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At least 307 records · Page 17

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DOE OSTI2022

Repurposing Fossil-Fueled Assets For Energy Storage

The annual retirement of U.S. coal-fired electricity generation units (CF-EGU) is at an all-time high and is expected to continue. This loss of reliable baseload generation, combined with predicted growth of variable renewable energy (VRE) generation, is expected to stress grid reliability as the number of load-following resources drops below the experienced load variability. Many regions are already experiencing challenges, and fossil retirement-related warnings by the North American Electric Reliability Corp. are becoming more dire. All CF-EGU retirements pose significant challenges to asset owners, local workforces, and their communities. Repurposing a retiring CF-EGU as a long-duration energy storage plant can address these challenges and offer a suite of additional benefits to asset owners, the grid, and society. This project performed a techno-economic evaluation and assessment of repurposing a Duke Energy fossil-fueled asset (in particular, a coal plant) into an energy storage system by integrating the retiring asset with a Malta long duration Pumped Heat Energy Storage (PHES) system. The project validated the technoeconomic benefits of repurposing retiring coal plants into long-duration energy storage using Malta’s PHES. Key findings for this project are summarized below: (1) Technical: (a) Retiring coal plants (and other steam turbine fossil generation) can be repurposed to enable the clean energy transition using Malta’s technology. (b) For older retiring coal plants, repurposing the site and electrical interconnection for a standalone PHES plant is the most economically favorable option. (c) For newer coal plants where there is also a local peaking capacity need, repowering the steam cycle into a hybrid integration with PHES is attractive. (d) A process was developed to assist fossil generation owners in choosing the best path for each plant’s circumstances. (2) Economic (a) Communities facing economic challenges caused by the retirement of fossil generation would benefit from repurposing the plant as long-duration energy storage using Malta’s PHES. (b) On a $/MW basis, repowering retiring coal units into Malta PHES plants can maintain the same number and types of jobs and economic activity. (c) For a 70% carbon reduction scenario, a 10-hour Malta PHES plant is more economic for the asset owner than similar-power 4-hour batteries. This project showed that repurposing a retiring coal unit into thermal energy storage, by integrating it with a Malta PHES system, makes techno-economic sense. At least two integration options are available, with the optimal solution depending on the coal plant and its location. Repurposing retiring coal plant into energy storage results in economic benefits for the plant owner and local communities.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2024

High-pressure phase transition in 3-D printed nanolamellar high-entropy alloy by imaging and simulation insights

Abstract We report on the high-resolution imaging and molecular dynamics simulations of a 3D-printed eutectic high-entropy alloy (EHEA) Ni 40 Co 20 Fe 10 Cr 10 Al 18 W 2 consisting of nanolamellar BCC and FCC phases. The direct lattice imaging of 3D-printed samples shows the Kurdjumov–Sachs (K–S) orientation relation {111} FCC parallel to {110} BCC planes in the dual-phase lamellae. Unlike traditional iron and steels, this alloy shows an irreversible BCC-to-FCC phase transformation under high pressures. The nanolamellar morphology is maintained after pressure cycling to 30 GPa, and nano-diffraction studies show both layers to be in the FCC phase. The chemical compositions of the dual-phase lamellae after pressure recovery remain unchanged, suggesting a diffusion-less BCC–FCC transformation in this EHEA. The lattice imaging of the pressure-recovered sample does not show any specific orientation relation between the two resulting FCC phases, indicating that many grain orientations are produced during the BCC–FCC phase transformation. Molecular dynamics simulations on phase transformation in a nanolamellar BCC/FCC in K–S orientation show that phase transformation from BCC to FCC is completed under high pressures, and the FCC phase is retained on decompression aided by the stable interfaces. Our work elucidates the irreversible phase transformation under static compression, providing an understanding of the orientation relationships in 3-D printed EHEA under high pressures.

