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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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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Optimizing Management of Persistent Data Structures in High-Performance Analytics

Large-scale data analytics workflows ingest massive input data into various data structures, including graphs and key-value datastores. These data structures undergo multiple transformations and computations and are typically reused in incremental and iterative analytics workflows. Persisting in-memory views of these data structures enables reusing them beyond the scope of a single program run while avoiding repetitive raw data ingestion overheads. Memory-mapped I/O enables persisting in-memory data structures without data serialization and deserialization overheads. However, memory-mapped I/O lacks the key feature of persisting consistent snapshots of these data structures for incremental ingestion and processing. The obstacles to efficient virtual memory snapshots using memory-mapped I/O include background writebacks outside the application’s control, and the significantly high storage footprint of such snapshots. To address these limitations, we present Privateer, a memory and storage management tool that enables storage-efficient virtual memory snapshotting while also optimizing snapshot I/O performance. Here, we integrated Privateer into Metall, a state-of-the-art persistent memory allocator for C++, and the Lightning Memory-Mapped Database (LMDB), a widely-used key-value datastore in data analytics and machine learning. Privateer optimized application performance by 1.22× when storing data structure snapshots to node-local storage, and up to 16.7× when storing snapshots to a parallel file system. Privateer also optimizes storage efficiency of incremental data structure snapshots by up to 11× using data deduplication and compression.

Computer science↗
DOE OSTI2024

Adaptive Power Flow Approximations With Second-Order Sensitivity Insights

The power flow equations are fundamental to power system planning, analysis, and control. However, the inherent non-linearity and non-convexity of these equations present formidable obstacles in problem-solving processes. To mitigate these challenges, recent research has proposed adaptive power flow linearizations that aim to achieve accuracy over wide operating ranges. The accuracy of these approximations inherently depends on the curvature of the power flow equations within these ranges, which necessitates considering second-order sensitivities. In this paper, we leverage second-order sensitivities to both analyze and improve power flow approximations. We evaluate the curvature across broad operational ranges and subsequently utilize this information to inform the computation of various sample-based power flow approximation techniques. Additionally, we leverage second-order sensitivities to guide the development of rational approximations that yield linear constraints in optimization problems. In conclusion, this approach is extended to enhance accuracy beyond the limitations of linear functions across varied operational scenarios.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

FIRE: A Failure-Adaptive RL Framework for Edge Computing Migrations

In edge computing, users' service profiles are migrated between edge servers due to user mobility. Reinforcement Learning (RL) frameworks have been proposed to do so, often trained on simulated data. However, existing RL frameworks overlook occasional server failures, which although rare, impact latency-sensitive applications like AR/VR and real- time obstacle detection. These rare failures, being not adequately represented in historical training data, pose a challenge for data-driven RL algorithms. We introduce FIRE, a framework that adapts to rare events by training a RL policy in an edge computing digital twin environment. We propose FIRE-ImRE, an importance sampling-based Q-learning algorithm, which samples rare events proportionally to their impact on the value function. FIRE considers delay, migration, failure, and backup placement costs across individual and shared service profiles. We prove FIRE-ImRE's boundedness and convergence to optimality. Next, we introduce novel deep Q-learning (FIRE-ImDQL) and actor critic (FIRE-ImACRE) versions of our algorithm to enhance scalability. Here, we extend our framework to accommodate users with varying risk tolerances of rare failure events. Through trace-driven experiments, we show that FIRE reduces edge computing costs compared to vanilla RL and the greedy baseline in the event of failures.

Edge computing↗
DOE OSTI2026

GeSn alloys with ∼21% Sn grown by effusion cell molecular beam epitaxy

We report the epitaxial growth of high quality GeSn alloys with Sn compositions up to 21.25 ± 1% by effusion-cell molecular beam epitaxy (MBE). Achieving such a high Sn content with effusion cells is particularly significant, since these sources typically impose stronger radiative heating on the substrate, which is a factor long considered a major obstacle to high-Sn GeSn epitaxy. Contrary to the prevailing assumption that high growth rates are good for suppressing Sn segregation, we demonstrate that carefully controlled low fluxes, combined with stable ultra-low substrate temperatures, enable significant Sn incorporation even under effusion-cell conditions. Structural analyses by high-resolution x-ray diffraction, reciprocal space mapping, atomic force microscopy, and transmission electron microscopy confirm sharp interfaces, high crystallinity, and smooth surfaces at high Sn contents. Furthermore, these findings establish the feasibility of MBE-grown high-Sn GeSn even under diffusion cells, thereby broadening opportunities for Si-compatible photonic and quantum devices.

