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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Critical role of solvation on CC13 porous organic cages for design of porous liquids

Efficient carbon capture requires the design of new materials with high CO 2 selectivity and gas adsorption capacity that can be incorporated into existing industrial processes. Porous liquids (PLs) are promising candidate materials that consist of a nanoporous host and a solvent forming a liquid with permanent porosity based on exclusion of the solvent from the interior of the nanoporous host. Stable PLs are based on solvent-nanoporous host interactions, which can be evaluated through molecular simulations. Here, time- and temperature-dependent density functional theory simulations were performed between four solvents, 2-bromophenol, 4-methylphenol, 2,4-dimethylphenol, and cyclohexanone and the CC13 porous organic cage (POC) as a prototypical PL composition. Overall, minimal reactions occurred in the PL including no changes in the POC structure. Additionally, POC-solvent coordination occurred through interactions of neighboring functional groups such as methyl/bromide and hydroxyl on the solvent molecules with the POC surface. Therefore, the location rather than the number of functional groups on the solvent molecule controls the POC-solvent interactions. Additionally, the POC pore window contracted or expanded up to 8% during solvation, which correlates with the experimental solubility and static solvent-POC binding, where solvents that caused less contraction of the POC pore window increased POC solubility. Finally, these results allow for the design of optimized POC-based PL compositions based on solvent-nanoporous host binding and variation in the pore window during solvation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Incorporation of Oxygen Carrier Recycle into Large-Scale Production of Cu-Based Oxygen Carriers

One of the greatest challenges in the chemical looping combustion (CLC) of solid fuels is developing an oxygen carrier material that is reactive and attrition resistant and can be prepared at a reasonable cost. Recent efforts in oxygen carrier development have followed two primary approaches: (1) using natural ores, such as ilmenite, or (2) developing highly attrition-resistant and reactive synthetic materials. Both approaches have shortcomings, namely, the low reactivity and incompatibility of ores with solid fuel CLC and the high cost and low durability of synthetic materials. Here, a different approach is taken where attrition is assumed inevitable and the recycling of spent oxygen carrier materials is incorporated into oxygen carrier manufacture. For solid fuel CLC, Cu-based oxygen carriers are attrited and are collected with fly ash. Copper oxides are more reactive with nitric acid than most ash materials, meaning that a copper-nitrate-rich leachate can be generated. This copper nitrate stream could then be reused in oxygen carrier synthesis by impregnation. For proof of concept, leaching experiments were conducted to verify that copper oxides are selectively leached from ash-containing spent oxygen carriers. Several cases for process design are proposed based on the composition of spent materials, as the degree of copper oxidation and type of solid fuel dictate leaching residence times and general processing intensity. The four stages proposed here include impurity removal, copper leaching and recovery, solid–liquid separation, and evaporation/concentrating. The resulting process should be able to recover up to 95% of copper while minimizing inclusion of undesirable ash-based impurities.

anions↗
DOE OSTI2021

Three-dimensional coherent X-ray diffraction imaging via deep convolutional neural networks

Abstract As a critical component of coherent X-ray diffraction imaging (CDI), phase retrieval has been extensively applied in X-ray structural science to recover the 3D morphological information inside measured particles. Despite meeting all the oversampling requirements of Sayre and Shannon, current phase retrieval approaches still have trouble achieving a unique inversion of experimental data in the presence of noise. Here, we propose to overcome this limitation by incorporating a 3D Machine Learning (ML) model combining (optional) supervised learning with transfer learning. The trained ML model can rapidly provide an immediate result with high accuracy which could benefit real-time experiments, and the predicted result can be further refined with transfer learning. More significantly, the proposed ML model can be used without any prior training to learn the missing phases of an image based on minimization of an appropriate ‘loss function’ alone. We demonstrate significantly improved performance with experimental Bragg CDI data over traditional iterative phase retrieval algorithms.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Living Filter Designs for In-Line Recovery and Sorting of Critical materials

