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At least 631 records · Page 35

Management of Risks Associated with Application of Novel Materials in Novel Operating Environments in Novel Reactor Designs

There is currently no widely agreed, detailed general method for licensing a novel plant incorporating novel materials (or materials being deployed in novel environments); in many such situations, there are no directly applicable engineering code cases for decision-makers (including regulators) to rely on. This paper discusses a framework for solving this problem that is based on the Reliability and Integrity Management (RIM) approach delineated in ASME BPVC Section XI Division 2. NRC Regulatory Guide 1.246, Rev. 0, endorses, with conditions, the subject portion of the ASME Code. The proposed framework is meant to support development of a licensing case by addressing certain technical challenges. The framework discussed here is compatible with the Licensing Modernization Project, but applying it in a specific case will call for advances in the state of practice, if not the state of the art. The RIM approach calls for applicants to (a) allocate reliability targets to plant structures, systems, and components (SSCs), (b) show that they are able to relate the currently observed physical condition of each SSC in the program to its failure probability well enough to determine whether the target reliability allocations are being satisfied, allowing for uncertainty related to the novelty of the materials/designs/operating environments, and (c) be able to demonstrate that the proposed program of surveillances will reliably detect unacceptable degradation of an SSC before SSC failure occurs. These challenges are discussed in the paper, and a potentially applicable modeling approach based on cumulative damage rather than failure rates is briefly illustrated.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Quantum entanglement distribution coexisting with high-rate, broadband classical optical communications over a real-world fiber connecting remote, synchronized nodes

Compatibility with existing classical network infrastructure offers a scalable path towards deploying large-scale quantum networks. Here, we demonstrate O-band polarization-encoded quantum entanglement distribution over an installed 24.4-km fiber while coexisting with a state-of-the-art fully loaded C-band classical communications line system and a picosecond-level precision L-band synchronization signal. The classical system carries two 800-Gbps channels while the remainder of the C-band is filled with amplified spontaneous emission, as is standard for such state-of-the-art communications systems. We examine the spontaneous Raman scattering spectrum generated from this broadband C-band light and offer insights into wavelength allocation for O-band quantum channels. Optimal wavelength selection and narrow filtering enable well-preserved Bell state fidelity when coexisting with 21.4-dBm aggregate launch power across the C-band suitable for 36-Tbps transmission. To the best of our knowledge, this is the first implementation of entanglement-based quantum communications between two remote nodes coexisting with independent classical communications traffic. We demonstrate coexistence of quantum entanglement with ultra-high power levels and record classical bandwidth, offering promise for real-world entanglement-based networking integrated within high-capacity communications infrastructure.

Talcott, Gina M. [Northwestern U.] (ORCID:00000002↗

Microstructure development during rapid alloy solidification

Abstract Solidification processing of structural alloys can take place over an extremely wide range of solid–liquid interface velocities spanning six orders of magnitude, from the low-velocity constitutional supercooling limit of microns/s to the high-velocity absolute stability limit of m/s. In between these two limits, the solid–liquid interface is morphologically unstable and typically forms cellular-dendritic microstructures, but also other microstructures that remain elusive. Rapid developments in additive manufacturing have renewed the interest in modeling the high-velocity range, where approximate analytical theories provide limited predictions. In this article, we discuss recent advances in phase-field modeling of rapid solidification of metallic alloys, including a brief description of state-of-the-art experiments used for model validation. We describe how phase-field models can cope with the dual challenge of carrying out simulations on experimentally relevant length- and time scales and incorporating nonequilibrium effects at the solid–liquid interface that become dominant at rapid rates. We present selected results, illustrating how phase-field simulations have yielded unprecedented insights into high-velocity interface dynamics, shedding new light on both the absolute stability limit and the formation of banded microstructures that are a hallmark of rapid alloy solidification near this limit. We also discuss state-of-the-art experiments used to validate those insights. Graphical abstract

36 MATERIALS SCIENCE↗

Effect of Sample Thickness on the Tensile Strength of Small Graphite Discs

This report formally documents the completion of the Advanced Reactor Technologies (ART) Level 3 Milestone (M3TG-24OR0501054), “Continue activities related to Split Disc-DIC - complete analysis of effect of sample thickness on one fine grain graphite,” due May 31, 2024. Details within this report outline the status of activities aimed at elucidating the effect of sample thickness on the tensile strength measurement using the small-disc, split-disc testing standard in support of the US Department of Energy’s ART Graphite R&D Program. The ASTM D8289, Standard Test Method for Tensile Strength Estimate by Disc Compression of Manufactured Graphite, was developed to provide an alternative means for testing tensile strength on smaller specimens, which are compatible with available irradiation capsule volumes, and other compatibility measurements. ASTM D8289 specifies that acceptable specimen diameter can range from 6 to 12.7 mm and that the maximum allowed sample thickness should be half of the diameter. However, information is limited with respect to the effect of thickness on the measured splitting tensile strength. This report documents efforts to understand the effect of sample thickness on splitting tensile strength. The work involved testing Ø12.7 mm samples of fine-grain graphites 2114 and IG-110 of different thicknesses (6.35, 5, 4, and 3 mm). The digital image correlation (DIC) method was applied to the samples, along with the ASTM D8289 Standard, to help interpret the measured results.

