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At least 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Physical and Thermomechanical Properties of Yttrium Hydride from Large Scale Bulk Metal Hydriding Furnace

Given the superior thermal stability and highly attainable hydrogen density, yttrium hydride is an excellent high-temperature moderator material in advanced thermal neutron spectrum reactors that require small core volumes. Yttrium hydride has been selected as the moderator material for the Transformational Challenge Reactor, which was launched at Oak Ridge National Laboratory (ORNL) in 2019. However, fabrication of large-scale crack-free yttrium hydride is challenging and very limited efforts have been committed to the characterization of bulk yttrium hydride in response to the need to establish a complete database of the thermomechanical properties of YHx. In this report, the challenges associated with fabricating large-scale crack-free yttrium hydride are discussed herein. In response to those challenges, a hydriding system was designed and constructed at ORNL and was used to successfully fabricate crack-free yttrium hydride in complex geometries at large scales. This was accomplished by precisely controlling the hydrogen’s partial pressure and the retort temperature, which was informed by the well-established thermodynamic properties of the binary H-Y system. Hydrogen content in as-fabricated hydride was determined by the weight change method and vacuum hot extraction technique, complemented by the X-ray diffraction (XRD). In addition, significant efforts are being dedicated to establishing a complete database of the thermomechanical properties of as-fabricated yttrium hydride. In FY2020, we investigated the thermophysical properties of yttrium hydrides as a function of temperature (room temperature to 700°C) and hydrogen concentration (H/Y ratio ranges from 1.52 to 1.93). The results indicate that at the temperatures below 300 °C, the hydrogen content did not have a significant influence on the thermal expansion, while the specific heat capacity, the thermal diffusivity, and the calculated thermal conductivity were slightly higher for the higher H/Y ratio. Between 300°C and 700 °C, a reversible second-order endothermic transition in all measured thermal properties was observed. It was also found that the onset temperatures of the observed transition varied, with the composition having inverse dependence on the hydrogen content. An attempt was made to explain the behavior of the thermophysical properties at higher temperatures by considering the order– disorder transition as a result of hydrogen redistribution. In addition, nanoindentation was employed to determine the elastic modulus and hardness and to capture the crystal orientation dependence of these parameters. Vickers hardness was also reported. The final section of the report introduces ongoing neutron irradiation campaign of yttrium hydride.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

A Multi-Scale Computational Platform for Predictive Modeling of Corrosion in Al-Steel Joints (Final Report)

