analyze the availability and technical potential of alternative marine fuels in proximity to U.S. PNW ports. The findings show most of the existing alternative fuel capacity within the region is from renewable diesel, biodiesel, and sustainable aviation fuel facilities. The largest growth in fuel capacity in the region by 2030 is projected to be in renewable diesel and hydrogen. The overall technical readiness of non-drop-in alternative fuel production and conversion technologies is more developed than alternative-fueled ships and associated fueling infrastructure. However, much of the fuel capacity in the region is comprised of drop-in fuels, making it technically possible to use existing infrastructure for transporting and bunkering to the existing fleet. Data to inform regional alternative fuel quantity estimations were collected from an extensive review of databases, reports, announcements, and other publicly available resources. A maturity index and sector competition factor were applied to announced fuel projects to determine the quantity of alternative fuel available to the marine sector in the region by 2030. Demand data were collected from fuel bunkering logs covering the PNW seaports (State of Washington 2021). Both supply and demand data were converted to very-low sulfur fuel oil gallon equivalents (VLSFO-GE) for better comparison. Qualitative data were gathered through interviews with stakeholders, project developers, and industry experts. Total alternative fuel capacity available to the marine sector in the region is estimated to be 824 million VLSFO-GE per year by 2030. This is sufficient to cover the requirements of a green shipping corridor between the United States and ROK. The findings from this report are being used to inform detailed feasibility studies for several U.S. PNW -ROK green shipping corridors. Updates from the U.S. PNW - ROK feasibility studies will continue to be published on Mission Innovation's green corridor tracking website (Zero Emission Shipping Mission, n.d.). In addition, this report has helped to inform further work on shipping decarbonization in the U.S. PNW, including the Pacific Northwest to Alaska Green Corridor focused on cruise vessels.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Feasibility of carbon foam-based sorbents for the abatement of gaseous mercury and iodine

The U.S. Department of Energy Hanford Site in Washington State is in the process of commissioning the Waste Treatment and Immobilization Plant to process a portion of the 54 million gallons of radioactive and chemical waste from cold war weapon production. Technologies for the capture of volatile species of concern are still being assessed, and new methods and materials are developed as operational and flowsheet mission risks are identified. One such area still being assessed is the abatement efficacy of the Carbon Adsorber units to retain gaseous mercury and 129 I released during processing. It is challenging to predict the mercury chemistry due to the variability of the feed, and different methods/materials are required for the capture of gaseous Hg 0 and Hg II compounds. In this study, the feasibility of using developmental carbon foam (CF) sorbents for the capture of iodine and mercury was assessed using static and dynamic flow testing and compared against a commercially available sorbent, BATII-37. Both CF and CF functionalized with bismuth particles (CF-Bi) chemisorbed iodine, and CF-Bi had similar mercury capture performance to BATII-37 in dynamic flow tests. While species loading concentrations were measurable, limitations in achieving a mass balance prevented a full evaluation of capture efficacy. Nonetheless, the results serve as an important first step in demonstrating the potential for simultaneous iodine and mercury capture.

Hanford site↗
DOE OSTI2025

PROTOCALC, a W -band Polarized Calibrator for Cosmic Microwave Background Telescopes: Application to Simons Observatory and CLASS

Current- and next-generation cosmic microwave background (CMB) experiments will measure polarization anisotropies with unprecedented sensitivities. The need for high precision in these measurements underscores the importance of gaining a comprehensive understanding of instrument properties, with a particular emphasis on the study of the beam properties, and especially their polarization characteristics and the measurement of the polarization angle. In this context, a major challenge lies in the scarcity of millimeter polarized astrophysical sources with sufficient brightness and calibration knowledge to meet the stringent accuracy requirements of future CMB missions. This led to the development of a drone-borne calibration source designed for the frequency band centered on approximately 90 GHz, matching a commonly used channel in ground-based CMB measurements. The Prototype Calibrator for Cosmology, PROTOCALC, has undergone thorough in-lab testing, and its properties have been subsequently modeled through simulation software integrated into the standard Simons Observatory analysis pipeline. Moreover, the PROTOCALC system has been tested in the field, having been deployed twice on calibration campaigns with CMB telescopes in the Atacama Desert. The data collected constrain the roll angle of the source with a statistical accuracy of 0$^°_•$045.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Bayesian Framework for Bioburden Density Estimation in Planetary Protection

