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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Inventory and Waste Characterization Status Report and OWL Update.

This report represents completion of milestone deliverable M2SF-18SNO10309013 "Inventory and Waste Characterization Status Report and OWL Update that reports on FY2018 activities for the work package (WP) SF-18SNO1030901. This report provides the detailed final information for completed FY2018 work activities for WP SF-18SN01030901, and a summary of priorities for FY2019. This status report on FY2018 activities includes evaluations of waste form characteristics and waste form performance models, updates to the OWL development, and descriptions of the two planned management processes for the OWL. Updates to the OWL include an updated user's guide, additions to the OWL database content for wastes and waste forms, results of the Beta testing and changes implemented from it. There are two processes being planned in FY2018, which will be implemented in FY2019. One process covers methods for interfacing with the DOE SNF DB (DOE 2007) at INL on the numerous entries for DOE managed SNF, and the other process covers the management of updates to, and version control/archiving of, the OWL database. In FY2018, we have pursued three studies to evaluate/redefine waste form characteristics and/or performance models. First characteristic isotopic ratios for various waste forms included in postclosure performance studies are being evaluated to delineate isotope ratio tags that quantitatively identify each particular waste form. This evaluation arose due to questions regarding the relative contributions of radionuclides from disparate waste forms in GDSA results, particularly, radionuclide contributions of DOE-managed SNF vs HLW glass. In our second study we are evaluating the bases of glass waste degradation rate models to the HIP calcine waste form. The HIP calcine may likely be a ceramic matrix material, with multiple ceramic phases with/without a glass phase. The ceramic phases are likely to have different degradation performance from the glass portion. The distribution of radionuclides among those various phases may also be a factor in the radionuclide release rates. Additionally, we have an ongoing investigation of the performance behavior of TRISO particle fuels and are developing a stochastic model for the degradation of those fuels that accounts for simultaneous corrosion of the silicon carbide (SiC) layer and radionuclide diffusion through it. The detailed model of the TRISO particles themselves, will be merged with models of the degradation behavior(s) of the graphite matrix (either prismatic compacts or spherical "pebbles") containing the particles and the hexagonal graphite elements holding the compacts.

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

Revealing the aging process of solid electrolyte interphase on SiOx anode

Abstract As one of the most promising alternatives to graphite negative electrodes, silicon oxide (SiO x ) has been hindered by its fast capacity fading. Solid electrolyte interphase (SEI) aging on silicon SiO x has been recognized as the most critical yet least understood facet. Herein, leveraging 3D focused ion beam-scanning electron microscopy (FIB-SEM) tomographic imaging, we reveal an exceptionally characteristic SEI microstructure with an incompact inner region and a dense outer region, which overturns the prevailing belief that SEIs are homogeneous structure and reveals the SEI evolution process. Through combining nanoprobe and electron energy loss spectroscopy (EELS), it is also discovered that the electronic conductivity of thick SEI relies on the percolation network within composed of conductive agents (e.g., carbon black particles), which are embedded into the SEI upon its growth. Therefore, the free growth of SEI will gradually attenuate this electron percolation network, thereby causing capacity decay of SiO x . Based on these findings, a proof-of-concept strategy is adopted to mechanically restrict the SEI growth via applying a confining layer on top of the electrode. Through shedding light on the fundamental understanding of SEI aging for SiO x anodes, this work could potentially inspire viable improving strategies in the future.

25 ENERGY STORAGE↗
DOE OSTI2011

Summary of Blast Shield and Material Testing for Development of Solid Debris Collection at the National Ignition Facility (NIF)

