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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Geologic hydrogen: From natural occurrences to anthropogenic generation – A review of fundamentals, potential, challenges and prospects

Growing demand for hydrogen is exposing the environmental and economic limits of reforming-based and carbon-managed supply chains, while the scale-up of electrolytic capacity remains capital-constrained. Geologic hydrogen, defined as molecular H₂ generated and stored within the Earth's crust offers a complementary, potentially lower-cost resource, yet exploration is still ad hoc. This review (1) revisits a global inventory of confirmed hydrogen seeps and subsurface occurrences; (2) analyzes the controlling reactions, migration pathways, and trapping conditions governing these occurrences; (3) proposes a process-based geologic hydrogen system concept analogous to, yet distinct from, the petroleum system; and (4) evaluates potential geologic hydrogen systems within the United States as a representative case study. Here, we contrast natural systems powered by serpentinization, mantle degassing or radiolysis with anthropogenic systems that stimulate the same reactions or convert in-situ hydrocarbons. Stable hydrogen accumulations require generation rates that outpace combined physical, chemical and microbial losses; the Bourakébougou field (Mali) exemplifies a self-recharging, free-gas reservoir sustained by meteoric-water serpentinization beneath an efficient caprock. Prospective geologic hydrogen resources are likely to occur in regions where iron-rich lithologies, deep-seated faults, and low-permeability sealing formations coexist. Applying this principle, we highlight three promising hydrogen play types in U.S. geological terrains: ophiolite belts (Appalachian and Californian regions), the Midcontinent Rift and the Lake Superior banded‑iron formations. Multiphysics numerical models and positive-unlabeled machine-learning workflows help to accelerate play screening and de-risk future production; yet, reaction kinetics, stimulation strategies, and full techno-economic and life-cycle assessments remain pivotal knowledge gaps.

Anthropogenic hydrogen generation↗
DOE OSTI2026

Fast and Accurate Intersections on a Sphere

We introduce a fast, high-precision algorithm for calculating intersections between great circle arcs and lines of constant latitude on the unit sphere. We first propose a simplified intersection point formula with improved speed and numerical robustness over the ones traditionally implemented in geoscience software. We then show how algorithms based on the concept of error-free transformations (EFT) can be applied to evaluate this formula within a relative error bound that is on the order of machine precision. Here, we demonstrate that, with a vectorized and parallelized implementation, this enhanced accuracy is achieved with no compute time overhead compared to a direct calculation in hardware floating point, making our algorithm suitable for performance-sensitive applications like regridding of high-resolution climate data. In contrast, evaluating our formula using high-precision data types like quadruple precision and arbitrary precision, or using the robust intersection computation routines from the Computational Geometry Algorithms Library, leads to significant computational overhead, especially since these alternatives inhibit vectorization. More generally, our work demonstrates how EFT techniques can be combined and extended to implement nontrivial geometric calculations with high accuracy and speed.

Environmental sciences↗
DOE OSTI2025

Even Higher-Level Synthesis: An Exploration of AI Hardware Accelerators using HLS4ML

