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DOE OSTI2024

Emerging magnetic materials for electric vehicle drive motors [Slides]

Increasing demand for electric vehicles (EVs) is increasing demand for the permanent magnets that drive their motors, as approximately 80% of modern EV drivetrains rely on high-performance permanent magnets to convert electricity into torque. In turn, these high-performance permanent magnets rely on rare earth elements for their magnetic properties. These elements are "critical" (i.e., at risk of limiting the growth of renewable energy technologies such as EVs), which motivates an exploration for alternative materials. In this article, we overview the relevant fundamentals of permanent magnets, describe commercialized and emerging materials, and add perspective on future areas of research. Currently, the leading magnetic material for EV motors is Nd 2 Fe 14 B, with samarium-cobalt compounds (SmCo 5 and Sm 2 Co 17 ) providing the only high-performing commercialized alternative. Emerging materials that address criticality concerns include Sm 2 Fe 17 N 3 , Fe 16 N 2 , and the L10 structure of FeNi, which use lower cost elements that produce similar magnetic properties. However, these temperature-sensitive materials are incompatible with current metallurgical processing techniques. We provide perspective on how advances in low-temperature synthesis and processing science could unlock new classes of high-performing magnetic materials for a paradigm shift beyond rare earth-based magnets. In doing so, we explore the question: What magnetic materials will drive future EVs?

42 ENGINEERING↗

DOE OSTI2024

Louisville Communities LEAP Engagement: Improving Energy Efficiency in Affordable Housing

This report is a comprehensive summary of the related workstreams pursued through the Communities Local Energy Action Program (Communities LEAP) pilot Technical Assistance (TA) program in Louisville, Kentucky. It begins with an analysis around energy efficiency technologies, focused on building envelope improvements, that explores the impact to individual residents as well as the impact to the community at-large if the upgrades were adopted city-wide. Community benchmarking ordinances and complementary policies are considered next, including comparisons of programs with peer communities. A workforce development section then covers the state of Louisville's workforce today and identifies programs in peer communities that Louisville could consider emulating to achieve a "right-sized" workforce. The document closes out with an overview of policies around energy efficiency in peer communities that Louisville could explore, with considerations for the City's unique policy context.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

Unified Software Architecture for Advanced Materials and Manufacturing Technologies Data Management and Processing: FY 2023 Multidimensional Data Correlation Platform

This report details the various digital manufacturing activities ongoing at ORNL as part of the Advanced Materials and Manufacturing Technologies (AMMT) program. The AMMT program is exploring a data-driven approach to demonstrate the use of AM for the fabrication of components for nuclear applications, with the goal of providing a greater understanding of manufacturing quality outcomes that would pave the way toward the development of standards for certification and qualification. The objective of this work package is to establish a digital manufacturing discipline common to all participants of the AMMT program to improve the performance, reliability, and lifetime of nuclear components. As part of this effort, we will develop a unified software architecture for AMMT data management and processing, deploy the digital platform across AMMT participants’ facilities, and generate pedigreed datasets in a common format across multiple labs and facilities. To this end, the MDDC work package has focused on three activities during FY23. First, the MDF Digital Tool was overhauled to better serve the needs of the AMMT program. Next, multiple laser powder bed fusion (L-PBF) systems at the MDF were upgraded to a common sensor package for collecting comparable in situ data across machines. Finally, various improvements relevant to the AMMT program were implemented in the ORNL-developed software tool, Peregrine. This report marks the completion of FY23 milestone M3CR-22OR0403051: Report Describing the Architecture of the Digital Platform to Support AMMT Activities.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Updated Report for the Natural Gas Community of the Future

Nicor Gas is developing the Natural Gas Community of the Future (later renamed the Nicor Gas Smart Neighborhood (TM), a high-performance residential neighborhood consisting of 50 homes connected to electricity and natural gas services in suburban South Chicago , built as low-income affordable housing. The National Renewable Energy Laboratory (NREL) has been assisting Nicor Gas to explore a synergy among energy efficiency, renewable technologies, affordability, and resilience enabled by natural gas in this community. Our goal is to demonstrate how energy efficiency, distributed energy resources (DERs), and advanced controls, in combination with existing natural gas and electricity infrastructure, can help historically underserved communities in a cold climate reduce energy burden and improve resilience to extreme weather conditions.

