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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Final report on assessment of molten salt corrosion testing of unirradiated and ion irradiated advanced manufactured high entropy alloys

Generation IV reactors and future fusion reactor designs have led to more demanding materials performance requirements due to their increased operating temperatures, corrosive coolants, and increased radiation doses compared to the current light-water reactor fleet. Among the innovative nuclear technologies under development, molten salt reactors stand out for their potential to offer superior fuel utilization, intrinsic safety characteristics, and economic viability. Of the proposed Generation IV designs, the gas fast reactor operates at 450 to 850°C and the molten salt reactor operates at 565 to 850°C, with the molten salt reactor design needing molten salt corrosion resistant materials [1, 2]. These increased temperatures and more extreme corrosion environments necessitate higher material performance, such as creep strength, radiation-tolerant microstructures, corrosion resistance, and high-temperature tensile properties. Hastelloy-N, a nickel-based alloy with additions of molybdenum and chromium, has been successfully employed to contain molten fluoride salt at temperatures up to 705°C. However, Hastelloy-N becomes embrittled upon neutron irradiation, primarily due to the accumulation of helium produced by (n,a) transmutation reactions. Furthermore, the corrosive nature of molten fluoride and chloride salts presents a formidable challenge, as these salts can react with and dissolve alloying elements such as Cr, Mo, and Fe, leading to selective leaching, loss of protective oxide layers, and accelerated degradation. High entropy alloys (HEAs) and refractory high entropy alloys (RHEAs) have emerged as a prominent area of interest, due to their ability to achieve tailored chemical compositions for specific applications. Unlike conventional alloys, HEAs are characterized by having multiple principal elements in equimolar or near equimolar ratios, leading to an unconventional alloying strategy [3]. This alloying strategy is believed to promote unique properties, such as single-phase stabilization of chemically compatible elements, lattice distortion effects due to atomic radius differences, and proposed sluggish diffusion effects. For extreme-environment applications, RHEAs have garnered much research interest because of the possibility of creating relatively ductile materials that can operate in extremely high-temperature environments, beyond the operating temperatures where other Ni-based superalloys begin to lose strength [4-6]. Idaho National Laboratory (INL) initiated a joint international effort with the Czech Republic to explore the feasibility of manufacturing HEAs for high-temperature nuclear applications using advanced manufacturing. This effort was funded at INL by the United States Department of Energy's Office of Nuclear Energy under the Advanced Reactor Technologies and Advanced Materials and Manufacturing Technologies (AMMT) Program. The HEAs were specifically designed for the corrosive and irradiation environments experienced in gas-cooled fast reactors, molten salt reactors, and fusion power. These alloys have been manufactured by multiple processes to determine the impact of manufacturing processes on the performance of the alloys in corrosive and irradiation environments. Preliminary molten salt corrosion testing showed that equimolar MoNbTiV and MoNbTi alloys exhibit exceptional performance, with arc-melted variants demonstrating only minimal degradation after 1000 hours of exposure to molten chloride salt at 700°C. Conversely, Nb2TiVZr2 showed significant molten salt corrosion susceptibility and microstructural instability during high-temperature molten salt exposures, and was, therefore deemed unfit for molten salt reactor applications. The MoNbTiV, MoNbTi, and Nb2TiVZr2 alloys were further evaluated through ion irradiation experiments conducted at the Michigan Ion Beam Laboratory at the University of Michigan. The microstructural stability and the evolution of irradiation-induced defects were characterized to assess the irradiation resistance of each of these alloys.

36 - MATERIALS SCIENCE↗
DOE OSTI2025

A Sensitive Electrochemical Cholinesterase-Inhibiting Biosensor for Organophosphorus Pesticides Based on Ti 3 C 2 TX MXene Quantum Dots