With the rise of artificial intelligence, the popularization of deep learning, and a constantly evolving industry, the demand for flexible and efficient tools has never been greater. As algorithms grow more complex, their runtime and energy consumption increase exponentially. Customized hardware accelerators, long used for specific mathematical operations, remain essential for managing modern applications' computational and power demands. Hardware accelerators can speed up complex computations by orders of magnitude, but their manual design and verification processes are often challenging and time-consuming. High-Level Synthesis (HLS) provides a solution by transforming high-level algorithm descriptions, typically written in C++ or SystemC, into synthesizable RTL suitable for hardware implementation. This approach reduces development time for RTL engineers while offering flexibility beyond what traditional handwritten RTL can provide. We extended this capability to the machine-learning domain with the open-source framework hls4ml, which allows neural networks trained in Python frameworks like Tensorflow or PyTorch to be synthesized into efficient hardware representations for the traditional FPGA and ASIC flows. This breakthrough addresses the growing need for reduced design turnaround and easy verification of ML hardware accelerators with low latency and power efficiency constraints. During this tutorial, we will demonstrate how Python complements HLS by simplifying the ML design process, bridging the gap between software and hardware development. Attendees will explore how we translate neural networks modeled in Python into fixed-point C++ models suitable for HLS workflows. We will dive into strategies like Value-Range Analysis and Quantization-Aware Training, which optimize these designs for deployment and evaluate their accuracy, power consumption, and energy efficiency. To exemplify these concepts, experts from Fermilab will share their experiences applying this technology to high-energy physics experiments, where real-time, low-latency processing is critical. Over the years, Fermilab engineers have demonstrated how deep neural networks, optimized for hardware using hls4ml, can meet the stringent requirements of trigger systems at the CERN Large Hadron Collider. These systems rely on rapid decision-making to process immense data volumes while retaining only the most relevant events for further analysis. The application of hls4ml has also been extended to innovative technologies like smart pixel arrays. These smart pixels integrate ML inference capabilities directly into sensor devices, enabling localized data processing at the pixel level. This approach drastically reduces the need to transmit raw data to external processing units, significantly decreasing power consumption and latency. By embedding neural networks within the pixel architecture, the smart pixels can identify and prioritize relevant data in real time, providing a highly efficient solution for edge computing in scenarios such as particle detectors and imaging systems. Fermilab's work highlights the potential of hardware-accelerated ML in scenarios where both speed and power efficiency are mission-critical. Through this tutorial, attendees will gain valuable insights into the challenges and solutions of deploying ML in hardware. Understanding how HLS and hls4ml streamline the development of neural network-based hardware accelerators is fundamental for the industry's future. Participants will learn how these technologies are shaping the future of AI and scientific computing.

Di Guglielmo, Giuseppe [Fermilab]↗
DOE OSTI2024

Developing multi-gene CRISPRa/i programs to accelerate DBTL cycles in ABF hosts engineered for chemical production

This project developed and implemented a modular CRISPR activation and interference (CRISPRa/i) platform to accelerate strain optimization and pathway development for industrially relevant microbial hosts. By integrating multiplexed transcriptional perturbation tools with data-driven Design–Build–Test–Learn (DBTL) workflows, the team achieved reductions in cycle time and enhanced production of industrial aromatics, particularly 4-aminocinnamic acid (4-ACA), in Pseudomonas putida. Key accomplishments included: ● Development of a robust, tunable CRISPRa/i system in P. putida that enabled efficient multi-target gene regulation via guide RNA (gRNA) programs ● Completion of two full DBTL cycles, guided by machine learning (ML) models trained on transcriptomic and performance data, reducing engineering time by over 30% ● Optimization of multi-gene regulatory programs to balance expression of host and pathway modules, improve 4-ACA titers, and resolve metabolic bottlenecks ● Demonstration of system portability through a limited proof-of-concept extension in Acinetobacter baylyi, underscoring the generalizability of the approach ● Evaluation of strain performance on lignocellulosic biomass-derived substrates, demonstrating the feasibility of converting renewable carbon into aromatic building blocks These results illustrate the feasibility of applying ML-guided CRISPRa/i perturbation strategies to accelerate strain development in complex microbial systems. The resulting tools and datasets contribute to DOE objectives by improving platform predictability, reducing development costs, and enabling broader access to sustainable, economically viable bioproduction technologies.

09 BIOMASS FUELS↗
DOE OSTI2026

Coupled CVD and Float Zone Reactor for Lower Cost, Higher Efficiency Si Boules (Final Technical Report)

This project modeled a new type of photovoltaic (PV) Si production reactor with the promise to reduce the cost, increase the efficiency, and reduce the energy required to manufacture Si wafers. The production of photovoltaic (PV) grade Si is well established, based on the pulling of single crystalline Si boules from polycrystalline Si created from trichlorosilane using the Siemens process. However, these processes are very energy intensive, and manufacturing of PV Si occurs almost entirely in China. To disrupt this paradigm and on-shore production of this critical material and provide benefits to the public, a substantial technological leap is required to move past incumbent technology. This study evaluated a new float zone chemical vapor deposition (Fz-CVD) concept in which trichlorosilane (TCS), the feedstock for polysilicon in the Siemens process, is injected directly into a float zone crystallizer to continuously deposit the feed rod for the boule pulling process through a combination of multiphysics modeling and technoeconomic analysis.

