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DOE OSTI2024

Characterization of Intrinsic Fiber Optic Temperature Sensors by In-core and Furnace Testing

Increased research and development in nuclear technology has raised the demand for novel sensors and instrumentation to meet data objectives, and survive in different conditions and environments, beyond conventional light water reactor (LWR) environments. Expediting the deployment of advanced nuclear technologies by developing, demonstrating, and qualifying advanced reactor fuel forms necessitates a deeper understanding of how irradiation affects fuels and materials' performance. To achieve a more comprehensive understanding of fuels and materials performance, researchers require more specialized experiments and measurements. The demand for innovative sensors to support nuclear fuel development arises from the complexity of materials' behavior under irradiation and the challenges of deploying instrumentation in Material Test Reactors (MTRs) for irradiation tests. Additionally, measurements of material properties require integrated measurement systems to characterize thermal properties, mechanical properties, chemistry, and microstructure [1]. Among the potential measurement techniques, optical fiber-based sensors have been identified as potential sensors to measure different physical phenomena such as temperature, strain, pressure, and fluid level. Optical fiber sensors have the capability to provide multi-sensing and multiplexing instrumentation, allowing the measurement of different physical parameters within a single sensor configuration, and transmitting data collected at multiple locations through a single fiber. They offer immunity to electromagnetic interference, electrical passivity, compatibility with various sensing methodologies, and cost-effectiveness. Beyond their widespread use in telecommunications, silica fiber-based instruments are utilized in industrial applications, even at temperatures reaching 300?400°C, such as distributed temperature sensing in oil and gas recovery. The Department of Energy (DOE) is interested in using fiber optics to support fuel cycle development [2]. Fiber optics are an excellent candidate for harsh environment sensing, including sensing at very high temperatures (1900oC for sapphire optical fibers). Distributed fiber optic sensing has been deployed in other harsh environments like coal gasification plants [3]. Distributed strain sensing, which operates similarly to distributed temperature sensing, has been deployed to monitor underground mines and fibers have been imbedded in soil to monitor sink-hole development [4][5]. The application of fiber optic sensors to advanced reactor development is a promising area of research.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Filling data analysis gaps in time-resolved crystallography by machine learning

There is a growing understanding of the structural dynamics of biological molecules fueled by x-ray crystallography experiments. Time-resolved serial femtosecond crystallography (TR-SFX) with x-ray Free Electron Lasers allows the measurement of ultrafast structural changes in proteins. Nevertheless, this technique comes with some limitations. One major challenge is the quality of data from TR-SFX measurements, which often faces issues like data sparsity, partial recording of Bragg reflections, timing errors, and pixel noise. To overcome these difficulties, conventionally, large volumes of data are collected and grouped into a few temporal bins. The data in each bin are then averaged and paired with the mean of their corresponding jittered timestamps. This procedure provides one structure per bin, resulting in a limited number of averaged structures for the entire time interval spanned by the experiment. Therefore, the information on ultrafast structural dynamics at high temporal resolution is lost. This has initiated research for advanced methods of analyzing experimental TR-SFX data beyond the standard binning and averaging method. To address this problem, we use a machine learning algorithm called Nonlinear Laplacian Spectral Analysis (NLSA), which has emerged as a promising technique for studying the dynamics of complex systems. In this work, we demonstrate the power of this algorithm using synthetic x-ray diffraction snapshots from a protein with significant data incompleteness, timing uncertainties, and noise. Our study confirms that NLSA is a suitable approach that effectively mitigates the effects of these artifacts in TR-SFX data and recovers accurate structural dynamics information hidden in such data.

Trujillo, Justin (ORCID:0000000285505360)↗

DOE OSTI2021

Evaluation of liquid-phase thermometry in impinging jet sprays using synchrotron x-ray scattering

Liquid thermometry during primary and secondary breakup of liquid sprays is challenging due to the presence of highly dynamic, optically complex flow features. This work evaluates the use of x-ray scattering from a focused, monochromatic beam of the Advanced Photon Source at Argonne National Laboratory for the measurement of liquid temperatures within the mixing zone of an impinging jet spray. The measured scattering profiles are converted to temperature through a previously developed two-component partial least squares (PLS) regression model. Transmitive mixing during jet merging is inferred through spatial mapping of temperatures within the impingement region. In this work, the technique exhibits uncertainties of ±2K in temperature and 2% in capturing the correct scattering profile, showing its potential utility for probing liquid temperature distributions in multiphase flows.