The research team proposed to develop innovative multi-scale models to predict corrosion and the resulting mechanical performances in aluminum-steel joints. The methods of joining considered are resistance spot welding, self-piercing riveting, and rivet-welding, all suitable for mass production applications. The multi-scale models integrate high throughput first-principle calculations based on density functional theory (DFT), high throughput calculation of phase diagrams (CALPHAD) modeling, and finite element method (FEM) simulations. These models are to be validated through laboratory experiments. Furthermore, the models are available as open source so as to enable scientists and engineers in the community to adapt and contribute to the development and application. The approaches rely on the research team’s extensive experience on the prediction of properties of individual phases at finite temperatures and variable compositions through DFT calculations, and our broad expertise on dissimilar material joining and their corrosion. The proposed computational framework enables high throughput computations for improved predictions of corrosion and the associated mechanical performance in dissimilar material joints, resulting in significant reduction in computational time needed by the current state-of-the-art methods. With the participation of researchers from three universities, an auto manufacturer, two manufacturing technology/equipment suppliers, and a software developer/vendor, the interdisciplinary research team applies the technical development on both phase-based modeling and laboratory experiments into the automobile body joining processes for validation and technology demonstration. The global cost of corrosion was estimated at about 3.4% of the global GDP in 2013. By using available corrosion control practices, it is estimated a saving between 15-35% of the cost of corrosion. In the U.S., more than $276 billion is spent repairing corrosion damage. Prediction of the corrosion and its impact on performance of the dissimilar material joints is critical for reducing the massive number of the current corrosion-based recalls for automobiles. Thus, the project goal is to develop models to enable predictive maintenance and end-of-life planning of multi-metal joints with risk of corrosion under different conditions such as exposure to high temperatures in summer and salt solutions in winter, quantified through its pH. An academia-industry consortium led by the University of Michigan and including Pennsylvania State University, University of Illinois Urbana-Champaign, University of Georgia, General Motors Company, Livermore Software Technology Corporation, and Optimal Process Technologies, LLC. created multi-scale models for prediction of corrosion in aluminum-steel joint structures such of them used in vehicle subassemblies – chassis and transmission systems. Starting from the first principle calculations, the team developed mathematical and data-driven models to predict the metallic components, which are formed during joining of two metals, for example aluminum and steel - a lightweight multilateral system which is currently used in more than 60% car bodies. These models were used for simulating chemical reactions that are happening when the joining metallic components are exposed to high temperatures and different pH values. The team was able to predict how the corrosion installs on the metallic components and how they lead to a sudden failure of components in cars. Newly developed machine learning algorithms combining Science, Technology, Engineering and Math disciplines, advanced finite element simulation and experimental validations have been integrated in a platform for prediction of the corrosion evolution and prediction the failure of joints under mechanical loadings and fatigue. Moreover, based on machine learning and inverse analysis, the team proposed solutions for designing new metallic alloys less susceptible to corrosion when joining multi-material assembles. An average of 4% error compared with experiments was achieved for the most common joints that are used in vehicle subassemblies.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A Call to Arms Control: Synergies between Nonproliferation Applications of Neutrino Detectors and Large-Scale Fundamental Neutrino Physics Experiments (A Snowmass White Paper)

The High Energy Physics community can benefit from a natural synergy in research activities into next-generation large-scale water and scintillator neutrino detectors, now being studied for remote reactor monitoring, discovery and exclusion applications in cooperative nonproliferation contexts. Since approximately 2010, US nonproliferation researchers, supported by the National Nuclear Security Administration (NNSA), have been studying a range of possible applications of relatively large (100 ton) to very large (hundreds of kiloton) water and scintillator neutrino detectors. In parallel, the fundamental physics community has been developing detectors at similar scales and with similar design features for a range of high-priority physics topics, primarily in fundamental neutrino physics. These topics include neutrino oscillation studies at beams and reactors, solar, and geological neutrino measurements, supernova studies, and others. Examples of ongoing synergistic work at U.S. national laboratories and universities include prototype gadolinium-doped water and water-based and opaque scintillator test-beds and demonstrators, extensive testing and industry partnerships related to large area fast position-sensitive photomultiplier tubes, and the development of concepts for a possible underground kiloton-scale water-based detector for reactor monitoring and technology demonstrations. Some opportunities for engagement between the two communities include bi-annual Applied Antineutrino Physics conferences, collaboration with U.S. National Laboratories engaging in this research, and occasional NNSA funding opportunities supporting a blend of nonproliferation and basic science R&D, directed at the U.S. academic community.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Enabling Predictive Scale-Bridging Simulations through Active Learning (Institutional Computing Annual Report (Project w21_alscalebridging)) [Slides]

The goal of this project was to develop, demonstrate, and provide a new capability to achieve greater physical fidelity in large-scale simulations, rather than the usual brute-force increases in the number of mesh elements or particles. Transport in nanoporous media, critical to hydrocarbon extraction from tight shale formations, is affected by molecular-level interactions. Several coarse-scale Lattice Boltzmann model (LBM) parameters cannot be directly computed, so instead we calibrate them to molecular dynamics (MD) simulations, by building emulators that mimic MD and LBM behavior and then training an upscaler. The resulting machine learning (ML)-based scale-bridging framework is up to 7 orders of magnitude faster than direct MD.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

