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Metal-Organic Frameworks (MOFs) Containing Frustrated Lewis Pairs (FLP) for H 2 Storage at Ambient Temperature

This final technical report summarizes the key accomplishments of the HyMarc Seedling project to develop new materials based on metal-organic framework (MOF) incorporated with frustrated Lewis pairs (FLP) termed as FLP@MOF, as next-generation of hydrogen storage sorbent that can meet or exceed DOE’s 2025 performance target of hydrogen storage gravimetric density of 5.5 wt.% and volumetric density of 0.040 kg H 2 /L. The project was carried out by the PI Shengqian Ma at the University of North Texas (UNT) along with Argonne National Laboratory (ANL) to develop FLP@MOF systems that exhibit high hydrogen storage capacity at ambient temperature under pressure <100 bar, as well as to obtain improved fundamental understanding of hydrogen adsorption mechanism in FLP@MOF system.

08 HYDROGEN↗

Deployment and Evaluation of SciStream on OLCF's Advanced Computing Ecosystem (ACE)

The growing demand for real-time analysis, experimental steering, and decision-making in scientific workflows has created a need for tightly coupled integrations between experimental facilities and high-performance computing (HPC) systems. The Department of Energy’s Integrated Research Infrastructure (IRI) initiative highlights data streaming as a key capability for enabling memory-to-memory data transfers, bypassing the limitations of traditional store-and-forward models. SciStream is a toolkit developed by researchers at Argonne National Laboratory (ANL) to support such streaming by addressing cross-domain security, delegated authentication, and application transparency. We deployed and evaluated SciStream on the Oak Ridge Leadership Computing Facility’s (OLCF) Advanced Computing Ecosystem (ACE) infrastructure, leveraging the Olivine OpenShift cluster and its high-bandwidth Data Streaming Nodes (DSNs) as gateway nodes. Our evaluation included synthetic streaming workloads derived from IRI science workflows, a streaming simulator, and integration with RabbitMQ to handle low-level messaging. This report documents the deployment process, performance evaluation, and challenges encountered, along with opportunities for future improvements.

97 MATHEMATICS AND COMPUTING↗

FAIR Surrogate Benchmarks Supporting AI and Simulation Research (Final Report)

Computational Science is being revolutionized by integrating AI and simulation and, in particular, by deep learning surrogate models that can replace all or part of traditional large‐scale HPC computations. Such surrogates can achieve remarkable performance improvements, as much as several orders of magnitude, and save both compute time and energy. The Surrogate Benchmark Initiative (SBI) project creates a community repository and FAIR (Findable, Accessible, Interoperable, and Reusable) data ecosystem for HPC application surrogate benchmarks. The SBI team comes from Argonne National Laboratory (ANL), Indiana University (IU), Rutgers University, the University of Tennessee, Knoxville (UTK), and the University of Virginia (UVA). SBI repositories include data, code, and all relevant collateral artifacts that the science and engineering community need to use and reuse these data sets and surrogates. SBI repositories generate active research from both the participants in SBI and the broad community of AI and domain scientists. This project develops surrogates that use several different neural nets to learn and quickly infer the results of simulations and data systems and captures them as surrogate benchmarks with a rich set of metadata covering: Data; Model; Metrics specification; Machine specification; and Science, Speed, and Power Results. We research FAIR metadata for these benchmarks. We develop application surrogate examples as benchmarks across many fields (ANL, UTK, IU, UVA). We also study non-Surrogate benchmarks that have many common features and similar issues as regards FAIRness. We work with MLCommons (UVA, UTK), which is a major machine learning benchmarking activity where we get metadata ontologies, software, and benchmarks, Benchmarks have datasets, models, and metadata and they need a technical framework developed by UTK and Rutgers and deployed by UVA. We study features of Surrogates including performance, training set size, and uncertainty quantification (Rutgers, UVA and IU).