14 SOLAR ENERGY↗
DOE OSTI2024

Quantifying Investment Risk: Analysis of the Purchase Decision of a Nuclear Power Plant (Presentation)

Cost overruns are an ill-fated part of the deployment history of nuclear power plants (NPPs) in the United States, and yet studies increasingly show the important role nuclear technologies must play in decarbonizing the U.S. economy. Paradoxically, then, a key piece of a coherent decarbonization strategy depends on attracting investor action to a purchase where historical cost overruns have been sizable. To address this challenge, this study aims to develop a financial model that quantifies the risk of cost overruns in the decision-making process for purchasing advanced reactor concepts. Using the concept of value at risk (VaR), the model is built to evaluate financial risk nuclear construction with the aim to identify risk mitigation strategies. The objective is to identify strategies to mitigate cost-risk challenges and assess the potential reduction in investor risk exposure. This paper presents the initial development and preliminary verification of the financial risk analysis model. The development of this model involved a comprehensive approach to estimating financial risk over the operating life of NPP that stems from construction uncertainties. By utilizing net present value (NPV) with discounted cash flows, the model captures the complex interconnections of project costs, construction timelines, revenue, and uncertainties. Verifying the model involved testing historical data from previous reactor construction projects against the construction project of Vogtle 3 and 4. This paper’s results present the comparison of the preconstruction cost overrun prediction with the current cost estimates from a nearly complete Vogtle 3 and 4.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Quantifying Investment Risk: Analysis of the Purchase Decision of a Nuclear Power Plant

Cost overruns are an ill-fated part of the deployment history of nuclear power plants (NPPs) in the United States, and yet studies increasingly show the important role nuclear technologies must play in decarbonizing the U.S. economy. Paradoxically, then, a key piece of a coherent decarbonization strategy depends on attracting investor action to a purchase where historical cost overruns have been sizeable. To address this challenge, this study aims to develop a financial model that quantifies risk of cost overruns in the decision-making process for purchasing advanced reactor concepts. Using the concept of Value at Risk (VaR), the model is built to evaluate financial risk nuclear construction with the aim to identify risk mitigation strategies. The objective is to identify strategies to mitigate cost-risk challenges and to assess the potential reduction in investor risk exposure. The paper presents the initial development and preliminary verification of the financial risk analysis model. The development of this model involved a comprehensive approach to estimating financial risk over the operating life of NPP that stems from construction uncertainties. By utilizing net present value (NPV) with discounted cash flows, the model captures the complex interconnections of project costs, construction timelines, revenue, and uncertainties. Verification of the model involved testing historical data from previous reactor construction projects against the construction project of Vogtle 3 and 4. The results of this paper present the comparison of the preconstruction cost overrun prediction with the current cost estimates from a nearly complete Vogtle 3 and 4.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Hear It? – New Physics Calls For a Healthy Target!

Nowadays, when the attention of the physics community is drawn to muon collider prospects and neutrino projects, a target as the primary source of such exotic particles is a key component of a particle physics experiment. The extreme conditions placed on the target, though, decrease its functionality and threaten the future of high-power targetry. Subject to superb magnetic fields, extreme temperatures, and radiation damage, the target is constantly at risk of unexpected failures. The Target Health Monitor (THM) aims to enable the continuous analysis of the target state throughout the experiment. Based on the optical concept of Brewster s angle and the reflectivity variation with the compositional changes in the target material, the THM will record and evaluate the radiation-caused transmutations in the target to foresee its malfunction before it affects the experimental results. The first steps in validating our THM concept have been made this summer. Continuing reflectivity measurements of the prospective target materials, we anticipate proving the THM potential to monitor target health effectively.