Organophosphorus pesticides (OPs) pose significant environmental and health risks due to their widespread use and toxicity, primarily by inhibiting acetylcholinesterase. Traditional detection methods are often slow and costly, highlighting the urgent need for advanced, sensitive, and accessible technologies. This study developed a highly sensitive electrochemical cholinesterase-inhibiting biosensor for OP pesticides, utilizing Ti 3 C 2 T x MXene Quantum Dots (MQDs), which was synthesized via a hydrothermal method. The biosensor’s performance was characterized using electrochemical impedance spectroscopy, differential pulse voltammetry (DPV), and cyclic voltammetry. DPV proved to be the optimal technique, exhibiting an ultralow detection limit of 1 × 10 −17 M and a wide linear range (10 −14 –10 −8 M) for chlorpyrifos (a model OP) with an estimated inhibition constant of 62 nM. The biosensor demonstrated high selectivity for OPs (chlorpyrifos, acephate, glyphosate) over a non-target pyrethroid (permethrin), confirmed by distinct electrochemical signatures and compared to in vitro cholinergic activity assays in bean beetle homogenates. The enhanced performance is attributed to the high surface-to-volume ratio, quantum confinement effects, and superior conductivity of the MQDs, as well as the robust enzyme immobilization facilitated by glutaraldehyde cross-linking and a chitosan matrix. This work presents a promising platform for rapid, sensitive, and selective detection of OP pesticides, with potential applications in environmental monitoring and public health protection.

Chemistry↗
DOE OSTI2026

High-Torque Heavy-Rare-Earth-Free Electric Motor Thermal Management

This project is part of a multi-lab Next-Generation Reliable Electric Drive Systems for Medium and Heavy-Duty Vehicles (NEXT-DRIVE) project led by Oak Ridge National Laboratory (ORNL), and including NREL, Sandia National Laboratories (SNL), and Ames Laboratory that leverages research expertise and facilities of these national labs to develop tools and approaches for reducing the design and development time of new electric drive technologies for medium and heavy-duty vehicles (MHDVs) and their associated costs while increasing reliability and asset utilization. The Next-Drive project aligns with the DOE's goals by introducing high-fidelity multi-physics and AI/ML-based modeling to design low-cost, highly reliable, and longer-lifetime drivetrains, aiming to achieve 25 years of progress in 5 years. The efforts of this project will focus on NEXT-DRIVE Task 4 (led by ORNL, NREL, and AMES) - developing high-fidelity modeling framework and identifying technologies enabling heavy-rare-earth-free electric motors for medium- and heavy-duty vehicles to achieve 1 million miles of operation. Contrary to conventional approaches that optimize the motor for power density, the focus will be to identify motor designs that achieve the best trade-off between motor power density and durable operation. NREL tasks include development of high-fidelity motor thermal models incorporating rotor windage losses and identification, evaluation and measurement of motor interface materials in key thermal pathways. The poster summarizes NREL's accomplishments for the first half of FY 2025 and outlines future plans.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Electricity Rate Designs for Large Loads: Evolving Practices and Opportunities

Electricity demand from large load customers such as data centers is projected to grow significantly in the near term. While data centers play an important role in advancing technology innovation and economic growth in the United States, data center energy needs present challenges and opportunities for electricity supply and infrastructure. This technical brief serves as a foundation for the discussion of issues and sharing of perspectives among utilities, regulators, large load customers, and other stakeholders. As utilities and regulators explore rate structures to address growing data center electricity demand, several issues have emerged: -Fair allocation of electricity system costs to large-load customers without unfair shifting of costs to other customers -Appropriate mitigation of the financial risks associated with stranded assets from underutilized utility system investments -Mitigation of operational and resource adequacy risks if electricity demand exceeds supply -Appropriate risk-sharing in commercializing newer electricity technologies such as advanced geothermal, small modular reactors, and long duration energy storage -Accommodating the diverse needs of large-load customers, such as having the option to match electricity consumption with output from carbon-free resources or using onsite generation to provide system capacity The technical brief also identifies key design elements that aim to address these issues and uses leading examples from pending and approved rate structures, agreements, and special contracts to ground the elements in practice.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Offshore Wind Market Report: 2024 Edition

The Offshore Wind Market Report: 2024 Edition provides detailed information on the U.S. and global offshore wind energy industries to inform policymakers, researchers, and analysts about technology, economic, and market trends. The report provides the status of more than 322 operating offshore wind energy projects in the global fleet through Dec. 31, 2023, as well as the broader global pipeline of projects in various development stages. To provide current information and discussion on the emerging offshore wind industry in the United States, this report tracks significant U.S. domestic progress and events from Jan. 1, 2023, to May 31, 2024.