Alloys↗
DOE OSTI2025

Nanoscale engineering and dynamic stabilization of mesoscopic spin textures

Thermalization, while ubiquitous in physics, has traditionally been viewed as an obstacle to be mitigated. In contrast, we demonstrate here the use of thermalization in the generation, control, and readout of “shell-like” spin textures with interacting 13 C nuclear spins in diamond, wherein spins are polarized oppositely on either side of a critical radius. The textures span several nanometers and encompass many hundred spins; they are created and interrogated without manipulating the nuclear spins individually. Long-time stabilization is achieved via prethermalization to a Floquet-engineered Hamiltonian under the electronic gradient field: The texture is therefore metastable and robust against spin diffusion. This enables the state to endure over multiple minutes before it decays. Our work on spin-state engineering paves the way for applications in quantum simulation and nanoscale imaging.

42 ENGINEERING↗
DOE OSTI2024

Color symmetry and confinement as an underlying superconformal structure in holographic QCD

Dedicated to the memory of our colleague, Harald Fritzsch, who, together with Murray Gell-Mann, introduced the color quantum number as the exact symmetry responsible for the strong interaction, thus establishing quantum chromodynamics (QCD) as a fundamental non-Abelian gauge theory. A basic understanding of hadron properties, however, such as confinement and the emergence of a mass scale, from first principles QCD has remained elusive: Hadronic characteristics are not explicit properties of the QCD Lagrangian and perturbative QCD, so successful in the large transverse momentum domain, is not applicable at large distances. In this article, we shall examine how this daunting obstacle is overcome in holographic QCD with the introduction of a superconformal symmetry in anti de Sitter (AdS) space which is responsible for confinement and the introduction of a mass scale within the superconformal group. When mapped to light-front coordinates in physical spacetime, this approach incorporates supersymmetric relations between the Regge trajectories of meson, baryon and tetraquark states which can be visualized in terms of specific SU(3) C color representations of quarks. Finally, we will also briefly discuss here the implications of holographic models for QCD color transparency in view of the present experimental interest.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

wa-hls4ml: A Benchmark and Surrogate Models for hls4ml Resource and Latency Estimation

As machine learning (ML) is increasingly implemented in hardware to address real-time challenges in scientific applications, the development of advanced toolchains has significantly reduced the time required to iterate on various designs. These advancements have solved major obstacles, but also exposed new challenges. For example, processes that were not previously considered bottlenecks, such as hardware synthesis, are becoming limiting factors in the rapid iteration of designs. To mitigate these emerging constraints, multiple efforts have been undertaken to develop an ML-based surrogate model that estimates resource usage of ML accelerator architectures. We introduce wa-hls4ml, a benchmark for ML accelerator resource and latency estimation, and its corresponding initial dataset of over 680,000 fully connected and convolutional neural networks, all synthesized using hls4ml and targeting Xilinx FPGAs. The benchmark evaluates the performance of resource and latency predictors against several common ML model architectures, primarily originating from scientific domains, as exemplar models, and the average performance across a subset of the dataset. Additionally, we introduce GNN- and transformer-based surrogate models that predict latency and resources for ML accelerators. We present the architecture and performance of the models and find that the models generally predict latency and resources for the 75% percentile within several percent of the synthesized resources on the synthetic test dataset.

Hawks, Benjamin [Fermilab] (ORCID:0000000157000288↗
DOE OSTI2024

Review—In Situ X-ray and Infrared Spectroscopic Studies of Electrochemical Systems

Despite of intense research and a wealth of data, the phenomena occurring during electrocatalysis are still a major obstacle in many chemical processes. Molecular analysis of the electrode/electrolyte interface is needed to correctly describe the reaction through identifying the species involved, their interaction with the environment and kinetics in situ, i.e. while the reaction is taking place. That can be done by coupling the electrochemical system with complementary non-electrochemical techniques. Particularly revealing are in situ X-ray spectroscopic techniques to analyze the electrode itself, providing the information on the changes in the catalyst during the reaction. The synergy of the traditional electrochemical techniques with the complementary spectroscopic methodologies offer understanding of the electrode/electrolyte interface above and beyond traditional experimental mainframe. Here we demonstrate how in situ X-ray absorption spectroscopy (XAS), in situ infrared reflection/absorption spectroscopy (IRRAS), and traditional voltammetric studies can increase our understanding of electrochemical processes during oxidation of ethanol. The results show the pronounced role of electrode surface in determining reaction kineticks and revealed the selectivity of the catalyst to complete oxidation pathway. They further provide understanding of the parameters that enhance its oxidation for future designing catalysts for alcohol oxidation fuel cells.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2024