03 NATURAL GAS↗

DOE OSTI2025

Thermal Management for Planar Package Power Electronics (CRADA Final Report)

The National Renewable Energy Laboratory (NREL) and John Deere Electronic Solutions (JDES) collaborated to develop and evaluate computer models and simulations related to the thermal performance of semiconductor device packaging for an inverter of an off-road vehicle ("Semiconductor Packaging"). The objective of the research was for NREL and JDES to develop a two or three-dimensional computer-aided design model of the Semiconductor Packaging ("Computer Model") for thermal performance evaluation in a simulation. The project developed computer models of a Semiconductor Package of silicon-carbide semiconductor devices with appropriate thermal dissipation via one or more of the following thermal features: a double-sided planar cooling configuration, an air-cooled configuration, a liquid-cooled configuration for off-road inverter applications in a relevant simulated operating environment. It is noted that surface area and prototype product embodiment consisting of air-cooled and liquid-cooled configurations may and may not be in direct contact with power semiconductor chips. The idea was to explore and develop packaging and thermal management technology for power semiconductors that was most effective in the performance yet had least burden in overall product cost for a given application.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2025

SF6 / Acetone Separation & Purification

Sulfur hexafluoride (SF₆) is recognized as the most potent greenhouse gas used in the power transmission and semiconductor sectors. In the past decade, its global emissions have increased sharply, largely due to the absence of effective disposal and recovery pathways. This concern was formally addressed under the Kyoto Protocol, which urged participating nations to adopt measures to limit SF₆ emissions and mitigate its role in climate change. In recent years, various abatement strategies have been explored, including non-thermal plasma (NTP) technologies such as radio frequency, microwave, dielectric barrier discharge, and electron beam systems. While these methods can decompose SF₆, they also produce hazardous by-products like sulfur oxyfluorides, sulfur dioxide, hydrofluoric acid, and fluorine gas. Because these compounds pose both environmental and health risks, replacing traditional disposal practices with modern, more effective treatment methods has become an urgent priority.

36 MATERIALS SCIENCE↗

DOE OSTI2024

On the Feasibility of Deep Geothermal Wells Using Numerical Reservoir Simulation

This study examines the geothermal energy extraction potential from the basement rock within the Denver–Julesburg Basin, focusing on the flow performance and heat extraction efficiency of different geothermal well configurations. It specifically compares U-shaped, V-shaped, inclined V-shaped, and pipe-in-pipe configurations against enhanced geothermal system setups. Through numerical modeling, we evaluated the thermal behavior of these systems under various operational scenarios and fracture conditions. The results suggest that while closed-loop systems offer moderate temperature increases, Enhanced geothermal system configurations show substantial potential for high-temperature extraction. This underscores the importance of evaluating well configurations in complex geological settings. The insights from this study aid in strategic geothermal energy planning and development, marking significant advancements in geothermal technology and setting a foundation for future explorations and optimizations.

15 GEOTHERMAL ENERGY↗

DOE OSTI2022

Designing the PR100 Study: Puerto Rico Grid Resilience and Transition to 100% Renewable Energy

Puerto Rico has committed to meeting its electricity needs with 100% renewable energy by 2050, along with realizing interim goals of 40% by 2025, 60% by 2040, the phaseout of coal-fired generation by 2028, and a 30% improvement in energy efficiency by 2040 as established in Act 17. [1] To meet these goals and support widespread end-use electrification, the territory must explore how renewable energy and other generation technologies can be developed with energy storage, distributed generation, distribution control, electric vehicles, and energy efficient and responsive loads in each of Puerto Rico's cities and communities. To support Puerto Rico in reaching its renewable energy goals; help ensure energy system resilience against future extreme weather events; improve energy justice; and provide inputs to LUMA Energy's walk, jog, and run approach in its coordinated planning roadmap, the U.S. Department of Energy, National Renewable Energy Laboratory, Argonne National Laboratory, Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory, Pacific Northwest National Laboratory and Sandia National Laboratories propose to evaluate 100% renewable energy pathways through an integrated analysis process. This talk will present steps in designing a two-year study entitled Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy (PR100). [1] U.S. Energy Information Administration (EIA). 2020. Puerto Rico Territory Energy Profile.