97 MATHEMATICS AND COMPUTING↗

Correlating Nb-SRF Surface Processing with Evolution of Surface Electronic States

The few nanometers of the surface exposed to RF field plays a major role in defining the RF performance of superconducting cavities. Over the past two decades, several pioneering surface treatment and processing methods have emerged, enabling remarkable improvements in cavity performance by simultaneously achieving high Q with increasing Eacc. These processing methods include: thermal treatment under ultra-high vacuum (UHV) conditions across lo¬¬¬¬¬¬¬w-, mid-, and high-temperature ranges and high temperature treatments under controlled N2 atmosphere. These processes also produce distinct surface oxide configurations with different valence states, thicknesses, and uniformity, as well as different oxygen concentration profiles in bulk Nb. In this work, we are trying to understand how do surface-processing methods and the resulting oxide/oxygen profiles affect the electronic structure of surface and the mechanism of superconductivity? With the help of Fermilab’s in-house X-ray photoemission facility and, in collaboration with the synchrotron-based angle-resolved photoemission (ARPES) facility at Argonne National Laboratory, we are investigating how the valence band structure and density of states (DoS) near the Fermi level modify with different surface treatments. Our observations show that different surface-processing methods lead to distinct evolutions of the valence-band states near the Fermi level during the superconducting transition. This behavior suggests variations in Nb-O orbital hybridizations and points towards the possibility of different underlying mechanisms of superconductivity governed by the surface chemistry and oxide configuration. We also correlate these distinct superconducting mechanisms with RF cavity performance, specifically focusing on measured surface resistance, the nature of the Q-slope, and quench fields observed in SRF measurements. These results will enable us to identify the potential limiting factors and relevant controllable parameters that can be further optimized to improve the performance of SRF cavities.

Tripathi, Malvika [Fermilab]↗

PowerAmerica (Final Technical Report)

The U.S. Department of Energy’s Advanced Manufacturing Office (predecessor to AMMTO) established PowerAmerica in December 2014 to develop and accelerate the adoption of wide bandgap (WBG) semiconductor chips and power electronics in manufacturing. The objective was to spark early commercialization of energy efficient products; educate and train the workforce; create high-tech jobs; and nurture the growth of the U.S. WBG semiconductor manufacturing industry. PowerAmerica isled by North Carolina State University by way of a five-year, $140M cooperative agreement with DoE. This private-public partnership with DoE includes member companies ranging from startups and small-medium enterprises to large system integrators, world-class universities, and national labs. The WBG power electronic ecosystem formed by our diverse membership is focused on using advanced manufacturing to 1) lower the cost of silicon carbide and gallium nitride semiconductor devices to be comparable to silicon devices; 2) demonstrate the system benefits and energy efficiency advantages of WBG semiconductor power electronics through system demonstrations that validate their effectiveness; and 3) build an education pipeline for a skilled workforce to meet the future demand for emerging WBG semiconductor markets — and enhance U.S. economic competitiveness globally. PowerAmerica was initially funded in six budget periods, each lasting 12 to 18 months. By the end of Budget Period 6 (August 2023), PowerAmerica had achieved its major objectives in technology development, semiconductor device cost reduction, ecosystem growth and engagement, and education and workforce development. Through strategic foundry investments, we helped to establish the first U.S. SiC foundry (X-FAB) and supported a lab (Microchip) to start SiC volume production. We’ve helped bring together companies from different parts of the supply chain, resulting in several successful new partnerships and business relationships. Through projects with some of the largest manufacturers of energy-intensive equipment in the U.S. — John Deere, GE, United Technologies, Raytheon, Carrier, Toshiba, and others — we have successfully demonstrated the energy and system benefits of WBG technology. We have also harnessed the unique capabilities and facilities of national labs — the Naval Research Laboratory, National Renewable Energy Laboratory, and Argonne National Laboratory — to help solve challenging technical problems for industry. Thanks to our many webinars, tutorials, annual events, and presence at major energy and electronics conferences around the world, the PowerAmerica name has become synonymous with WBG technology advancement. The commercial interest in WBG technology is higher than ever; companies and governments around the world have announced hundreds of millions of dollarsin future investment to build capacity — and compete with silicon in many markets and applications. We have trained hundreds of engineering students, from universities across the U.S., through hands-on projects and WBG coursework. Working professionals have also benefited through the years from our many targeted short courses, tutorials, and technical webinars. In short, PowerAmerica has made great strides in each of our key objectives, and the organization has been operating without government or NC State

14 SOLAR ENERGY↗

Iodine Mass Tracking Research and Development Needs for Pyrochemical Fuel Cycles

This report was generated jointly by Argonne National Laboratory (ANL) and Idaho National Laboratory to provide a high-level summary of the current knowledge on the behavior of fission product iodine during reprocessing of used nuclear fuel, as well as provide recommended path forward for research and development activities to fill particular knowledge gaps. The focus of this work is on pyrochemical processing as is applied to light water reactor (LWR) oxide-based used nuclear fuels (UNF), however, some discussion of electrorefiner behavior from metal fuel processing equipment is also included.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Finding ways to reduce nuclear waste: searching for the unknown one step at a time