Enabling Predictive Scale-Bridging Simulations through Active Learning (Institutional Computing Annual Report (Project w20_alscalebridging)) [Slides]

The goal of this project was to develop, demonstrate, and provide a new capability to achieve greater physical fidelity in large-scale simulations, rather than the usual brute-force increases in the number of mesh elements or particles. This was done by using machine learning (ML) techniques to develop emulators for subscale physics that can be used in coarse-scale continuum simulations, trained on fine-scale molecular dynamics (MD) simulations that are launched on-the-fly via active learning. raditional inertial confinement fusion (ICF) simulations rely on numerical diffusion to simulate molecular effects such as non-local transport and mixing without truly accounting for molecular interactions; our approach directly accounts for this physics.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Centers for Disease Control and Prevention (CDC) Radiation Hazard Scale (Expanded Data Product Feedback Report)

During radiation emergencies, it is important to communicate clearly as radiation risks are often unfamiliar to many members of the general public and emergency responders, including public health workers. To partially address this issue, the Centers for Disease Control and Prevention (CDC) developed the Radiation Hazard Scale to communicate radiation risk to the general public, community leaders, and decision makers. The simple numeric scale does not require a background in radiation physics or health effects and can be used to assist people in understanding their risk and motivate protective action compliance. Lawrence Livermore National Laboratory has assisted the US Department of Energy National Nuclear Security Administration and the CDC in the development of Radiation Hazard Scale data products. This report documents the feedback received from Federal response officials on an expanded data product set. This expanded set accounts for the effects of building protection on radiation exposure and allows for the comparison between different response actions, including sheltering in place, based on the LLNL developed Regional Shelter Analysis methodology.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Using the Criticality Accident Alarm System modeling capabilities in SCALE [Slides]

The following is a summary of advice for CAAS modeling in SCALE. Refer to the SCALE Criticality Safety and Radiation Shielding training slides or to the SCALE manual for exact syntax. Use a mesh for the fission source that is the most adequate for the problem to solve (coarse/fine). Don’t spend unnecessary resources; simplify the model if it does not impact the final results of interest. Be careful to deactivate secondary fissions in MAVRIC or the calculation may never end. Check that k eff and $\overline{\upsilon}$ calculated results are logical. Between KENO and MAVRIC, cross section libraries, materials, geometry, and mesh grid can be the same or different. Iterative calculations are usually complex problems that need variance reduction. It will be hard to find the best solving parameters in the first attempt; expert judgement is needed. Check each step separately. Use Fulcrum to visualize fission source, mesh source, and spatial/energy distributions to find potential errors or impactful imprecisions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

The Strange Case of Ground-Coupled Airwaves on Seismoacoustic Stations at Local to Near-Regional Scales

Here we investigate the application of ground-coupled airwaves observed by seismoacoustic stations at local to near-regional scales to detect signals of interest and determine back-azimuth information. Ground-coupled airwaves are created from incident pressure waves traveling through the atmosphere that couple to the earth and transmit as a seismic wave with retrograde elliptical motion. Previous studies at sub-local scales (<10 km from a source of interest) found the back-azimuth to the source could be accurately determined from seismoacoustic signals recorded by acoustic and 3-component seismic sensors spatially separated on the order of 10 to 150 m. The potential back-azimuth directions are estimated from the coherent signals between the acoustic and vertical seismic data, via a propagation-induced phase shift of the seismoacoustic signal. A unique solution is then informed by the particle motion of the 3-component seismic station, which was previously found to be less accurate than the seismoacoustic-sensor method. We investigate the applicability of this technique to greater source-receiver distances, from 50-100 km and up to 400 km, which contains pressure waves with tropospheric and stratospheric ray paths, respectively. Specifically, we analyze seismoacoustic sources with ground truth from rocket motor fuel elimination events at the Utah Test and Training Range (UTTR) as well as a 2020 rocket launch in Southern California. From these sources we observe evidence that while coherent signals can be seen from both sources on multiple seismoacoustic station pairs, the determined ground-coupled airwave back-azimuths are more complicated than results at more local scales. Our findings suggest more complex factors including incidence angle, coupling location, subsurface material, and atmospheric propagation effects need to be fully investigated before the ground-coupled airwave back-azimuth determination method can be applied or assessed at these further distances.