36 MATERIALS SCIENCE↗

50 MW Segmented Ultralight Morphing Rotors for Wind Energy

A multi-institutional team designed a 50 Megawatt (MW) rated wind turbine featuring downwind aeroelastic morphing to reduce blade loads and allow an ultralight segmented rotor (mass reduction of about 25% compared to a conventional upwind rotor). The team used a control co-design approach with state-of-the art simulations including for the rotor and tower design using non-linear fluid-structure interactions and control algorithms, and the team also designed, built, and field-tested an aeroelastically-scaled downwind rotor to demonstrate this novel technology and validate the design tool fidelity. In a follow-on phase, these results were used along with an updated Levelized Cost Of Energy (LCOE) methodology to co-design a more detailed set of 25 MW rated turbine designs (including individual pitch control) based on minimum LCOE with highly flexible blades for an Atlantic Ocean offshore fixed-bottom design targeted towards market technology evaluation. A set of upwind and downwind designs at 25 MW rated scales were found to provide the best LCOE, with strong improvements over all previous offshore reference turbines (NREL 5MW, DTU 10 MW and IEA 15 MW). The optimized design would represent the world’s largest offshore turbine design, which combines several state-of-the-art structural, aerodynamic, and control technologies into a new and optimized system concept.

17 WIND ENERGY↗

Addressing Issues with Working Memory in Video Object Segmentation

Contemporary state-of-the-art video object segmentation (VOS) models compare incoming unannotated images to a history of image-mask relations via affinity or cross-attention to predict object masks. We refer to the internal memory state of the initial image-mask pair and past image-masks as a working memory buffer. While the current state of the art models perform very well on clean video data, their reliance on a working memory of previous frames leaves room for error. Affinity-based algorithms include the inductive bias that there is temporal continuity between consecutive frames. To account for inconsistent camera views of the desired object, working memory models need an algorithmic modification that regulates the memory updates and avoid writing irrelevant frames into working memory. A simple algorithmic change is proposed that can be applied to any existing working memory-based VOS model to improve performance on inconsistent views, such as sudden camera cuts, frame interjections, and extreme context changes. The resulting model performances show significant improvement on video data with these frame interjections over the same model without the algorithmic addition. Our contribution is a simple decision function that determines whether working memory should be updated based on the detection of sudden, extreme changes and the assumption that the object is no longer in frame. By implementing algorithmic changes, such as this, we can increase the real-world applicability of current VOS models.

97 MATHEMATICS AND COMPUTING↗

Unifying Combinatorial and Graphical Methods in Artificial Intelligence

Recently, a new graph Laplacian, called the inner product Laplacian, was introduced which generalizes many existing Laplacians, including the normalized and combinatorial Laplacian and their weighted variants. The key observation behind the inner product Laplacian is that by defining appropriate inner product spaces on the vertices and edges, the standard Laplacians can be recovered as Hodge Laplacians over the simplicial complex formed by the edges and vertices. These inner product spaces form a natural way to incorporate non-combinatorial information into the definition of a domain-specific Laplacian. In particular, in contrast to current domain-specific weighting schemes which rely solely on edge weights, information regarding the similarity of non-adjacent vertices and arbitrary pairs of edges can be effectively incorporated into the Laplacian. In order to illustrate this approach we consider the problem of calculating the potential energy of an atomistic configuration using Graph Neural Networks. In comparison with start-of-the-art approaches, such as SchNet, our approach replaces a learned (via auto-encoder) representation of the atom types with an inner product space on atoms based on scientific knowledge (e.g., electronegativity). We will illustrate how this approach captures key chemical properties of the molecules and compare the energy calculations with state-of-the-art neural network approaches. However, to compute the resulting Laplacian involves a mixture of sparse and dense matrix computation and yields a dense matrix as the basis for the graph convolution. This dense convolutional kernel necessitates moving away from the standard message passing framework for graph neural networks and increases the computational cost of applying the kernel. In order to mitigate these costs we investigate means of leveraging the mixed sparse and dense computations to reduce the overall computational cost and how these approaches can be automatically transferred to energy efficient hardware (e.g., field programmable gate arrays (FPGAs)).