3-D Printing↗

DOE OSTI2020

Wireless Sensor Modalities at a Nuclear Plant Site to Collect Vibration Data

One of the major contributors to the total operating costs of domestic nuclear fleet of reactors today is the operation and maintenance (O&M) costs. These include labor-intense preventive maintenance programs involving manually-performed inspection, calibration, testing, and maintenance of plant assets at periodic frequency and time-based replacement of assets at periodic frequency, irrespective of their conditions. This has resulted in a labor-centric business model to achieve high capacity factors. To build an optimal maintenance program, it’s time to transition from this labor-centric business model to a technology-centric business model. Fortunately, there are technologies (advanced sensor, data analytics, and risk assessment methodologies) that will support this transition. The technology-centric business model will result in significant plant life extension and reduction of time-based maintenance activities. This will drive down O&M costs as labor is a rising cost and technology is a declining cost. This approach will lay the foundation for real-time condition assessment of plant assets, allowing condition-based maintenance to enhance plant safety, reliability, and economics of operation. The goal of this project is to address challenges in the area of digital monitoring, i.e., the application of advanced sensor technologies (particularly wireless sensor technologies) and science-based data analytic capabilities to advance online monitoring and predictive maintenance in nuclear plants to improve plant performance (efficiency gain and economic competitiveness). To achieve the project goal, in partnership with Exelon Generating Company (Exelon), researchers from Idaho National Laboratory (INL) and Oak Ridge National Laboratory (ORNL) are performing research and development (R&D) to demonstrate application of wireless sensors using the distributed antenna system and advanced data analytics to achieve predictive maintenance. In the report, wireless vibration sensors, vibration data and its indicator are described. The wireless vibration sensors presented in this report support three types of wireless communication, namely, Wi-Fi, cellular, and 900 MHz. These wireless vibration sensors are considered by partner plant site for installation on plant asset to enable online vibration monitoring to replace periodic measurements. These vibration data along with other plant process data will be utilized to develop diagnostic and prognostic models.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

The Reductive Leaching of Chalcopyrite by Chromium(II) Chloride for the Rapid and Complete Extraction of Copper

A hydrometallurgical process is developed to lower the costs of copper production and thereby sustain the use of copper throughout the global transition to renewable energy technologies. The unique feature of the hydrometallurgical process is the reductive treatment of chalcopyrite, which is in contrast to the oxidative treatment more commonly pursued in the literature. Chalcopyrite reduction by chromium(II) ion is described for the first time and superior kinetics are shown. At high concentrate loadings of 39, 78, and 117 gL –1 , chalcopyrite reacted completely within minutes at room temperature and pressure. The XRD, SEM-EDS, and XPS measurements indicate that chalcopyrite reacts to form copper(I) chloride (CuCl). After the reductive treatment, the mineral products are leached by iron(III) sulfate to demonstrate the complete extraction of copper. The chromium(II) ion may be regenerated by an electrolysis unit inspired by an iron chromium flow battery in a practical industrial process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Nanoscale Imaging and Control of Volatile and Non-Volatile Resistive Switching in VO 2

Control of the metal-insulator phase transition is vital for emerging neuromorphic and memristive technologies. The ability to alter the electrically driven transition between volatile and non-volatile states is particularly important for quantum-materials-based emulation of neurons and synapses. The major challenge of this implementation is to understand and control the nanoscale mechanisms behind these two fundamental switching modalities. In this study, in situ X-ray nanoimaging is used to follow the evolution of the nanostructure and disorder in the archetypal Mott insulator VO 2 during an electrically driven transition. Our findings demonstrate selective and reversible stabilization of either the insulating or metallic phases achieved by manipulating the defect concentration. This mechanism enables us to alter the local switching response between volatile and persistent regimes and demonstrates a new possibility for nanoscale control of the resistive switching in Mott materials.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Methane pyrolysis by Joule heating for graphitic carbon and hydrogen production

The global energy transition toward sustainability requires technologies that can decarbonize energy carriers and fuels while producing valuable materials. Methane, a primary component of natural gas, is both a high-energy-density fuel and a significant greenhouse gas. This study reports an approach for methane pyrolysis utilizing Joule heating within the deposition substrate to drive the endothermic reaction. With electric current passing through a resistive porous carbon cloth, heat is generated to break C-H bonds of methane molecules. Here, the decomposition of methane as it flows through the cloth results in hydrogen production and the formation of conformally layered graphite around the carbon fibers. The effects of input power, chamber pressure, feedstock flow rate, and process duration on hydrogen and graphite production are characterized via in situ mass spectrometry and laser absorption spectroscopy, resulting in methane conversion rates up to 88%, with hydrogen and carbon yields of 82% and 72%, respectively. Material characterization verifies uniform high-quality graphite deposition, with a Raman I D /I G ratio of 0.1 and 3.38 Å d-spacing. This Joule heating method for catalyst-free methane pyrolysis offers the potential for advancing hydrogen production technology by simultaneously producing valuable materials such as solid graphite, thus enhancing the economic viability of the fuel decarbonization process.