In my home country, Venezuela, research has been stagnant. Due to the political turmoil and the crisis, many educated people have left the country in search for a better life. This has caused a deficit in any technological and scientific advances, making Venezuela one of the first South American countries to have its rate of publications decline by 29% in 2013. Currently, Venezuela lacks the infrastructure and the means to keep up with the research progress as compared to other countries in South America, such as Brazil. Since coming to the United States (US), and currently working for a national laboratory, the active research environment endorses a wide range of careers and engineering programs that allow researchers to thrive at any given field. Researchers have access to funds and tools to succeed in developing materials for the future. There are 17 national laboratories in the US, and all of these have a different research focus/objective. As examples, Los Alamos National Laboratory and Sandia National Laboratory focus is on national homeland security, weapon science, radiation effects, among others. Argonne National Laboratory focuses on nuclear energy, energy storage, high performance computing, etc. At Idaho National Laboratory (INL) the research focuses on innovating nuclear energy and clean energy resources, critical infrastructure materials, along with fuel cycle solutions to manage, dispose and find ways to recycle current and future radiological waste. Compared to other national laboratories, INL focuses slightly more on applied processes and how nuclear energy can be innovated to next reactor design and technologies. The research being conducted at INL made me apply for a Seaborg distinguished postdoctoral position. For the position itself, the researcher must submit a proposal related to actinide chemistry on a research field area. In this position, 50% of my time will be focused on my own proposal. The proposal that I am working on is focused on the innovation of nuclear energy and fuel cycle recycling, which is why I was mainly interested on working at this national laboratory. To give a bit more context of what my proposal is about, a little bit of background is necessary: After the nuclear fuel (UO2) is used in a reactor, the fuel matrix is then characterized by various fission products (FP). Among these FP (including rare earth elements, alkali/alkaline earths, and actinides), many can potentially be recovered through nuclear reprocessing technologies. In pyroprocessing, the used nuclear fuel undergoes electrochemical dissolution into a molten chloride salt mixture in an electrorefiner. Initially, uranium is reduced onto an inert cathode by applied potentials. However, numerous remaining FPs accumulate in the melt and pose challenges for recovery by an inert electrode, particularly the rare earth elements (e.g., Nd, Gd, Pr, Sm) due to their multivalent oxidation states and tendencies toward side reactions, leading to their dissolution in the electrolyte. These recovery challenges result in inefficiencies and necessitate the continual discarding of the molten chloride salt, thereby generating additional waste. Furthermore, the presence of rare earth elements and other fission products in the molten salt electrolyte alters its physical and chemical properties, affecting both uranium recovery efficiency and the longevity of the molten chloride salt. To improve the recovery efficiency of the FP, specifically rare earth elements, I am investigating the fundamental interactions between rare earth elements in the molten chloride salt and their metallic form. The kinetic pathways and the chemical reactions of these elements will give insights on how the recovery efficiency can be improved. The interactions and speciation of these elements are being studied by spectro-electrochemistry at high temperature environments in quartz and other ceramic materials (e.g., alumina crucibles). Some of the challenges I am facing specifically relates the reactivity of some of these elements with different glass and crucible materials. Although my research focuses on fundamental science, it will benefit the applied process by generating new scientific knowledge and closing the gap for an efficient recycling of the waste: one step at a time.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Conformable, Composite Tank for Liquid Hydrogen Storage in Heavy-duty Ground Transportation