This project explored “bio-mining” of critical materials from electronic waste (E-waste) streams by developing living filters arrays capable of recovering these materials, focusing on the platinum group metals (PGMs) and rare earth elements (REEs). While highly toxic, E-waste is considered a valuable “urban mine” as it contains critical materials such as PGMs and REEs with orders of magnitude higher purity than the richest ores. The aim of the project was to: (1) develop mechanically robust, silk-based biomaterial filtration membranes that can capture REEs from dilute aqueous waste; (2) design and build 3D bioprinted living filters containing encapsulated electrochemically active bacteria (EAB) capable of bio-reducing PGMs and recovering them from waste streams; and (3) constructing combined living filter arrays using both components to efficiently capture REE and PGM from the same waste stream. The developed silk-based filtration membranes were self-assembled using silk-nanofibrils (SNFs) derived from silkworm (Bombyx mori) cocoons in conjunction with recombinant silk-elastin-like proteins (SELPs), which contained lanthanide-binding peptide tags (LBTs) with a high affinity and specificity towards REEs. These 100% biodegradable protein-based membranes were capable of recovering up to 85% of model REE ions (Tb 3+ ) filtered through the membrane, with ~50% recovery achieved in the presence of high concentrations (100X) of common interfering metals (Ca 2+ , Cu 2+ , Fe 3+ , Zn 2+ ). REE captured by the membranes were easily recovered by applying a low pH desorption buffer. The membranes also demonstrated substantial reusability, with only a 30% loss in binding capacity after 4 cycles of REE binding and recovery. To recover the PGMs, we created a bottom-up assembling strategy to construct a living hydrogel composed of a seamlessly integrated living catalyst, Shewanella loihica PV-4 (PV-4), for metal reduction, and their structural and functional linkers, bio-reduced graphene oxide (B-rGO). This hydrogel demonstrated a close to 90% recovery of model metal ions, Pd, from a simulated e-waste leaching stream with minimum-to-no biomass production. It’s also worth noting that the Pd recovery is initiated immediately after the introduction of living hydrogel, compared to conventional biocarriers that required start-up times within hours to days. Overall, these living hydrogels demonstrated superior bioactivity, structural integrity, and agility over existing biocarriers, which offers extensive opportunities to advance the biological metal recovery with unparallel efficiency, reduced energy/material consumption, and minimal environmental impact.

36 MATERIALS SCIENCE↗
DOE OSTI2025

POWER ELECTRONICS GRID TIED SYSTEM FINAL REPORT

Across the country, electric utilities are grappling with the persistent hurdles of integrating Distributed Energy Resources (DERs). Managing these assets safely and effectively is a complex endeavor, complicated by varying ownership structures, management philosophies, and the diversity of the technologies themselves. Consequently, the industry has seen a proliferation of bespoke system designs, control strategies, and communication frameworks—forcing utilities to spend significant time and resources developing one-off integration solutions. This project addressed these integration hurdles through a scalable demonstration of intelligent devices designed to coordinate and control diverse resources in low-voltage applications. This concept minimized the need for complex integration by transforming the separate DERs into a dispatchable virtual power plant (VPP) with integrated resiliency functions (called a Node). By collaborating with a utility partner, the project focused on developing rapidly implementable use cases that bridged the gap between theoretical control and real-world deployment

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Understanding the Charging Flexibility of Shared Automated Electric Vehicle Fleets

The combined anticipated trends of vehicle sharing (ride-hailing), automated control, and powertrain electrification are poised to disrupt the current paradigm of predominately owner-driven gasoline vehicles with low levels of utilization. Shared, automated, electric vehicle (SAEV) fleets offer the potential for lower cost and emissions and have garnered significant interest among the research community. While promising, unmanaged operation of these fleets may lead to unintended negative consequences. One potentially unintended consequence is a high quantity of SAEVs charging during peak demand hours on the electric grid, potentially increasing the required generation capacity. This research explores the flexibility associated with charging loads demanded by SAEV fleets in response to servicing personal mobility travel demands. Travel demand is synthesized in four major United States metropolitan areas: Detroit, MI; Austin, TX; Washington, DC; and Miami, FL. In each of these four cities, SAEV simulations are performed using local projected electricity prices from the Regional Energy Deployment System (ReEDS) for a handful of supply side scenarios. A coordinated charging model is introduced that seeks to reduce fleet charging costs in response to time-varying electricity prices and increasing shares of personal trip demand served (between 1% and 25% of all metro trips served by the SAEV fleet). Simulation results are presented across various scenarios assuming fleetwide coordination to minimize charging energy costs while constrained by offering adequate mobility service to fleet customers. The results indicate that the SAEV charging load is highly flexible; energy costs were shown to reduce between 13% and 46% across a wide range of simulated scenarios. In addition, these savings were realized without detrimentally impacting the fleet’s ability to service trips.