97 MATHEMATICS AND COMPUTING↗

Lessons from Artist in Residence Program Design and Impact

As a national laboratory, Pacific Northwest National Laboratory (PNNL) seeks to be on the leading edge of public interest research and deliver innovation, a core value of the institution. Through the support of the U.S. Department of Energy’s Water Power Technologies Office, PNNL has convened a workshop entitled Advancing Energy Futures through Art in Seattle, Washington, on August 19th and 20th, 2024. An explicit focus on Artist in Residence (AiR) programs initiates the discussion, as this is one of the few clear places where public interest research, artistic engagement, and energy futures have aligned. The workshop proposes to hear from program managers of successful AiR programs, scientists, and artists who work in the energy futures space, to discuss AiR program models and successful modalities for art and storytelling. This paper is provided as background context for workshop participants.

99 GENERAL AND MISCELLANEOUS↗

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↗

Enhancing the Design of Photocathodes with 90% polarization and QE > 1% for DOE NP (Final Report)

This project’s 3 major goals were the following: 1. Fabricate state-of-the-art spin-polarized photocathodes using MOCVD and develop knowledge of fabrication parameters. 2. Enhance the design of 2 structures of spin-polarized photocathodes (strained-superlattice and strained-superlattice with distributed Bragg reflector) to assess paths to the next generation of spin-polarized photocathodes. 3. Provide a supply of state-of-the-art spin-polarized photocathodes to both Brookhaven National Laboratory and the Thomas Jefferson National Accelerator Facility.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

The National Solar Radiation Database Final Report: Fiscal Years 2022-2024

The National Solar Radiation Database (NSRDB) is the leading public source of high-resolution solar resource data in the United States, with more than 400,000 users annually. This database represents the state of the art in the satellite-based estimation of solar resource information and uses a unique physics-based modeling approach that enables improvements in accuracy with the deployment of the next-generation geostationary satellites. Making the highest-quality, state-of-the-art, regularly updated datasets available on a timely basis for users reduces costs of solar deployment by providing accurate information for siting studies and system output prediction and thereby reduces project financing costs and risks.

14 SOLAR ENERGY↗

Considerations for a Medium-Voltage DC Electrolysis Testbed

Here we present the results of a study focused on the feasibility of using Medium Voltage DC (MVDC) power distribution from wind power generation to electrolyzers for hydrogen production. This approach, using hybrid energy generation in a MVDC microgrid, offers many advantages. These include possible improvements in efficiency, reliability and installation cost compared to a more typical state-of-the-art AC distribution configuration. It also eliminates the need for transformers, which have recently been subject to price volatility and availability concerns. This study highlights the practical feasibility of MVDC distribution networks for integrating various energy sources, offering improved efficiency and reduced system complexity compared to conventional AC-based solutions. Future work will focus on enhancing fault protection strategies, scaling the system to larger renewable installations, and conducting hardware implementation at the National Renewable Energy Laboratory's (NREL) Flatirons Campus (FC). In the sections that follow we show that a DC Collection and Distribution System (DC CDS) reduces the losses associated with the electrical conversion / distribution process relative to a state-of-the-art AC approach, improving overall efficiency by 5%. On the qualitative side, reducing the number of conversion stages is likely to improve reliability, reduce capital investment cost, and enable simpler control algorithms to be used, and reduced risk of instabilities and malfunctions.