To comply with the international planetary protection policy set forth by the Committee on Space Research and NASA Agency level requirements, spacecraft destined to biologically sensitive planetary bodies have to minimize terrestrial biological contamination. Analysis, testing and inspection are the standard forward verification activities that are used to demonstrate compliance with the biological contamination requirements. For testing of spacecraft surface areas, a swab or wipe sample is collected from surfaces prior to last access and subsequently processed in the lab using NASA Approved Planetary Protection Methods for Culture Based Assays. Raw data resulting from this assay is then statistically treated employing a mathematical paradigm stemming from the 1970’s Viking Lander Project to generate the bioburden density and total microbial bioburden present. This standard approach arbitrarily accounts for error and provides an upper conservative bound as it reports the maximum number of spores estimated to be present on flight hardware surfaces. A bioburden density estimate factors in the following variables: the observed bioburden count, representative volume processed, sampling efficiencies. Notably, to account for error in the approach, a 0 observed count is arbitrarily changed to a count of 1 for each hardware grouping. The data generated by spacecraft bioburden verification campaigns in the past have resulted in <80% of wipes and <90% of swabs containing a bioburden count of 0. As such, having a robust and well documented statistical approach for dealing with the probability of low incident rates is necessary to be able to estimate spacecraft bioburden. Being able to statistically describe the bioburden distribution and associated confidence level is a gamechanger for the development of bioburden allocations during mission design and will allow for tighter management of risk throughout spacecraft build. Thus, Empirical Bayes statistical approach was evaluated to estimate the microbial bioburden on spacecraft to mitigate the aforementioned mathematical concerns and provide a probabilistic bioburden distribution of the flight hardware surface. For application of this approach to performing bioburden calculations, a range of non-informative prior assumptions on hardware surfaces are explored for Bayesian analyses while informative priors using posterior distributions from prior assays are utilized for Empirical Bayes analyses. Several non-informative priors are currently under investigation to assess fitness including use of these priors to serve as a foundation to build off of NASA specification values or a basis of risk to account for unknowns during the integration and testing process. Informative priors under consideration are generated using sampled bioburden values from hardware originating within like processing environments (e.g. vendor cleaning process or similar assembly process), temporal spacecraft status events as a prediction for hardware cleanliness of future samples, and heritage system bioburden actuals to predict allocation for subsequent missions. Informative priors and probabilistic bioburden distributions are then validated using data sets from the Mars Exploration Rover, Mars Science Laboratory, and InSight missions. Using Empirical Bayes approach to generate a probabilistic bioburden distribution as demonstrated through mission use cases provides a valid approach for use in the end-to-end requirements verification process.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Detector Materials Scoping Study: Research and Development Recommendations

Radiation detection materials have a unique role in many nuclear security missions. The variety of different applications requires the use of different materials whose characteristics are determined by the specific application requirements. While baseline capabilities have been established to use radiation detection in these applications, the potential to greatly advance those capabilities still exists through the development of superior radiation detection materials and/or the development of new materials that enable new technologies to be implemented more effectively. In 2024 the Defense Nuclear Nonproliferation Research and Development (DNN R&D) Near Field Detection Portfolio charged a detector materials scoping study, composed of a group of radiation-detection materials subject matter experts, to produce a community-wide consensus view of the current state of radiation materials research and to set recommendations for expanded investment over a ten-year time frame. This scoping study sought to understand and document the landscape of how radiation detection materials are used, what characteristics drive the selection of various materials, and what developments are needed to drive the state of the art. To respond to this charge, the scoping study created three working groups, each focusing on a different topical area in radiation detection materials research - Semiconductor Materials, Inorganic Scintillators and Organic Scintillators - with the task to identify the current state of the art in materials research and to provide mission-relevant research and development recommendations. Each working group was chaired by two members of the project team with widely recognized expertise in the field. Solicitations were sent out to experts at the DOE national laboratories, industry, academia and federal government agencies to participate in these working groups. The working groups met at regular intervals throughout 2024 and early 2025, each delivering a technical roadmap designed to enable the pursuit of R&D more intensely on high-impact materials challenges and detector solutions that are deemed as the greatest strategic value to DNN R&D and its stakeholders. The roadmap is also intended to help communicate recommended programmatic priorities within DNN R&D and across the nonproliferation and research communities.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Alaska Liquid Natural Gas Pipeline Front-End Engineering & Design (Final Technical Report)