autonomous vehicle↗
DOE OSTI2024

Profiling the molecular destruction rates of temperature and humidity as well as the turbulent kinetic energy dissipation in the convective boundary layer

A simultaneous deployment of Doppler, temperature, and water-vapor lidars is able to provide profiles of molecular destruction rates and turbulent kinetic energy (TKE) dissipation in the convective boundary layer (CBL). Horizontal wind profiles and profiles of vertical wind, temperature, and moisture fluctuations are combined, and transversal temporal autocovariance functions (ACFs) are determined for deriving the dissipation and molecular destruction rates. These are fundamental loss terms in the TKE as well as the potential temperature and mixing ratio variance equations. These ACFs are fitted to their theoretical shapes and coefficients in the inertial subrange. Error bars are estimated by a propagation of noise errors. Sophisticated analyses of the ACFs are performed in order to choose the correct range of lags of the fits for fitting their theoretical shapes in the inertial subrange as well as for minimizing systematic errors due to temporal and spatial averaging and micro- and mesoscale circulations. We demonstrate that we achieve very consistent results of the derived profiles of turbulent variables regardless of whether 1 or 10 s time resolutions are used. We also show that the temporal and spatial length scales of the fluctuations in vertical wind, moisture, and potential temperature are similar with a spatial integral scale of ≈160 m at least in the mixed layer (ML). The profiles of the molecular destruction rates show a maximum in the interfacial layer (IL) and reach values of ϵ m ≃ 7 x 10 -4 g 2 kg −2 s −1 for mixing ratio and ϵ θ ≃ 1.6 x 10 -3 K 2 s −1 for potential temperature. In contrast, the maximum of the TKE dissipation is reached in the ML and amounts to ≃ 10 -2 m 2 s −3 . We also demonstrate that the vertical wind ACF coefficient k w ∝ $\overline{w'^{2}}$ and the TKE dissipation ϵ ∝ ($\overline{w'^{2}}$) 3/2 . For the molecular destruction rates, we show that ϵ m ∝ $\overline{m'^{2}}$ ($\overline{w'^{2}}$) 1/2 and ϵ θ ∝ $\overline{θ'^{2}}$ ($\overline{w'^{2}}$) 1/2 . These equations can be used for parameterizations of ϵ, ϵ m , and ϵ θ . All noise error bars are derived by error propagation and are small enough to compare the results with previous observations and large-eddy simulations. The results agree well with previous observations but show more detailed structures in the IL. Consequently, the synergy resulting from this new combination of active remote sensors enables the profiling of turbulent variables such as integral scales, variances, TKE dissipation, and the molecular destruction rates as well as deriving relationships between them. The results can be used for the parameterization of turbulent variables, TKE budget analyses, and the verification of large-eddy simulations.

dissipation rate↗
DOE OSTI2023

Improving Subsurface Stress Characterization for Carbon Dioxide Storage Projects by Incorporating Machine Learning Techniques

The overall objective of this project is to develop a framework for reliable characterization and prediction of the state of stress in the overburden and underburden (including the basement) in CO 2 storage reservoirs using machine learning and integrated geomechanics and geophysical methods. Specifically, we propose to develop workflow encompassing of technologies and/or methods to predict stress and pressure changes due to CO 2 injection in an active tertiary recovery site and their impacts on subtle fault activation, fractures and occurrence of microseismic events and compare responses to field observations. In this project, we anticipate using dataset from the Farnsworth field Unit (FWU) which is operated by Purdure Petroleum. A novel elastic-waveform VSP inversion technique will be used to estimate high-resolution spatial and temporal changes of elastic moduli in CO 2 storage reservoirs, which will be combined with velocity-stress relationship derived from laboratory tests to obtain subsurface pressure and stress. Clustered microseismic data will be jointly inverted for improved focal mechanisms. Least-squares reverse-time migration of microseismic waveform data will be performed to directly image fracture/fault zones. Additionally, a deep neural network machine learning technique with convolutional and recurrent layers will be used for learning the spectro-temporal structures in microseismic waveforms. The results of this geotechnical data analysis will be integrated to develop a high-resolution 3D mechanical earth model extending from the overburden sealing formations to the underburden including the basement. Mechanical properties will be derived through integration of mechanical logs, tests, available results from chemo-mechanical laboratory tests, and elastic inversion of seismic data using a combination of Bayesian and stochastic methods as well as machine learning technique. Failure features (faults/fractures) will be represented and/or modeled based on seismic and core data analysis. A transient hydrodynamic-geomechanical model will be developed through coupling with the calibrated FWU reservoir simulation model. The full physics coupled model will be used to train a reduced order proxy model using machine learning algorithm for estimating stress which will then be used with appropriate constitutive relationships and forward seismological models to simulate pressure changes and induced microseismicity. An advanced optimization framework will be developed to perform a history match to minimize error between field observations and simulated. The history matched proxy model will be verified against the full-physics equivalent. The field observations that will be used in the coupled model calibration process include pressure/stress inverted from VSP, moment magnitude from microseismic analysis, real time downhole pressure measurements, production and injection data. Parameter sensitivity and uncertainty analysis will be performed to characterize the impact of model parameter uncertainty on stress estimates. The proposed project will have significant impact on future field implementation of the proposed technology. Because the project field site is an ongoing CO 2 EOR development, the value of the new technology will be demonstrated in an operational context and evaluated as a viable risk mitigation strategy. Cost/benefit will be evaluated together with the various commercial incentives for CO 2 sequestration available to oil and gas operators. The extensive available dataset and ongoing data acquisition under the SWP Phase III work plan provides flexibility for investigation of multiple approaches and reduces technical risk.