42 ENGINEERING↗

DOE OSTI2022

A radioisotope - enabled reactive transport model for deep vadose zone carbon

In mountainous regions, which constitute the principle source of recharge to major rivers and regional aquifers, infiltration occurs through fractured, partially saturated, weathered bedrock that acts as a boundary layer between saturated aquifers and surface soil. Commonly this deep vadose zone (DVZ) is many meters thick, and yet its role in regulating the generation, retention and mobility of reactive solutes, including nutrients, contaminants and weathering products, is largely unknown. In particular, many of the key reactions that drive the formation of the weathered DVZ and the quality of water moving through it are redox processes, regulated by the availability of organic carbon and oxygen below the soil layer. The role of the DVZ is thus also poorly constrained in the context of carbon stocks and mobility, particularly in lithologies that are naturally high in organic carbon, such as shales. The overarching hypothesis of this study is that upland regions developed in geologic settings with abundant petrogenic carbon store and actively cycle carbon in the weathered DVZ below the soil and above the water table at rates that are significant and currently unconstrained. In order to quantify this cycling, the current study combines novel instrumentation techniques allowing new direct sampling of DVZ systems with advanced numerical reactive transport simulations of carbon transport and transformation. Critically, these simulations will explicitly treat the three isotopes of carbon (the abundant 12C, the stable rare 13C and the radioactive 14C) in a unified framework, thus clearly parsing between the contributions of modern surface derived carbon and lithologic carbon sources in integrated measurements of fluid and gas phase fluxes. This novel model capability will be applied to test the role of DVZ carbon cycling as a regulator of water quality and geological weathering in two complementary field sites both located in organic carbon rich shale lithologies. The first is the Eel River Critical Zone Observatory (ERCZO) in Mendocino County, California, and the second is the Lawrence Berkeley National Laboratory Watershed Function Scientific Focus Area (SFA) in the East River watershed, near Crested Butte, Colorado. At the ERCZO, a novel vadose zone monitoring system has been installed in a 20 m thick, partially saturated, weathered shale hillslope, and preliminary data already indicate substantial CO2 flux generated many meters below the soil surface. At the SFA field site, an instrumented hillslope transect indicates a more complex multi-dimensional fluid and solute transport regime, which will serve as a key test of the calibrated models. Collectively, this project will advance understanding of the cycling of carbon belowground and in relation to transport pathways across the poorly constrained DVZ characteristic of primary water recharge areas. The key product of this work will be enhanced isotope simulation capabilities that are robust and publicly available for application across a broad diversity of systems.

58 GEOSCIENCES↗

DOE OSTI2025

Application of Electrochemical Methods to Molten Salt Reactors: Draft TLR Documenting Assessment of Electrochemical Monitoring

Nuclear Regulatory Commission (NRC) is developing the regulatory framework and technical expertise to support regulatory review of advanced non-water reactors, including molten salt reactors (MSRs). In an MSR, it is essential that the salt chemistry be maintained in a desired range in terms of redox potential for reliable operation and mitigation of corrosion to structural materials in the reactor, particularly the reactor vessel and heater exchanger. Measuring the redox potential of the salt in the reactor would also allow for the material lifetimes to be predicted more accurately, and chemical issues to be diagnosed more quickly. In addition to the chemical composition analysis by ICP-MS, electrochemical methods including potentiometry and linear wave scanning (LSC) were also used in molten salt reactor experiment (MSRE) for redox potential monitoring purposes. Electrochemcial methods offers unique advantages such as quick turnaround in results and unique capability of in-line monitoring of redox potential, and are considered popular electroanalytical techniques that can be used to monitor redox potentials and salt chemistry including impurities. The last two decades have seen significant advances in science and engineering of electrochemical methods for potential application to molten salts. The primary goal of this report is to assist NRC in understanding the monitoring of the salt chemistry by electrochemical methods and provide NRC reviewers with necessary information and tools to support regulatory review of MSR designs. This reports consists of two majors parts—Part 1, chemical potential of molten salts and effects by fission process in MSR; Part 2, assessment of electrochemical methods for application to MSRs. The TRLs of the typical relevant electrochemical methods for molten salts were evaluated based on the DOE TRL guidelines and upon a review of the current status of the electrochemical methods for two typical salt systems, fluoride and chloride, for MSRs.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Current challenges in hydrate‐based desalination: Kinetic and thermodynamic perspective