Energy Resources↗

DOE OSTI2025

Developing Fluorescence-Based Sensors to Support Rare Earth Element Separation

Rare earth elements (REEs) are essential to most renewable energy technologies. Unfortunately, as we transition to sustainable energy production, the demand for REEs is rapidly growing well beyond current rates of production. As a result, novel means of efficient, scalable, and easily adaptable methods for processing primary and recycle feedstocks are needed. Development and integration of sensors for highly selective in-line monitoring can support more efficient design and testing of such novel separation processes, as well as more cost-effective deployment of those separation flowsheets. Work here will explore the application of fluorescence spectroscopy, a highly sensitive and selective technique, to quantify multiple lanthanides in complex mixtures including known interferents or quenching agents. Results include identification of the optimal excitation wavelength and the limit of detection of various rare earth elements as well as the performance of data-science-based quantification approaches in streams where “unknowns” are present. Overall, the data science tools in conjunction with optical sensor data were able to quantify analytes in the presence of other lanthanides which can be anticipated in the actual industrial stream. Here we include characterization of lanthanides in a microfluidic device similar to those used in new process development. This study demonstrates the capability of utilizing fluorescence spectroscopy to quantify analytes in a complicated solution matrix, suggesting this is a successful approach for in-line monitoring to optimize the separation efficiency in an industrial stream.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Non-fluorinated electrolyte for high-voltage anode-free sodium metal battery

Abundant sodium (Na) batteries are a sustainable alternative to resource-constrained lithium-ion batteries, offering huge cost advantages. However, developing high-voltage anode-free sodium metal batteries (SMBs) to narrow the energy density gap with lithium-ion batteries is hindered by a critical challenge: existing electrolytes cannot simultaneously achieve ultra-high Na coulombic efficiency and anodic stability. Here, in this study, we present a rationally designed non-fluorinated electrolyte (1.0 M NaPF 6 in 1,2-diethoxyethane/1,2-di-tert-butoxyethane) to address this key limitation, achieving Na coulombic efficiency of >99.95% and anodic stability of >4.8 V. For coin cells (2.0 mAh cm −2 , N/P = 1.7), our electrolyte design enables 4.0 V Na | |Na 3 V 2 (PO 4 ) 3 (NVP) at 5 C and 4.3 V Na | |NaNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC622) at 0.3 C for 5,000 and 500 cycles with a capacity retention >80%. Remarkably, the 50 mAh anode-free pouch cells 4.0 V Al | |NVP and 4.3 V Al | |NMC622 also achieve 500 and 300 cycles (retention >75%) with a specific energy of >360 Wh kg (electrode) −1 . This work focuses on electrolyte optimization and conceptual advances, whereas critical aspects such as safety, large-scale manufacturability and practical feasibility of SMBs require further investigation. The electrolyte design using non-fluorinated solvents enhances the anodic stability without sacrificing Na efficiency, laying groundwork for advancing low-cost, high-energy SMBs and supporting the transition to sustainable battery technologies.

25 ENERGY STORAGE↗

DOE OSTI2022

CP‐SyNet: A tool for generating customised cyber‐power synthetic network for distribution systems with distributed energy resources

Abstract The integration of distributed energy resources and advancement in information technology has enabled the transition of traditional power distribution systems to active cyber‐physical distribution systems. A growing amount of research has been done on the modelling, analysis, and optimisation of power distribution system behaviour. However, existing publicly available distribution test feeders are limited in numbers and have minimal features. Furthermore, these test feeders do not include cyber models and are not customisable. To bridge this gap, we propose and develop Cyber‐physical synthetic distribution system network (CP‐SyNet), a tool for generating customisable cyber‐physical synthetic distribution test feeders. CP‐SyNet generates three‐phase unbalanced test feeders according to users' requirements, while simultaneously considering both the cyber side and the physical side of the network for cyber‐physical analysis. The physical test network is developed using a graph‐theoretical approach that employs information from existing test feeders. The cyber side considers an equivalent communication network by transforming the physical topology into possible and feasible simulated network. Two examples are presented to demonstrate the feasibility of the proposed framework to generate cyber‐physical test feeders.

