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DOE OSTI2024

Molten Salt Loop Operational Experience and Test Campaigns in FY24

The Facility to Alleviate Salt Technology Risks (FASTR) at the US Department of Energy (DOE) Oak Ridge National Laboratory (ORNL) was developed to demonstrate technology for high-temperature chloride salt systems (Figure 1). FASTR is primarily constructed using alloy C-276 and is designed to operate at temperatures of up to 725°C. The facility is loaded with 250 kg of NaCl-KCl-MgCl 2 salt. This salt provides a relevant test environment for de-risking technology while avoiding the costs and hazards associated with beryllium-based or uranium-bearing salts. The facility’s major components include a centrifugal pump for salt circulation, an air-based heat exchanger to reject heat, a suite of instrumentation, and trace heating to prevent salt freezing. The salt was purified in 2020 and 2022, and the pumped loop first operated in December 2022. FASTR is a unique US capability for high-temperature molten halide salt testing. FASTR’s scale, co located purification system, and relatively large power (465 kW) differentiates it from other testing systems. Furthermore, access to the DOE-supported facility and efficient communication of results— which are generally disseminated publicly—distinguish FASTR as being broadly significant throughout the molten salt reactor community. FASTR is similar to ORNL’s Liquid Salt Test Loop (LSTL), although FASTR contains chloride-based salt instead of the fluoride-based salt (LiF-NaF-KF) found in LSTL. Furthermore, FASTR is approximately 2× larger than LSTL in terms of pipe size and length, power, salt volume, flow rate, and number of thermocouples. The LSTL first operated in 2016. At the end of FY23, there was a suspected gas leak in the LSTL that halted operation. At the start of FY24, a leak in the LSTL pump’s tank gas space was confirmed. Because the gas-space leak prevented operation of LSTL, FY24 efforts were focused on operation of FASTR. This report summarizes the progress made during FY24 in support of the DOE Office of Nuclear Energy (DOE-NE) work package, AT-24OR070202 Salt Loop and Capability for Testing Sensors and Off Gas Components.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

NOAA National Centers for Environmental Information Fisheries Acoustics Archive Network Deep Dive

EPOC uses the Deep Dive process to discuss and analyze current and planned science use cases and anticipated data output of a particular use case, site, or project to help inform the strategic planning of a campus or regional networking environment. This includes understanding future needs related to network operations, network capacity upgrades, and other technological service investments. A Deep Dive comprehensively surveys major research stakeholders’ plans and processes in order to investigate data management requirements over the next 5–10 years. Deep Dives help ensure that key stakeholders have a common understanding of the issues and the actions that a campus or regional network may need to undertake to offer solutions. The EPOC team leads the effort and relies on collaboration with the hosting site or network, and other affiliated entities that participate in the process. EPOC organizes, convenes, executes, and shares the outcomes of the review with all stakeholders. Between May 2021 and August 2021, staff members from the Engagement and Performance Operations Center (EPOC) met with researchers and staff from the National Oceanic and Atmospheric Administration (NOAA)'s N-Wave (the Enterprise network that supports the NOAA mission) and National Centers for Environmental Information (NCEI)'s Fisheries Acoustics Archive for the purpose of a recording a Deep Dive into research drivers. The goal of these meetings was to help characterize the requirements for the research use case, and to enable cyberinfrastructure support staff to better understand the needs of the researchers they support.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

University of Central Florida Campus-Wide Deep Dive

EPOC uses the Deep Dive process to discuss and analyze current and planned science use cases and anticipated data output of a particular use case, site, or project to help inform the strategic planning of a campus or regional networking environment. This includes understanding future needs related to network operations, network capacity upgrades, and other technological service investments. A Deep Dive comprehensively surveys major research stakeholders’ plans and processes in order to investigate data management requirements over the next 5–10 years. Deep Dives help ensure that key stakeholders have a common understanding of the issues and the actions that a campus or regional network may need to undertake to offer solutions. The EPOC team leads the effort and relies on collaboration with the hosting site or network, and other affiliated entities that participate in the process. EPOC organizes, convenes, executes, and shares the outcomes of the review with all stakeholders. Between December 2020 and August 2021, staff members from the Engagement and Performance Operations Center (EPOC) met with researchers and staff at University of Central Florida (UCF) for the purpose of a Campus-Wide Deep Dive into research drivers. The goal of this meeting was to help characterize the requirements for five campus research use cases and to enable cyberinfrastructure support staff to better understand the needs of the researchers they support.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2021

