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DOE OSTI2022

A stilbene–strontium iodide based radioxenon detection system for monitoring nuclear explosions

Atmospheric measurement of noble gases has been extensively used for monitoring clandestine nuclear weapon explosions for many years. The ratios of four xenon isotopes of interest ( 131 mXe, 133 mXe, 133 Xe, and 135 Xe) help in discriminating regular reactor operations from nuclear tests. A new coincidence-based detection system using stilbene and strontium iodide [SrI 2 (Eu)] for electron and photon detection respectively was developed at Oregon State University to address some of the challenges of the radioxenon systems deployed in the field such as memory effect, and poor energy resolution. Silicon photomultipliers (SiPMs) were used for sensing optical photons from all scintillation media. Real-time coincidence identification was achieved using the eight-channel digital pulse processor. The detection system was evaluated using lab check sources and Oregon State TRIGA reactor irradiated radioxenon samples. A 48-hour background coincidence spectrum was collected yielding a coincidence count rate and background rejection rate of 0.0174 ± 0.0003 counts per second (cps) and 98.9% respectively. The minimum detectable concentration (MDC) of the system was evaluated to be 0.11 ± 0.01, 0.13 ± 0.02, 0.20 ± 0.02, and 0.73 ± 0.08 for 131 mXe, 133 mXe, 133 Xe, and 135 Xe respectively. The memory effect of the detection system was found to be 0.069 ± 0.015%, which is almost a 70-fold reduction compared to traditional plastic scintillators. Here, the detection elements, custom-designed electronics, and the detector response to radioxenon are detailed in this work.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2018

Investigating the interaction between MED5 and CDK8 in Arabidopsis

Plant metabolic networks are precisely regulated by the spatial and temporal expression of suites of genes. Among the various transcription (co)factors, a multi‐protein complex, Mediator has been identified as a hub for transcription regulation. The core Mediator complex, comprising the head, middle and tail domains, functions as a bridge between transcription factors and basal transcription machinery, whereas the CDK8 kinase module plays a repressive regulatory role. It is still unclear, however, how the kinase module represses target genes especially in planta . Using a forward genetic screen, our lab determined that MED5, an Arabidopsis Mediator tail subunit, is required for maintaining phenylpropanoid homeostasis. A semi‐dominant mutant ( ref4‐3 ) characterized by a single amino acid substitution in MED5a (G383S) was isolated as a strong suppressor of phenylpropanoid pathway, indicated by decreased soluble phenylpropanoid metabolite accumulation, reduced lignin content and dwarfism. In contrast, knocking out MED5a and MED5b ( med5a/5b ) results in the accumulation of increased levels of phenylpropanoid pathway derivatives. Considering that the CDK8 kinase module is a repressive module in Mediator, we tested the hypothesis that Arabidopsis MED5 represses phenylpropanoid pathway by interacting with CDK8. To test this hypothesis, CDK8 knockout lines ( cdk8‐1 ) were crossed with ref4‐3 , and the phenylpropanoid content of the resulting double mutants was evaluated. In ref4‐3 cdk8‐1 plants, the concentration of sinapate esters and total lignin content are as low as they are in ref4‐3 , yet the growth defect in ref4‐3 is largely rescued. To further determine the genes targeted by MED5 and CDK8 in maintaining proper plant growth, we performed an RNA‐seq analysis which showed that a majority of the genes involved in salicylic acid (SA) biosynthesis and signaling are up‐regulated in ref4‐3 compared to wild type and ref4‐3 cdk8‐1 . Consistent with this observation, both free and total SA, both of which have been previously implicated in dwarfing in lignin‐modified plants, are accumulated to elevated levels in ref4‐3 but not in wild type and ref4‐3 cdk8‐1 . Nevertheless, blocking SA biosynthesis is not sufficient to restore the growth deficiency of ref4‐3 , suggesting that the hyperaccumulation of SA is more likely to be an effect rather than a cause for its dwarf phenotype. At the molecular level, to elucidate how ref4‐3 regulates downstream gene targets in either a CDK8‐dependent manner, we performed RNA polymerase II (Pol II) ChIP‐seq analysis in wild type, ref4‐3 , cdk8‐1 and ref4‐3 cdk8‐1 . The Pol II ChIP‐seq data may provide additional information for us to identify the genes that are causative for the dwarfism of ref4‐3 . Taken together, this study identifies the genetic interaction between MED5 and CDK8 in Arabidopsis, which enhances our understanding in the function of Mediator in plant metabolism and its role in lignin‐modification‐induced dwarfism. Support or Funding Information Department of Energy; Global Climate and Energy Project This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