58 GEOSCIENCES↗
DOE OSTI2024

Stabilizing Nickel‐Rich Cathodes in Aqueous Process through Nanocellulose as Water Barrier

Nickel-rich LiNi 0.8 Co 0.1 Mn 0.1 O 2 (NMC 811) cathode offers high voltage and high specific capacity, making it promising for high energy density batteries. However, large-scale manufacturing of aqueous-processed NMC 811 electrodes remains challenging due to proton exchange causing material decomposition and capacity loss. This work addresses this issue by constructing an in situ nanocellulose protective layer for NMC 811 particles via electrostatic interactions during the slurry preparation. For the first time, the interatomic spacing between inter-chains of nanocellulose is measured through wide-angle X-ray scattering and demonstrate the ability to effectively confine interlayer water using atomistic simulations. Moreover, this nanocellulose coverage simultaneously minimizes Li + surface segregation and mitigates water infiltration. Owing to less material decomposition during the aqueous processing, nanocellulose-protected NMC electrodes exhibit higher initial coulombic efficiency (83% vs 62% at 0.1C) and capacity (133 vs 59 mAh g −1 at 6C) than unprotected electrodes. Additionally, optimized aqueous-processed NMC electrodes offer comparable or even superior electrochemical properties compared to the electrodes fabricated using the conventional toxic organic solvent, N-methyl-2-pyrrolidone. Consequently, the developed approach enables affordable, sustainable aqueous processing for Nickel-rich NMC 811 cathodes with excellent electrochemical performances.

25 ENERGY STORAGE↗
DOE OSTI2022

Impacts of annealing treatment on the microstructure of U-Mo monolithic fuel plates

The objective of this paper is to analyze the effect of different heat treatments on the fuel microstructure and texture in laboratory scale monolithic U-Mo fuel plates. Such analyses are relevant as they could possibly inform future fabrication methods for the optimization of microstructure and of material properties to ultimately improve fuel performance during irradiation. For this reason, detail characterization including Energy x-ray dispersive spectroscopy (EDS) and electron backscattered diffraction (EBSD) techniques were applied on U-Mo plates fabricated with different heat treatments to understand the influence of fabrication on fuel microstructure. Here, U-Mo fresh fuel specimens with or without annealing treatments (homogenization and stress release annealing) after rolling were analyzed in this work. In this study for the first time EBSD was systematically used to analyze the heat treatments influence on texture present in fresh fuel monolithic U-Mo fuel plates. Such changes were connected to other known microstructural and chemical changes. In this work minimization of molybdenum concentration variation and gamma phase decomposition of the U-Mo fuel core after homogenization was observed. Also, an increase in the interaction layer of the U-Mo fuel core with the Zr interlayer diffusion barrier was observed with the UZr 2 growing up to 1 µm in thickness. Such microstructural changes were aligned to the changes in texture and grain structure. Indeed, common texture observed in body-centered cubic (BCC) metal after cold rolling (e.g., α, ξ, γ fibers) were minimized by the annealing/homogenization process. Moreover, grain structure was influenced by the fabrication route with elongated grains formed in the rolled sample and equiaxed grains found after annealing. Such features are relevant since the formation of microstructural features formed during fuel fabrication can impact fuel performance in reactor.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Current Status on the Manufacturing of Nanomaterials for Proton Exchange Membrane Energy Systems by Vapor-Based Processes