Strategies for microgrid operation under real-world conditions

Microgrids are an increasingly relevant technology for integrating renewable energy sources into electricity systems. Based on a microgrid implementation in California, in this study we investigate microgrid operation under real-world conditions. These conditions have not yet been considered in combination and encompass energy charges, demand charges, export limits, as well as uncertainty about future electricity demand and generation in the microgrid. Under these conditions, we evaluate the performance of two frequently applied groups of strategies for microgrid operation. The first group is composed of proactive strategies that optimize decisions based on forecasts of future electricity generation and demand. The second group includes reactive strategies that make operational decisions based exclusively on the current state of the microgrid. We evaluate the performance of the strategies under varying operational parameters, forecast accuracies, and microgrid configurations—well beyond our Californian showcase. Our results confirm the expectation that proactive strategies outperform reactive ones in the majority of settings. Yet, reactive strategies can perform better under short control intervals or under moderate prediction errors of PV generation or demand. Furthermore, the interplay between real-world conditions and operational strategies reveals several additional insights for research on microgrid operation. First, we find that demand charges and export limits decisively affect microgrid performance. Second, the impact of forecast errors is highly non-linear and non-monotonous. Third, escalating negative interactions between forecast errors and demand charges make proactive strategies benefit from longer control intervals. This result is contrary to existing best practice, which promotes short control intervals to minimize the impact of uncertainty.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Recovery and Refining of Rare Earth Elements from Lignite Mine Wastes

The University of North Dakota (UND), in collaboration with a comprehensive team of technical, business and host-site partners, built on prior technology development to complete a front-end engineering and design (FEED) and business planning study to recover and refine rare earth elements (REE) and critical minerals (CM) from North Dakota (ND) lignite mine wastes. The end of project goal was to have an investment quality project and a committed team ready to commercialize the proposed technologies in a future construction and operations phase.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2025

Integrated Methane Monitoring Platform Extension, Volume I: Final Technical Report

The IMMPE project, DE-FE0032284, was to enhance methane monitoring technologies and their applications across various natural gas asset classes. The scope included deploying advanced methane detection and monitoring technologies to identify and mitigate fugitive methane emissions, measuring emission rates, and assessing impacts. The findings included the successful mitigation of identified emissions and quantification of emission rates. A key outcome was the development of a comprehensive template and summary of recommendations for methane emissions monitoring, which is replicable for both upstream and downstream applications. Furthermore, the project emphasized the importance of education by providing training opportunities for technicians and regulators, thereby fostering awareness and promoting the adoption of cost-effective methane emissions monitoring and management techniques.

02 PETROLEUM↗

DOE OSTI2020

The global energy footprint of information and communication technology electronics in connected Internet-of-Things devices

Information and communication technology (ICT) has been critical to the emergence of a new Internet-of-Things (IoT) era, as a rapidly increasing number and variety of IoT electronic devices in a wide range of end-use sectors require massive data communication in terms of volume, velocity/speed, and variety. Additionally, semiconductor technology advancements have played a key role in ICT and unlike the past ICT energy footprint analysis, which focused on the final electronic product, an attempt has been made to examine the global energy impacts for the period 2016–2025 based on the market forecasts of three major IoT IC types, i.e., sensors and actuators, connectivity, and processor ICs distributed among four major IoT device components.Total global IoT semiconductor primary energy demand is projected to increase from 2 EJ in 2016 to 35 EJ by 2025, resulting mainly from a substantial projected increase energy needed in the manufacturing of ICs, with growth in the use of sensors and energy-intensive next fab generation manufacturing. Unlike the trend in manufacturing energy, total global operational energy use is projected to decrease significantly with the development of smaller transistor size, low-power devices, and faster wireless data communication technology. Total operational energy is projected to significantly decrease from 118 TWh/year (1,2 EJ/year) to less than 1 TWh/year (0.003 EJ/year) in spite of a significantly higher anticipated growth in its market size during the 2016–2025 forecast period. Its annual share of total primary energy use is projected to reach an insignificant level of 0.01% by the end of 2025, consistent with the past limited electronic product life cycle analyses besides the analysis focus here limited to ICs in IoT devices.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Assessment of Nuclear Energy to Support Negative Emission Technologies