Havryshchuk, Kateryna↗
DOE OSTI2025

Large Area Airborne Contamination Monitoring

The individual components of a Large Area Airborne Contamination Monitoring (LAACM) system have been demonstrated as functional and the concept of a low-cost, rapidly deployable, and rapidly expandable system has been validated. All components of a previously demonstrated system were re-evaluated. Based on this evaluation, recommendations were made for air collection equipment, scintillating material was synthesized and optimized for application, and improved images were acquired. A preliminary concept of operations was developed, outlining the need for an automated scintillation application system and software for data acquisition and analysis. The work conducted under this program in FY24 has raised the Technology Readiness Level (TRL) of the LAACM from TRL 3 to TRL 4.

Whiteside, Tad S. [Savannah River National Laborat↗
DOE OSTI2025

Analysis of pumped thermal energy storage using particle media integrated with concentrating solar power

Pumped Thermal Energy Storage (PTES) is an electricity storage system that converts electricity into thermal energy which is stored and later transformed back into electricity. Previous work has illustrated that particles have low capital costs and can be operated over a wide range of temperatures. PTES with particle storage achieves higher round-trip efficiency and specific power output than when molten salt thermal energy storage is used. This article explores hybrid systems that combine PTES with Concentrating Solar Power (CSP). Hybrid systems share the majority of components thereby reducing costs compared to two stand-alone devices. In addition, hybrid systems can provide multiple services (such as renewable power generation and electricity storage services). Using particle thermal storage in these hybrid concepts provides freedom in choosing the design conditions, since a wide range of operating temperatures is allowable, therefore making it possible to identify hybrid system designs that have good performance. In this article, two concepts for hybrid PTES-CSP are introduced. Thermodynamic models are developed and these are used to evaluate the performance of two hybrid systems. These models account for turbomachinery efficiency, and approach temperature and pressure loss in heat exchangers, as well as other sources of inefficiency, such as motor-generator losses, and air fan power. The “Solar Top-Up” Concept uses CSP to increase the temperature delivered by the charging heat pump. The discharging system uses a topping gas cycle and a bottoming steam cycle to fully exploit the available energy. Using solar heat to increase the maximum temperature from 750 K to 1100 K increases the round-trip efficiency from 41 % to 62 % and the specific work output from 88 kJ/kg to 301 kJ/kg. The second concept is a “Dual-Mode” device which provides both electricity storage and solar electricity generation with the same set of components. The PTES-mode and CSP-mode performance are optimized at different design values but careful parameter selection leads to good performance of both modes: one design produces PTES round-trip efficiency > 60 %, CSP heat engine efficiency > 40 %, and specific work outputs > 150 kJ/kg (for both cycles), when the particle receiver temperature is > 1200 K and maximum heat pump temperature is 1100 K.

14 SOLAR ENERGY↗
DOE OSTI2025

Thermal mechanical assessment of a SiC-SiC-composite clad fuel pin concept in a light water reactor environment

Accident Tolerant Fuels (ATFs) are designed to increase coping time following an accident scenario while preserving or improving current steady state reactor operational performance. A potential ATF concept is SiC-SiC composite claddings. Fuel performance simulations were conducted on a SiC-SiC based cladding concept utilizing a multilayered approach for improved performance. This cladding concept referred to as the Duplex concept is a duplex structure composed of a monolithic SiC layer placed on the outside of a SiC-SiC composite. A liquid metal is added to fuel-cladding gap for improved heat dissipation from the fuel. The monolithic SiC layer is used to improve the coolant corrosion characteristics and protect the SiC-SiC composite layer from exposure to the coolant. The fuel performance code BISON was used to conduct fuel performance simulations on the cladding concepts. Comparisons are made with a current prototypic fuel rod design (UO 2 fuel enclosed in Zircaloy-4 cladding). Representative steady-state cases were considered for normal power and two cycle power histories. Additionally, a PCI ramp case was simulated to analyze potential anticipated operational occurrences. Transient response during a Loss of Coolant Accident and a Reactivity Initiated Accident were also simulated. This computational study demonstrated that for normal operating conditions, the SiC concept cladding performed as well as the baseline for the standard power cases evaluated. The ramping evaluations indicate potential fracturing of the SiC-SiC composite of the composite cladding compared to the Zircaloy-4 cladding due to the temperature gradient and the subsequent differential thermal conductivity degradation and swelling across the composite thickness. In conclusion, the rod fails early at low enthalpy for RIA but survives a LOCA with minimal material loss due to high temperature steam corrosion.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Proceedings of the 2024 Advancing Chemical Safety and Security Education Symposium at the 27th IUPAC International Conference on Chemistry Education