58 GEOSCIENCES↗
DOE OSTI2022

Layer Time Control for Large Scale Additive Manufacturing Using High Performance Computing

This work proposes to optimize an additive manufacturing AM process to reduce energy and printing cost. The polymer AM process is inherently dependent on the time-temperature history of each layer to maintain geometric tolerances and mechanical integrity. Our preliminary study shows that regression-based layer time control model using thermal images could result in up to 30% build time reduction for simple geometries. This proposed work would use high-performance computing (HPC) to couple the data-driven model with thermal simulation for better predicting layer temperature profiles, improving throughput of large-scale additive manufacturing, and reducing its energy cost. We have developed a method to optimize a layer deposition time (a.k.a. layer time) for large-scale AM via physics-based simulations. A long layer time leads to an over-cooled surface on which a new layer is deposited, and therefore, it may result in a weak bonding or debonding between layers, cracking, or warping. A short layer time leads to a high temperature of the structure due to insufficient cooling, and therefore, the structure may not be stiff enough and may collapse during manufacturing. Therefore, it is important to estimate the optimal layer time in additive manufacturing for a high-quality product. The temperature of a top layer right before deposition is recommended to be slightly higher than the glass temperature of the material. A temperature cooling was approximated to an exponential function of time, and the optimized layer time was obtained based on a target temperature while maintaining a minimal printing time. The material used is carbon fiber-reinforced polycarbonate (CF/PC), and the large-scale deposition system used is LSAM TM from Thermwood Corporation. Three different layer time cases were used for experiments, and a series of thermal images were obtained via an infra-red (IR) camera during the entire AM processes. AM process simulations were performed using a finite element method and the temperature profiles from the simulation were in good agreements with those from experiments. The layer time optimization was performed based on the temperature profiles from the simulations. A layer temperature with the optimal layer time was confirmed as the target temperature through simulation. In addition to the development of a layer time optimization method, we have developed a numerical framework for AM simulation with element activations in sync with toolpath, based on an open source finite element framework, DEAL.II. A major portion of this work was presented at SAMPE 2022 Conference and Exhibition on May 2022, and published in Proceedings of SAMPE 2022.

42 ENGINEERING↗
DOE OSTI2022

The BREKTRIA 500 – A Breakthrough in Technology and Power Density for an Advanced 500kW Utility-Scale String Inverter (Final Technical Report)

The primary goal of this development project, planned to be 36 months in duration, was to create a 500kW utility-scale string inverter, demonstrating an advanced hybrid architecture that would achieve unprecedented high power density, and bring the inverter to the stage of production readiness. Specific key objectives for the 500kW utility-scale string inverter were: Create a 500kW 3-phase 600Vac inverter that was similar in overall size to the existing 250kW string inverters in the market, thereby demonstrating dramatically increased power density; Achieve a cost of goods, including all manufacturing-related costs and overheads, at or below 2.5¢/Wac ($12,500); Demonstrate full-power operation at a 45-50C ambient temperature with no power de-rating; Accommodate a PV array DC input of up to 1MWdc, aka a DC/AC Ratio of 2.0; Demonstrate peak efficiency greater than 99% at any operating dc voltage, and a CEC weighted average efficiency greater than or equal to 98.5%. The motivation for this project was to leapfrog the competition by creating the world’s most powerful string inverter, utilizing an innovative topology and achieving a step change increase in power density. Achieving the goals of the project would have enabled Yaskawa Solectria Solar to demonstrate its technology leadership, manufacture the utility-scale string inverter in the company’s facilities in Illinois, and bring to the market a highly-differentiated and compelling product to help the company grow its share in the large and growing utility market segment. During the course of this project, BREK Electronics’ hybrid architecture inverter was taken from an early-stage 125kW prototype, to a more mature and successfully demonstrated power stage at twice the power. Two 250kW power stages were planned to build the 500kW inverter. Significant progress was made in the inverter controls, achieving a clean AC sinewave and closed-loop operation into the grid, and improved efficiency by control of the high-speed switching. Further, the updated 250kW power stage was on track to achieve full power operation at an ambient temperature of 50C. At the time of the project’s closure in September 2022, global semiconductor supply remained limited, with shortages creating dramatic swings in both availability and price. Given this situation, our ability to predict cost-of-goods two years out with any accuracy or confidence was limited. As a result, the probability of attaining the target cost of 2.5¢/Wac for the 500kW inverter remained uncertain at the closure of the project. This project successfully demonstrated the potential for the advanced hybrid architecture inverter that emerged from a decade of university research on Si IGBTs and SiC mosfets, leading to this unique inverter topology. The team has taken the first steps toward an evolutionary advancement in inverter technology that remains to be fully realized.