Raytheon Technologies Research Center (RTRC), with its partners, Argonne National Labs and University of Dayton Research Institute proposed to design and manufacture a conformable composite tank prototype to store liquid Hydrogen (LH2) for heavy-duty truck applications. A dual-wall tank concept was proposed where an outer shell covers and protects an inner pressure vessel that stores liquid hydrogen. The inner pressure vessel is liner-less and designed with a conformable concept, derived from prior RTRC ARPA-E program where multiple vessels are coalesced into one, maximizing space utilization and reducing surface area for heat leak. The gap between the dual wall is evacuated of air pressure, and filled with multi-layer insulation to minimize radiative heat transfer. Fiber reinforced composites were proposed for light-weighting and conformable shape manufacture. To minimize LH2 leakage, carbon nanotubes-infused composites were proposed, in addition to use of thin plies. The project was divided into two 18-month budget periods (BP), BP1 and BP2, separated by a Go/No-Go gate review. The high-level goal for BP1 was to demonstrate the feasibility of the overall approach, the tank design, material selection, and manufacturing methodology, build and test a prototype tank; and the goal for BP2 was to design and manufacture a conformal tank per DOE requirements (minimum 20 kg of LH2) and perform a successful test of the tank. The program was terminated about two-thirds of the way through BP1. The outcome of this program would have permitted long-haul trucks and construction vehicles to use liquid Hydrogen, reducing the emission of green-house gases. This technology is applicable to other transportation sectors as well.

08 HYDROGEN↗

Pitch Bearing Rating and Service Life Analysis

Pitch bearings are an essential component in wind turbines used to connect the blade root to the hub. They support the resulting simultaneous radial, axial, and overturning moment loads while allowing relative rotation of the blade to the hub. The most recent evidence indicates the replacement rate for pitch bearings on 3+ MW turbines can be several percent per year, reaching 10% by year 5. This is a far higher replacement rate than both older 1.5 to 2 MW turbines and 2 to 3 MW turbines, which only reach a 10% replacement rate by 14 to 24 years compared to the expected design life of at least 20 years. Typical pitch bearing replacements require the use of a large, expensive crane and removal of the blade(s) or rotor, with a significant amount of downtime. Given the most recent developments in pitch bearing reliability and the publication of the updated NREL and Fraunhofer IWES pitch bearing design guide, the purpose of this report is to update the performance and rating analysis of the example 1.9-meter diameter pitch bearing representative of that installed on a 1.5 MW wind turbine, compare the rating life to the observed service life of similar pitch bearings, and validate the service life modification factor with this large population of bearings. The report will also summarize the pitch bearing contact conditions, thereby serving as a guide for planned bench-level fretting wear tests at Argonne National Laboratory.

17 WIND ENERGY↗

Final report: Insights from ARM observations into aerosol processing and transport by extratropical cyclones and aerosol effects on cyclone clouds

This project advanced understanding of aerosol–cloud interactions in extratropical cyclones using observations from the Atmospheric Radiation Measurement (ARM) Eastern North Atlantic (ENA) observatory and ACE-ENA field campaigns, along with satellite datasets and numerical modeling. We have quantified the susceptibility of frontal clouds to aerosols, showing that this susceptibility is similar to that in non-frontal clouds despite substantial (factor 2) differences in droplet concentrations between these cloud types, and also significant differences in cloud albedo. A key finding was that Aitken-mode (here, 60-100nm diameter) aerosols play a disproportionately important role in droplet activation in frontal clouds, and concentrations of these particles are frequently strongly biased in climate models. Activation of aerosols depends strongly on updraft speeds, and via collaboration with Argonne National Laboratory we contributed to quantifying these better with the ARM radar wind profiler at the ENA site. Our studies in the North Atlantic have analogs in the Southern Ocean, and to draw these out we examined data from the MARCUS and SOCRATES field campaigns. We identified new particle formation within extratropical cyclones as a potentially important source of cloud condensation nuclei in these pristine marine environments. By combining ARM observations with perturbed parameter ensemble simulations, we demonstrated that surface observations can effectively constrain aerosol–cloud adjustments and reduce uncertainty in simulated cloud liquid water path responses by approximately 15%, yielding stronger constraints on historical aerosol cooling effects. The work further established precipitation processes as a dominant control on aerosol–cloud interactions and Earth system predictability.

Gordon, Hamish [Department of Chemical Engineering↗

Free-Piston Expander for Hydrogen Cooling

This final report details work done by GTI Energy, in partnership with University of Texas at Austin – Center for Electromechanics (UTCEM), Argonne National Laboratory (ANL), and Quantum Fuel Solutions (Quantum) to successfully design, fabricate, and test a linear free-piston hydrogen expander controlled by linear motors which also generates electrical power during the process.