100% renewable energy↗

DOE OSTI2020

Development of a Convolutional Neural Network Classifier for Data Starved Spectra - 20199

The Institute for Clean Energy Technology (ICET) at Mississippi State University is exploring the utility of machine learning in augmenting its mobile radiation surveying platforms, which are currently being developed as means to survey depleted uranium contaminated areas in support of remediation and decommissioning efforts. Mobile survey platforms provide a means to efficiently scan large areas of interest while reducing human exposure to radiation and other hazards. The survey platforms can also be used for scanning for any gamma emitting isotope in addition to depleted uranium. The spectral data that the platforms collect may be data starved with relatively low counts and poorly defined spectral features depending on the speed of the platforms and scintillation detector selection. Such data-starved spectra are difficult to use for isotope identification, requiring advanced knowledge of the possible radionuclides that could be present and environmental factors that could attenuate signals or introduce background noise. These factors in combination with the volume of survey data increases the time it takes to perform analysis of survey data when the source type is unknown. There are a number of algorithms in the field of machine learning that can be used to classify data that would be challenging and time-consuming for a human to identify. Supervised machine learning algorithms train models based on extensive amounts of human-labeled training data. Once sufficiently trained, these models can be used to quickly make high-fidelity predictions on new data. Convolutional neural networks are machine learning algorithms that excel in learning representations of 'shapes'. They do this by taking numerical input data and convolving them with spatial feature detectors referred to as filters. These filters are incrementally adjusted to reduce the prediction error on the data during the backpropagation step of training. Discussed in this paper is the development of a convolutional neural network classifier (CNNC) that can utilize spectral survey data for source discrimination and isotope identification. Bench-top laboratory experiments data using LaBr{sub 3}(Ce) scintillation detectors were used to train and evaluate the performance of the developed CNNC. The CNNC is capable of discriminating a variety of gamma emitting source types, differentiating different forms of uranium (depleted vs. natural), and estimating the amount of uranium for a known geometry. The discussed CNNC may be useful in scenarios where survey systems are deployed in situations where hazardous radioactive material maybe present, but the type is unknown. When used in remediation applications the CNNC can be used to screen-out false positives, helping reduce remediation costs. (authors)

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2024

A Simulation Modeling Approach to Optimizing Nuclear Waste Dispositioning

The dispositioning of nuclear waste generated at facilities across the country is an ongoing battle that affects us all. National laboratories and research centers dealing in medical research, clean energy, and other nuclear activities such as the Department of Energy (DOE) facilities face the need to properly manage and dispose of nuclear waste. A dynamic modeling solution would enable the DOE and others to make decisions on waste disposal and technological options. In doing so, this research explores modeling techniques using available data to address these situations. The focus being on developing an initial robust and adaptable discrete event model using the ExtendSim tool. This modeling effort will target the dispositioning of transuranic waste at the Savannah River National Laboratory (SRNL) which can be expanded to represent the current state of disposition process for waste generated at other DOE facilities. The model aims to assess resource allocation and waste processing options to stabilize productivity and cut the backlog of nuclear waste. By assessing the results of different scenarios, this research aims to provide actionable insights for the DOE. This approach has the potential to significantly improve the management of radioactive waste, offering the capability of evaluating options for optimizing the process for nuclear waste disposal. The findings of this study can serve as a valuable resource for decision-makers and other national laboratories, or research entities engaged in nuclear operations by enabling them to make more informed choices.

Andaverde, Alexis↗

DOE OSTI2026

Embedding Fiber Optic Sensors in Stainless Steel using Spark Plasma Sintering for Structural Health Monitoring in Harsh Environments

Embedded fiber optic sensors such as fiber Bragg gratings (FBGs) offer a unique route for distributed real-time in-situ imaging of various engineering parameters for numerous purposes. This study advanced the current sensor embedding approaches by exploring a spark plasma sintering (SPS)-assisted technology to embed FBGs in high-temperature structural materials and demonstrated the capability of temperature measurement. In this approach, single-mode FBGs were integrated into stainless steel (SS) 316L components using SPS, followed by the evaluation of the bonding quality between the FBGs and matrix, the optical attenuation of the fibers induced by embedding, and the sensing characters of the FBGs under temperature stimuli. The results demonstrated that superior bonding was achieved between the FBGs and highly-densified SS316L. Examination of the behavior of Bragg gratings validated signal fidelity after embedding. Real-time thermal imaging under temperature cycling using the FBGs demonstrated the effectiveness of the technique for smart materials manufacturing.

36 - MATERIALS SCIENCE↗

DOE OSTI2020

Integrating Commercial Ready Autonomous Robotic Platforms to Enhance Worker Safety and Efficiency - 20053