Development of novel technologies for catalyst synthesis and membrane electrode assembly (MEA) fabrication is of primary importance for further improvement of the performance and economics of proton exchange membrane fuel cells (PEMFCs) and proton exchange membrane water electrolyzers (PEMWEs). While the traditional manufacturing methods are time-consuming, energy intensive, and require many processing steps, the new vapor-based methods provide many benefits including the development of improved catalysts and catalyst supports, deposition of uniform thin films, reduction of catalyst loading, and minimizing the number of manufacturing steps. Recent publications in the field identified spray pyrolysis, reactive spray deposition technology, chemical vapor deposition, and atomic layer deposition as advanced vapor-based catalyst synthesis and deposition methods used for fabrication of MEAs for PEMFCs and PEMWEs. Here, the MEAs fabricated via vapor-based processes have shown significant performance improvements in comparison to the state-of-the-art MEAs, which are attributed to better catalyst distribution, improved catalyst supports, and controlled, uniform catalyst layer microstructures. This review provides an overview of the vapor-based synthesis and deposition methods currently being used for the development of PEM-based devices. The advantages and disadvantages of these methods are critically compared and discussed while the outlook for future development is provided.

25 ENERGY STORAGE↗
DOE OSTI2020

Long-Range Exciton Diffusion in Two-Dimensional Assemblies of Cesium Lead Bromide Perovskite Nanocrystals

Förster resonant energy transfer (FRET)-mediated exciton diffusion through artificial nanoscale building block assemblies could be used as an optoelectronic design element to transport energy. However, so far, nanocrystal (NC) systems supported only diffusion lengths of 30 nm, which are too small to be useful in devices. In this work, we demonstrate a FRET-mediated exciton diffusion length of 200 nm with 0.5 cm 2 /s diffusivity through an ordered, two-dimensional assembly of cesium lead bromide perovskite nanocrystals (CsPbBr 3 PNCs). Exciton diffusion was directly measured via steady-state and time-resolved photoluminescence (PL) microscopy, with physical modeling providing deeper insight into the transport process. This exceptionally efficient exciton transport is facilitated by PNCs' high PL quantum yield, large absorption cross section, and high polarizability, together with minimal energetic and geometric disorder of the assembly. This FRET-mediated exciton diffusion length matches perovskites' optical absorption depth, thus enabling the design of device architectures with improved performances and providing insight into the high conversion efficiencies of PNC-based optoelectronic devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Computational Optimization of 133m Xe Production via Neutron Irradiation in a TRIGA Reactor

Here, the Comprehensive Nuclear-Test-Ban Treaty bans all nuclear tests worldwide. As part of treaty compliance, the concentration of radioactive nuclides in the atmosphere is monitored to detect nuclear weapons tests. Radioactive noble gas fission products, specifically radioxenon, can vent into the atmosphere after a nuclear weapons test, even if the test is well contained underground or underwater. Radioxenon thus serves as a signal for nuclear weapons tests. All atmospheric monitoring systems require samples of radioxenon isotopes for detector calibration, quality control, and certification. Here, we present a novel, improved method for creating samples of 133m Xe via neutron irradiation of 132 Xe in the Washington State University TRIGA reactor. 132 Xe neutron absorption results in either 133 Xe or 133m Xe—thermal neutron absorption results in 133m Xe 12% of the time, while fast neutron absorption (above ~1 MeV) results in 133m Xe ~50% of the time. To optimize the production of 133m Xe via neutron absorption in 132 Xe in the thermal TRIGA reactor, spectral tuning using an irradiation chamber is required to maximize the fraction of fast neutrons being absorbed and minimize the number of thermal neutrons interacting with the 132 Xe. We used MCNP to tally 132 Xe absorptions with the isotopic tally function, flux tallies and neutron attenuation to estimate the number of neutrons reaching the 132 Xe through the irradiation chamber, and the adjoint importance function to improve the source strength estimate. Additionally, we performed a heat transfer analysis for safety considerations. It was determined that the use of a 96% enriched 10 B boron carbide chamber, placed next to the fuel elements in reactor position D8, increases the 133m Xe/ 133 Xe activity ratio from a baseline value of 0.3 to 1.0, a 233% increase. Additionally, it was determined that the alpha heating produced in the boron does not become an unmanageable problem in the Washington State University reactor.