The inaugural Advancing Chemical Safety and Security Education symposium was held at the 27th IUPAC International Conference on Chemistry Education (ICCE2024). Speakers showcased innovative strategies for seamlessly integrating security concepts into established safety programs, addressing specific needs of diverse academic institutions, and evaluating the effectiveness of different pedagogical approaches. Here, this proceedings publication encapsulates insights from 11 oral presentations, 12 poster presentations, and panel discussions including key recommendations for future advancements in educating chemical safety and security education for academic and industry audiences.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

HPDF Data Catalog and Lakehouse Demo Heuristic Evaluation and Roadshow Feedback Reports

The December 2025 roadshow gathered rapid feedback from community members on the proof of concept AmSC/HPDF data lakehouse and catalog solution 1. This provided the opportunity to demonstrate our current state of progress and gather input on workflows and AI agents. We recognize that the proofs of concept interfaces (OpenMetadata and Goose) are not intended for our end users so we have captured feedback to keep in mind as additional technical and conceptual design work is undertaken.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Hardware-in-Loop Modules for Testing Automated Ventilator Controllers

Automated ventilator controllers have the potential to simplify oxygen and carbon dioxide management for trauma. In the pre-hospital or military medicine environment, trauma care can be required for prolonged periods by personnel with limited ventilator management training. As such, there is a need for closed-loop control systems that can adapt ventilator management to a complex, ever-changing medical environment. Here, we present a novel hardware-in-loop test platform for the independent troubleshooting and evaluation of oxygen and carbon dioxide automated ventilator management capabilities. The oxygen management system provides an analogue blood oxygen signal that is responsive to the fraction of inspired oxygen and the peak inspiratory pressure ventilator settings. A tested oxygenation controller successfully reached the target oxygen saturation within 5 min. The carbon dioxide removal system integrates with commercial ventilator technology and mimics carbon dioxide generation, lung compliance, and airway resistance while providing an end-tidal carbon dioxide level that is responsive to changes in the tidal volume and respiratory rate settings. A test mechanical ventilator controller was able to regulate EtCO2 regardless of the starting value within 10 min. This highlights the system’s functionality and provides proof-of-concept demonstrations for how the hardware-in-loop test platforms can be used for evaluating closed-loop controller technologies.

Berard, David (ORCID:0000000322863846)↗
DOE OSTI2025

Accelerating Resilience of the Community through Holistic Engagement and use of Renewables (ARCHER) Planning Framework

The primary objective of the Accelerating Resilience of the Community through Holistic Engagement and Use of Renewables (ARCHER) initiative was to identify and incorporate the unique variations in energy burden, social vulnerability, living conditions, and access to essential services that differ across communities. By accounting for these localized factors—down to the neighborhood level—the project supports more targeted and effective investments in community resilience. The framework seeks to establish practical planning guidance, methods, and performance measures for community energy resilience, integrate community-level and electric utility system resilience planning, and assess its effectiveness through comparison with conventional and operational planning approaches. A key component of the project was its data exchange platform, which is used to evaluate and demonstrate the tools, methodologies, and planning approaches developed through ARCHER. This open-source platform enables developers and vendors of distribution and outage management systems to build upon the research by incorporating its concepts into their own tools and workflows. This capability is enabled by the transparent availability of data, functional requirements, and the underlying information model. The project yielded several important insights. First, meaningful engagement with communities is essential to achieving comprehensive resilience outcomes. Second, resilience planning is most effective when electric grid considerations and broader community needs are addressed in a coordinated manner. Third, the use of platforms that allow for real-time input from communities can enhance utility responsiveness during restoration activities. Fourth, a structured and systematic planning approach can successfully translate ARCHER concepts into practice. Fifth, the development of an integrated metric that reflects both grid performance and community impacts provides a more holistic basis for evaluating resilience. Finally, incorporating community engagement and equity considerations into grid operations is critical, particularly during severe weather events that result in extended outages.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Initial Design Curves for Alloy 709 for an Improved Creep-fatigue Design Method