Mao, Xiangying↗

DOE OSTI2020

1 K refrigerator for the CLAS12 Polarized Target Design, Construction, and First Results

A dynamically polarized target of protons and deuterons in irradiated NH3 and ND3 will be employed with the CLAS12 detector system to explore the spin structure of the nucleon in Hall B at Jefferson Lab. This target will feature a versatile, horizontal 1 K refrigerator that has been constructed by a collaboration of Christopher Newport University, Old Dominion University, the University of Virginia, and the JLab Target Group. A description of the challenges involved with designing the target for the CLAS12 experiments and the collaboration’s solutions will be presented. These include a modular and compact design of the 1 K refrigerator and its ancillary equipment, as well as a novel mechanism for loading the target samples. Initial test results of the system will also be included.

Brock, James↗

DOE OSTI2023

Uncertainty Aware Deep Learning for Fault Prediction Using Multivariate Time Series Signals

The superconducting radio-frequency cavities are a crucial component of the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. When a cavity faults, beam delivery to experimental end users is disrupted. Prediction of cavity faults prior to onset is essential to reduce operation and maintenance costs. In this work, a parallel long short-term memory (LSTM)-convolution neural network (CNN)-based deep learning (DL) model is proposed to predict impending faults using pre-fault signals. Further, we introduce an uncertainty quantification approach using Monte Carlo dropout with the LSTM-CNN model to ascertain confidence in the prediction. The model was tested using multivariate time series signals from stable cavity operations and before faults. Initial results show that on the test dataset, the model can identify impending faults before their onset with an average 10-fold cross validation accuracy of 97.39% and a standard deviation of 0.12% using a 100-ms time window. It is also observed that the model performs better as the prediction time moves closer to the fault onset. For additional context, we compare the performance of the model with three machine-learning-based (ML) fault prediction models. Our proposed parallel LSTM-CNN-based DL method shows better performance than the ML-based methods.

Rahman, Md Monibor↗

DOE OSTI2018

Testimony to the House Science Space and Technology Committee.

Chairman Smith, Ranking Member Johnson, and distinguished members of the Committee on Science, Space, and Technology, I thank you for the opportunity to testify today on the role of science, engineering, and research at Sandia National Laboratories, one of the nation’s premiere national labs and the nation’s largest Federally Funded Research and Development Center (FFRDC) laboratory. I am Dr. Susan Seestrom, Sandia’s Associate Laboratories Director for Advanced Science & Technology (AST) and Chief Research Officer (CRO). As CRO I am responsible for research strategy, Laboratory Directed Research & Development (LDRD), partnerships strategy, and technology transfer. As director and line manager for AST I manage capabilities and mission delivery across a variety of the physical and mathematical sciences and engineering disciplines, such as pulsed power, radiation effects, major environmental testing, high performance computing, and modeling and simulation.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2022

Machine-Learning-Assisted Enhancement of Perovskite Stability and Photovoltaic Performance

Lab scale perovskite solar cells (PSCs) have reached power conversion efficiencies on par with silicon solar cells. Their potential for low-cost manufacturing combined with high performance make them attractive for commercialization. The major challenge impeding widespread development of PSCs is their stability. Halide perovskites are vulnerable to decomposition in the presence of moisture, oxygen, light, and heat. Furthermore, the chemical differences between halide perovskites and conventional semiconductors used in photovoltaics (e.g., silicon, chalcogenides, and III-V compounds) may render established accelerated lifetime testing protocols inaccurate.