03 NATURAL GAS↗

U.S. Department of Energy-National Lab Equity Summit: Grid Planning and Operations (Workshop Report)

This report summarizes the U.S. DOE and national laboratories equity summit that was held on February 5, 2024, and focused on grid planning and operations. The objectives of the summit were to connect DOE and lab researchers working on grid-related equity issues, share information on current and planned grid-related equity projects and initiatives, and inspire and educate participants by hearing from our panelists about solutions and challenges to integrating equity in grid planning and operations. The summit included two panels of industry leaders. The first was a state and community perspectives panel that included representatives from a state public utility commission (Oregon Public Utility Commission), a state energy office (Washington Department of Commerce), a state utility consumer advocate (Connecticut Consumer Counsel), and industry consultants (Elevated Engagement and ArkSpring Consulting). Panelists shared successes they have seen, critical challenges related to equity and grid planning and operations, and other considerations. The second panel addressed utility perspectives and included representatives from two utilities (Commonwealth Edison and Tacoma Power), the National Rural Electric Cooperative (NRECA), and a former utility employee and legal consultant. Panelists discussed the role of the utility concerning equity, the most significant technical and data modeling needs and opportunities, and the role the labs could help advance equity in grid planning and operations. There was also a session on partner organization presentations. Argonne National Laboratory made a short presentation on the Grid Modernization Laboratory Consortium (GMLC) project they are leading on equity-informed power system planning. NARUC, NASEO, and the Clean Energy States Alliance, as partners of the GMLC project also shared updates on relevant activities and resources. During the summit, there were two rounds of lightning presentations by national labs and DOE highlighting research that addresses equity and grid planning and operations (Tables 5 and 6 and slides in the Appendix). The goal of the lightning rounds was to share information between participants to encourage collaboration and leverage ongoing research at labs and DOE. The summit included two interactive exercises where summit participants shared their perspectives on relevant equity projects and initiatives (Table 2), key challenges regarding equity and grid planning and operations (Table 3), and promising innovations or progress (Table 4). At the end of the session, participants were asked to share essential insights from the event (Table 7) and an action they plan to take as a result of the event. Participants agreed that the event was useful in helping them share and learn from each other. The project team plans to use the information from the summit as a starting point to help inform future research and technical assistance. In 2026, another Equity Summit will be held (virtually or in person) as part of the same project to help raise awareness and disseminate research and resources completed during the project's duration.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Cross Section Generation Capability in Griffin

The Griffin code is a Multiphysics Object-Oriented Simulation Environment (MOOSE) based reactor multiphysics analysis application jointly developed by Idaho National Laboratory and Argonne National Laboratory. The code includes a variety of steady-state solvers for fixed-source, k-eigenvalue, adjoint, and subcritical multiplication, as well as transient solvers for point-kinetics, improved quasi-static, and spatial dynamics. The code reads multigroup cross sections in the ISOXML format generated from external deterministic or Monte Carlo cross section generation codes. The implementation of the cross section generation capability in Griffin was initiated last year by plugging in the cross section application programming interface (CSAPI) and reviewing the methodologies for treating particulate fuels. The focus this year was on improving the CSAPI integration and implementing advanced self-shielding methods for applications to advanced reactor problems with TRISO fuels. First, the process for cross section library generation was updated to accurately and rigorously produce isotopic cross section data. Second, the on-the-fly slowing down method for the resonance treatment was implemented in CSAPI to improve the accuracy of effective multigroup cross sections in the resonance energy range. Among various on-the-fly slowing down methods, the equivalent Dancoff factor cell method was employed. Third, the iterative local spatial self-shielding method was implemented under the calculation framework of the equivalent Dancoff factor cell method to accurately deal with the double heterogeneity effect of particulate fuel. The updated CSAPI with the advanced self-shielding methods, together with the cross section libraries generated based on the improved process, were tested for the very high temperature reactor (VHTR), high temperature test reactor (HTTR), and Empire benchmark problems with various resonance self-shielding conditions, indicating that the updated CSAPI in Griffin is able to produce multigroup cross sections accurately and efficiently. We also show that the methodology works well for pebble bed fuel from HTR-10, but the capability still needs to be fully integrated into CSAPI. In the future, further benchmark tests will be performed for various thermal reactor core problems, including particulate fuel-based pebble bed reactors.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Performance Improvements of the Griffin Solvers in FY24