The ability to collect solid debris from the target chamber following a NIF shot has application for both capsule diagnostics, particularly for fuel-ablator mix, and measuring cross sections relevant to the Stockpile Stewardship program and nuclear astrophysics. Simulations have shown that doping the capsule with up to 10 15 atoms of an impurity not otherwise found in the capsule does not affect its performance. The dopant is an element that will undergo nuclear activations during the NIF implosion, forming radioactive species that can be collected and measured after extraction from the target chamber. For diagnostics, deuteron or alpha induced reactions can be used to probe the fuel-ablator mix. For measuring neutron cross sections, the dopant should be something that is sensitive to the 14 MeV neutrons produced through the fusion of deuterium and tritium. Developing the collector is a challenge due to the extreme environment of the NIF chamber. The collector surface is exposed to a large photon flux from x-rays and unconverted laser light before it is exposed to a debris wind that is formed from vaporized material from the target chamber center. The photons will ablate the collector surface to some extent, possibly impeding the debris from reaching the collector and sticking. In addition, the collector itself must be mechanically strong enough to withstand the large amount of energy it will be exposed to, and it should be something that will be easy to count and chemically process. In order to select the best material for the collector, a variety of different metals have been tested in the NIF chamber. They were exposed to high-energy laser shots in order to evaluate their postshot surface characterization, morphology, degree of melt, and their ability to retain debris from the chamber center. The first set of samples consisted of 1 mm thick pieces of aluminum that had been fielded in the chamber as blast shields protecting the neutron activation diagnostic. Ten of these pieces were fielded at the equator and one was fielded on the pole. The shields were analyzed using a combination of scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), x-ray fluorescence (XRF), neutron activation analysis (NAA) and chemical leaching followed by mass spectrometry. On each shield, gold debris originating from the gold hohlraum was observed, as well as large quantities of debris that were present in the center of the target chamber at the time of the shot (i.e., stainless steel, indium, copper, etc.) Debris was visible in the SEM as large blobs or splats of material that had encountered the surface of the aluminum and stuck. The aluminum itself had obviously melted and condensed, and some of the large debris splats arrived after the surface had already hardened. Melt depth was determined by cross sectioning the pieces and measuring the melted surface layers via SEM. After the SEM analysis was completed, the pieces were sent for NAA at the USGS reactor and were analyzed by U. Greife at the Colorado School of Mines. The NAA showed that the majority of gold mass present on the shields was not in the form of large blobs and splats, but was present as small particulates that had most likely formed as condensed vapor. Further analysis showed that the gold was entrained in the melted aluminum surface layers and did not extend down into the bulk of the aluminum. Once the gold mass was accounted for from the NAA, it was determined that the aluminum fielded at the equator was collecting a fraction of the total gold hohlraum mass equivalent to 120% ± 10% of the solid angle subtended by the shield. The attached presentation has more information on the results of the aluminum blast shield analysis. In addition to the information given in the presentation, the surfaces of the shields have been chemically leached and submitted for mass spectrometric analysis. The results from that analysis are expected to arrive after the due date of this report and will be written up at a later time. Based on the results of the aluminum blast shield analysis, it was determined that additional materials needed to be tested as potential collectors in the NIF chamber. 1-2 mm thick pieces of tantalum, niobium, vanadium, silver, titanium, molybdenum, and graphite foil were fielded in the Wedge Range Filter (WRF) mount at a distance of 50 cm from target chamber center during the shock timing campaign. The pieces were subsequently removed and analyzed in a similar fashion to the aluminum shields. As of this writing, the pieces are still under analysis, but initial results indicate that gold debris was collected on the various materials. Currently, the pieces are being cross-sectioned so that the melt depths of each material can be compared. In addition, NAA and/or mass spectrometry will be performed in order to determine the total gold mass that was collected on each surface.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Acoustic-based monitoring and machine learning of component status for microreactor applications

This report provides a description and assessment of recent efforts to couple acoustic-based experimental measurements and characterization with machine learning models in order to enhance structural health monitoring capabilities for nuclear microreactors. With resilient embedded sensors in development by others supported by programs funded by the US Department of Energy’s Office of Nuclear Energy, the work described herein builds upon ongoing efforts to improve non-destructive testing technology that relates measured acoustic signatures to component stresses and/or structural defects, using a combination of new experimental measurements and machine learning architectures. The experimental procedure remained similar to that developed for the previous year’s demonstration of damage detection by the authors, with the same damaged sample tested under similar applied stress conditions. Notably, a new mounting fixture was designed and implemented to improve measurement consistency and a more sophisticated laser Doppler vibrometer was employed to make high-fidelity vibration measurements. Two nominally identical sets of training data were collected for each experimental setup to better understand the repeatability of the experiment and to better test the generality of trained neural network models. Additionally, we obtained new high-quality 3D mode shapes of the damaged test article at various stress and excitation levels, providing greater insights into the physical response of the sample during testing. Previously, we demonstrated that a machine learning model based on a convolutional neural network can predict structural details of an artificially introduced interface (intact, rough cut, smooth cut), and the applied torque level. In this study, we have transitioned to graph-based neural network architectures to better develop and test a flexible framework that is more suitable to being transferred away from controlled benchtop experiments and into more applied settings where less-structured data inputs may be expected. In general, performance testing of a graph neural network on frequency-domain representations of the data indicates strong and consistent identification of test conditions for datasets recorded on damaged components. With goals of predicting damage location and other changing experimental conditions using limited datasets, predictive models using a graph neural network architecture correctly predicted the applied torque level with an accuracy of 85% using only a single measurement point and predicted within one torque level in 95% of test windows. Predictions of damage location had limited success due to the symmetry and minimal number of the damage scenarios presented during model training. Results were ambiguous as to whether the model could detect the location of the artificial damage, or if it was instead learning the location of a given measurement point on the part and subsequently detecting which points were closest to the location of the damage. This finding will be factored into upcoming planned work on damaged graphite components, where new experimental tests with a larger number and variety of damage scenarios are expected to provide improved validation of recent developments in monitoring methodology.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Photocatalytic degradation of organic pollutants coupled with simultaneous photocatalytic H 2 evolution over graphene quantum dots/Mn-N-TiO 2 /g-C 3 N 4 composite catalysts: Performance and mechanism