14 SOLAR ENERGY↗

DOE OSTI2025

Boosting efficiency and reducing graph reliance: Basis adaptation integration in Bayesian multi-fidelity networks

The computational cost of high-fidelity numerical models makes outer-loop analysis, which requires repeated interrogation of the model such as uncertainty quantification, computationally demanding. Multi-fidelity methods, which construct a surrogate model using data from an ensemble of models of varying cost and accuracy, can substantially reduce the cost of outer-loop analysis. However, these methods can be difficult to apply when the model ensemble does not admit a clear hierarchy a priori and the correlations between models are low. Consequently, in this paper, we present a multi-fidelity method that leverages dimension reduction to enhance the correlation between models, thereby reducing the amount of data needed to train a surrogate from an unordered ensemble of models. Our method utilizes basis adaptation to build low-dimensional polynomial chaos expansions of each model and employs Multi-fidelity Networks to encode the relationships among models. We show that the resulting method exhibit two notable advantages over its counterpart: (1) enhanced accuracy (both reduced bias and variance); and (2) reduced dependency on the graph structure encoding relationships among models. We demonstrate the approach on an analytical test problem and a challenging finite element model for a spent nuclear fuel. Our method produces a surrogate model that is significantly more accurate than either a single-fidelity surrogate or a multi-fidelity surrogate constructed without basis adaptation.

42 ENGINEERING↗

DOE OSTI2022

Data from: "Lab and Field Warming Similarly Advance Germination Date and Limit Germination Rate for High and Low Elevation Provenances of Two Widespread Subalpine Conifers"

This archive contains data used to draw conclusions in “Lab and Field Warming Similarly Advance Germination Date and Limit Germination Rate for High and Low Elevation Provenances of Two Widespread Subalpine Conifers”, by Kueppers et al. 2017. Cone collection and field experiments were conducted on Niwot Ridge, Colorado, with the latter completed within the Alpine Treeline Warming Experiment (ATWE). Laboratory germination experiments were conducted at the University of California Merced. Geospatial files are also provided for additional geographical context.There are four data file formats in this package: comma-separated values (.csv), Microsoft Excel (.xlsx), keyhole markup language (.kml), and ESRI shapefile (.shp). The latter two are geospatial file formats. .csv files can be opened using any simple text editor program such as TextEdit (Mac) and Notepad (Windows), and .xlsx files can be opened using Microsoft Excel or Google Sheets. The .kml file contains coordinate data, and is compatible with Google Earth and Google Maps. ESRI shapefiles (.shp) are compatible with any geospatial software able to read the file type, such as QGIS and ESRI’s ArcGIS Suite. This data user’s guide is available in as a .pdf, and can be opened using software such as Adobe Acrobat Reader.-----------------------------------------------------------------------------------------------------------------------------------Accurately predicting upslope shifts in subalpine tree ranges with warming requires understanding how future forest populations will be affected by climate change, as these are the seed sources for new tree line and alpine populations. Early life history stages are particularly sensitive to climate and are also influenced by genetic variation among populations. We tested the climate sensitivity of germination and initial development for two widely distributed subalpine conifers, using controlled-environment growth chambers with one temperature regime from subalpine forest in the Colorado Rocky Mountains and one 5 °C warmer, and two soil moisture levels. We tracked germination rate and timing, rate of seedling development, and seedling morphology for two seed provenances separated by ~300 m elevation. Warming advanced germination timing and initial seedling development by a total of ~2 weeks, advances comparable to mean differences between provenances. Advances were similar for both provenances and species; however, warming reduced the overall germination rate, as did low soil moisture, only for Picea engelmannii. A three-year field warming and watering experiment planted with the same species and provenances yielded responses qualitatively consistent with the lab trials. Together these experiments indicate that in a warmer, drier climate, P. engelmannii germination, and thus regeneration, could decline, which could lead to declining subalpine forest populations, while Pinus flexilis forest populations could remain robust as a seed source for upslope range shifts.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

US DOE Regional Test Centers Program - 2016 Annual Report.

The US Department of Energy’s Regional Test Center (RTC) program provides outdoor validation and bankability data for innovative solar technologies at five sites across the US representing a range of climate conditions. Data helps get new technologies to market faster and improves US industry competitiveness. Managed by Sandia National Laboratories and the National Renewable Energy Laboratory (NREL), the RTC program partners with US manufacturers of photovoltaic (PV) technologies, including modules, inverters, and balance-of-system equipment. The study is collaborative, with manufacturers (also known as RTC industry partners) and the national labs working together on a system design and validation strategy that meets a clearly defined set of performance and reliability objectives.