Visualization at exascale: Making it all work with VTK-m

The VTK-m software library enables scientific visualization on exascale-class supercomputers. Exascale machines are particularly challenging for software development in part because they use GPU accelerators to provide the vast majority of their computational throughput. Algorithmic designs for GPUs and GPU-centric computing often deviate from those that worked well on previous generations of high-performance computers that relied on traditional CPUs. Fortunately, VTK-m provides scientific visualization algorithms for GPUs and other accelerators. VTK-m also provides a framework that simplifies the implementation of new algorithms and adds a porting layer to work across multiple processor types. This paper describes the main challenges encountered when making scientific visualization available at exascale. Here, we document the surprises and obstacles faced when moving from pre-exascale platforms to the final exascale designs and the performance on those systems including scaling studies on Frontier, an exascale machine with over 37,000 AMD GPUs. We also report on the integration of VTK-m with other exascale software technologies. Finally, we show how VTK-m helps scientific discovery for applications such as fusion and particle acceleration that leverage an exascale supercomputer.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Non-perturbative cathodoluminescence microscopy of beam-sensitive materials

Cathodoluminescence microscopy is now a wellestablished and powerful tool for probing the photonic properties of nanoscale materials, but in many cases, nanophotonic materials are easily damaged by the electronbeam doses necessary to achieve reasonable cathodoluminescence signal-to-noise ratios. Two-dimensional materials have proven particularly susceptible to beam-induced modifications, yielding both obstacles to high spatial-resolution measurement and opportunities for beam-induced patterning of quantum photonic systems. Here pan-sharpening techniques are applied to cathodoluminescence microscopy in order to address these challenges and experimentally demonstrate the promise of pan-sharpening for minimally-perturbative high-spatial-resolution spectrum imaging of beam-sensitive materials.

2D materials↗
DOE OSTI2025

Production and purification of research scale 161 Tb using cation-exchange semi-preparative HPLC for radiopharmaceutical applications

Terbium-161 ( 161 Tb) is emerging as a promising radionuclide for cancer therapy due to its favorable nuclear properties that are similar to clinically established lutetium-177 ( 177 Lu) along with its therapeutic edge arising from the higher number of Auger and conversion electrons per decay. These low energy electrons result in higher cytotoxicity within a short range of the decaying nuclei to enhance therapeutic efficacy. Despite these promising characteristics, a significant challenge remains in the lack of a domestic 161 Tb supply in the United States, which poses an obstacle to the advancement of 161 Tb-based radiopharmaceutical research and development. Here, this study developed a reliable cation-exchange high-performance liquid chromatography-based method for purification of reactor-produced 161 Tb at quantities suitable to support research and preclinical studies. The purified 161 Tb product showed high radionuclidic purity with excellent radiochemical purity, and the successful labeling studies with the DOTA chelator and DOTA-TATE peptide demonstrated the effective incorporation of the purified 161 Tb into radiopharmaceuticals designed for targeted cancer therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2025

Influence of pre-existing defects on thermal transport in nuclear graphite

Nuclear graphite is a critical material in high-temperature nuclear reactors due to its superior thermal and mechanical properties. The manufacturing process leaves multi-scale ‘pre-existing’ defects that can affect thermal transport characteristics. Because these defects are remnant of graphitization temperature, they cannot be thermally annealed. This study employs a non-thermal electron wind force (EWF) annealing technique to avoid this obstacle. 2 min of EWF treatment of the as-received graphite IG-110 at temperatures below 100 °C led up to 67% increase in thermal diffusivity and ~ 35% decrease in electrical resistivity in average. Differential scanning calorimetry also showed similar outcome for specific heat. X-ray diffraction characterization was performed by fitting a bi-modal crystallite size distribution model to reveal the enhancement in crystallinity after the EWF treatment. The findings emphasize the potential of EWF annealing for optimizing thermal performance in nuclear graphite and its implications for reactor efficiency and safety.