Abstract Water scarcity is becoming a severe problem worldwide due to inadequate freshwater resources and swift population growth. Seawater desalination is one of the vital approaches to meet the demand for freshwater. However, energy and associated costs with conventional seawater desalination techniques are incentivizing non‐conventional water desalination processes. Water desalination using gas hydrates formation is one of the emerging non‐conventional processes. In this perspective article, recent advances in hydrate‐based seawater desalination (HBSD) have been critically analyzed to outline a future path towards a clean and efficient hydrate‐based desalination process. It provides a detailed comparison of various processes developed over decades, and measured desalination efficiencies with their process details. Moreover, the current challenges, limitations, and future perspectives of hydrate‐based desalination are also discussed. The study also recapitulates the thermodynamics and kinetics aspects of the hydrate‐based desalination process. In addition, various factors controlling the desalination efficiencies, such as control of the separation of hydrate crystals, salt deposition on hydrate particles, and hydrate morphology, were thoroughly investigated with their proposed process designs. The kinetics of hydrate formation is also assessed, with the possibility of a zero‐induction regime and its consequent impact on hydrate morphology. The current capabilities of the thermodynamics models (Gibbs energy minimization + electrolyte equation of state) were discussed using various commercially available software. Additionally, the role of hydrate promotors is also discussed, which can reduce the higher cost associated with the hydrate‐based desalination process.

Khan, Muhammad Naveed↗

DOE OSTI2021

Multisensor Agile Adaptive Sampling of Convective Storms Driven by Real-time Analytics

Convective storms vertically transport water vapor and condensate from Earth’s surface to the upper troposphere. Life on Earth is fundamentally linked to this transport which determines the hydrological cycle, and the intensity of severe weather responsible for the destruction of life and property. Despite advances in high-resolution modeling and better observational capabilities, the scientific community continues to be confronted with knowledge gaps about convective storms that limit our predictive capabilities. The ongoing developments in the high-resolution Energy Exascale Earth System Model (E3SM), large eddy simulations, and AI-based analytics to evaluate uncertainties are expected to provide a comprehensive framework for new scientific discovery. The model-experiment (MODEX) approach suggests that the aforementioned advancements in model development and AI-based inference techniques should be complemented by similar advancements in the experimental (observational) side so that the former does not outstrip the ability of the latter to provide meaningful constraints. What are the recent advancements in observations that will provide the necessary leap forward in improving our predictive capabilities? To address this question, we propose a new experimental paradigm called Multisensor Agile Adaptive Sampling (MAAS) that capitalizes on advancements in communications (5G), computational resources (edge/fog computing), sensor capabilities, and machine learning (ML) and AI techniques (Kollias et al., 2020). The MAAS framework allows for the collection of higher spatiotemporal resolution and quality observations of convective storms than is traditionally possible. The MAAS framework is scalable and applicable to atmospheric observatories such as those operated by the Department of Energy (DoE) Atmospheric Radiation Measurement (ARM) facility.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Performance of Embedded Sensors in 3D Printed SiC

This report summarizes recent advances in embedding sensors in 3D printed silicon carbide (SiC) ceramic components under the Transformational Challenge Reactor (TCR) program. The additive manufacturing technologies developed under this program will enable fabrication of complex structures with embedded fuels and sensors. The sensors will be capable of characterizing fuel performance using spatially distributed measurements at the most strategic locations that would be otherwise inaccessible using conventional manufacturing techniques. While previous programmatic updates describe initial concepts for embedding sensors, materials selection, and initial characterization of the embedded sensors, the technology requires further demonstration, and quality-significant procedures must be established before the embedding technology is ready for adoption by industry. To this end, this report describes the most effective techniques that have been used to embed functional sensors in 3D printed components using a combination of binder-jet additive manufacturing and chemical vapor infiltration (CVI). A detailed procedure describes each step in the process and is available upon request. Molybdenum (Mo)-sheathed thermocouples have been successfully embedded in complex SiC components, and temperatures were monitored in situ during the embedding process. Post-embedding measurements showed no significant hysteresis, and characterization of the interface revealed qualitatively strong bonding around the entire perimeter of the sensor sheath. Distributed fiber-optic temperature sensors were able to briefly measure temperature profiles during CVI, but they ultimately failed prior to completion of the CVI run. The failure appears to be related to the fiber coating at temperatures close to 1,000°C. Future work will focus on irradiation testing of embedded thermocouples and other sheathed electrical sensors, as well as the identification of fiber-optic sensor coatings that can survive CVI.