14 SOLAR ENERGY↗
DOE OSTI2022

SCALE 6.2.4: Validation Overview

SCALE is a multi-application code system with tools for reactor physics, criticality safety, radiation shielding, and spent fuel characterization for a range of nuclear systems. The last of the SCALE 6.2 series, version 6.2.4, was released in June 2020. Validation studies in nuclear criticality safety, reactor physics, and shielding applications were performed to confirm results, assess accuracy, and identify biases from SCALE simulations. Nuclear criticality safety applications yield small code biases for a wide range of systems, generally overestimating cross section uncertainty. Reactor physics applications improvements in nuclide inventory and full-core eigenvalue predictions, with similar performance in decay heat predictions. Radiation shielding applications yield sufficient agreement in comparisons to measurements and alternate simulations for eight shielding experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Updated Primers Generated for SCALE 6.2 for KENO V.a and KENO-VI [Slides]

Primers were developed and published for the use of the KENO V.a and KENO-VI codes in 2005 and 2008, respectively. These primers were both developed for SCALE 5 using the GeeWiz graphical user interface (GUI). Many new capabilities have been added to the transport codes since the release of these primers. The GUI was also changed to Fulcrum with the release of SCALE 6.2. For these reasons, updated versions of both primers were developed for a planned released in September 2020. The KENO V.a and KENO-VI codes are almost always run within the associated CSAS5 and CSAS6 sequences within SCALE, so the primers use the sequences and do not address running the codes in stand-alone mode.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

SCALE Newsletter (Number 52, Spring 2020)

SCALE Newsletter is published by the Reactor and Nuclear Systems Division of the Oak Ridge National Laboratory. This issue, number 52 from Spring of 2020, holds information about the current state, planned updates, and previews of the SCALE system designed and maintained by ORNL staff. This issue contains employee spotlights for Dr. Kursat Bekar as well as Dr. Andrew M. Holcomb and displays data and charts from new/updated features of SCALE such as new data libraries, Fulcrum 3D visualizations, and interactions with ENDF/B-VIII.0 data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