14 SOLAR ENERGY↗

DOE OSTI2021

Materials Challenges and Opportunities for Energy Generation, Conversion, Delivery, and Storage (Applied Energy Tri-Laboratory Consortium Workshop Report)

This report documents the outcomes of the Tri-Laboratory Materials Workshop that was held July 31 and August 1, 2019 to begin addressing the needs, opportunities, and challenges associated with the development, fabrication, and testing of the needed materials and components for integrated hybrid energy systems (i.e., incorporating nuclear, fossil, and renewables for electric and thermal applications). This was accomplished by assembling the research program leads and principal investigators at Idaho National Laboratory (INL), National Energy Technology Laboratory (NETL), and National Renewable Energy Laboratory (NREL), who support the research and development of new technology and system integration. The team then identified and prioritized key materials development needs. This effort was intended to enhance communications and synergy among the Tri-Lab partners. Advanced functional and structural materials are central to transformative energy technologies for energy generation, conversion, delivery, and storage. With that in mind, the workshop focused on identifying and assessing the foundational materials research needs at both the basic and applied levels. Materials challenges include the ability to withstand harsh environments, such as high temperatures and pressures, corrosion, oxidation, or irradiation while maintaining flexible mission profiles and long service lifespans. Advanced energy system material challenges and needs range from materials for the capture, upgrading/concentration, storage, and delivery of low-grade heat to materials for high temperature environments that involve liquid metals, molten salt, and very high temperature gas heat delivery and storage systems. Material improvements are needed for hybrid energy systems due to accelerated corrosion and stress-fatigue failure of materials and equipment, which results from increased frequency and amplitude of thermal, mechanical, and electrical cycling of systems components. Multifunctional materials are needed for high temperature solid-oxide fuel cells, advanced electrochemical reactors, and in-process separation. Relative to materials manufacturing, application of advanced additive and subtractive methods need to be understood to develop both thin-layer homogenous materials and materials of graded composition. Materials modeling and machine learning will be critical to accelerate the design and production of power electronics, and nuclear reactor materials and fuel, as well as to gain an understanding of beneficial materials phenomena or deleterious microstructure evolution. There is also a need for standardized models, computational structures, data reporting protocols and modeling tools across the three laboratories. This would allow consistent results, analysis, and data sharing. Combining computational capabilities between the three laboratories (e.g., hardware, software) would greatly increase computational capabilities and throughput. The workshop identified the need for laboratories to anticipate and address problems that will occur during scale-up. Laboratory work must connect with industry to ensure that research focuses on processes that are scalable and marketable. Industry input and perspective are essential to guide laboratory research to meet these requirements and deploy new technology in industrial demonstrations. Another aspect of scale-up is the integration of multiple systems since new challenges often arise at the subsystem interfaces. Establishing a scale-up manufacturing demonstration/pilot plant, potentially as an industrial user facility, would be beneficial to the laboratories and industry. That modular scale-up manufacturing demonstration/pilot plant would allow researchers to find and resolve interface problems that cannot be identified by focusing only on individual parts. Communication exchanges among the organizers, attendees, and workshop survey responses indicate that the workshop was successful in achieving its goal to identify key technology gaps and research needs. Strong positive feedback was received on the sharing of ideas, capabilities, talent, and passion to move forward on the materials-related action items.

36 MATERIALS SCIENCE↗

DOE OSTI2016

Polarized fusion, its Implications and plans for Direct Measurements in a Tokamak

Our energy-hungry world is burning. A long-term solution, possibly the only ultimate one, that is just approaching the horizon after decades of struggle, is fusion. Recent developments allow us to apply techniques from spin physics to advance the viability of this critical option. The cross section for the primary fusion fuel in a tokamak reactor, D+T /to sigma + n, would be increased by a factor of 1.5 if the fuels were spin polarized parallel to the local field. Simulations predict further non-linear power gains in large-scale machines such as ITER, due to increased alpha heating. These are significant enhancements that could lower the requirements needed to reach ignition and could be used to extend useful reactor life by compensating for neutron degradation of critical components. The potential realization of such benefits rests on the survival of spin polarization for periods comparable to the energy containment time. Interest in polarized fuel options had an initial peak of activity in the 1980s, where calculations predicted that polarizations could in fact survive a plasma environment. However, concerns were raised regarding the cumulative impacts of fuel recycling from the reactor walls. In addition, the technical challenges of preparing and handling polarized materials prevented any direct tests. Over the last several decades, this situation has changed dramatically. Detailed simulations of the ITER plasma have projected negligible wall recycling in a high power reactor. In addition, a combination of advances in three areas - polarized material technologies developed for nuclear and particle physics as well as for medical imaging, polymer pellets developed for Inertial Con nement, and cryogenic injection guns developed for delivering fuel into the core of tokamaks - have matured to the point where a direct in situ measurement is possible. A Jefferson Lab - DIII-D/General Atomics - University of Virginia collaboration is developing designs for a proof-of-principle polarization survival experiment using the isospin mirror reaction, D +3 He /to sigma + p, at the DIII-D tokamak in San Diego.