The Griffin code is a MOOSE-based reactor physics application jointly developed by Idaho National Laboratory and Argonne National Laboratory under the Department of Energy Office of Nuclear Energy Nuclear Energy Advanced Modeling and Simulation Program. This fiscal year, we have made significant efforts to improve the performance of transport solver options and cross-section generation for the efficient use of Griffin in advanced reactor applications. For the HFEM-PN solver, the residual evaluations of HFEM kernels were optimized by utilizing the pre- computed averaged cross sections for individual elements. Numerical integration involving the evaluation of basis functions at quadrature points was bypassed by facilitating precomputed element mass matrices for response matrices. Red-black iterations were improved by introducing a new generalized minimum residual based solver. The memory usage of response matrix storage was significantly reduced by applying basis function rotations on interfaces and calculating volumetric odd-parity moments on the fly. Additionally, the adjoint flux and transient calculation capabilities of the HFEM-PN solver were successfully implemented and verified using the TWIGL benchmark problem. For the DFEM-SN solver, memory footprint and computation time were significantly reduced by not treating angular flux vectors as the MOOSE nonlinear system vectors. Specifically for IQS, scalar adjoint weighting was introduced to further eliminate angular adjoint flux storage in the MOOSE auxiliary system. It was demonstrated through the three-dimensional Advanced Burner Test Reactor core problem that the memory usage for transient calculations with the IQS method was reduced by over 7.5× compared to before the optimizations. For the self-shielding application programming interface, a new double-heterogeneity treatment method, named the Bell Function-Based Analytic Two-Region Slowing Down Method, was developed to efficiently flux-volume homogenize TRISO particles with the matrix. Additionally, optimizations were made to hyper- fine group (HFG) slowing down calculations by pretabulating collision probability coefficients and grouping isotopes, significantly reducing the computational time for calculating scattering sources per HFG. Lastly, the pin power reconstruction module was extended to account for temporal behavior in a microreactor analysis problem, specifically for a control drum transient. Verification tests for each of these improvements demonstrated significant performance enhancements and memory reduction.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Benchmarking DAOS Filesystem on Aurora

We benchmark the DAOS filesystem on Argonne's Aurora supercomputer (127 nodes, 4,064 targets) using fio, IOR, mdtest, and IO500 to characterize I/O and metadata performance across the DFS API and DFuse+POSIX. Single-client fio shows POSIX bandwidth saturating at 1–2 MiB I/O sizes, with write-heavy workloads outperforming reads. Multi-node IOR shows DFS bandwidth scaling well up to ~32 tasks/node, with write latency growing faster than read latency. An 8-node IO500 evaluation shows DFS achieving ~5x higher bandwidth and ~190x higher IOPS than POSIX. Results indicate DAOS is well-suited to read-heavy workloads like AI training data loading, given appropriately sized transfers and concurrency.

George, Rebecca [College of William and Mary, Will↗

Large Language Model for Validation, Optical Calibration, and Learning (VOCAL) Distributed Temperature Sensing Interface

Distributed temperature sensing (DTS) using fiber optic sensors (FOS) offers a promising method for temperature measurements in advanced reactors, such as sodium fast reactors and molten salt cooled reactors. To support the calibration and validation of DTS measurements, Argonne National Laboratory developed the Validation, Optical Calibration, and Learning (VOCAL) software package. This report describes the integration of a local large language model (LLM) with a retrieval-augmented generation (RAG) system into the VOCAL interface to serve as an interactive user assistant. The LLM framework enhances the VOCAL platform’s accessibility to users by explaining interface components, clarifying inputs and outputs, and answering user queries dynamically in real-time. The accuracy of the LLM assistant performance was evaluated with 20 queries regarding the interface and its parameters using experimental data from the Thermal Hydraulic Experimental Test Article (THETA) facility. Results demonstrate that the LLM achieved a 95% accuracy rate, with a BERTScore of 0.8816 and SBERT value of 0.7417. Furthermore, validation of the RAG system within the LLM framework showed optimal accuracy with k-values between 1 and 2 using the k-refinement convergence test. The prompt perturbation analysis demonstrated good initial consistency for the RAG system, exhibiting the highest accuracy under punctuation variations and the greatest sensitivity under query reordering. Notably, the model’s errors were limited to data retrieval failures rather than factual hallucinations, reinforcing its baseline reliability. The integration of LLM provides a highly accurate, userfriendly enhancement to the VOCAL platform without disrupting its core computational capabilities for FOS calibration and validation.