High Solids Performance Testing in a Scaled TSCR System

The Tank Side Cesium Removal (TSCR) project is a technology demonstration that will pretreat Hanford tank waste supernatant in support of the Direct Feed Low-Activity Waste (DFLAW) mission. The TSCR system employs two key separation technologies: dead-end filtration (DEF) and ion exchange (IX) using crystalline silicotitanate (CST) media. DEF will be used to remove undissolved solids from tank waste to protect the functionality of the IX columns and the IX system will remove Cs-137 from tank waste. The separation technologies (DEF and IX) used in TSCR are technically mature and have also been successfully deployed at the Savannah River site in a similar facility known as the Tank Closure Cesium Removal (TCCR) system. While testing with simulants and real waste has been successfully performed under conditions expected during the initial operation of TSCR, test data is absent for assessing off normal high solids loading that may be in the TSCR waste feed. Normal TSCR treatment operations are expected to handle wastes with solids content on the order of 200 ppm, and off normal solids loading could be much larger than the nominal level. The testing program described in this report was conducted to understand the consequence of operating the TSCR system at elevated solids loadings up to the high-solids limit of 15,000 ppm [i.e., 1.5-wt%] identified in the TSCR design basis. Although the system is not required to make throughput above the nominal solids loading, the testing was intended to provide important information related to potential off normal operations. At off normal levels near the high-solids limit, there are potential implications for TSCR performance in the areas of throughput, DEF pressure drop, filter backflush frequency, and IX column pressure drop. In addition, intrusion of solids into the IX column was postulated to impact the Cs-137 loading behavior by promoting channeling or flow maldistribution in the column; since the magnitude of the postulated effect was unknown, assessing it was also of interest. The testing was performed using representative waste simulants and a prototypic, integrated TSCR system designed and assembled specifically to conduct the high solids performance assessment. Overall, the scaled TSCR testing demonstrated that full-scale unit operations can succeed in fulfilling their processing objectives in the presence of solids up to 3,000 ppm, but there are potential performance challenges to filtration operations at solids loadings as low as ~500 ppm. The severity of the challenge is likely to be dependent on the type and size distribution of solids, of which the current testing only examined a single type and size distribution. To provide some flexibility for future full-scale operations, the results of the testing suggest two possible risk reduction strategies that can be implemented without any changes in TSCR design or configuration. One option would be to enact an administrative limit on the solids loading to protect TSCR from feeds that are likely to require a high DEF swap frequency. Another option is to permit operation of the DEFs at differential pressures greater than 2 psid before swapping filters. The selection of a higher differential pressure target is not anticipated to adversely impact DEF backflushing efficacy and would reduce both swap frequency and the amount of waste sent to AP-108.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

In Situ Infrared Spectroscopy of a Plasma Jet and Data-Driven Solution of Multi-Scale Plasma Chemistry Problems

Multi-scale problems are commonly known in many scientific and engineering fields where microscopic behaviors are coupled with macroscopic processes. This is also an unsolved problem in low-temperature plasma chemistry where hundreds of chemical species are involved in thousands of chemical reactions. To address this problem, a physics-informed data-driven modeling is developed to solve such a multi-scale problem using the experimental Fourier-transform infrared spectroscopy (FTIR) measurements of several species’ concentrations. The modeling based on modern machine learning techniques provides concentrations of other relevant species along with the electron temperature and gas temperature at the location of FTIR measurements. For example, the concentrations O, OH, and H 2 O 2 play key roles in plasma-based cancer therapy. This approach overcomes the multi-scale difficulties of microscopic low-temperature plasma chemistry coupling with macroscopic gas flow and allows the acquisition of a full picture of output species concentrations. Presented here for the helium-air jet at atmospheric pressure, the ML-based modeling can be used to describe and possibly control multiscale systems using partial experimental data sets.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Initial Systems-Level Assessment of a Distributed Direct Air Capture System Concept at the Urban-scale (UrbanDAC)