Creep-fatigue (CF) interaction damage is the primary damage mode for high-temperature structural components subjected to cyclic loading. Over the past several decades, researchers within the American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel Code (BPVC), Section III, Division 5, have focused on developing elevated temperature code rules to ensure conservative structural designs that mitigate CF failure in high-temperature reactors. The existing CF evaluation methodologies in the Code are based on the creep and fatigue damage diagram approach, which is complex and often excessively conservative. The alternative CF evaluation approach proposed here is intended to significantly simplify the evaluation procedure while reducing conservatism in high-temperature component design analysis. This alternative CF evaluation method integrates the elastic–perfectly plastic (EPP) analysis approach with the simplified model test (SMT) CF design concept, leveraging the advantages of both methods. This report presents the preliminary analysis and the approach for developing CF design curves for Alloy 709, utilizing fatigue and CF data generated for the 100,000-hr Code Case to support its qualification to ASME Section III, Division 5 for Class A construction of high temperature reactors. This study is to support the incorporation of Alloy 709 in this alternative CF evaluation method. Recommendations for the remaining work needed to complete the effort are also provided.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Hydrodynamic characterization of the coastal pioneer array ocean observing system

Ocean observation buoys require relatively small amounts of power, yet traditionally necessitate costly resupply trips for battery replacement. With the offshore location of the buoys and small power requirements, wave energy may be an effective solution for providing consistent and reliable power to support the buoy instrumentation. The US National Science Foundation Ocean Observatories Initiative (OOI) includes arrays of point absorber-like buoy systems used for ocean observation that have been deployed at multiple locations including the Southern Mid-Atlantic Bight. A study is currently underway to design a pitch resonator wave energy converter to supplement existing renewable energy generation for powering observation instrumentation. This paper details field measurements from surface moorings of the OOI Coastal Pioneer Array, which informs the subsequent development of a numerical model for the moored observation system. The model is developed in Wave Energy Converter Simulator (WEC-Sim), which leverages the Simscape multibody solver within the MATLAB/Simulink framework and linear potential flow theory to simulate the hydrodynamic interactions and multibody dynamics in 6 degrees of freedom. Multiple tuning variables are considered to produce a model for the system that matches well with empirical data (about 8% error). In conclusion, the WEC-Sim model will serve as a platform for integrating the pitch resonator wave energy converter concept and deployment preparation (detailed design including power take-off and control systems, response evaluation, etc.).

hydrodynamic modeling↗
DOE OSTI2025

Compatibility of Zircaloy-4 in eutectic PbSn and PbBiSn liquid metals

Here, a novel nuclear fuel concept has been proposed, consisting of UO₂ particles suspended in a liquid metal alloy. To evaluate its feasibility, the compatibility of Zircaloy-4 cladding with candidate eutectic PbSn and PbBiSn alloys—as well as with pure Pb, Bi, and Sn—was investigated through 1000-hour exposures at 400 °C and 600 °C. Severe degradation of the Zircaloy-4 specimens was observed in eutectic PbSn at 600 °C, whereas oxidation and oxygen diffusion were evident after exposure at 400 °C. At 600 °C, the formation of Zr₃Fe precipitates at the oxide–alloy interface was identified in specimens exposed to Pb and PbBiSn. Thermodynamic analysis suggested that the observed intermetallic formation resulted from the destabilization of Laves phases due to oxygen ingress at elevated temperatures.

Bismuth↗