Hong, Evan↗

Control Room of the Future Testbed Workshop – After-Action Report

The U.S. Department of Energy’s Office of Electricity is supporting a one-year, multi-laboratory effort to define the needs and requirements for a Control Room of the Future testbed, or CROFT. The effort responds to increasing grid complexity driven by large new loads, dynamic generation resources, and the growing adoption of advanced technologies and tools, including artificial intelligence (AI) and machine learning (ML). To support safe, secure, and effective grid modernization, CROFT will focus on how emerging technologies and tools can be rigorously evaluated in realistic operational settings, with attention to human-machine interaction, cognitive load, and workforce readiness. The project team includes Argonne National Laboratory, Idaho National Laboratory, National Laboratory of the Rockies, and Pacific Northwest National Laboratory. As part of the scoping effort, the team conducted two industry-focused workshops: one at DTECH on February 5, 2026, informed by prior industry interviews, and a second on May 4, 2026, adjacent to IEEE T&D. These engagements brought together utilities, vendors, consultants, national laboratories, academia, and government stakeholders to identify and prioritize use cases, barriers, validation needs, data-sharing constraints, and near- and longer-term requirements. This feedback will directly inform CROFT’s architecture and research focus areas, ensuring the testbed is grounded in real-world operational needs and designed to evaluate emerging technologies and tools in realistic control-room environments.

artificial intelligence↗

Integration of Online Cross-Section Generation Capability with Depletion and Transient Solvers in Griffin

Griffin is a Multiphysics Object-Oriented Simulation Environment (MOOSE)-based reactor multiphysics analysis application jointly developed by Argonne and Idaho National Laboratories under the DOENE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. In FY25, an online crosssection generation capability based on the Self-Shielding Application Programming Interface (SSAPI) was demonstrated for TRISO-fueled reactor problems under steady-state conditions. This fiscal year, that capability was extended to support depletion and transient multiphysics calculations, enabling high-fidelity analyses that generate self-shielded cross sections on the fly from the actual evolving composition and temperature states rather than from pre-tabulated libraries. For depletion, a two-way coupling was established in which SSAPI computes compact-averaged self-shielded cross sections that the depletion solver then uses to advance the Bateman equations, with the updated compositions returned to SSAPI at each step; the depletion module was refactored to support both library-based and SSAPI-based cross sections, and additional logic was added to track daughter isotopes and to exclude minor isotopes for efficiency. For transient analysis, the SSAPI multigroup library was extended with the kinetics data required for time-dependent calculations, the Improved Quasi-Static (IQS) scheme was coupled with SSAPI, and several supporting capabilities were implemented, including a self-shielding treatment that lets control rods and drums move within a self-shielded model, which had previously been impossible and had ruled out rod- and drum-movement transients with on-the-fly cross sections altogether, a new mixing scheme for delayed-neutron precursor decay constants, a checkpoint-based restart workflow, and performance improvements such as pointwise cross-section interpolation and the bypassing of unnecessary Dancoff factor calculations. The implemented capabilities were verified against Serpent Monte Carlo solutions. For depletion, a prismatic pin-cell problem based on a Next Generation Nuclear Plant (NGNP) Very High Temperature Reactor benchmark showed excellent agreement, with eigenvalue differences within 200 pcm over the entire burnup range (up to 140 MWD/kgU) and fission-product and actinide inventories agreeing to within 0.8% and 2.5%, respectively; a heat-pipe microreactor assembly problem with a much higher fuel loading confirmed the same behavior and quantified the bias introduced when the multigroup equivalence effect is neglected. For transient analysis, a pin-cell problem with a step reactivity insertion and temperature feedback reproduced the analytically expected asymptotic power and showed close agreement between the direct and IQS solutions, and a two-dimensional microreactor core problem with control-drum rotation exercised the new moving-drum self-shielding treatment and demonstrated successful coupling of the online crosssection generation with both the direct and IQS transient methods. The capability was further exercised on a full-core pebble-bed problem, in which Griffin was coupled with the System Analysis Module (SAM) to simulate load-following operation of the gPBR with the Doppler feedback resolved at the TRISO fuel kernel temperature. These developments in Griffin provide a convenient, high-fidelity approach to cross-section generation for advanced thermal reactors with geometrically complex and highly heterogeneous configurations, including TRISO-fueled prismatic and pebble-bed systems, and support steady-state, depletion, and transient multiphysics calculations. They also enable self-shielded cross sections to be evaluated directly at the actual coupled state of the system, thereby establishing a foundation for high-fidelity, fully coupled multiphysics analysis of advanced reactors

Park, H.↗