08 HYDROGEN↗

Determination of Scale Bar for AGHCF Metallography Data

The DOE Nuclear Energy Advanced Reactor Technologies (ART) Fast Reactor Program (FRP) has supported the development of several databases containing information on the safety performance of fast reactors, components, and fuels. This growing collection of legacy experimental data, operating data, and analysis is available online to registered users. Metallography data represents one of the most critical types of post-irradiation examination (PIE) data being collected, organized, and archived in several ART Fast Reactor Databases (https://frdb.ne.anl.gov), including the Metallic Fuels Irradiation & Physics Database (FIPD), Out-of-Pile Transient Database (OPTD), and TREAT (the Transient Reactor Test Facility) Experimental Relational Database (TREXR). These databases contain three principal sets of metallography data. The first set comprises metallography data from Experimental Breeder Reactor-II (EBR-II) and Fast Flux Test Facility (FFTF) irradiated fuel pins examined in the Hot Fuel Examination Facility (HFEF). The second set consists of metallography data from EBR-II irradiated fuel pins examined in the Alpha-Gamma Hot Cell Facility (AGHCF). The third set includes metallography data from transient-tested fuel pins (including both out-of-pile furnace tests and TREAT tests) examined in AGHCF. Since both the second and third sets were generated in AGHCF, they are governed by identical specifications. The metallography data in the databases consist of digital images scanned from either positive or negative photographic films. To analyze the microstructure of a fuel pin, a series of preparatory steps are required, including sectioning, epoxy mounting, mechanical grinding and polishing, and etching. Following sample preparation, specimens are transferred for metallographic examination. The AGHCF and HFEF metallography data were generated using optical microscopes manufactured by Leitz and Bausch and Lomb (B&L). Images were recorded on Polaroid film at preset magnifications. Magnification verification for the Leitz and B&L metallographs was conducted every two months prior to 1989 and at least every six months from 1989 through the conclusion of the IFR program. Magnifications determined from imaging of microslide standards were compared to the instrument settings for magnifications ranging from 50× to 500×. If the magnifications determined from standards deviated from the instrument settings, adjustments were made to the bellows extension until agreement was achieved. The specifications for AGHCF and HFEF legacy metallography data have been established based on available hard-copy and digital records, most of which have been incorporated into the data repositories associated with FIPD, OPTD, and TREXR. Detailed specifications including hard-copy records, digitized records, cutting diagrams and sectioning schemes, high-magnification photographs, photomosaics (composites), information tags, scale bars, and magnification verification procedures can be found in a separate report.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Uinta Basin CarbonSAFE II: Storage Complex Feasibility (Final Report)

The primary objective of this CarbonSAFE Phase II project was to establish the technical and commercial feasibility of a commercial-scale CO 2 geological storage complex for Deseret Power Electric Cooperative Bonanza Power Plant and other CO 2 sources in the northeast Uinta Basin, Utah, with the goal to securely store at least 50 million metric tons of captured CO 2 and accelerate CO 2 capture, utilization, and storage (CCUS) deployment. The project team established high-potential technical and commercial feasibility for a storage site within the east Uinta Basin (Utah), in the Cretaceous sandstones (Frontier, Dakota, and Buckhorn), Entrada Sandstone, Nugget Sandstone, and/or Weber Sandstone southwest of the Bonanza coal-fired power plant. This project collected and analyzed state-of-the-art data to characterize the storage complex consistent with Environmental Protection Agency (EPA) permitting standards. The team conducted extensive analog studies, outcrop mapping, and data sampling, which largely contributed to understanding the subsurface lithology and facies. Existing data were obtained and assessed from Utah Division of Oil, Gas, and Mining (DOGM), Utah Geological Survey (UGS), Colorado Geological Survey (CGS), U.S. Geological Survey (USGS), and EPA. These data were analyzed using state-of-the-art CCUS technologies for Societal Considerations, Site Characterization, Modeling and Simulations, Risk Assessment, Management and Monitoring, potential Underground Injection Control (UIC) Class VI Well Permitting, and Technical/Economic Feasibility. Through these high-resolution data collection and feasibility studies, this project was expected to provide a reference for initiating Underground Injection Control (UIC) and other commercial-scale geological storage permitting processes in the Western United States, ultimately contributing to the nation's decarbonization goals through low-risk, cost-effective commercial-scale carbon capture, utilization, and storage (CCUS) projects.

42 ENGINEERING↗

CdTe Core: Final Technical Report (FTR)