42 ENGINEERING↗

DOE OSTI2024

Enhancing Biopreparedness through a Model System to Understand the Molecular Mechanisms that Lead to Pathogenesis and Disease Transmission: NW-BRaVE

The science of biopreparedness to counter biological threats hinges on understanding the fundamental principles and molecular mechanisms that lead to pathogenesis and disease transmission. Our vision to address this challenge is to create a powerful and user-friendly platform to elucidate the fundamental principles of how molecular interactions drive pathogen-host relationships and host shifts. We will enable groundbreaking discoveries by integrating a wide range of structural, genomics, proteomics, and other advanced omics measurements, along with evolutionary and artificial intelligence predictions. To make sure the system is applicable to real-world problems, we will develop it in the context of a tractable model system, the small, abundant, and accessible photosynthetic cyanobacteria and their constantly co-adapting viral pathogens, cyanophages. This model will maintain the system’s applicability to real-world problems and techniques, but the overall focus will be on elucidating general principles of detecting, assessing, and surveilling molecular interaction, adaptation, and coevolution that are system agnostic and therefore extensible to other viral-host interactions. Our overall objectives are to (1) identify the molecular complexes that comprise the cyanobacteria redox macromolecular subsystem and how they dynamically change with bacteriophage infection in situ, using cryo-electron tomography; (2) profile regulatory changes during infection using proteomics, multiomics, and experimental validation, and integrate the data with in situ structures; (3) use genomics and metagenomics to determine environmental and population factors across time scales that impact the interactions between marine cyanobacteria and their cyanophage parasites, predicting the evolutionary origins of in situ structural and functional interactions, convergence and coevolution; and (4) develop a data integration and transformation platform that facilitates the integration of in situ, proteomic, and evolutionary measurements of molecular interactions to surveil diverse hosts and parasites in various environmental contexts. These objectives address Focus Area 2 Reveal Molecular Interactions Across Biological Scales for Design of Targeted Interventions. Our powerful and user-friendly platform will enhance connections between the often-siloed fields of structure, molecular phenotype, and evolutionary genomics that are key to biopreparedness, but in need of integration (Figure 1). We will build an integrated navigation tool to facilitate the effective use of globally distributed experimental data for integrated analysis and predictive modeling. The project will develop, implement, and test a platform to assess host-pathogen molecular interactions, adaptation to hosts and host shifts, and coevolution between hosts and pathogens, successfully impacting the research community by revolutionizing abilities to study any host-pathogen interaction, encourage diverse community contributions, and gain fundamental insights into how proteins adapt to new contexts. This ability will be critical for designing early interventions to address future threats. We will build surveillance training capability, aiming for a fair and equitable response to future pandemics and biothreats.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Real-Time Artificial Intelligence for Particle Reconstruction and Higgs Physics

With the discovery of the Higgs boson at the CERN LHC, the world's highest-energy particle accelerator complex, scientists have acquired an important tool to study the fundamental building blocks of the universe. Precision measurements of Higgs bosons produced with large momentum allow for unique insights into the structure of the interactions of the Higgs boson with other particles that may shed light on physics beyond the standard model. While experimentally challenging, exploring such interactions with novel artificial intelligence (AI) methods can advance our understanding of the Higgs sector, including the Higgs boson's self-interaction. Moreover, the LHC is undergoing a major upgrade to further increase its particle collision rate and thereby operate for an additional decade. The experimental detectors at the upgraded facility must process at least a factor of ten more data at rates of hundreds of terabytes per second all under challenging conditions. New AI techniques are required to reconstruct and select, or trigger on, the most physics-sensitive events in real-time to handle the resulting avalanche of data. The proposed research will achieve the goals of the LHC program at the CMS experiment by developing a sub-microsecond event reconstruction system using real-time AI algorithms that employ field-programmable gate array technologies. By harnessing sophisticated AI techniques, this research focuses on measuring the production of Higgs bosons at large momentum while enhancing particle reconstruction methods in the trigger and beyond. Overall, the proposed research has broader implications for the use of AI in resource-constrained, low-latency embedded applications across all fields of science.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Investigation of the thermal conductivity of molten LiF-NaF-KF with experiments, theory, and equilibrium molecular dynamics