Sandorfi, Andrew↗

DOE OSTI2023

Development of Laboratory Testbeds Simulating Real-World Greenhouse Gas Emissions [Slides]

In this presentation, I discussed the development of laboratory test beds that simulate field greenhouse gas emissions. Field experiments are used to test new landscape management practices that could reduce greenhouse gas emissions. However, field experiments are very expensive and time consuming. Laboratory experiments are generally more cost efficient and timesaving. There are methods that can be used to make these laboratory tests more closely replicate natural systems for the improvement of agricultural lands used in biofuel and food production. The goal of this project is to develop a laboratory testbed that will mimic field greenhouse gas emissions. To achieve this goal, we used soil cores taken from agricultural and marginal lands, then attached fiberglass wicks to improve the drainage system in the core to simulate a more natural hydraulic system. The combination of using native soils and fiberglass wicks should demonstrate similar greenhouse gas emissions between the lab and the field. Our preliminary results suggest that the carbon dioxide and nitrous oxide flux from the agricultural land site were comparable to the greenhouse soil cores equipped with the drainage wicks. The data suggests that laboratory testbeds can be used to mimic field greenhouse gas emissions if parameters, such as soil water content are in a set range.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

X-Ray Afterglows from the Gamma-Ray Burst “Large-angle” Emission

In this work, we derive basic analytical results for the timing and decay of the gamma-ray burst (GRB) counterpart and delayed afterglow light curves for a brief emission episode from a relativistic surface endowed with angular structure, consisting of a uniform core of size ${\theta }_{c}$ (Lorentz factor ${{\rm{\Gamma }}}_{c}$ and surface emissivity ${i}_{\nu ^{\prime} }^{{\prime} }$ are angle independent) and an axially symmetric power-law envelope (${\rm{\Gamma }}\sim {\theta }^{-g}$). In this "large-angle emission" model, radiation produced during the prompt emission phase (GRB) at angles $\theta \gt {\theta }_{c}$ arrives at the observer well after the burst (delayed emission). The dynamical time range of the very fast decaying GRB "tail" and of the flat afterglow "plateau" and the morphology of the GRB counterpart/afterglow are all determined by two parameters: the core's parameter ${{\rm{\Gamma }}}_{c}{\theta }_{c}$ and the envelope's Lorentz factor index g, leading to three types of light curves that display three post-GRB phases (type 1: tail, plateau/slow decay, post-plateau/normal decay), two post-GRB phases (type 2: tail and fast decay), or just one (type 3: normal decay). We show how X-ray light-curve features can be used to determine core and envelope dynamical and spectral parameters. Testing of the large-angle emission model is done using the Swift/XRT X-ray emission of two afterglows of type 1 (GRB 060607A, GRB 061121), one of type 2 (GRB 061110A), and one of type 3 (GRB 061007). We find that the X-ray afterglows with plateaus require an envelope Lorentz factor ${\rm{\Gamma }}\sim {\theta }^{-2}$ and a comoving-frame emissivity ${i}_{\nu ^{\prime} }^{{\prime} }\sim {\theta }^{2}$; thus, for a typical afterglow spectrum ${F}_{\nu }\sim {\nu }^{-1}$, the lab-frame energy release is uniform over the emitting surface.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Development of an ERT‐Based Framework for Bentonite Buffers Monitoring From Laboratory Tests: 2. Quantitative Moisture Dynamics Estimation Model