17 WIND ENERGY↗
DOE OSTI2024

Performance of a Drifting Acoustic Instrumentation SYstem (DAISY) for characterizing radiated noise from marine energy converters

Marine energy converters can generate electricity from energetic ocean waves and water currents. Because sound is extensively used by marine animals, the radiated noise from these systems is of regulatory interest. However, the energetic nature of these locations poses challenges for performing accurate passive acoustic measurements, particularly with stationary platforms. The Drifting Acoustic Instrumentation SYstem (DAISY) is a modular hydrophone recording system purpose-built for marine energy environments. Using a flow shield in currents and mass–spring–damper suspension system in waves, we demonstrate that DAISYs can effectively minimize the masking effect of flow noise at frequencies down to 10 Hz. In addition, we show that groups of DAISYs can utilize time-delay-of-arrival post-processing to attribute radiated noise to a specific source. Consequently, DAISYs can rapidly measure radiated noise at all frequencies of interest for prototype marine energy converters. Furthermore, the resulting information from future operational deployments should support regulatory decision-making and allow technology developers to make design adjustments that minimize the potential for acoustic impacts as their systems are scaled up for utility-scale power generation.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Recent Experience with the CMS Data Management System

The CMS[1] experiment manages a large-scale data infrastructure, currently handling over 200 PB of disk and 500 PB of tape storage and transferring more than 1 PB of data per day on average between various WLCG[2] sites. Utilizing Rucio[3] for high-level data management, FTS[4] for data transfers, and a variety of storage and network technologies at the sites, CMS confronts inevitable challenges due to the system’s growing scale and evolving nature. Key challenges include managing transfer and storage failures, optimizing data distribution across different storages based on production and analysis needs, implementing necessary technology upgrades and migrations, and efficiently handling user requests. The data management team has established comprehensive monitoring to supervise this system and has successfully addressed many of these challenges. The team’s efforts aim to ensure data availability and protection, minimize failures and manual interventions, maximize transfer throughput and resource utilization, and provide reliable user support. This paper details the operational experience of CMS with its data management system in recent years, focusing on the encountered challenges, the effective strategies employed to overcome them and the ongoing challenges as we prepare for future demands.

Öztürk, Hasan [CERN]↗
DOE OSTI2025

Evaluation of additive manufacturing side channels for nuclear nonproliferation applications

The nuclear industry is continuing to grow and adopt new technologies to manufacture components. One of the technologies under consideration is additive manufacturing (AM). AM could make production of components at lower cost and could lessen lead times significantly. However, AM could be prone to proliferation risks. AM machines give off signatures during the manufacturing process, and these signatures offer an alternative means of observing the component. Correlations between these signatures and the geometry being manufactured could be developed; enabling proliferators as they could take advantage of these correlations to steal AM manufacturing instructions relating to nuclear technology. This work pertains to preliminary work exploring the feasibility of tapping into AM side channels to predict geometries being manufactured on AM machines. The feasibility of utilizing vibration to draw geometric correlations will be assessed on an Ultimaker 2 + thermoplastic 3D printer.

Additive manufacturing↗
DOE OSTI2023

Challenges and Prospects of Sodium‐Ion and Potassium‐Ion Batteries for Mass Production

The exponential growth of the lithium‐ion (LIB) market is causing a significant disparity between the supply chain and demand for its resources. In this regard, sodium‐ion and potassium‐ion batteries are promising alternatives to LIBs due to their low cost. However, the larger sizes of Na + and K + ions create challenges that prevent them from achieving energy densities comparable to LIBs while maintaining an acceptable cycle life. Here, in this perspective, the aim is to evaluate the status of Na‐ion and K‐ion batteries and the challenges associated with them on both fundamental and commercial levels. The focus is on the structural instability arising from phase transitions during cycling, intricate chemical degradation processes, and potential avenues for enhancing their performance with a specific goal of improving their viability for grid‐scale energy storage. Materials production and abundance limitations for the chemistries of the state‐of‐the‐art materials and account for critical parameters from both the perspective of researchers and investors are analyzed. This analysis aims to provide insights into the strategic trade‐offs required to effectively implement the technology in real‐world applications, such as grid‐scale storage and other areas. Furthermore, the utilization of metals with low or no supply‐chain problems as an important aspect of these trade‐offs is considered.