Annealing↗
DOE OSTI2024

A prospective on machine learning challenges, progress, and potential in polymer science

Abstract Artificial intelligence and machine learning (ML) continue to see increasing interest in science and engineering every year. Polymer science is no different, though implementation of data-driven algorithms in this subfield has unique challenges barring widespread application of these techniques to the study of polymer systems. In this Prospective, we discuss several critical challenges to implementation of ML in polymer science, including polymer structure and representation, high-throughput techniques and limitations, and limited data availability. Promising studies targeting resolution of these issues are explored, and contemporary research demonstrating the potential of ML in polymer science despite existing obstacles are discussed. Finally, we present an outlook for ML in polymer science moving forward. Graphical Abstract

Struble, Daniel C. (ORCID:0009000093410612)↗
DOE OSTI2025

Fiber-Optic Sensing for Earthquake Hazards Research, Monitoring, and Early Warning

The use of fiber‐optic sensing systems in seismology has exploded in the past decade. Despite an ever‐growing library of ground‐breaking studies, questions remain about the potential of fiber‐optic sensing technologies as tools for advancing if not revolutionizing earthquake‐hazards‐related research, monitoring, and early warning systems. A working group convened to explore these topics; we comprehensively examined the application of fiber optics in various aspects of earthquake hazards, encompassing earthquake source processes, crustal imaging, data archiving, and technological challenges. There is great potential for fiber‐optic systems to advance earthquake monitoring and understanding, but to fully unlock their capabilities requires continued progress in key areas of research and development, including instrument testing and validation, increased dynamic range for applications focused on larger earthquakes, and continued improvement in subsurface and source imaging methods. A key current stumbling block results from the lack of clear data archiving requirements, and we propose an initial strategy that balances data volume requirements with preserving key data for a broad range of future studies. In addition, we demonstrate the potential for fiber‐optic sensing to impact monitoring efforts by documenting the data completeness in a number of long‐term experiments. Finally, we outline the features of a instrument testing facility that would enable progress toward reliable and standardized distributed acoustic sensing data. Overcoming these current obstacles would facilitate progress in fiber‐optic sensing and unlock its potential application to a broad range of earthquake hazard problems.

58 GEOSCIENCES↗
DOE OSTI2024

Transactive Energy Practices Survey

For nearly two decades, the idea of using market-based approaches in field deployments that coordinate the flexible operation of electricity customer assets has occupied the efforts of transactive energy practitioners. While the purported benefits of this distributed decision-making approach encourage transactive energy designs have been well explored, the practical aspects of implementing such a system to address real-world problems are just beginning to emerge. This report surveyed 24 field-deployed programs and interviewed experts instrumental in these deployments. The results of the survey and interviews reveal the diversity of designs and applications. They highlight the technical promise of the approaches as well as challenges with system integration, sustainable business strategy, and regulatory policy obstacles. Insights from the survey offer considerations to direct future effort and investment.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Ultrafast High Voltage Kicker System Hardware for Ion Clearing Gaps

Jefferson Lab (JLab) will collaborate with Radiabeam, LLC in a DOE SBIR Phase II Project (DOE Grant No. DE-SC0019684, title: “Ultrafast High Voltage Kicker System Hardware for Ion Clearing Gaps”) to develop and test a MHz high voltage nanosecond kicker system that enables the time structure required by the ion traps for high current electron beam cooling. High current (in particular energy recovery) linac based electron cooling facilities for medium to high energy bunched proton or ion beams are of great interest for the recently funded Electron-Ion Collider (EIC) to which Jefferson Lab plays a critical role. The successful execution of this project will enable the capability to mitigate the ion trapping effect and circumvent a major obstacle preventing reliable operation of the crucial cooling facilities.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Concrete Thermal Energy Storage Enabling Flexible Operation without Coal Plant Cycling