This paper will explore the challenges and triumphs of implementing advanced robotic systems and the supporting technology for the waste management industry. Deployment-ready solutions for autonomous robotic platforms are new to the radioactive waste management industry and have been slow to implement across the complex. Specifically, it will explore Hanford Tank Operations Contractor's implementation of ground-based autonomous robotic platforms to enhance workforce safety and efficiency. The first objective of the project is to demonstrate safe operation of autonomous instrumented robots, followed by a scaling up of capabilities for the platform to meet any additional requests of internal stakeholders. Autonomous robotics platforms offer a fantastic range of capabilities that will aid in decreasing long-term liability of radioactive waste management industry by enhancing clean-up efforts and worker safety. Over the past five years, deployment-ready solutions for autonomous robotic platforms have come a long way. Autonomous robotic platforms are increasingly available to purchase from many vendors, often for prices under $100,000. Additionally, the vendors who produce these products are efficient in accommodating customized solutions to unique challenges, such as those often found in the radioactive waste management industry. However, the newness of this technology to the radioactive waste management industry and has resulted in a slow implementation across the complex. This paper will explore the challenges and triumphs of implementing advanced robotic systems and supporting technology for the waste management industry. Specifically, it will explore Hanford Tank Operations Contractor's implementation of ground based autonomous robotic platforms to enhance workforce safety and efficiency. While the company has utilized robots in many parts of the tank farms mission, this was first attempted in the deployment of an autonomous platform that required no operator with only minor maintenance and created challenges not yet encountered. These challenges included stakeholder buy-in, operational safety, procurement uncertainties, adaption of 'off the shelf products, overcoming the 'Fukushima complexity' perception, security concerns, and the initial criteria down select. Hanford Tank Operations Contractor's management identified the need for a workforce protecting low cost robotics solution in the fall of 2017. The project scope generated was part of the response to the Tank Vapor Assessment Team recommendation to enhance the safety of the workforce by utilizing new technology. Since the projects inception, it has been incorporated into the Tank Stewardship Plan. This project was unique to Hanford Tank Operations Contractor, as the company does not frequently incorporate advanced technology for field deployment quickly. The project was also progressive to the Hanford Tank Operations Contractor as it functions as a partnership project with a local university. The first objective of the project is to demonstrate safe operations of autonomous instrumented robotics, monitoring and collecting data, and the wireless transmission of data to a central computing system. Following the completion of this first objective, the project will scale up capabilities of the platform to meet the requests of additional internal stakeholders throughout the tank farms - including completion of specific in-field tasks. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

AstroPix: A pixelated HVCMOS sensor for space-based gamma-ray measurement

A next-generation medium-energy gamma-ray telescope targeting the MeV range would address open questions in astrophysics regarding how extreme conditions accelerate cosmic-ray particles, produce relativistic jet outflows, and more. One concept, AMEGO-X, relies upon the mission-enabling CMOS Monolithic Active Pixel Sensor silicon chip AstroPix. AstroPix is designed for space-based use, featuring low noise, low power consumption, and high scalability. Desired performance of the device include an energy resolution of 5 keV (or 10% FWHM) at 122 keV and a dynamic range per-pixel of 25–700 keV, enabled by the addition of a high-voltage bias to each pixel which supports a depletion depth of 500 μ m. This work reports on the status of the AstroPix development process with emphasis on the current version under test, version three (v3), and highlights of version two (v2). Version 3 achieves energy resolution of 10.4 ± 3.2% at 59.5 keV and 94 ± 6 μ m depletion in a low-resistivity test silicon substrate.

Astrophysics instrumentation↗

DOE OSTI2022

Techno-economic and life cycle assessment of aluminum electrorefining from mixed scraps using ionic liquid

Aluminum production from bauxite ore uses significantly high amount of energy and capital expenditure. Recycle and reuse of aluminum can be economical and minimize the environmental impacts. Smelter based recycle and reuse of aluminum is used in recent days, however, it also uses high amount of energy with high cost of production and yields high life cycle impacts. The University of Alabama has developed aluminum electrorefining technology from mixed scraps using ionic liquids as an alternative to traditional smelter based recycle and reuse. This study has explored the techno-economical, and life cycle viability of that technology. An excel-based techno-economic and life cycle assessment model was developed at Idaho National Laboratory for techno-economic and life cycle assessment. SimaPro was used to get the necessary database for the life cycle assessment. This study determined that a 20,000 kg/day ionic liquid-based electrorefining system can be profitable with a net yearly profit of $2.00 million. Further, in terms of net global warming potential, it emits 0.92 kg CO 2 equivalent per kg of aluminum recycled, whereas the traditional smelter-based recycle technology emits 1.57 kg CO 2 equivalent per kg of aluminum recycled, and the aluminum production from bauxite ore emits 17.8 kg CO 2 equivalent per kg of aluminum produced. In other life cycle assessment categories, electrorefining of aluminum emits >88 % less than aluminum production from bauxite ore and it is also better than traditional aluminum recycling in six out of ten categories studied. This makes ionic liquid-based electrorefining technology a very promising technology in terms of process economics and environmental sustainability.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Hybrid renewable energy systems: the value of storage as a function of PV-wind variability