25 ENERGY STORAGE↗
DOE OSTI2025

Identifying preferential flow from soil moisture time series: Review of methodologies

Abstract Identifying and quantifying preferential flow (PF) through soil—the rapid movement of water through spatially distinct pathways in the subsurface—is vital to understanding how the hydrologic cycle responds to climate, land cover, and anthropogenic changes. In recent decades, methods have been developed that use measured soil moisture time series to identify PF. Because they allow for continuous monitoring and are relatively easy to implement, these methods have become an important tool for recognizing when, where, and under what conditions PF occurs. The methods seek to identify a pattern or quantification that indicates the occurrence of PF. Most commonly, the chosen signature is either (1) a nonsequential response to infiltrated water, in which soil moisture responses do not occur in order of shallowest to deepest, or (2) a velocity criterion, in which newly infiltrated water is detected at depth earlier than is possible by nonpreferential flow processes. Alternative signatures have also been developed that have certain advantages but are less commonly utilized. Choosing among these possible signatures requires attention to their pertinent characteristics, including susceptibility to errors, possible bias toward false negatives or false positives, reliance on subjective judgments, and possible requirements for additional types of data. We review 77 studies that have applied such methods to highlight important information for readers who want to identify PF from soil moisture data and to inform those who aim to develop new methods or improve existing ones. Core Ideas Soil moisture data can be used to identify the occurrence of preferential flow (PF) and its initiating conditions. Various data‐analysis methods to identify PF differ in susceptibility to error, bias, and subjectivity. These methods can utilize vast amounts of data from soil moisture monitoring networks to develop understanding of when, where, and under what conditions PF occurs. Newly developed methods may lead to better accuracy and reliability, and reduce the need for subjective judgments. Plain Language Summary Preferential flow through soil occurs when a large amount of water is suddenly available, as during an intense storm. This type of flow moves rapidly through the soil in distinct narrow pathways rather than moving evenly throughout the body of soil, with major consequences for groundwater resources, ecosystems, spreading of contaminants, and other vital concerns. Methods of detecting preferential flow have been developed that utilize measurements of soil water content made by sensors installed at various depths. This measurement technology has been widely implemented, many locations now having datasets years in length, and various methods have been developed for using these to identify preferential flow. The various methods are based on different features in the soil moisture records and vary in their advantages and shortcomings. In this review, we explain and evaluate these methods, highlighting important information for their implementation to identify preferential flow from soil moisture data and for efforts to develop new methods or improve existing ones.

Nimmo, John R↗
DOE OSTI2024

First-Principles Study on the Role of Cu and Cl-Based Dopants in NiO

Utilization of wide band gap oxide-based materials in thin-film solar energy technologies has increased in recent years. Among the numerous candidate oxide materials, NiO has shown many desirable optoelectronic properties that are applicable to thin-film PV technologies such as cadmium telluride PV. However, one critical factor requiring further investigation is the p-type doping behavior of NiO, specifically when the cadmium telluride solar cell undergoes conventional processes such as copper doping and chlorine-based activation treatment. The previous literature has shown a large degree of variability in hole concentrations in NiO when copper is used as the primary dopant. This study uses first-principles computational modeling based on density functional theory coupled with defect equilibria calculations to quantitatively explore the role of copper and chlorine-based extrinsic dopants in the p-type doping activity of NiO. The study reveals the importance of extrinsic dopants and their binding interactions with nickel vacancies to effectively p-dope NiO. It is suggested that both the formation of V Ni + Cu Ni and V Ni + Cl O defect pairs under a supersaturated state of NiO are potential mechanisms for increasing hole densities. On the other hand, the production of 2Cu Ni severely limits the effectiveness of p-doping in NiO, even in the presence of the aforementioned defect pairs. Furthermore, the study provides a guideline for experimentalists interested in using copper or chlorine species to understand how to controllably p-dope NiO during thin-film synthesis.