Direct Air Capture (DAC) systems offer a promising solution for mitigating global carbon emissions by directly removing ambient carbon dioxide (CO 2 ) from the atmosphere. While future DAC facilities are typically envisioned as being large and centralized, small-scale systems present an alternative approach with advantages such as adaptability and lower uptake costs. By harnessing waste heat from the built environment, such small-scale systems become distributed DAC at the urban scale (UrbanDAC) that benefit from existing urban infrastructure, while presenting challenges such as identifying eligible buildings and sustainable transportation and storage of captured CO 2 . Collaborating with engineering experts and developers of a DAC unit that can be co-located with cooling towers of existing commercial buildings, this study explores the systems-level implications of UrbanDAC using a geographically explicit multi-decision criteria analysis (MCDA) framework. By considering various infrastructure and environmental factors, network analysis and geospatial techniques are applied to identify optimal building candidates for distributed DAC units within Knoxville, Tennessee, USA, as a representative mid-size city. The selected outputs of the MCDA are used to explore a scenario that assumes a CO 2 collection and transport route for 20 high-ranking candidate buildings; total carbon emissions, EV energy consumption, and net carbon dioxide removal (CDR) are then calculated. Results suggest that the spatial variation of optimal candidates between thriving commercial areas is an important planning consideration. Examining the feasibility of UrbanDAC at an urban planning level provides valuable insights into the barriers and enabling conditions for CDR in cities, where the vast majority of CO 2 emissions are produced, and supports decision-making processes for the implementation of decarbonization initiatives. Through this initial assessment, this research acts as a pilot study for an emerging technology that highlights the importance of distributed DAC technologies in addressing climate change and emphasizes the need for further research and exploration in this domain.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Development of Nanocomposite Coatings for Future Large-Scale Time Projection Chambers

In the context of this award we tested the performance of thin high-resistivity coatings for their potential usage as field shaping systems in future large scale xenon Time Projection Chambers (TPC). A successful implementation of such thin coatings would likely simplify the design of potential future detectors, allowing to overcome some of the challenges observed with traditional systems constituted by massive discrete electrodes. We studied a wide range of materials and characterized their optical and electrical performances as functions of temperature and wavelength. The measurement campaign indicated that uniform coatings covering the full PTFE substrate (usually used as reflector in LXe TPCs) impact too severely on the light collection performance of such detectors when used with deep UV light. Despite tuning the composition and thicknesses of nanocomposite coatings, we were not able to identify a single coating, properly working at LXe temperature, that would simultaneously fulfill the resistance and optical requirements. Following the risk mitigation strategy identified in the proposal we moved the focus of the R&D to identify proper materials that, when coated with grid-like patterns on PTFE, would not alter meaningfully its optical properties (with respect to bare PTFE panels) but would still serve as effective field shaping systems, properly containing the drift field in TPC detectors. Among the various materials we identified germanium as the most promising one, providing a good adhesion to PTFE and the proper range of sheet resistivity. The Ge-patterned coating tested within a small scale LXe TPC showed good performance as a field shape system and, as desired, did not reduce the detector light yield. These results are encouraging and such technology should further be investigated as a potential alternative to more traditional field shaping electrodes. Incidentally, in the context of this R&D, we stumbled upon an unexpected behavior suggesting that some of the treatments performed on the PTFE panels, in preparation of the coatings, meaningfully boosted the PTFE reflectivity. The most probable candidate is the O2 plasma cleaning procedure. This hypothesis will be tested in the near future by operating the small scale TPC at UChicago first with regular PTFE panels and then with panels bombarded with O2 plasma (but no coatings). This finding, if confirmed, might open up the possibility of further boosting UV light collection in future large detectors by performing such a treatment on the PTFE surfaces.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Scaled up Process Report – Apparatus and Model

Advanced voloxidation with NO 2 is a proposed process for used nuclear fuel head-end reprocessing scheme that converts UO 2 to higher oxides, and it also converts partitioning volatile fission products into the gas phase, thus facilitating fuel dissolution and actinide recovery. NO 2 voloxidation is being studied on small batches of UO 2 Simfuel, but the real test of process feasibility will be when it is scaled up to work with >100 g of irradiated material. This report discusses the aspects of scale-up that must be considered for NO 2 voloxidation, including development of a stirred reactor to promote agitation of the mixture during processing, online process monitoring, and automation controls. Brief details on parallel efforts are also provided in this report, including (a) demonstration of iodine release from Simfuel made by Spark Plasma Sintering, and (b) development of an order-of-magnitude scale-up to react 100 g of UO 2 Simfuel in a metal reactor.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