37 - INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL C↗
DOE OSTI2023

Production and testing of the large-area photon detector ArCLight

Compact large-area dielectric photon detectors that ensure modular noble liquid detectors can sense scintillation light signals for triggering and reconstruction purposes with minimal impact to the overall target volume. ArCLight is a small-volume, sizeable sensitive-area detector that consists of a light trap covered in a thin layer of TPB that can be placed inside a time projection chamber's electric field. These sensors are used in the Deep Underground Neutrino Experiment Near Detector liquid argon (DUNE ND-LAr). They are constructed and tested at the University of Bern and will be deployed in the prototype experiment ProtoDUNE-ND. The talk discusses the details of assembling ArCLights, the quality control methods, and the test studies done with LEDs to assess their performance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Smart Planning for Radioactive Source Transport Advanced Tools for Increased Safety and Efficiency

End-of-life (EOL) management of high-activity radioactive sources is made uniquely challenging by the inherent risks associated with storage and transportation of these sources, the complex logistics involved, and the strict requirements for regulatory compliance. Traditional methods lack comprehensive tools for accurate site assessments and precision planning for the transportation of radioactive sources. They also frequently fail to provide the adaptability required to consider diverse operational environments, resulting in inefficiencies and potential safety concerns. This paper introduces a novel software solution developed to address these issues by integrating advanced technologies such as light detection and ranging (LiDAR)-based 3D environment modeling, smart dynamic route planning, and customizable measurement functionalities. This software enables detailed terrain visualizations, facilitating thorough environmental assessments and enabling users to virtually navigate, analyze, and plan site-specific operations. Among the key features are a user-centric interface for virtual navigation, precise site measurement tools for site evaluations, interactive visualizations that highlight potential operational hazards, dynamic route planning capabilities, and real-time collision detection to promote safe workflows. By demonstrating the effectiveness of this tool through real-world application, the present work underscores the tool’s potential to revolutionize radioactive source EOL management by improving operational efficiencies, minimizing risk, and advancing the state of practice to achieve suitable and secure radioactive material handling.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Flexure Upgrade System Engineering Project

At the National Ignition Facility (NIF), a system of lasers is used to implode and blow-up targets and create temperatures and pressures unlike any other place on earth. There are many target types that are used on experiments, but they can be broadly put in two categories – room temperature targets and cold targets. All targets can be mounted on any of the three target positioners on NIF, and two of these three target positioners can cryogenically cool the targets in the low Kelvin range for the cold targets. To minimize the ice buildup and infrared light exposure to these cold targets, a shroud surrounds the targets and seals the target from the outer environment. By shrouding the target, air, water, and other molecules have a difficult time reaching the target and some particles get cryo trapped into the shrouds themselves.

42 ENGINEERING↗
DOE OSTI2023

Transformative Manufacturing of Adaptive Wire Feedstocks with Atomic Layer Deposition of Nb 2 O 5 onto Depleted Uranium [Slides]

Project Motivation: Uranium corrosion susceptible and highly catalytic; Exposure thickens oxide impacting material performance. This worsens with time; Sigma is uniquely positioned to tackle R&D challenges with Uranium processing. Possible Solutions: 1) Make new material for each weld. Occupational exposure, difficult to align resources ; 2) Coatings? Coating adds foreign material: can this be minimized?

36 MATERIALS SCIENCE↗
DOE OSTI2022

Inputs and Outputs for paper "The DESC stellarator code suite. Part 1. Quick and accurate equilibria computations"

Contains the DESC and VMEC input and output files used in the paper, as well as the plotting scripts used to create the figures in the paper (Current with the arXiv Mar 31 2022 version, https://arxiv.org/abs/2203.17173v1): 3D equilibrium codes are vital for stellarator design and operation, and high-accuracy equilibria are also necessary for stability studies. This paper details comparisons of two 3D equilibrium codes, VMEC, which uses a steepest-descent algorithm to reach a minimum-energy plasma state, and DESC, which minimizes the MHD force error in real space directly. Accuracy as measured by final plasma energy and satisfaction of MHD force balance, as well as other metrics, will be presented for each code, along with the computation time. It is shown that DESC is able to achieve more accurate solutions, especially near-axis. DESC's global Fourier-Zernike basis also yields the solution everywhere in the plasma volume, not just on discrete flux surfaces. Further, DESC can compute the same accuracy solution as VMEC in an order of magnitude less time.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