The feasibility and performance of nuclear energy coupled with Negative Emission Technology (NET) processes were investigated in this report. Three overarching questions from nuclear NET systems guided this research: which NET would be able to use heat and/or electricity from nuclear power plants (NPPs); what is the performance and cost of a nuclear NET system; and what would be the market outlook for this system? Among the various NETs that are actively being developed, several were found to potentially benefit from coupling with an NPP via (1) large amounts of decarbonized and constant-output electricity; (2) free waste heat or cheap low-temperature heat; or (3) high-temperature heat. NPPs were found to be compatible with Direct Air Capture (DAC) systems, and a detailed techno-economic analysis of coupled NPP&DAC systems was performed. Preliminary analysis also indicated that biomass and water-based NETs are potentially compatible with NPPs, but further work is needed to quantify the performance of these nuclear NET systems. Design and performance analyses were completed for both liquid solvent DAC (L-DAC) and solid sorbent DAC (S-DAC) technologies. A 1.0-GWth NPP coupled with L-DAC and S-DAC was found to be able to capture 12–15 Mt CO 2 /yr and 1.0–1.5 Mt CO 2 /yr, respectively. While the L-DAC process enables much greater CO 2 capture than the S-DAC process when both are sized with a 1 GWth NPP, the NPP&L-DAC system considered also requires >2 GWth natural gas oxy-combustion to reach adequate temperature in the calciner. CO 2 generated from natural gas combustion is also captured as part of the calcination process, in addition to the CO 2 captured from air, resulting in overall CO 2 sequestration of close to 30% more than what is captured from air. The cost of carbon capture calculated with the levelized cost of DAC (LCOD) had a range of $\$170–260$/tCO 2 for NPP&L-DAC systems and a range of $\$650–680$/tCO 2 for NPP&S-DAC systems. For both DAC systems, the NPP provides economic benefit when compared to previous National Energy Technology Laboratory (NETL) studies of non-nuclear DAC systems, leading to reduction of LCOD by 5–7% for L-DAC, and 8–13% for S-DAC. For the NPP&DAC systems, a preliminary market analysis reviewed potential CO 2 market prices and eligibility for incentives. The estimated potential revenues for CO 2 capture (coming from federal incentive, CO 2 commodity markets, or offset market) is in the range of $\$170–979$ tCO 2 , and the results show that because of lower LCOD, the NPP&L-DAC process would be more attractive to a market than the NPP&S-DAC process. The large investment needed for NPP&DAC processes would require long-term certainty of sufficient market size, CO 2 prices, and incentives. Enabling NPPs to ramp DAC operation up or down based on electricity market price is not expected to significantly increase revenues of the NPP&DAC system. This is because the revenues from CO 2 sequestration are required to be very high to justify the deployment and continuous operation of the very expensive DAC technologies. In this analysis, several new research questions were uncovered, and follow-up analyses are recommended for further investigation, including a detailed feasibility study of NPP coupled with other NET systems such as biomass pyrolysis and gasification with carbon capture and storage, and seawater carbon capture.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2023

Power Electronics Thermal Management

The 2017 Electrical and Electronics Technical Team Roadmap [1] proposes aggressive research and development targets aimed at improving power electronics technology to enable the mass-market penetration of electric-drive vehicles. Achieving these aggressive targets will require a decrease in cost (year 2025 cost target: $2.70/kW) and an increase in power density (year 2025 power density target: 100 kW/L) as compared with current on-road technology. Replacing traditional silicon device-based components with more efficient and higher-temperature wide-bandgap (WBG) semiconductor device-based components will enable increased power density. However, meeting the power density target will also require innovative thermal management solutions to increase the heat fluxes dissipated and allow for compact electronics packaging. This project conducts research to develop new power electronics thermal management technologies to increase power density, enable high WBG temperature operation, and decrease cost. The performance (e.g., thermal resistance, pumping power) of the power electronics cooling technologies developed in this project are compared to the performance of current, on-road technology. One of the main challenges to achieving high power densities is associated with packaging high-temperature (up to 250 degrees C) WBG devices near lower-temperature-rated components (e.g., electrical boards and capacitors).

ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

Analytical Modeling of Biomass Transport and Feeding Systems

The processing of biomass solids in a biorefinery consists of pretreatment, enzyme hydrolysis / concurrent fermentation of sugars to ethanol, product recovery, and drying. Sustainable operation requires a front end that transforms wet solids into a pumpable slurry. Otherwise the biorefinery will suffer unscheduled shut-downs and inefficient operation due to solids that obstruct pumps and other equipment and resist mixing in a bioreactor. Downtime in pioneer biorefineries due to interruptions from materials handling problems has been 50% or more, leading to unsustainable manufacturing processes. This work addresses new technology, predictive computational models, and definition of operational conditions that result in formation of slurries of corn stover at up to 300 g/L using low enzyme loadings (1 to 3 FPU cellulase/g) before the biomass (corn stover) enters the pretreatment step. A team of researchers from Purdue University, Idaho National Laboratory (INL), Forest Concepts, AdvanceBio, Argonne National Laboratory, and DOE BETO have combined their knowledge in agricultural and biological engineering, bioprocess engineering, mechanical engineering, chemical engineering, agricultural economics, materials engineering and enzyme and microbial technology to address the challenge of making lignocellulose flow. This team effort has resulted in the development and validation of conditions that employ low levels of commercial enzyme in an agitated bioreactor to which corn stover pellets are added resulting in formation of slurries at high solids loadings, before pretreatment. This approach overcomes challenges caused by handling of dry, particulate biomass materials at the front end of the biorefinery. The subsequent materials handling issues cause obstruction at pumps, pipes and valves. Formation of high loadings slurries with low yield stress, as reported here, significantly decreases the potential for process interruption and enhances plant operability. Key advances in the knowledge of how slurry formation occurs is reported here and in recently published journal papers. We found that pellets are needed to achieve high solids loading, and that commercial enzymes are effective in forming slurries of corn stover particles from pellets that have not been pretreated. Our work has resulted in models that predict solids behavior for formation of compressed solids and pellets that in turn facilitate slurries made of high concentrations of corn stover particles. A computational model was developed that gives mechanistic insights into properties of particles and mixing process that gives the slurry rheology needed to facilitate pumping. Hence, the corn stover may be pumped into a pretreatment reactor in place of auguring in solids against high pressure which is a root cause of interruptions at the front end of a biorefinery. Subsequent mixing in enzyme and microbial bioreactors results in conversion of lignocellulose to sugars in a biorefinery in agitated bioreactors, with flows in and out of the vessels being less likely to be interrupted due to plugging or materials handling problems. The obtained data coupled to process models, techno-economic assessment (TEA) and Life Cycle Analysis (LCA) were used to assess whether this approach is practical. These results are based on a foundation of laboratory characterization and pilot runs. The NREL biochemical sugar model was utilized to carry out techno-economic analysis of enzyme catalyzed liquefaction followed by enzyme hydrolysis. The minimum sugar selling price was between 17.5 and 18.3 ¢/pound or about the same as calculated by the NREL model for dilute acid pretreatment followed by enzyme hydrolysis. Life cycle analysis (LCA) based on Argonne’s Greet Model showed the enzyme catalyzed route had the lowest greenhouse gas emissions of the three combinations studied (i.e., enzyme, enzyme mimetic, and enzyme + mimetic combined). GHG emissions for enzyme-based corn stover liquefaction step, alone, were about 21 g CO 2 -equivalent/kg of liquefied slurry. We believe this approach will further enhance operability of a pioneer biorefinery, and bring large-scale conversion of lignocellulosic biomass to low carbon footprint biofuels closer to implementation.

09 BIOMASS FUELS↗

DOE OSTI2021

Considerations regarding the Use of Computer Vision Machine Learning in Safety-Related or Risk-Significant Applications in Nuclear Power Plants

With the advancements made to date in the field of artificial intelligence (AI), significant potential exists to utilize AI capabilities for nuclear power plant (NPP) applications. AI can replicate human decision making and it is usually faster and more accurate than humans. For implementations that impact critical NPP applications (e.g., safety-related or non-safety systems that potentially affect overall plant risk), a deeper safety analysis of the AI methods is necessary. AI applied to NPP operations could resemble the use of digital I&C (DI&C) because such applications involve digital computer hardware and custom-designed software that input plant data, execute complex software algorithms, and output the results to a system or licensed human operator to potentially provoke an action. For AI methods to be compliant with current safety requirements for DI&C, AI compatibility must be evaluated, and AI-related gaps may exist that prevent the prompt deployment of AI in NPPs. This effort aims to evaluate how example AI technologies align with the DI&C safety framework, and discusses how they could be analyzed, modeled, tested, and validated in a manner similar to typical DI&C technologies. Because AI is a broad field that encompasses areas such as machine learning (ML), natural language processing, and computer vision, this research focused on a subset of methods categorized as the computer vision ML (CVML) methods. This report explores two CVML use cases, gauge reading and fire watch, considered relevant to the DI&C standards, as they could play a safety-critical role. For the gauge reading use case, a CVML-enabled technology that can read gauges at oblique angles is utilized. For the fire watch use case, a CVML-enabled technology is utilized that migrates fire watch from a manual (human) approach to automated fire detection. These use cases are mainly intended to give context to the CVML system discussion. This effort assumes the worst-case scenario, with the CVML system being used to replace a safety-related or risk-significant system, thus requiring evaluation. Evaluating CVML against most of the relevant safety requirements for DI&C yielded several CVML-specific considerations due to the uniqueness of its characteristics in comparison with typical DI&C systems. For example, CVML models often employ commonly used (open-source) datasets, and it is not always possible to determine the level of overlap among open-source datasets. Therefore, the independence of the developed CVML models when demonstrating diversity is questionable, therefore creating vulnerability to common cause failure (CCF). The design verification process is also impacted since the data overlap could result in overestimation of the software validation and verification (V&V) performance results. Section 2 of this report evaluates a list of the identified CVML-specific characteristics and discusses the resulting considerations and potential solutions in the context of each referenced requirement. A summation is provided in Section 3. This report is not to be used as a guideline. It was developed to identify and consider issues in the implementation of ML technologies used to augment activities that may have a bearing on plant operation. The report draws parallels to the use of DI&C technologies, for which many standards are available to guide their use in nuclear plant operation. It considers the technologies and some of the potential implications of their use in safety-related applications but is not intended to address regulatory or licensing related issues.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Regulatory Considerations for Nuclear Energy Applications of Digital Twin Technologies