Molten salts are being proposed for numerous advanced energy applications, including advanced nuclear reactors, concentrating solar power plants, thermal energy storage, and fusion reactors. Accurate knowledge of the thermophysical properties of molten salts directly impact the performance of these energy systems and are essential for design and safety analyses. Thermal conductivity data for fluoride molten salts and mixtures are especially lacking. In this work, experimental measurements of thermal conductivity using the steady-state variable gap technique were performed on eutectic LiF-NaF-KF from 834 to 1195 K. The experiment accounts for radiative, convective, and conductive heat losses. In addition, theoretical and molecular dynamics models are used, from 750 K up to 1300 K, to estimate the thermal conductivity for comparison with the experimental results. The results of experiments show a weak negative deviation of thermal conductivity with temperature, unlike previous experimental results in the literature. The measured thermal conductivity magnitudes agree with the theoretical and molecular dynamics predictions, aside from the data above 1100 K, where heat losses and radiative errors are the most significant, having a 16% maximum deviation from theory. These experimental results provide new thermal conductivity data for the LiF-NaF-KF system and further validation of the predictive models. The theoretical model was used to map the composition and temperature dependent thermal conductivity of LiF-NaF-KF and the mapping’s deviation from a linear additivity estimation of thermal conductivity. Additionally, this mapping showed the highest deviations from linearity for KF-LiF rich mixtures and increasing deviation with temperature. Notably, the deviation from linearity near the LiF-NaF-KF eutectic composition was around 25%.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Young’s modulus of V 3 O 5 thin films

Vanadium oxide V 3 O 5 exhibits an insulator-to-metal transition (IMT) near 430 K, which is the highest value for all vanadium oxides exhibiting IMTs. This makes it interesting for advanced electronic applications. However, the properties of V 3 O 5 have been little studied, and, in particular, there are no reports of experimentally determined mechanical properties. In this work, Young’s modulus of sputter-deposited V 3 O 5 thin films has been determined by measuring the fundamental resonant frequency of V 3 O 5 -coated silicon microcantilevers using a laser beam deflection technique. After deposition, the films were characterized by x-ray diffraction, resistivity measurements, and atomic force microscopy. The value of Young’s modulus experimentally determined for V 3 O 5 was 198 ± 14 GPa, which is slightly lower than the computationally derived values for bulk crystal V 3 O 5 .

36 MATERIALS SCIENCE↗

DOE OSTI2020

Momentum-resolved superconducting energy gaps of Sr 2 RuO 4 from quasiparticle interference imaging

Sr 2 RuO 4 has long been the focus of intense research interest because of conjectures that it is a correlated topological superconductor. It is the momentum space ( k -space) structure of the superconducting energy gap Δ i ( k ) on each band i that encodes its unknown superconducting order parameter. However, because the energy scales are so low, it has never been possible to directly measure the Δ i ( k ) of Sr 2 RuO 4 . In this work, we implement Bogoliubov quasiparticle interference (BQPI) imaging, a technique capable of high-precision measurement of multiband Δ i ( k ). At T = 90 mK,we visualize a set of Bogoliubov scattering interference wave-vectors q j : j = 1 – 5 consistent with eight gap nodes/minima that are all closely aligned to the (±1, ±1) crystal lattice directions on both the α and β bands. Taking these observations in combination with other very recent advances in directional thermal conductivity, temperature-dependent Knight shift, time-reversal symmetry conservation, and theory, the BQPI signature of Sr 2 RuO 4 appears most consistent with Δ i ( k ) having d x 2 – y 2 ( B 1 g ) symmetry.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Criegee intermediates: production, detection and reactivity

In the context of tropospheric chemistry, Criegee intermediates denote carbonyl oxides with biradical/zwitterionic character (R 1 R 2 COO) that form during the ozonolysis of alkenes. First discovered almost 70 years ago, stabilised versions of Criegee intermediates formed via collisional removal of excess energy have interesting kinetic and mechanistic properties. The direct production and detection of these intermediates were not reported in the literature until 2008. However, recent advances in their generation through the ultraviolet irradiation of the corresponding diiodoalkanes in excess O 2 and detection by various spectroscopic techniques (photoionisation, ultraviolet, infrared, microwave and mass spectrometry) have shown that these species can react rapidly with closed-shell molecules, in many cases at or exceeding the classical gas-kinetic limit, via multiple reaction pathways. These reactions can be complex, and laboratory measurements of products and the temperature and pressure dependence of the reaction kinetics have also revealed unusual behaviour. The possible role of these intermediates in atmospheric chemistry is significant, altering models of the oxidising capacity of the Earth's atmosphere and the rate of generation of secondary organic aerosol.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Experimental neutrino physics in a nuclear landscape