CdTe is presently the cost-leading thin-film PV technology, directly competing with Si at scale, even when domestically manufactured. While an impressive technology, its efficiency remains much below the detailed balance limit with the largest cause due to its low photovoltage and fill factor. To realize gains, the carrier concentration, minority carrier lifetime, and interface recombination all need to be improved simultaneously over historic levels. Using a new defect chemistry (group V doping instead of copper) has been identified as a viable route using single crystal systems. This project focused on implementing this new defect chemistry in scalable, polycrystalline thin-film photovoltaic CdTe devices with tasks focusing improvements to the front interface, absorber, and rear interface as well as capability development & stakeholder engagement. The goal of the project was to establish a strategy using devices, test structures, detailed characterization, and modeling to quantify the sources of losses in state-of-the-art CdTe photovoltaic devices. Using this strategy and advanced synthesis, losses at the front interface, absorber, and rear interface were worked on in parallel. The final objective was to significantly improve the voltage deficit in CdTe devices to enable improvements in photovoltage and efficiency that can be implemented by industry in the near-term. Over the course of the project, the team developed new characterization techniques, analysis, and modeling which were then applied to state-of-the-art materials generated internally and collaboratively. In particular to enable rapid progress, NREL worked closely with First Solar where NREL grew complete devices as well as ones that interleaved process steps where First Solar had completed different steps such as absorber growth or absorber growth and activation using their baseline methods. Using detailed characterization and analysis including photoemission, photoluminescence, and scanning probe techniques enabled understanding of the loss pathways and area for improvements in our own and First Solar s materials. Ultimately, this contributed to the first series of new world record CdTe efficiencies since 2016, culminating in a 23.1% certified cell that was P-doped along with As-doped cells of similar performance. Internally, NREL improved the statistical variation in baseline As-doped devices and improved average photovoltage by over 100 mV. This was done through an improvement in absorber quality, changed front interface, and improved back contact. In addition to materially improving the fabrication processes at NREL, characterization, analysis, and modeling were developed and disseminated. NREL also played a pivotal role in community building over the course of this project working closely with the Cadmium Telluride Accelerator Consortium. NREL worked in a series of collaborations with academic and industry partners, leveraging knowledge and innovations from this project, as well as helped organize a series of workshops to ensure rapid progress in the field. Working closely with the academic community has led to a dissemination of knowledge; working with First Solar as increased US competitiveness First Solar expanded domestic production to ~10 GW and opened new facilities.

14 SOLAR ENERGY↗

Automatic Image Point Matching

Sparse Image Point Matching (SIPM) is a foundational technology for photo triangulation, structure from motion (SfM), Simultaneous Location and Mapping (SLAM), and data fusion. The goal of the matching is to automatically generate sets of image coordinates that identify the same feature across images. Ideally, the process should be robust to lighting, scale, perspective, and modality changes. The scope of the image matching topic in the field of remote sensing (RS) is enormous because of the variety of collection platforms, modalities, sensor types, applications, and subjects. In this work, we report the history of and assess the state of the art of visible-spectrum (panchromatic and color) image matching of the Earth’s surface. Work specific to large-format images (LFI) (e.g., metric aerial cameras and Earth-observing satellites) will be highlighted. However, the state of the art in this century will mostly be traced through machine vision research and benchmarks because research specific to LFI is rare.

97 MATHEMATICS AND COMPUTING↗

2026 Annual Molten Salt Reactor Campaign Review

This report documents the 2026 Annual Molten Salt Reactor (MSR) Campaign Review held in Albuquerque, New Mexico, from April 21–24, 2026. The review was organized by Dr. Patricia Paviet, National Technical Director of the Advanced Reactor Technology (ART) MSR program for the U.S. Department of Energy Office of Nuclear Energy (DOE-NE), and included participation from principal investigators, federal managers, developers, regulators, and members of the broader MSR community. The 2026 review expanded beyond the ART-MSR campaign to include related DOE-NE programs supporting molten salt reactor advancement, including the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the Advanced Materials and Manufacturing Technologies (AMMT) program, Advanced Reactor Safeguards and Security (ARSS), Material Protection, Accounting and Control Technologies (MPACT), and relevant advanced fuels activities. Three days were dedicated to technical presentations and panel discussions covering thermal properties, off-gas management, modeling and simulation, safety and licensing, safeguards and security, materials and corrosion, and irradiation activities. A fourth day was dedicated to technical tours of Sandia National Laboratories and Kairos Power facilities. Attendance was strong and comparable to the prior annual review, with approximately 75 in-person participants per day, 75–80 virtual attendees per day, and approximately 30 participants in the tour day. The review fostered significant technical exchange across national laboratories, universities, industry, regulators, and international participants. This report summarizes the review structure, technical themes, participation, tours, feedback, and conclusions relevant to future planning for the MSR campaign.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Low-latency Jet Tagging for HL-LHC Using Transformer Architectures

Transformers are the state-of-the-art model architectures and widely used in application areas of machine learning. However the performance of such architectures is less well explored in the ultra-low latency domains where deployment on FPGAs or ASICs is required. Such domains include the trigger and data acquisition systems of the LHC experiments. We present a transformer-based algorithm for jet tagging built with the HGQ2 framework, which is able to produce a model with heterogeneous bitwidths for fast inference on FPGAs, as required in the trigger systems at the LHC experiments. The bitwidths are acquired during training by minimizing the total bit operations as an additional parameter. By allowing a bitwidth of zero, the model is pruned in-situ during training. Using this quantization-aware approach, our algorithm achieves state-of-the-art performance while also retaining permutation invariance which is a key property for particle physics applications. Due to the strength of transformers in representation learning, our work also serves as a stepping stone for the development of a larger foundation model for trigger applications.

Laatu, Lauri [Imperial Coll., London]↗