As shares of variable renewable energy (VRE) on the electric grid increase, sources of grid flexibility will become increasingly important for maintaining the reliability and affordability of electricity supply. Lithium-ion battery energy storage has been identified as an important and cost-effective source of flexibility, both by itself and when coupled with VRE technologies like solar photovoltaics (PV) and wind. In this study, we explored the current and future value of utility-scale hybrid energy systems comprising PV, wind, and lithium-ion battery technologies (PV-wind-battery systems). Using a price-taker model with simulated hourly energy and capacity prices, we simulated the revenue-maximizing dispatch of a range of PV-wind-battery configurations across Texas, from the present through 2050. Holding PV capacity and point-of-interconnection capacity constant, we modeled configurations with varying wind-to-PV capacity ratios and battery-to-PV capacity ratios. We found that coupling PV, wind, and battery technologies allows for more effective utilization of interconnection capacity by increasing capacity factors to 60%–80%+ and capacity credits to close to 100%, depending on battery capacity. We also compared the energy and capacity values of PV-wind and PV-wind-battery systems to the corresponding stability coefficient metric, which describes the location-and configuration-specific complementarity of PV and wind resources. Our results show that the stability coefficient effectively predicts the configuration-location combinations in which a smaller battery component can provide comparable economic performance in a PV-wind-battery system (compared to a PV-battery system). These PV-wind-battery hybrids can help integrate more VRE by providing smoother, more predictable generation and greater flexibility.

14 SOLAR ENERGY↗

DOE OSTI2023

Quantum Computing and Visualization: A Disruptive Technological Change Ahead

The focus of this Visualization Viewpoints article is to provide some background on quantum computing (QC), to explore ideas related to how visualization helps in understanding QC, and examine how QC might be useful for visualization with the growth and maturation of both technologies in the future. In a quickly evolving technology landscape, QC is emerging as a promising pathway to overcome the growth limits in classical computing. In some cases, QC platforms offer the potential to vastly outperform the familiar classical computer by solving problems more quickly or that may be intractable on any known classical platform. As further performance gains for classical computing platforms are limited by diminishing Moore’s Law scaling, QC platforms might be viewed as a potential successor to the current field of exascale-class platforms. Importantly, while present-day QC hardware platforms are still limited in scale, the field of quantum computing is robust and rapidly advancing in terms of hardware capabilities, software environments for developing quantum algorithms, and educational programs for training the next generation of scientists and engineers. After a brief introduction to QC concepts, the focus of this article is to explore the interplay between the fields of visualization and QC. First, visualization has played a role in QC by providing the means to show representations of the quantum state of single-qubits in superposition states and multiple-qubits in entangled states. Second, there are a number of ways in which the field of visual data exploration and analysis may potentially benefit from this disruptive new technology though there are challenges going forward.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

High performance heat exchangers for next generation hybrid cooler (CRADA NFE-19-07891 Final Report)

The evaporative cooling process has been successfully deployed in multiple energy conversion processes such as power generation, process cooling, heating, ventilation & cooling (HVAC), and commercial and industrial refrigeration. The heat exchanger is a very common yet extremely critical component of such systems. The device is important since the performance of the overall cooling system heavily relies on the thermal-hydraulic efficiency of the heat exchanger. The possible wet operation as evaporative cooling heat exchanger complicates the issue. Indeed, based on the hybrid nature of operation (fully dry, partially wet, fully wet) the efficiency can vary significantly and can cause performance variation for the whole system. Understanding the importance of the issue, Oak Ridge National Laboratory (Contractor) and Baltimore Aircoil Company (Participant) propose an activity focused on the analysis of the existing heat exchanger technology used in air and evaporative cooling processes and design, development and demonstration of a novel heat exchanger design based on porous materials. The potential candidates include metallic wire meshes and metal foams carefully designed for the proposed application. Prior research has indicated that these materials have great potential for deployment in thermal systems, particularly heat sinks and heat exchangers. It is expected that the successful completion of the project will lead to novel heat exchanger technology for hybrid systems (capable of dry and wet operation) by exploring newly emerging materials and their potential for heat transfer application. The overall goal is to develop a next generation heat exchanger technology which can be deployed in evaporative cooling systems. The impact of the such development is significant since, it will not only make the overall system highly efficient but will also, reduce the total refrigerant charge in the heat exchanger, a critical aspect for the deployment of refrigerants with lower Global Warming Potential (GWP).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

High performance heat exchangers for next generation hybrid cooler (CRADA Final Report)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