The Alaska Gasline Development Corporation (AGDC) is Alaska’s natural gas infrastructure development corporation established in 2013. AGDC’s mission is to maximize the benefit of Alaska’s vast North Slope natural gas resources for Alaskans through the development of infrastructure necessary to move the gas into local and international markets. AGDC was identified for a Congressionally Directed Spending (CDS) project for funding in the Energy and Water Development and Related Agencies Appropriations Act, 2023 under the heading: “Congressionally Directed Energy Efficiency and Renewable Energy Projects.” The CDS included $\$$4,000,000 of direct funding, with required match funds, to move the project forward. Alaska’s North Slope holds America’s largest proven and conventional natural gas supply. The integrated Alaska LNG Project will deliver 3.5 billion cubic feet of natural gas per day from Alaska’s North Slope gas fields to Alaskans as well as to a marine terminal located at tidewater in Cook Inlet. Alaska LNG is an integrated gas infrastructure project with three major components: a gas treatment plant (GTP) located at Prudhoe Bay, an 807-mile (1,287 km) gas pipeline (Mainline Pipeline) to Southcentral Alaska with interconnections for in-state gas use, and a natural gas liquefaction facility (LNG Facility) in Nikiski, Alaska. The integrated Alaska LNG Project has several strategic advantages including proven gas resources, existing upstream infrastructure, an advantageous arctic climate for LNG production, proximity to LNG markets, a track record of reliability from a state that first began exporting LNG to Japan in 1969, and broad support from Alaskans. North Slope natural gas is a conventional resource and can be produced with minimal drilling at a fraction of the carbon dioxide emissions of shale gas from the Lower 48 states. Through the development of the Alaska LNG Project, Alaska can provide energy security to Alaskans and a stable source of LNG to the Asia-Pacific region for generations. The Alaska LNG Project has been progressed through Pre-Front-End Engineering Design (Pre-FEED) and has obtained all major federal and State of Alaska permits and authorizations to construct the project, including the Federal Energy Regulatory Commission (FERC) Order Granting Authorization Under Section 3 of the Natural Gas Act. On September 5, 2024, the U.S. Department of Energy (DOE), National Energy Technology Laboratory (NETL) awarded Project No. DE-FE0032307 to AGDC with the objective to progress the project to Front-End Engineering Design (FEED) entry for the Alaska LNG Project Phase 1 Pipeline. The award Start Date was made effective July 1, 2023, with a Period of Performance through June 30, 2025. On March 27, 2025, AGDC announced the execution of definitive commercial agreements with Glenfarne Alaska LNG, LLC, an affiliate of Glenfarne Group, LLC, (together as “Glenfarne”), to lead the development of the Alaska LNG Project and enter FEED for the Phase 1 Pipeline. Project activities are now funded and directed by this private sector partner who holds a 75% interest in 8 Star Alaska, LLC (8 Star). 8 Star holds the assets of the Alaska LNG Project. As planned, AGDC continues to hold 25% minority interest in 8 Star and will play a governance role moving forward with Alaska LNG. This definitive commercial agreement milestone led to the successful completion of AGDC’s Statement of Project Objectives (SOPO) for FEED entry and led to the completion of DOE Project No. DE-FE0032307. At conclusion of the SOPO, AGDC also reached the award’s maximum federal cost share of $\$$4,000,000. AGDC is, therefore, providing Final Technical Report to close out DOE Project No. DE-FE0032307.

02 PETROLEUM↗
DOE OSTI2026

Space Mission Options for Reconnaissance and Mitigation of Asteroid 2024 YR4

Near-Earth asteroid 2024 YR 4 was discovered on 2024-12-27 and its probability of Earth impact in December 2032 peaked at ~3% on 2025-02-18. Additional observations ruled out Earth impact by 2025-02-23. However, the probability of lunar impact in December 2032 then rose, reaching ~4% by the end of the apparition in May 2025. James Webb Space Telescope (JWST) observations on 2025-03-26 estimated the asteroid’s diameter at 60 ± 7 m. Studies of 2024 YR 4 ’s potential lunar impact effects suggest lunar ejecta could increase micrometeoroid debris flux in low Earth orbit up to 1000 times above background levels over just a few days, possibly threatening astronauts and spacecraft. In this work, we present options for space missions to 2024 YR 4 that could be utilized if lunar impact is confirmed. Here, we cover flyby & rendezvous reconnaissance, deflection, and robust disruption of the asteroid. We examine both rapid-response and delayed launch options through 2032. We evaluate chemical and solar electric propulsion, various launch vehicles, optimized deep space maneuvers, and gravity assists. Re-tasking extant spacecraft and using built spacecraft not yet launched are also considered. The best reconnaissance mission options launch in late 2028, leaving only approximately three years for development at the time of this writing in August 2025. Deflection missions were assessed and appear impractical. However, kinetic robust disruption missions are available with launches between April 2030 and April 2032. Nuclear robust disruption missions are also available with launches between late 2029 and late 2031. Finally, even if lunar impact is ruled out there is significant potential utility in deploying a reconnaissance mission to characterize the asteroid.

Asteroid deflection↗
DOE OSTI2026

Genesis Mission-Enabled Secure AI to Fortify Energy Process Safety (Genesis-SAFE)

Argonne National Laboratory is supporting the U.S. Department of Transportation’s (USDOT’s) Bureau of Transportation Statistics (BTS) with collaborative research on development and application of privacy preserving AI frameworks that leverage unmatched AI expertise and secure computing resources made available through the U.S. Genesis Mission1 . This research advances U.S. energy security goals by supporting a safe offshore energy industry with secure, domain-specific AI tools to analyze confidential industry datasets collected by BTS to rapidly improve identification of hazards, precursors, and systemic safety risks in high-risk operational environments. The staged, security-first approach begins with development and testing of Argonne’s Genesis Mission-enabled Secure AI to Fortify Energy Process Safety (Genesis-SAFE) framework within Argonne’s accredited secure computing enclave (ABLE) leveraging Argonne’s AI scientific assistant substrate (AISAC). Methods to build synthetic datasets were developed together with BTS for use in preparing synthetic datasets that can be used to validate data containment, governance, and security controls in the ABLE environment. Future research directions would focus on applying the Genesis-SAFE framework to CIPSEA-protected datasets entirely within ABLE to support confidentiality-preserving analysis of safety risks, trends, and contributing factors.

Kim, Hyekyung [Argonne National Laboratory (ANL), ↗