chlorine↗
DOE OSTI2025

Ultrahigh-power-density flexible piezoelectric energy harvester based on freestanding ferroelectric oxide thin films

Flexible piezoelectric nanogenerators are emerging as a promising solution for powering next-generation flexible electronics by converting mechanical energy into electrical energy. However, traditional ferroelectric ceramics, despite their excellent piezoelectric properties, lack flexibility; while piezoelectric polymers, although highly flexible, have low piezoelectricity. The quest to develop materials that combine high piezoelectricity with exceptional flexibility has thus become a research focus. Herein, we present a breakthrough in this field with the fabrication of freestanding (111)-oriented PbZr 0.52 Ti 0.48 O 3 single crystalline thin films, which exhibit remarkable flexibility and a high converse piezoelectric coefficient (~585 pm/V). This is achieved through water-soluble sacrificial layer to relieve substrate clamping and controlling the crystal orientation to further enhance the piezoelectric response. Our nanogenerators, constructed using these freestanding nanoscale membranes, demonstrate a record-high output power density (~63.5 mW/cm 3 ), excellent flexibility (with a strain tolerance >3.4%), and superior mechanical stability in cycling tests (>60,000 cycles). These advancements pave the way for high-performance, flexible electronic devices utilizing ferroelectric oxide thin films.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Advanced Oxygen-Free Electrolyzer for Ultra-Low-Cost H 2 Storage for Fossil Plants (Final Technical Report)

DOE’s Office of Fossil Energy and Carbon Management has determined that long-duration energy storage solutions co-located with fossil energy assets offer significant benefits to the fossil industry, electric utilities, and customers. T2M Global has developed an Advanced O 2 -Free Electrolyzer System (AES) Technology for low-cost, long-duration H 2 energy storage for fossil plants. The MW-class AES Module conceptual design aims to upgrade stranded assets (dilute/waste syngas streams, excess electricity, and waste heat) at fossil plants to higher value H 2 for additional revenue and greater sustainability. The H 2 energy storage equips fossil plants with the load following capability needed for the lucrative grid-support services market created by Variable Renewable Energy resources.

08 HYDROGEN↗
DOE OSTI2024

Characterization Inform Sustainable Recovery of Critical Minerals from Fossil Energy Waste Feedstocks

Rare earth elements (REE) and other critical minerals (CM, e.g., Co, Ni, Li) have important uses in green energy and modern technologies, yet are vulnerable to potential supply chain disruptions. One potential domestic CM source is fossil energy wastes, such as acid mine drainage (AMD) and treatment solids (AMD solids), coal combustion ash, and Oil and Gas (O&G) drilling wastes (drill cuttings and produced waters). While they can contain lower CM concentrations then traditional ore, the quantity and fast availability as waste feedstock makes them a promising CM resource. To explore their promise, researchers at DOE’s National Energy Technology Laboratory (NETL) have collected and analyzed CM data for aforementioned fossil energy wastes, and utilized advanced geochemical characterization (e.g., synchrotron microprobe and sequential extraction) to identify the CM speciation and binding environments, and developed sustainable and targeted CM recovery. Successful examples include: (1) the discovery of easily mobile REE phases in Ca-rich coal combustion ash and developing a patented REE recovery process from Ca-rich Powder River Basin coal ash; (2) the successful identification of REE/Co/Ni/Zn hosting phases in acid mine drainage treatment solids (AMD solids) with diverse chemical composition (Al, Mn, or Fe-rich) informing the sequential recovery of different REE/CMs from AMD solids; (3) the recovery potential of Li and other CMs in O&G produced waters and drill cuttings. The innovations driven by characterization have the potential to offset the cost of waste management and wastewater treatments while reducing the cost and environmental footprint of CM extraction.

Stuckman, Mengling↗
DOE OSTI2025

Electrical Validation Testing for ORPC MHK Generator, Modification 6: ORPC SBV for MHK Generator System (CRADA Final Report)

For the U.S. Department of Energy’s (DOE) 2016 Small Business Voucher for Marine and Hydrokinetic (MHK) System, Second Round 2016, ORPC intends to work with the National Renewable Energy Laboratory (NREL) to perform dynamometer testing of the MHK generator systems and its associated controls and inverters. ORPC will provide the generator, variable frequency drives (VFD), controls, and inverter for this testing. NREL will utilize the NREL Energy Systems Integration Facility (ESIF) and dynamometer facilities at the National Wind Technology Center (NWTC) for this work. Modification 6: Additionally, NREL will conduct a feasibility study for implementing passive DC rectification at the turbine.