The work described in this report is responsive to the Office of Fossil Energy program “Energy Storage for Fossil Power Generation.” The pilot plant built as a result of this project demonstrated the feasibility and performance of a concrete thermal energy storage (CTES) system integrated with a supercritical coal power plant. The 10 MWh electrical (>25 MWh thermal) CTES unit, developed by Storworks Power, was designed to enable flexible operation of coal plants without cycling damage. The project's key technical achievements showcase a significant advancement in energy storage technology. A modular CTES system using 42 “Bolderblocs” units was successfully designed and constructed at Alabama Power’s Plant Gaston Unit 5, with each block containing embedded stainless-steel coils in specialized, cost-effective high-temperature concrete. The system interfaced seamlessly with the plant's 3500 psig (241 barg), 1000°F (538°C) supercritical steam, demonstrating operational flexibility. Over 86 full cycles, the CTES exhibited rapid charging and discharging capabilities, effectively mimicking steam turbine feed conditions and handling varying load profiles and storage durations. Performance validation confirmed the system's ability to consistently meet design target steam conditions of 75 bar-a and ~400°C for nominal baseline discharge. The concrete material withstood repeated thermal cycling without degradation, validating earlier lab-scale tests. Integration of balance of plant components, including a condensate management system with storage tank and air-cooled condenser, minimized plant interfaces and water consumption. A robust control scheme ensured safe, automated operation across various scenarios. Key learnings from the project were invaluable: 1. Initial concrete drying and commissioning procedures were refined for future deployments, enhancing efficiency in subsequent installations. 2. System flexibility exceeded expectations, with rapid response to changing conditions. 3. Design improvements were identified including optimized insulation and piping that will enhance overall system efficiency in future deployments 4. Full cycle thermal roundtrip efficiencies exceeded 88%. While the roundtrip electrical efficiency was somewhat limited by known challenges using input steam, such constraints may be mitigated by swapping steam for hot air as thermal input. 5. A summary of key performance parameters for the pilot test and predicted performance of a full scale commercial system with specified improvements determined from the pilot are shown in Section 8. The project faced challenges, including COVID-19 delays and host plant availability constraints. However, these were overcome through adaptive planning and execution. The successful management of these obstacles demonstrated the resilience and adaptability of the project team and the robustness of the CTES technology. This successful pilot demonstrates the potential for CTES to enhance coal plant flexibility, supporting grid stability as renewable penetration increases. The validated design and operational data provide a solid foundation for scaling up to utility-scale implementations, potentially transforming how thermal plants operate in evolving energy landscapes. The system's ability to rapidly respond to changing grid conditions while maintaining high efficiency makes it a promising solution for balancing intermittent renewable energy sources. Furthermore, the project highlighted the potential for even greater efficiencies in future iterations. The use of air as an input medium could potentially eliminate the limitations observed with steam input, opening new possibilities for energy storage applications beyond coal plant integration. In conclusion, this pilot project not only achieved its primary goals but also uncovered additional benefits and potential applications of the CTES technology. It represents a significant step forward in addressing the challenges of grid stability and flexibility in an increasingly renewable-driven energy landscape.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

SAM Code Enhancements for Modeling of Liquid Metal-Cooled Fast Reactor Concepts

The SAM code is under development and supported by DOE-NE’s Nuclear Energy Advanced Modeling and Simulation program as a modern system-level modeling and simulation tool for advanced non-light water reactor safety analyses. These advanced reactor concepts incorporate novel and improved approaches to achieve safety and economic feasibility. This report summarizes two major efforts in addressing the modeling gaps in SAM for liquid-metal-cooled fast reactor (LMFR) applications, i.e. thermal mixing and stratification phenomena in large pools and corrosion-oxidation of components in flowing lead. A new one-dimensional model for thermal mixing and stratification effects in large pools and enclosures is developed and implemented. Thermal mixing and stratification occur when fluid enters a pool at a temperature different than the bulk fluid itself, a scenario often encountered during transients in pool-type systems. These phenomena are critical for the safety of reactors, impacting phenomena like natural circulation, which is essential for passive cooling. The improved model in SAM addresses limitations of state-of-the-art approaches by combining one-dimensional (1D) channels, representing the coolant jet flow, with lumped-parameter zero-dimensional (0D) pools, representing the rest of coolant in the tank. Energy exchange between the 1D jet and the 0D pools is based on heat transfer correlations calibrated against 3D simulations. It is verified that this model can handle various flow configurations, including hot jets in colder pools, cold jets in hotter pools, and the presence of features like ceilings, free surfaces, and obstacles. Additionally, validation against experimental data demonstrates the ability of the model to capture mixing and stratification effects in a wide range of conditions. The flexibility and improved accuracy of the new model make it a valuable tool for reactor safety analysis, allowing for the simulation of different geometries encountered in advanced reactors. A system-level corrosion modeling capability is developed and implemented in SAM to support Lead Fast Reactor (LFR) development. Although the initial focus of this capability will be on LFR application, this can later be expanded to include other liquid metals such as Lead-Bismuth Eutectic (LBE) and PbLi. This report summarizes the common corrosion mitigation strategies and outlines the progress on implementing and validating a corrosion-oxidation model in SAM. Verification and validation of the corrosion-oxidation portion of the model was performed using analytical solution and measured data from samples tested in the non-isothermal pumped lead loop at IPPE Obninsk. The iron transport and corrosion/precipitation portion of the model was assessed using an analytical model and measured corrosion depths from a natural convection lead loop experiment performed at CEA. It is demonstrated that the model implemented in SAM performed well in these assessments.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