Digital twins (DTs) in complex industrial and engineering applications have potential benefits that include increased operational efficiencies, enhanced safety and reliability, improved security engineering, reduced errors, faster information sharing, and better predictions. The interest in DT technologies continues to grow, and many of these advanced technologies are expected to experience rapid and wide industry adoption in the near future. Some of the potential application areas for DTs in the nuclear industry are design, licensing, plant construction, training simulators, predictive operations and maintenance, autonomous operation and control, failure and degradation prediction, physical protection modeling and simulation, and safety and reliability analyses. The Office of Nuclear Regulatory Research at the U.S. Nuclear Regulatory Commission (NRC) has initiated a future-focused research project to assess the regulatory viability of DTs for nuclear power plants and other NRC-regulated activities, such as fuel cycle facilities and operations. This report explores the potential impact of DT technologies in nuclear applications on NRC-regulated activities of interest. This report describes a nuclear DT system and its capabilities for nuclear power plant applications, followed by identification and discussion of some regulated activities that merit special consideration and present opportunities in implementing DT-enabling technologies and capabilities.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2026

Analysis of Truck Platooning on Rural Highways

An analysis by the National Laboratory of the Rockies on truck platooning technology used on Ohio highways found that truck platooning operated for 40% of driving distances, showcasing its potential to enhance freight efficiency and safety. While energy savings were evident, further optimization of gap distances and operational consistency is needed to fully evaluate fuel savings benefits across diverse driving conditions. While more study is needed, advanced connected and automated vehicle technologies such as platooning demonstrate significant promise for transforming commercial vehicle efficiency and operations.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

Development of Methods for In-line Monitoring of Yield Stress During the Transfer of Radioactive Waste - 20435

Radioactive waste slurries at the Savannah River Site (SRS) and Hanford often behave as non-Newtonian fluids with a yield stress. The yield stress increases the size of equipment needed to transport or mix these slurries and can increase the risk of process upsets. This property is often measured by collection of samples and transportation to a laboratory, which can increase the risk of personnel exposure and even change the rheology. In addition, slurry rheology has been observed to change with time. Real-time in-line monitoring (RTIM) of rheological properties of slurries can have substantial benefits to critical processes which are currently in operation or will be part of future plans in Department of Energy (DOE) complex processes. The need for an appropriate RTIM technology that can potentially minimize or eliminate numerous sampling operations was recently identified. This research at Florida International University focuses on addressing the need for a reliable RTIM technology at US Department of Energy sites. The objective of this work is to investigate and develop appropriate and reliable technologies that can perform accurate and easy measurements of yield stress with minimal changes to the flow conditions at US Department of Energy sites. Use of ultrasound in longitudinal and shear modes was considered as a method for monitoring of yield stress variations with no disturbance to the flow. Measurement of shear wave velocity (in shear mode) and monitoring of sound velocity variations with start of flow from rest (longitudinal mode) are the underlying principles. Measurement of pressure loss and liquid rise (due to static differential pressure) during flow of slurries were two other methods that were considered and investigated. In addition, analysis of stability depth of a penetrometer in slurry medium (penetrometer method) revealed a potential suitability. This paper presents efforts associated with investigation of different methods mentioned earlier for kaolin-water mixtures at different concentrations. Theoretical analysis showed that all methods under investigation were capable of monitoring yield stress in a desirable range of 0 to 70 pascal. A bench scale test setup was constructed for investigation of pressure loss and liquid rise methods. Simulants at different concentrations were created for initial testing campaigns. For ultrasonic testing, effects of yield stress on sound propagation speed in longitudinal and shear modes were investigated for simulants placed inside PVC pipes. Parameters such as simulant concentration and pipe diameter were varied to find optimal values. It was found that spacing (or medium thickness) of 1/8 inch or less was necessary to observe echoes with sufficient strength. In addition, a significant effect of yield stress on sound propagation velocity was observed. For the liquid rise method, kaolin-water simulant at 1.17 specific gravity was pumped through a 1/4 inch pipe and liquid height was measured in a vertical riser branching off a three-way connection. Static gauge pressure was varied within [0.3 to 1.1] psi range by increase of pumping pressure and flow. Results showed consistent yield stress data within 10% deviation from values reported by a rheometer. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