Abstract The long‐term containment of high‐level radioactive waste in geological disposal repositories relies on Engineered Barrier Systems (EBS), with bentonite clay emerging as a candidate material due to its unique properties. Understanding moisture dynamics within bentonite buffers is crucial for EBS performance, as it directly influences the material's swelling capacity, thermal and hydraulic conductivity, mechanical properties, and long‐term evolution under complex thermal‐hydrological‐mechanical (THM) processes. This study develops an advanced Electrical Resistivity Tomography (ERT)‐based framework to quantitatively monitor moisture dynamics under THM conditions. Our framework extends the Waxman‐Smits model to incorporate the coupled effects of temperature, water content, fluid chemistry, and mechanical changes on bentonite's electrical properties. Utilizing HotBENT‐Lab data from our companion paper, which includes electrical conductivity, CT density, and thermocouple measurements, this study offers a novel methodological framework bridging different scales of the model. Our results show that the extended model can estimate water content from ERT data, capturing spatial and temporal variations in moisture distribution within bentonite columns. However, the model tends to overestimate water content compared to CT density‐derived measurements. We address this discrepancy by incorporating a simplified swelling effect model, which improves agreement between ERT and CT density‐based water content estimates. We also discuss model limitations, including simplified treatment of swelling and micropore effects, and propose a conceptual framework for transitioning from laboratory to field applications, addressing challenges such as parameter scalability, field validation methods, and integration of diverse data sources. This ERT‐based framework can potentially advance real‐world moisture monitoring of bentonite‐based EBS in nuclear waste repositories. Plain Language Summary Safely containing high‐level radioactive waste depends on barriers made from materials like bentonite clay, which is effective because it swells and seals in the waste. To ensure these barriers work well over time, it's important to understand how moisture moves through the clay. Our study developed a new method using ERT to monitor moisture levels in bentonite under conditions that mimic those in actual storage sites, including changes in temperature, water content, and mechanical stress. This study improved an existing model to better account for how these factors affect the clay, allowing us to create more accurate moisture maps. Initially, the proposed model overestimated the amount of water in the clay, but its accuracy was improved by factoring in how the clay swells when wet. This study also identified some limitations of the model and suggested ways to adapt it for use in real‐world waste storage sites. This new approach could lead to better monitoring and safety checks for nuclear waste storage systems, helping to ensure long‐term containment. Key Points This work develops an ERT‐based framework extending the Waxman‐Smits model to monitor bentonite moisture dynamics during coupled THM processes The extended model accurately estimates water content from Electrical Resistivity Tomography data, incorporating swelling effects to improve precision This work proposes a conceptual framework for transitioning from laboratory to field applications, advancing EBS monitoring in nuclear waste repositories

Chen, Hang↗

DOE OSTI2022

ROAM: A Remotely Operated Accelerator Monitor

Monitoring accelerators in operation is a well known challenge due to the radiation environment. However, there are significant benefits in being able to deploy particular sensors in specific locations of accelerator enclosures for monitoring or troubleshooting purposes. Learning from experience at other labs, we used Commercial Off The Shelf (COTS) components and an open source robot control software framework (ROS) to build a remotely controlled robot platform including a standard suite of instruments such as cameras, LIDAR, and ultrasound, with the ability to incorporate other ad-hoc sensors for specific measurements, such as a Gamma radiation monitor. Special attention was given to the robot's ability to maintain safety in the high risk environment of an accelerator, with multiple failure contingencies in place to ensure collision free operation. Testing was performed to prove the platform's viability and showcase its capability for accelerator monitoring.

Thayer, Thomas C.↗

DOE OSTI2025

Management and Operation of the Oak Ridge National Laboratory

ThermaMatrix, Inc provides novel vision inspection solutions for a wide range of manufacturers and industries, providing and implementing the leading technologies for nondestructive inspection (NDI) and material characterization. Many other inspection solutions are either not adequate or are not approachable due to implementation barriers needing expert level operators, excessive inspection time, and high cost. ThermaMatrix’sadvanced vision inspection technology addresses all of these limitations. The Lab Embedded Entrepreneurial Program (LEEP) opportunity by the Department of Energy (DOE) allows small-business start-ups to leverage national laboratory capabilities and skilled scientists to rapidly develop their technology that aligns with DOE goals. ThermaMatrix, Inc.was positioned in the Innovation Crossroads program at Oak Ridge National Laboratory to further develop thenovel Watson Vision Inspection System to support manufacturing quality control efforts. Theresearch goals were (1) explore fundamental parameters that would improve preexisting capabilities, (2) full-scale industrial setup for demonstration, and (3) capability testing and verification. Manufacturing is demanding more NDI implementation to support their quality control needs, which this technology development would support. Figure 1: Ryan Spencer of ThermaMatrix with Watson Vision Inspection System.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