Wang, Lusha↗

DOE OSTI2024

DIRAC current, upcoming and planned capabilities and technologies

DIRAC is the interware for building and operating large scale distributed computing systems. It is adopted by multiple collaborations from various scientific domains for implementing their computing models. DIRAC provides a framework and a rich set of ready-to-use services for Workload, Data and Production Management tasks of small, medium and large scientific communities having different computing requirements. The base functionality can be easily extended by custom components supporting community specific workflows. DIRAC is at the same time an aging project, and a new DiracX project is taking shape for replacing DIRAC in the long term. This contribution will highlight DIRAC’s current, upcoming and planned capabilities and technologies, and how the transition to DiracX will take place. Examples include, but are not limited to, adoption of security tokens and interactions with Identity Provider services, integration of Clouds and High Performance Computers, interface with Rucio, improved monitoring and deployment procedures.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Opinion dynamics in financial markets via random networks

We investigate financial market dynamics by introducing a heterogeneous agent-based opinion formation model. In this work, we organize individuals in a financial market according to their trading strategy, namely, whether they are noise traders or fundamentalists. The opinion of a local majority compels the market exchanging behavior of noise traders, whereas the global behavior of the market influences the decisions of fundamentalist agents. We introduce a noise parameter, q , to represent the level of anxiety and perceived uncertainty regarding market behavior, enabling the possibility of adrift financial action. We place individuals as nodes in an Erdös-Rényi random graph, where the links represent their social interactions. At any given time, individuals assume one of two possible opinion states ±1 regarding buying or selling an asset. The model exhibits fundamental qualitative and quantitative real-world market features such as the distribution of logarithmic returns with fat tails, clustered volatility, and the long-term correlation of returns. We use Student’s t distributions to fit the histograms of logarithmic returns, showing a gradual shift from a leptokurtic to a mesokurtic regime depending on the fraction of fundamentalist agents. Furthermore, we compare our results with those concerning the distribution of the logarithmic returns of several real-world financial indices.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Transfer of EP and Doping Technology for PIP-II HB650 Cavities from Fermilab to Industry

Fermilab has optimized the surface processing conditions for PIP-II high beta 650 MHz cavities. This encompasses conditions for bulk electropolishing, heat treatment, nitrogen doping, post-doping final electropolishing, and post-processing surface rinsing. The technology has been effectively transitioned to industry. This paper highlights the efforts made to fine-tune the process and to smoothly share them with the partner labs and an associated vendor.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Multi-Gas Sensors for Enhanced Reliability of SOFC Operation

GE Research, in partnership with SUNY Polytechnic Institute (SUNY Poly), designed, built, and tested gas sensors for in situ monitoring of H 2 and CO anode tail gases produced with on-site steam reforming in solid oxide fuel cell (SOFC) systems. The knowledge of the H 2 /CO ratio of these anode tail gases should allow accurate determination and control of the efficiency of the reforming process in the SOFC system and should deliver a lower operating cost for SOFC customers. The project objectives were to achieve multi-gas monitoring capability with a single multivariable sensor, and to sustain this performance in the presence of gaseous interferences and a potential poison for the sensor. The duration of the project was 24 months with the project structure that included three technical tasks such as (1) development of design rules of photonic nanostructures for H 2 and CO gas detection, (2) laboratory validation of photonic nanostructures for selective H 2 and CO gas detection, and (3) validation of photonic nanostructures for initial stability and poison-resistance against H 2 S. To build multivariable sensors for selective H 2 and CO gas detection in the presence of interferences, we expanded our earlier knowledge of multi-gas sensors into new fabrication and functionalization methodologies as well as into new methodologies for the spectral data analysis of multi-gas responses. We have advanced our design rules of the three-dimensional (3D) photonic nanostructures that allowed detection of H 2 and CO at high temperatures as individual gases and as their mixtures and rejection of interferences such as CO 2 , H 2 O, CH 4 , and other hydrocarbons for SOFC applications. Our advanced design rules should be attractive for building the new generation of cost-effective industrial sensors. Stability and poison resistance of our 3D photonic nanostructures was tested in the laboratory conditions. While initially we utilized conventional machine learning data analysis tools, we have found that they were unable to correct for the sensor drift. Thus, we have implemented new methods of machine learning for the analysis of our spectral data. These learnings pave the way to move the future studies into advanced testing of effects of interferences, aging and field tests. In future, our work will continue to advance our sensing designs to operate in conditions with known and unknown interferences by implementing nanostructures with enhanced spectral diversity of responses to gaseous species of interest and interferences. Our systematic reduction of technical risks in this completed project and in future studies will ensure transition of this sensing technology to commercialization.