17 WIND ENERGY↗
DOE OSTI2026

Cost Analysis of Heavy-Duty Vehicle Proton Exchange Membrane Fuel Cell Stationary Power Plants

Heavy-duty PEM fuel cells could be a low-cost, low emission alternative to combustion turbines for re-electrifying hydrogen if used as part of a long duration grid energy storage systems. Many studies expect heavy duty PEM fuel cell production costs to reduce as manufacturing volumes ramp up and their expected durability of 25,000-30,000 hours aligns well with a 30-year life for hydrogen seasonal energy storage plants that would likely operate less than 10% of the year. The labor, material, and equipment costs associated with installing PEM fuel cells and their required balance of plant for stationary applications have not been thoroughly explored, however. This study performs a detailed design and cost analysis of a 100 MW stationary PEM fuel cell power plant, capturing costs such as cooling, power electronics, pipes, valves, fittings, cabling, conduit, concrete foundations, buildings, and land. It employs methods consistent with NLR's solar PV benchmarking cost analysis and annual technology baseline to derive the total installed costs of stationary PEM fuel cell plants that utilize heavy duty PEM fuel cells.

08 HYDROGEN↗
DOE OSTI2025

Transformers and Long Short-Term Memory Transfer Learning for GenIV Reactor Temperature Time Series Forecasting

Automated monitoring of the coolant temperature can enable autonomous operation of generation IV reactors (GenIV), thus reducing their operating and maintenance costs. Automation can be accomplished with machine learning (ML) models trained on historical sensor data. However, the performance of ML usually depends on the availability of large amount of training data, which is difficult to obtain for GenIV, as this technology is still under development. We propose the use of transfer learning (TL), which involves utilizing knowledge across different domains, to compensate for this lack of training data. TL can be used to create pre-trained ML models with data from small-scale research facilities, which can then be fine-tuned to monitor GenIV reactors. In this work, we develop pre-trained Transformer and long short-term memory (LSTM) networks by training them on temperature measurements from thermal hydraulic flow loops operating with water and Galinstan fluids at room temperature at Argonne National Laboratory. The pre-trained models are then fine-tuned and re-trained with minimal additional data to perform predictions of the time series of high temperature measurements obtained from the Engineering Test Unit (ETU) at Kairos Power. The performance of the LSTM and Transformer networks is investigated by varying the size of the lookback window and forecast horizon. The results of this study show that LSTM networks have lower prediction errors than Transformers, but LSTM errors increase more rapidly with increasing lookback window size and forecast horizon compared to the Transformer errors.

LSTM↗
DOE OSTI2026

Advanced Facility Design and AI/ML Enabled Safeguards to Establish Secure, Economical Recycling of Fast Reactor Fuels (Final Scientific/Technical Report)

The project, "Advanced Facility Design and AI/ML Enabled Safeguards to Establish Secure, Economical Recycling of Fast Reactor Fuels," represents a significant advancement in nuclear fuel recycling technology. It integrates cutting-edge multimodal sensor fusion, machine learning (ML), and digital twin (DT) technologies to address challenges in material safeguarding, process optimization, and regulatory compliance for pyroprocessing facilities. This research has significantly enhanced the understanding of pyrochemical fuel recycling processes by developing innovative tools and methodologies. The Multimodal Safeguards Monitoring Unit (MSMU) combines electroanalytical techniques, Raman spectroscopy, and differential thermal analysis (DTA) to enable high-fidelity, near-real-time material accountancy measurements. Machine learning techniques, such as Long Short-Term Memory (LSTM) autoencoders, are utilized to detect anomalies in material balances and sensor data, improving the reliability of safeguards monitoring. Additionally, digital twin technology has been established to provide real-time system-level monitoring and diagnostics, integrating physics-based models with sensor data to optimize process safety and efficiency.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