Field Testing of Safeguards Technologies in the Hot Fuel Examination Facility

Recent developments in nuclear fuel reprocessing techniques have yielded more efficient processes and fuel cycle options that strengthen the nuclear industry and production of clean energy. One such area of interest is pyroprocessing of used oxide fuel. However, with these advances in the back end of the nuclear fuel cycle, advances in safeguards instrumentation, measurements, and approaches are needed to ensure special nuclear material (SNM) is accounted for according to regulatory requirements. As a high-level overview of a nominal pyroprocessing approach, used oxide fuel from commercial light water reactors (LWR) is mechanically removed from the metallic cladding. Then the fuel is crushed and randomized representative samples are taken and sent to an analytical lab for analysis. The analytical results of the feed material are used for input accountancy into the rest of the process. The crushed oxide fuel is then moved to the oxide reduction (OR) furnace where it is reduced from an oxide to metallic form. The OR product is distilled to remove salt and then moved to an electrorefiner (ER), where it is immersed in a eutectic mixture of lithium chloride potassium chloride (LiCl-KCl) that typically ranges between 450-550 ?. Within the ER, the usable uranium is electrochemically transported through the molten salt from the anode to the cathode, and then subsequently removed as a relatively pure U product.. A simplified model of pyroprocessing techniques with added emphasis on the safeguards can be seen below in Fig. 1

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Casing Annulus Monitoring of CO 2 Injection Using Wireless Autonomous Distributed Sensor Networks

Effective and secure carbon subsurface storage, involving the deep underground injection of CO 2 into geological formations where it is permanently trapped, is paramount to mitigating CO 2 emissions (Figure I). Ensuring the integrity of these storage sites and detecting potential leakage through the casing annulus necessitates robust monitoring. This work provides the first integrated demonstration of a wireless casing-annulus monitoring architecture that can operate in highly attenuating cement-brine environments relevant to CO 2 storage. This project focused on developing and validating a novel sensor system for integration with autonomous monitoring near the cement reservoir interface. The goal was a fully integrated Technology Readiness Level (TRL) 4/5 field validation of a distributed wireless intelligent sensor system providing real-time, direct subsurface formation measurements to enhance fluid movement monitoring in the cemented casing annulus. Achieving this objective required the development and integration of 1) wireless autonomous microsensor technology by California Institute of Technology (Caltech); 2) sensor packaging and emplacement technology by Research Triangle Institute (RTI); and 3) smart well completions using wireless active casing collars and NOV pipe by the Sandia National Lab (SNL). The collaboration with the Caltech team in this project aimed to develop millimeter-scale radio frequency identification (RFID) sensors capable of detecting CO 2 , pH, and/or methane levels. These sensors are engineered to be impervious to fluids, allowing them to be mixed with cement and installed within the casing annulus. They operate using RFID protocols at frequencies of 902–928 MHz for both power and communication. A Sandia National Laboratories’ team engaged their expertise in the development of a Smart Collar system designed for the wireless data collection from these RFID sensors embedded in the cement annulus and transmission of this information to the ground surface via IntelliPipe/IntelliServ NOV drill pipe. This is accomplished through inductive coupling at the collar, which facilitates data transfer through each segment of the pipe. Because the system cannot transmit a direct current signal to power the Smart Collar, both power and communication were implemented using alternating current and electromagnetic signals at varying frequencies. Furthermore, the developed microsensor technology had to be demonstrated and validated in comparison with reference transducer measurements in a field test site at The University of Texas at Austin (UT-Austin). Although the full sensor suite did not reach field-deployment readiness, the system-level integration achieved in this project establishes a validated pathway for future incorporation of advanced microsensors.

47 OTHER INSTRUMENTATION↗