03 NATURAL GAS↗

DOE OSTI2020

Workshop Report for Next-Gen AI for Proliferation Detection: Accelerating the Development and Use of Explainability Methods to Design AI Systems Suitable for Nonproliferation Mission Applications

Artificial intelligence (AI) promises powerful new capabilities in an expansive array of applications. One area is proliferation detection, where AI can provide transformative tools to achieve objectives currently inaccessible using conventional methods. In particular, AI affords the opportunity to use new indicators and process massive amounts of heterogeneous data that can increase sensitivity to proliferant activities and push proliferation detection to the earliest possible stages. However, existing AI tools are not ready to achieve such potential, falling short in regard to some important considerations involved in proliferation detection. One crucial aspect that requires improvement is the explainability of the most powerful AI algorithms (i.e., understanding how the algorithms actually arrive at their conclusions)-the lack of which prevents widespread adoption in national security missions. The Data Science and AI portfolio within the National Nuclear Security Administration's Office of Defense Nuclear Nonproliferation Research and Development is driving the development of next-generation AI for proliferation detection through the expertise and work of the national laboratories and partners in academia. The "Next-Gen AI for Proliferation Detection: Accelerating the Development and Use of Explainability Methods to Design AI Systems Suitable for Nonproliferation Mission Applications" workshop aimed to further this objective. The meeting was held virtually on Sept. 15-16, 2020 and included more than 170 participants, primarily from the national laboratories with additional contributions from university researchers and mission partners. Each day included a keynote presentation, four technical presentations about cutting-edge research in explainability, and a panel to explore considerations in applying explainability and developing AI systems that can accelerate the transition of emerging AI technologies among partners and end users to solve critical mission questions. This report summarizes the Next-Gen AI for Proliferation Detection workshop's content and findings.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2024

Transfer of EP and Doping Technology for PIP-II HB650 Cavities from Fermilab to Industry

Chouhan, V.↗

DOE OSTI2025

Data Sharing as a Catalyst for Expanding the Energy Frontier

As the energy landscape evolves to include technologies such as geothermal energy, comprehensive data become essential for driving innovation and scalability, particularly with the growing use of tools like machine learning and artificial intelligence. In emerging sectors, the cost of gathering high-quality data across large spatial areas can present a significant barrier. A key solution is leveraging existing data from well-established industries like oil and gas. However, the proprietary nature of data in these industries often hinders collaboration. This paper explores how cultivating a culture of data sharing can act as a catalyst for progress, fueling breakthroughs across both conventional and renewable energy sectors. Practical compromises that protect business interests while enabling data access are proposed, and real-world success stories are highlighted, demonstrating how collaboration has accelerated advancements in geothermal, carbon capture, and other innovative technologies.

15 GEOTHERMAL ENERGY↗

DOE OSTI2026

Ultra Wide Bandgap Laser Addressable Photoconductors

Wide Band Gap (WBG) and Ultra Wide Band Gap (UWBG) photoconductors have the potential to meet several critical mission needs for LLNL and the broader USG due to their exceptional characteristics related to large critical electric field. In particular, high energy laser systems such as the National Ignition Facility would benefit from the development of new materials for active optical devices such as the Optically Addressable Light Valve (OALV) used in the Programmable Spatial Shaper System. Missions in Global Security would benefit from higher performance Photoconductive Semiconductor Switches for pulsed power and radiofrequency amplifiers. This project examined the suitability of both commercially available and custom synthesized semi insulating WBG and UWBG materials for several of these applications. We developed high laser damage threshold OALVs for optical systems based on several of these materials as well as new RF, pulsed power, and power electronics devices based on the same. These devices show superior power handling in terms of laser damage threshold, electric field, and power output. A number of the technologies developed have been transitioned to both internal and external customers.

42 ENGINEERING↗

NASA NTRS1972

Oceanographic observation of New York Bight from ERTS-1

The author has identified the following significant events. The Earth Resources Technology Satellite made a transit over New York Bight on 16 August, 1972. Imagery from this transit shows several oceanographic features that demonstrate the usefulness of remote sensing for large area, synoptic observation of changes in water quality in the coastal zone. Both the extent and turbulent character of the Hudson River plume are discernible in the image. Residue from a dump of waste acid is visible over a five mile area in the apex of the Bight. Little dispersion of this residue has occurred which suggests that this feature will be a persistent signature in images from future satellite transits.

Maul, G. A.↗