Graphene quantum dots/Mn-N-TiO 2 /g-C 3 N 4 (GQDs/TCN) composite photocatalysts have been designed, synthesized and characterized by XRD, SEM, TEM, Raman, BET, and XPS. The photodegradation of organic pollutants (p-nitrophenol, diethyl phthalate and ciprofloxacin, called as 4-NP, CIP and DEP, respectively) coupled with simultaneous photocatalytic production of hydrogen was successfully achieved using the GQDs/TCN catalysts. The 5%GQDs/TCN-0.4 sample shows the best photocatalytic hydrogen production and organic pollutant degradation rate under simulated solar irradiation in the simultaneous photocatalytic oxidation and reduction system. Furthermore, the photocatalytic H 2 evolution rates in the solution of 4-NP, CIP and DEP are all larger than that in pure water system over the 5%GQDs/TCN-0.4 catalyst. And the H 2 evolution rate in the solution of 4-NP is smaller than that in the solutions of CIP and DEP. Accordingly, the photodegradation rate of 4-NP is larger than that of CIP and DEP. The analyses of density functional theory and liquid chromatography mass spectrometry indicate that some photogenerated electrons were used in the photodegradation process of 4-NP but not in that of CIP and DEP. And it leads to the photocatalytic rate of H 2 evolution in the 4-NP solution smaller than that in the solution of CIP and DEP. For the first time, the present work illuminates the photocatalytic enhancement of the GQDs/TCN-0.4 catalyst and the mechanism of the effect of different organic pollutants on photocatalytic H 2 evolution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Sub-pilot-scale Production of High-Value Products from U.S. Coals