There are profound connections between neutrino physics and nuclear experiments. Exceptionally precise measurements of single and double beta-decay spectra illuminate the scale and nature of neutrino mass and may finally answer the question of whether neutrinos are their own anti-matter counterparts. Neutrino–nucleus scattering underpins oscillation experiments and probes nuclear structure, neutrinos offer a rare vantage point into collapsing stars and nuclear fission reactors and techniques pioneered in neutrino nuclear physics experiments are advancing quantum sensing technologies. In this article, we review current and planned efforts at the intersection of neutrino and nuclear experiments. This article is part of the theme issue ‘The liminal position of Nuclear Physics: from hadrons to neutron stars’.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Survey of spatio-temporal couplings throughout high-power ultrashort lasers

The investigation of spatio-temporal couplings (STCs) of broadband light beams is becoming a key topic for the optimization as well as applications of ultrashort laser systems. This calls for accurate measurements of STCs. Yet, it is only recently that such complete spatio-temporal or spatio-spectral characterization has become possible, and it has so far mostly been implemented at the output of the laser systems, where experiments take place. In this survey, we present for the first time STC measurements at different stages of a collection of high-power ultrashort laser systems, all based on the chirped-pulse amplification (CPA) technique, but with very different output characteristics. This measurement campaign reveals spatio-temporal effects with various sources, and motivates the expanded use of STC characterization throughout CPA laser chains, as well as in a wider range of types of ultrafast laser systems. In this way knowledge will be gained not only about potential defects, but also about the fundamental dynamics and operating regimes of advanced ultrashort laser systems.

Jeandet, Antoine (ORCID:0000000345493067)↗

DOE OSTI2026

Online and Offline Analytical Techniques to Quantify Chloride Salts

This report serves as the deliverable for Milestone- M3FT-26AN080502017: Summary of Accomplishments for Online and Offline Analytical Qualification of Chloride Fuel Salts. The qualification of chloride fuel salts is a critical challenge for the development and deployment of molten salt reactors (MSRs), requiring precise control and verification of chemical and isotopic composition to ensure predictable neutronics, manageable radiological behavior, and safe plant operation. Currently, there is no universally accepted standard for fuel salt qualification, particularly for chloride-based systems, which underscores the need for robust, science-based analytical methodologies. This report presents a comprehensive evaluation of both online and offline techniques for quantifying chloride fuel salts, including multielectrode array voltammetry, differential thermal analysis (DTA) probes, inert gas fusion (IGF) analyzers, and gamma spectrometry using the Mirion NAIS-2x2 NaI(Tl) detector. The integration of these methods enables real-time monitoring of actinide concentrations, redox state, and thermophysical properties, as well as high-precision measurement of impurities and isotopic composition. The acquisition of advanced instruments such as the Bruker Leonardo G6 for IGF and the Mirion NaI detector enhances analytical capabilities, supporting the establishment of operational envelopes and impurity thresholds. These approaches provide essential data for neutronic impact evaluation, feedstock documentation, and compliance with nuclear safety standards. The methodologies developed and validated in this report lay the groundwork for future standardized protocols, bridging the gap between laboratory research and commercial reactor operation, and advancing the safe and efficient deployment of chloride-fueled MSRs.

Polke, Amber↗

DOE OSTI2024

Advanced Power Electronics and Electric Machines

The advanced power electronics and electric machines (APEEM) research group at the National Renewable Energy Laboratory (NREL) has developed world-class experimental and modeling capabilities for designing and evaluating efficient and reliable power electronics and electric machines thermal management systems. They also design, fabricate and characterize advanced power electronics packaging, and are developing state-of-health monitoring techniques. These researchers deliver safe, reliable, high performing, power-dense components that allow seamless integration between renewable energy sources, electric transportation, and the grid, helping to make widespread electric vehicle (EV) adoption and greenhouse gas emissions reduction more feasible. This document outlines the group's major capabilities in the areas of power electronics; module development and characterization; thermal modeling and management; thermomechanical reliability analysis of devices, modules, inverters/converters, and electric machines; physics-of-failure-based reliability analysis; and microelectronics. It also overviews the group's state-of-the-art equipment for fluid-based thermal management; thermal measurement & characterization; thermomechanical reliability analysis; micro- and power electronics measurement & characterization; and prototype fabrication, as well as the group's world-class modeling and simulation capabilities.

advanced gate drivers↗