OPERATOR 4.0 FOR HYBRID MANUFACTURING

Hybrid manufacturing, a combination of additive and subtractive manufacturing capabilities in one system, has recently become a more viable production option across several industries. Although current hybrid manufacturing research covers a broad range of topics, there is a lack of focus on how this new technology impacts both the designer and the operator of hybrid systems. This paper identifies areas of literature across design theory and Industry/Operator 4.0 research efforts and presents a path for applying this research to hybrid manufacturing users. The unique relationship between operator and designer is highlighted as they learn new strategies and develop new intuitive judgements over time to become the first experienced/expert users of hybrid manufacturing. The potential impact of excessive cognitive workload due to the novel combination of processes is discussed. This paper begins a critical discussion about proper knowledge transfer to other hybrid designers and operators, as well as towards efforts of monitoring, inspecting, and automating hybrid manufacturing processes.

Fillingim, Blane↗

DOE OSTI2020

Device-Level Multidimensional Thermal Dynamics With Implications for Current and Future Wide Bandgap Electronics

Researchers have been extensively studying wide-bandgap (WBG) semiconductor materials such as gallium nitride (GaN) with an aim to accomplish an improvement in size, weight, and power of power electronics beyond current devices based on silicon (Si). However, the increased operating power densities and reduced areal footprints of WBG device technologies result in significant levels of self-heating that can ultimately restrict device operation through performance degradation, reliability issues, and failure. Typically, self-heating in WBG devices is studied using a single measurement technique while operating the device under steady-state direct current measurement conditions. However, for switching applications, this steady-state thermal characterization may lose significance since the high power dissipation occurs during fast transient switching events. Therefore, it can be useful to probe the WBG devices under transient measurement conditions in order to better understand the thermal dynamics of these systems in practical applications. In this work, the transient thermal dynamics of an AlGaN/GaN high electron mobility transistor (HEMT) were studied using thermoreflectance thermal imaging and Raman thermometry. Also, the proper use of iterative pulsed measurement schemes such as thermoreflectance thermal imaging to determine the steady-state operating temperature of devices is discussed. These studies are followed with subsequent transient thermal characterization to accurately probe the self-heating from steady-state down to submicrosecond pulse conditions using both thermoreflectance thermal imaging and Raman thermometry with temporal resolutions down to 15 ns.

42 ENGINEERING↗

DOE OSTI2025

Beam optics design of a prototype 20 kW conduction-cooled SRF accelerator for medical sterilization

Superconducting technology has significantly advanced the capabilities of particle accelerators, facilitating higher beam-power operations for fundamental research at a comparatively lower cost. However, the conventional implementation of superconducting technology introduces complexities in the form of cryogenic plants, cryogenic distribution systems and substantial construction and operational cost. In response to these challenges, recent research efforts at Fermilab have been dedicated to the development of a cryogen-free, conduction-cooled Nb3Sn-based superconducting technology. This paper outlines the beam optics design of a 20-kW conduction-cooled compact superconducting accelerator for medical sterilization. The paper reviews both the physics and practical constraints associated with high beam-power operation within the context of industrial applications. The focus is on providing insights into the potential of this innovative technology to overcome existing challenges and pave the way for more accessible and efficient industrial particle accelerators.

Saini, A. [Fermilab]↗

DOE OSTI2024

Beam Optics Design of A Prototype 20 kW Conduction-Cooled SRF Accelerator for Medical Sterilization

43 PARTICLE ACCELERATORS↗