Investigators from the University of Utah, University of Wyoming and Marshall University pursued a program to study the conversion of raw coal to high-value products of carbon fiber and silicon carbide. Team members also developed an initial framework for a data portal that can incorporate laboratory data on coal processing and product quality, and also work with tools for machine learning for data analysis, data visualization and economic assessment. Experimental R&D efforts focused on the conversion of raw coal to coal tar and other byproducts, and the resulting tar intermediates were upgraded to form anisotropic and isotropic pitch materials. These pitch materials were produced from coal using both thermal (pyrolysis) and chemical (mild solvolysis liquefaction) decomposition of raw coal. Four different coals were studied: Utah bituminous coal (Sufco), Wyoming PRB coal (Black Thunder), Illinois bituminous coal (Illinois #6), and West Virginia bituminous coal (Flying Eagle). Both metallurgical-grade coking coals and lower-grade steam coals were investigated, and controlled secondary gas-phase reactions were used during a two-stage pyrolysis process to induce cracking and condensation reactions among the pyrolytic tar species. This approach successfully improved the performance of the lower grade coals for yielding pitch materials, with properties more consistent with a commercial-grade pitch that had previously demonstrated success for quality carbon fiber production. The use of waste plastic materials was also studied, to help improve physical and chemical characteristics of the intermediate tars and final pitch product; in particular, for lowering the pitch softening point to an acceptable level for melt spinning carbon fiber. Mild solvolysis liquefaction was also used as a method for producing pitch for carbon fiber production. As expected, significantly higher pitch yields were obtained using this approach, and waste plastic materials were also successfully used to reduce pitch softening point to an acceptable level. The plastic materials were also utilized to create a solvent for the mild solvolysis process, and this plastic-derived solvent was shown to provide results consistent with more expensive commercial chemical solvents, and could thus avoid the need for costly recovery and recycle of a liquefaction solvent. Additional experimental R&D focused on the production of silicon carbide (β-SiC) from the residual char byproduct from pitch production, and also on the production of carbon fiber from the anisotropic pitch. SiC was successfully synthesized using a mixture of residual char and sandstone at a ratio of 1:1. Reaction temperature and residence time were optimized and yielded a product purity of 81%. For carbon fiber production, the most successful pitch samples were obtained from the mild solvolysis liquefaction approach, combined with the use of a plastic (HDPE)-derived solvent. Fiber properties improved over time as laboratory fiber production methodologies improved, and final yields of carbon fiber were obtained with a diameter of 12.14 ± 1.10 um, Modulus of 173.73 ± 15.25 GPa, and Tensile Strength of 1.04 ± 0.10 GPa. A proof-of-concept Modern Community Research Data Portal (MCRDP) was developed and deployed for coal and coal-derived pitch characterization, with the full support of (i) remote web-based access, (ii) distributed analysis, (iii) interactive visualization and exploration, (iv) shared and long-term data access, (v) advanced query capabilities and (vi) real-time collaboration. The Coal to Products Data Portal “coaltoproducts.org” provides researchers with space to store and share data within a project, tools for analyzing and understanding data for scientific investigation, and the ability to publish data to the broader community for reproducibility. The portal leverages the Material Commons 2.0 (MC) platform developed by the Center for PRedictive Integrated Structural Materials Science (PRISMS) of the University of Michigan, to achieve long-term longevity of data collections and, more importantly, collaborative science. A number of data visualization tools were also assessed and implemented for interrogating the experimental and modeling data. The machine learning portion of this project analyzed datasets from two different coal conversion processes performed on a diverse set of coal samples from both the coal pyrolysis experiments and the solvent liquefaction experiments. The work was initiated by exploring standard regression models on the pyrolysis data, aiming to understand the impact of sample characteristics and processing conditions on key product metrics. Over the course of the project, the focus expanded to include a variety of machine learning tools, delving into both supervised and unsupervised learning methods. Models tested on the pyrolysis data included linear, ridge, lasso, elastic-net, Gaussian process, random forest regression, and AutoSklearn, and the approach was continually refined to enhance predictive accuracy and model interpretability. Similar techniques were applied to the liquefaction data with an additional focus on feature engineering. Along with mesophase content, additional outputs of interest were the pitch yield, softening point, and QI content. Insights derived from these analyses are crucial in determining the factors influencing the quality and yield of coal-derived products. As the work progressed, the research evolved from foundational model comparisons to analyses of random forests, decision paths, and feature importance scores. A thorough market analysis was performed to examine the prospects of coal-based carbon fibers. The best opportunities for coal come from its lower and more stable price relative to petroleum, particularly for subbituminous coals, which is the primary advantage that a coal refinery may have over a petroleum refinery. Before a commercial CTP production facility can be modeled, however, several things need to be understood regarding the nature of the would-be coal refinery. These include the technology to be deployed, the size of facility, the volume(s) of co-product(s), and the waste and emissions profile of the plant. The volume of co-products and waste may be substantial and will require separate market analysis to ensure viability. In the near-term, the importance of coal tar pitch, in the form of carbon pitch, to the aluminum and steel industries is likely to overshadow the alternative use of this material as an input for carbon fiber. The importance of steel and aluminum in building materials, and the need for carbon materials in their manufacturing, will ensure that demand for these products remains for the long run. In addition, carbon fiber may also be the best substitute for steel and aluminum well into the future. While society will eventually be able to shift production of much of its electricity needs to renewables, it will not be able to shift away from fossil fuels for production of high-strength construction and vehicular materials. Demand for carbon fiber is expected to increase quickly, but the volume of carbon fiber and the amount of coal that would be needed to produce even a sizeable share of this market may still be relatively small compared to current coal production. Thus, other coal-based products like graphene, graphite, carbon foams, resins, and carbon-based building products will play important roles in sustaining coal production as coal-fired power generation continues to decline.

01 COAL, LIGNITE, AND PEAT↗